Neuroanatomy

The simplest way to divide the cortex is into the frontal and posterior regions. The frontal cortex (frontal lobe) specializes in action, encompassing cognition, emotion, autonomic control, movement, and speech. The posterior cortex (parietal, temporal, and occipital lobes) is concerned with perception and memory. Together with subcortical structures and the peripheral nervous system, these regions provide the hierarchically arranged feedback loops that allow us to interact with our environment to achieve goals successfully.

The prefrontal cortex (PFC), the cortex rostral to the motor association cortex, directs cognitive and emotional processes called perception-action cycles, which adapt (and preadapt) us to our environment. In essence, the PFC predicts and creates the future. Working in cooperation with networked brain structures, it marshals executive functions such as planning, attention, working memory, and decision-making to develop innovative actions in pursuit of future goals (Fuster, 2015).

The nervous system uses bottom-up (feedforward) and top-down (feedback) processing to maintain homeostasis. This interconnectedness is best illustrated by the relationship between the thalamus and cortex: ascending thalamocortical neurons distribute sensory information to appropriate cortical and subcortical regions, while descending corticothalamic neurons convey instructions back to the thalamus. The nervous system generates EEG activity ranging from DC potentials to beta-gamma rhythms, using multiple generators that operate as what neuroscientist William Calvin called a "cerebral symphony."

BCIA Blueprint Coverage

This unit addresses II. Basic Neurophysiology and Neuroanatomy - B. Neuroanatomy.

This unit covers Basic Neuroanatomy of Ascending Sensory Pathways to the Cortex, Thalamic, Cortical, and Subcortical Generators of the EEG, General Cortical and Subcortical Anatomy, Major Functions of Cortical Lobes and Major Subcortical Structures and Brodmann Areas, and Overview of Connectivity, Phase, and Coherence Concepts Related to EEG Networks and Tracts.

Full-Length Lecture: Neuroanatomy

Basic Anatomy of Ascending Sensory Pathways to the Cortex

This section examines how sensory information travels from the body's receptors to the cortex, focusing on the visual, auditory, and somatosensory systems. Understanding these pathways is essential for biofeedback practitioners because sensory input directly shapes the EEG patterns you will assess and train. Sensory input produced by activities like reading a novel or listening to music can desynchronize cortical activity, resulting in lower-amplitude, higher-frequency EEG waveforms (Neumann, Strehl, & Birbaumer, 2003). Arousal and specific forms of cognitive activity may reduce alpha amplitude or eliminate it entirely, a phenomenon called alpha blocking, while increasing EEG power in the beta range (Andreassi, 2007).

The classical routes for EEG activation consist of ascending sensory pathways that distribute information to specialized thalamic nuclei, which then project the results of thalamic processing to the appropriate cortical regions. A hallmark of these pathways is their hierarchical structure, which preserves the spatial location from which signals arise, with specialized thalamic nuclei serving as critical relay points. The one exception is olfaction (smell), which bypasses the thalamus and projects directly to the primary olfactory cortex.

The old-school view held that these ascending pathways exercise purely bottom-up control of perception as feedforward circuits. This overlooks the fact that ten times more cortical efferent neurons target the sensory thalamus than thalamic afferent neurons project to the cortex. The new-school view recognizes extensive interconnections between the thalamus and cortex that permit a substantial degree of top-down cortical control over perception (Kandel et al., 2021). Subcortical areas, including the midbrain, thalamus, and cerebellum, also participate in ascending and descending transmission and processing of neural messages.

In summary, sensory pathways are not one-way streets but dynamic, bidirectional systems in which the cortex actively shapes the information it receives. We will now examine the visual, auditory, and somatosensory systems to illustrate these principles.

Visual System

Retinal ganglion cells, which comprise the optic nerves, ascend to the midline optic chiasm where the two optic nerves meet. At the chiasm, temporal axons (those toward the side of the head) continue on their own side's optic tract, while nasal axons cross over to join the opposite side's optic tract. Most optic tract axons project to the lateral geniculate nucleus (LGN) of the thalamus.

While the LGN relays visual information to the cortex, brainstem and cortical neurons actively modulate its activity. Brainstem neurons that mediate alertness and attention can adjust the LGN's response to visual input. The cortex can also exert top-down selection to increase attention to a salient region of the visual field at the expense of others (Bear, Connors, & Paradiso, 2020). This is clinically relevant because it demonstrates that even at the earliest relay station, perception is shaped by attention and arousal, the very processes biofeedback practitioners aim to train.

LGN neurons form the optic radiations and project to the primary visual cortex (V1) in the occipital lobe's cortical layer IV. A minority of retinal ganglion cell axons target the dorsal midbrain superior colliculus, which directs visual gaze and selective attention to visual objects (Breedlove & Watson, 2023). The cortex contains many specialist regions for processing visual properties like color, shape, location, motion, and orientation, organized into two major streams originating in V1.

The dorsal stream projects from V1 to the parietal lobe, helping us localize objects and guide movements. The adjacent motor association cortex contains neurons with both visual and motor properties, called mirror neurons, whose networks may play a role in learning actions by observing others, understanding intentions, and empathy. The lower ventral stream projects to inferior temporal and frontal areas and allows us to identify objects and faces.

Auditory System

The cochlea's inner hair cells within the organ of Corti send approximately 30,000 auditory fibers to several destinations: the superior olivary nuclei of the pons and the midbrain inferior colliculi, and the medial geniculate nucleus of the thalamus. The superior olivary nuclei process binaural (two-ear) information to localize sound, while all ascending auditory neurons ultimately innervate the inferior colliculi, some via intermediate relays.

The inferior colliculi integrate information about spatial localization and multiple sensory modalities, including somatosensory information. They project to the thalamus' medial geniculate nucleus (MGN), which in turn projects to several cortical auditory areas using two separate pathways. The MGN mainly relays frequency, amplitude, and binaural information to the auditory cortex in the temporal lobe.

The auditory cortex processes auditory information within dorsal and ventral streams, paralleling the visual system's organization. The dorsal stream, extending to the parietal lobe, helps us spatially localize sounds. The lower ventral stream, projecting to the temporal lobe, analyzes sound components, possibly including speech sounds (Breedlove & Watson, 2023). As with the visual pathways, the auditory system involves extensive feedback: brainstem neurons innervate outer hair cells that adjust basilar membrane sensitivity to specific frequencies, and auditory cortex axons innervate both the inferior colliculi and MGN to exercise top-down control (Bear, Connors, & Paradiso, 2020).

Somatosensory System

The somatosensory system employs specialized receptors to perceive itch, pain, temperature, and touch. For touch, the axon of a unipolar neuron enters the dorsal horn of the spinal cord and synapses with a dorsal column neuron in the medulla. Axons from this neuron decussate (cross the midline) and innervate the thalamus' ventral posterior nucleus (VPN), which in turn distributes this information to the primary somatosensory cortex (S1).

While each hemisphere's S1 maps touch information from the opposite side of the body, the secondary somatosensory cortex (S2) maps both sides. The maps are overlaid so that the left and right arms are represented in the same region of the body surface map (Breedlove & Watson, 2023). This bilateral representation in S2 may help explain why somatosensory processing can produce widely distributed EEG changes that clinicians observe during assessment.

As with the visual and auditory systems, the ascending somatosensory pathways do far more than relay information. These networks process and alter sensory information at each successive synapse, and the cortex exercises top-down control over neurons in the dorsal column and VPN to dynamically adjust cortical inputs (Bear, Connors, & Paradiso, 2020). The recurring theme across all three sensory systems is bidirectional communication: the cortex is not a passive receiver but an active participant that shapes the sensory data it processes.

Thalamic, Cortical, and Subcortical Generators of the EEG

This section explores how the brain generates the EEG rhythms central to neurofeedback practice. We will cover thalamic pacemakers, cortical resonant loops, and subcortical modulators, then survey each major EEG frequency band. Understanding these generators helps clinicians interpret why certain rhythms appear at specific scalp locations and what they signify about brain function.

Thalamic Generators

Andersen and Andersson (1968) advanced the facultative pacemaker theory, proposing that thalamic neurons activate both cortical neurons and thalamic inhibitory interneurons via recurrent collaterals. While these thalamocortical neurons only excite a limited number of cortical neurons, the inhibitory interneurons suppress a large pool of thalamocortical relay neurons. When the inhibition ends after about one-tenth of a second, the relay neurons experience rebound excitation, a synchronized depolarization that excites both cortical neurons and another round of thalamic inhibitory interneurons, initiating a new cycle that produces rhythmic EEG activity (Fisch, 1999).

The networking of excitatory and inhibitory thalamic neurons imposes a group rhythm on its members, which is then transmitted to cortical macrocolumns by thalamocortical neurons (Bear, Connors, & Paradiso, 2020). The nucleus reticularis of the thalamus may function as a pacemaker by releasing the inhibitory transmitter GABA at synapses with thalamocortical neurons. When this inhibition ends, these neurons depolarize cortical neurons and thalamic inhibitory interneurons through burst discharges.

As discussed in the Neurophysiology unit, oscillatory activity may involve an interaction between thalamocortical relay neurons (TCR), nucleus reticularis neurons (RE), and interneurons, mediated by diverse neurotransmitters including acetylcholine and GABA. The thalamus is the dominant pacemaker for rhythmic EEG activity, including theta (4-7 Hz), alpha (8-12 Hz), and SMR (12-15 Hz) (Amzica & Lopes da Silva, 2018). For biofeedback practitioners, this means that many of the rhythms you train have their origin not in the cortex beneath the electrode, but in deeper thalamic circuits.

Cortical Generators

The cerebral cortex (gray matter) consists of neuronal cell bodies, glial cells, and blood vessels, while white matter lies beneath it, composed of myelinated nerves, nonmyelinated fibers, and glial cells. The EEG mainly originates from pyramidal neurons in layers III, V, and VI of the gray matter, the six-layered outer portion of the cerebrum that contains neuronal cell bodies. Cortical thickness ranges from about 1 to 4.5 mm and averages roughly 2.5 mm.

Why do pyramidal neurons dominate the scalp EEG? Their long apical dendrites run parallel to one another and perpendicular to the cortical surface, so that synchronous synaptic currents along these dendrites create aligned electrical dipoles whose fields add together rather than cancel, a configuration known as an open field (Kirschstein & Köhling, 2009). Neurons whose dendrites radiate symmetrically in all directions, such as many stellate and thalamocortical cells, instead form a closed field in which opposing currents largely cancel, so they contribute little to the scalp signal (Buzsáki, Anastassiou, & Koch, 2012). Because each dipole is tiny, thousands of neighboring pyramidal neurons must depolarize or hyperpolarize together for their summed field to survive volume conduction through the meninges, skull, and scalp and reach a recording electrode (Buzsáki et al., 2012).

Vertical cortical macrocolumns, on the order of a millimeter across, contain hundreds of thousands of pyramidal neurons together with supporting stellate and basket cells (Thompson & Thompson, 2015). Each cortical pyramidal neuron may receive on the order of 5,000 to 30,000 synapses. These macrocolumns are positioned side by side and perpendicular to the cortical surface, and since neighboring macrocolumns often receive the same afferent messages, they tend to fire together and generate a potential detectable from the scalp. A reliable scalp EEG requires a minimum of 6 cm² of synchronized cortex (Dyro, 1989).

Although thalamic pacemakers generate EEG rhythms, resonant loops between cortical macrocolumns represent another source (Traub et al., 1989). Over 97 percent of the brain's conversations are cortical-to-cortical, primarily within the same hemisphere (Thompson & Thompson, 2015). A resonant loop develops when macrocolumns that share afferent input fire synchronously to generate an electrical potential. The distance between participating macrocolumns is one determinant of EEG frequency: the closer the macrocolumns, the higher the frequency they can generate (Lubar, 1997).

There are three types of resonant loops driven by afferent input or thalamic pacemakers. Local loops couple neighboring macrocolumns and may generate frequencies above 30 Hz in the high-beta and gamma ranges. Regional loops couple macrocolumns separated by several centimeters and may produce alpha and beta rhythms. Global loops couple macrocolumns as distant as 7 cm (for example, between the frontal and parietal lobes) and may create delta and theta rhythms. The graphic below is conceptual, and should not be taken literally with respect to distance or anatomical location.

While only 3 percent of linkages are thalamocortical, they greatly influence the EEG by subcortically connecting distant cortical regions and producing most synchronous activity (Steriade, 2005).

Lubar (1997) proposed a violin analogy: the thalamic pacemakers firing at varying frequencies are the strings, and the resonant loops introducing different time delays are the instrument's resonant cavity.

Spindling is a synaptically generated oscillation in a circuit that includes the reticular nuclei (Steriade, 2005). The video of alpha spindling © John S. Anderson.

Different spindle frequencies result from corresponding durations of thalamocortical neuron hyperpolarization. Longer hyperpolarizations associated with EEG synchronized states produce 7-Hz or lower-frequency spindles, while relatively short hyperpolarizations result in 14-Hz spindles (Steriade, 2005). The electrical potentials generated by the thalamus can volume conduct near the speed of light through cerebrospinal fluid (CSF), brain tissue, the skull, and the scalp, so that nearly identical waveforms can simultaneously appear at distant sites (Fisch, 1999; Thompson & Thompson, 2015). This is an important consideration when interpreting EEG topographic maps. Activity at a given electrode may not originate from the cortex directly beneath it.

The Locus Coeruleus Inhibits Thalamic Alpha Generators

When we are inattentive, thalamic pacemakers generate the alpha rhythm. When we need to focus attention, we activate the brainstem noradrenergic locus coeruleus, a small but powerful nucleus roughly 15 mm long. The increased release of norepinephrine by this structure focuses attention and abolishes alpha oscillations by suppressing thalamic alpha generators. This may be an underlying mechanism of the phenomenon of alpha blocking.

Although researchers cannot noninvasively monitor locus coeruleus activity in human participants, it correlates with pupil dilation. In human studies, the greater the alpha blocking response and pupil dilation, the better the performance on demanding attention tasks (Dahl et al., 2020; Dahl et al., 2022). Critically, the alpha rhythm is not a cause but a sign that incoming stimulation is too weak to overcome inhibition by the reticular nucleus. EEG activity is not causal; it reflects network activity that has already occurred.

Additional Subcortical Generators

Several subcortical systems desynchronize or disrupt brain rhythms through ascending projections. These include the basal forebrain, reticular formation, locus coeruleus, and raphe systems. These neurons receive information from most sensory systems and cortical regions, and they desynchronize the EEG both directly through synapses on cortical neurons and indirectly through innervation of thalamic pacemakers. Desynchronization shifts pyramidal neurons from burst firing to more continuous single-spike generation (Fisch, 1999).

The cholinergic basal forebrain, located in the ventral frontal lobe and anterior hypothalamus, influences cerebral blood flow and cognitive activity. The basal forebrain comprises several structures, including the basal nucleus of Meynert, medial septal nuclei, substantia innominata, nucleus accumbens, ventral pallidum, and olfactory tubercle. Of these, the basal nucleus of Meynert and the medial septal nuclei are the principal sources of the neurotransmitter acetylcholine.

The reticular activating system (RAS) includes a network of roughly 90 nuclei within the central brainstem, extending from the lower medulla to the upper midbrain, that activates the brain to promote attention, consciousness, and wakefulness. This network receives input from ascending sensory tracts (auditory, olfactory, somatosensory, and visual systems) and projects both to the thalamus and diffusely to the cortex, including pathways that bypass the thalamus entirely.

The noradrenergic brainstem locus coeruleus system projects to the thalamus, limbic system, and cerebral cortex and contributes to wakefulness and vigilance for salient stimuli. The neurotransmitter norepinephrine (also called noradrenaline) is synthesized chiefly by neurons of the locus coeruleus, a small, pigmented nucleus situated in the dorsal pons along the lateral floor of the fourth ventricle. Its axons project diffusely throughout the neuraxis, reaching the cerebral cortex, hippocampus, amygdala, thalamus, and cerebellum, along with descending fibers to the spinal cord. Through these widespread connections, the locus coeruleus regulates arousal, selective attention, the sleep-wake cycle, and the physiological response to stress.

Within these neurons, norepinephrine is produced through a sequential enzymatic pathway. Tyrosine hydroxylase converts the amino acid tyrosine to L-DOPA, aromatic L-amino acid decarboxylase then yields dopamine, and dopamine β-hydroxylase completes the final step inside synaptic vesicles. Although the locus coeruleus supplies most of the forebrain's norepinephrine, additional noradrenergic populations in the lateral tegmentum and medulla contribute to autonomic and brainstem circuits.

Finally, the serotonergic raphe system is a midline network of cell bodies within the brainstem and midbrain that may influence alertness and vigilance through reciprocal connections with the suprachiasmatic nucleus of the hypothalamus (Monti & Jantos, 2008). Together, these subcortical systems determine the brain's overall state of arousal, a critical variable in any biofeedback session.

Cortical and Subcortical Generators of Specific EEG Rhythms

Slow Cortical Potentials (0-1 Hz)

A slow cortical potential (SCP) is a gradual, sustained shift in the cortex’s baseline voltage that lasts from roughly 300 milliseconds to several seconds and reflects changes in the excitability of large populations of cortical neurons (Birbaumer et al., 1990). Slow cortical potentials (SCPs) have been identified in cortical neurons, the thalamus, and glial cells. Cortical neurons in layers II to VI generate slow oscillations even when the thalamus is removed or when cortical tissue is studied in vitro (in an artificial environment) or in vivo (within a living organism). Thalamic reticular neurons exhibit similar slow spontaneous oscillations when studied in vitro, and synchronized intracortical oscillations may depend on a corticothalamic network that targets these thalamic neurons.

The prevailing account attributes surface-negative SCPs to the synchronous depolarization of pyramidal apical dendrites, with a contribution from glial cells rather than a purely glial origin. Glia contribute by buffering extracellular potassium and by coupling to one another through gap junctions, which are direct electrical connections between glial cells. Glial cells communicate among themselves and with neurons, and their slow oscillations may influence the timing of neuronal firing through their control of potassium ion outflow (Steriade, 2005). These slow oscillations appear to organize the generation of other brain rhythms.

"The concept of a unified corticothalamic network that generates diverse types of brain rhythms grouped by the cortical slow oscillation (Steriade, 2001a,b) is supported by EEG studies in humans" (Mölle et al., 2002). Caton (1875) reported feeble currents of varying direction from electrodes placed on the cortical surface and observed that the surface becomes relatively negative during functional activity. Caton recorded galvanometer deflections rather than calibrated voltages, so his one-page report contains no microvolt figures; the numerical gradients sometimes attributed to him do not appear in it. Underlying "tone" or valence factors determine the firing characteristics of neurons within a network: when SCPs are more positive, reduced cortical neuron firing occurs due to hyperpolarization; when SCPs are more negative, increased firing occurs due to depolarization.

The following 19-channel BioTrace+ /NeXus-32 display of 0.1-1 Hz SCP activity © John S. Anderson.

Perspective on Fast Cortical Potentials

EEG "bands" are somewhat arbitrary ranges of frequencies that have evolved from observation and usage. The following BioTrace+ /NeXus-32 video of raw and spectral EEG displays © John S. Anderson. Frequency is plotted along the horizontal axis, and amplitude is shown on the vertical axis.

While frequency band labels are helpful descriptors, they can also be misleading. Classification of an EEG rhythm is based on context (measurement conditions and EEG activity during the specific epoch), frequency, and waveform morphology. Note, however, that for some purposes it is useful to define individual-specific frequency bands that depart somewhat from the classical definitions. For example, although the individual alpha peak typically sits near 10 Hz, some individuals peak nearer 8 or 9 Hz and others nearer 12 Hz, and this shift can affect the settings selected for neurofeedback (Tarasi & Romei, 2024).

The process of up-training or down-training signal amplitude in one or more of the EEG bands using an EEG is called EEG biofeedback or neurofeedback. Minimum EEG voltages of 20-30 μV are seen in children and adults (Krauss et al., 2011).

Brainwaves Reflect Behavior

The ratio of slow (theta) to faster (beta) brainwaves indicates how alert you are; this is the theta/beta ratio. A higher ratio suggests greater drowsiness or inattention, while a lower ratio reflects focused alertness. This metric is one of the most widely used in neurofeedback assessment.

In the next section, we will examine delta, theta, rhythmic slow-wave, alpha, mu, synchronous "alpha," SMR, beta, high or fast beta, and gamma activity.

Local Versus Global Decision-making

The short time windows of fast oscillators facilitate local integration and decision-making, primarily because of the limitations of axon conduction delays. In contrast, the long time windows of slow oscillators can involve many neurons in large or distant brain areas, favoring complex, global decisions. This principle has direct clinical implications: when you observe a client's EEG dominated by slow activity, it may reflect an over-reliance on global, less differentiated processing at the expense of focused, efficient local integration.

Delta (1-4 Hz)

There are two delta rhythms: a slow oscillation under 1 Hz and a traditional 1-4 Hz oscillation. The slow 0.3-0.4 Hz oscillation originates in the neocortex and persists when the thalamus is removed, while thalamocortical neurons generate the 1-4 Hz oscillations observed during human stage-3 sleep. Slow neocortical oscillations may synchronize the thalamic delta rhythm (Steriade, 2005).

Delta activity is generated by cortical neurons when other connections do not activate them and is found predominantly in frontal areas. Delta is associated with sleep and infancy, and during stage 3 (N3) sleep it accompanies the replenishment of astrocyte glycogen stores. Clinicians observe delta in clients diagnosed with ADHD, brain tumors, learning disorders, and traumatic brain injury (TBI). Rhythmic high-amplitude delta is particularly associated with TBI when localized, while diffuse delta may appear in ADHD and learning disorders.

Delta waves are the main EEG activity during infancy, reflecting the immature brain's low-frequency cortical activity. As neural networks develop and mature, faster rhythms like alpha and beta replace delta dominance in waking states. In adults, waking delta activity is minimal but may transiently appear during drowsiness or relaxation.

Normal Amplitudes

Delta should not be present in significant amounts in the awake adult EEG. "Apparent" delta is usually an eye movement artifact, although some delta activity probably occurs in the normal waking adult EEG. In clinical practice, delta bands are inhibited or down-trained but rarely rewarded, though delta desynchronization can be rewarded.

The following 19-channel BioTrace+ /NeXus-32 display of eyes-open 1-4 Hz activity from a 10-year-old male © John S. Anderson.

Theta (4-7 Hz)

Researchers define the boundaries of EEG frequency bands somewhat differently; theta is variously set at 3-8, 4-7, or 4-8 Hz. This curriculum uses 4-7 Hz throughout, which is also the boundary used by the glossary entries for the septohippocampal system and the entorhinal cortex. Where a cited study or a training display uses a wider band, the study's own boundary is retained and named.

The mechanisms that generate the theta rhythm are poorly understood, and theta's functions differ depending on location and source. Amzica and Lopes da Silva (2018) consider the classic septal/diagonal band pacemaker model incomplete. Hippocampal interneurons exercise top-down control over the hypothetical medial septum pacemaker, and the hypothalamic supramammillary nucleus, with extensive connections to the brainstem, diencephalon, and medial septum, may also pace and modulate hippocampal theta. A non-cholinergic theta source has also been found within the entorhinal cortex of the hippocampus.

Theta is associated with creativity, global synchronization, memory formation, and recall. Increased theta amplitudes correspond with hypo-perfusion (reduced blood flow) and decreased glucose metabolism. Excessive frontal theta is linked with depression, daydreaming, distractibility, and inattention. Theta/beta (T/B) ratios are developmentally mediated, so any cutoff has to be age-referenced. In Monastra et al. (1999), the control mean fell from roughly 3.0 at ages 6-11 to roughly 1.5 at ages 21-30, and the ADHD thresholds fell in parallel (see the table below). A ratio of 3.0 is therefore unremarkable in a 6-to-11-year-old and markedly elevated in a young adult.

Normal Amplitudes

Theta voltage is age-related in the awake EEG, diminishing from age 8 to 30 with minimal amounts over age 30. A typical 6-7 Hz rhythm in the frontal midline (FCz) is associated with mental activity such as problem-solving and a wide variety of other functions. This rhythm appears to be limbic in origin and is higher in amplitude and more synchronous when processing feedback that an error has occurred. The 4-Hz rhythm is associated with childhood pleasurable experiences and memory searches in adults.

Rhythmic Slow Wave (RSW or Theta)

Clinicians inhibit frontal theta to remediate symptoms and reward posterior RSW in alpha/theta training for addictions, global synchronization, optimal performance, and PTSD. RSW is generally not increased frontally. Clinicians may also train for increases or decreases in phase synchrony. RSW is mainly seen in the frontal-midline (FCz) when awake with eyes open and is generated by the limbic system and thalamus. Depending on location, RSW may represent slowed alpha as thalamic output decreases in frequency.

The following 19-channel BioTrace+ /NeXus-32 display of eyes-open 4-8 Hz activity from a 10-year-old boy © John S. Anderson.

Alpha (8-12 Hz)

The 8-12-Hz alpha rhythm differs from spindle waves in both its source and the activity during which it is observed. Alpha 1 (low alpha) ranges from 8-10 Hz, and alpha 2 (high alpha) from 10-12 Hz (Thompson & Thompson, 2015). Some authors extend the alpha band to 13 Hz; this unit uses 8-12 Hz throughout. Alpha rhythms depend on the interaction between rhythmic burst firing by a subset of thalamocortical (TC) neurons linked by gap junctions and rhythmic inhibition by widely distributed reticular nucleus neurons (Hughes & Crunelli, 2005). The alpha rhythm is maintained and propagated by cortical networks (Amzica & Lopes da Silva, 2018).

Researchers have correlated the alpha rhythm with relaxed wakefulness, though there are age- and function-related differences. Spindle waves, in contrast, originate in the thalamus and occur during unconsciousness and stage-2 sleep (Steriade, 2005). Alpha is the dominant rhythm in adults and is located posteriorly.

The 8-10 Hz range is associated with ADHD, daydreaming, fogginess, OCD, and TBI, while frontal asymmetry with excess left frontal alpha is associated with depression. The 10-12 Hz range is seen with inner calm (calm and alert) and meditation. Clinicians train alpha amplitude and phase synchrony up or down depending on location and presenting symptoms.

Posterior Dominant Rhythm (PDR)

The posterior dominant rhythm (PDR) is the posterior alpha rhythm, first visible at about 4 months of age with a frequency of around 4 Hz. Between 3 and 5 years, this rhythm is approximately 8 Hz with amplitudes as high as 100 μV. From 6 to 15 years, it reaches 9 Hz by age 7 and 10 Hz by ages 10-15, with a mean amplitude of 50-60 μV. Girls show a statistically faster maturation of posterior alpha frequency than boys.

From 13 to 21 years, the mean alpha frequency is 10 Hz, and amplitudes decline throughout this period. Faster alpha frequencies are associated with higher IQ and better memory performance. This developmental trajectory illustrates why age-appropriate normative comparisons are essential in clinical qEEG assessment.

The following 19-channel BioTrace+ /NeXus-32 display of the response of the posterior dominant rhythm to eyes opening and closing © John S. Anderson.

Normal Amplitudes

The typical adult alpha peak frequency ranges from 9.5-10.5 Hz, and alpha below 8 Hz is considered abnormal. Alpha frequency and amplitude decline throughout adulthood and into old age. Most adult amplitudes fall below 60 μV: about 66% of adults show 20-60 μV, 28% show less than 20 μV, and 6% show greater than 60 μV (Schomer & Lopes da Silva, 2011).

Higher alpha amplitudes are observed over the non-dominant (right) hemisphere, a normal pattern known as alpha asymmetry. Most studies show no effect of handedness. Asymmetry is generally no more than 20 μV or 20% of the greater of the two amplitudes (Amzica & Lopes da Silva, 2018). Clinicians should be familiar with these normative values, since departures from them often guide neurofeedback protocol selection.

Causes of Excessive Alpha Amplitudes

Sleep deprivation or metabolic exhaustion can result in high amplitude and slowing of the peak frequency, along with persistent alpha during an eyes-open condition. Meditation practices can cause increased amplitudes and slowing, a faster alpha response to an eyes-closed condition, and persistent alpha in an eyes-open condition.

Marijuana use and abuse can also cause increased amplitudes and slowing, along with persistent alpha in an eyes-open condition, depending on the type of marijuana. These effects can persist for many years following abstinence. Clinicians should consider substance use history when interpreting alpha findings.

The following 19-channel BioTrace+ /NeXus-32 display of eyes-closed 8-12 Hz activity from a 13-year-old girl © John S. Anderson.

Mu Rhythm (7-11 Hz)

While the 7-11-Hz mu rhythm usually overlaps with the alpha range, it is arc-shaped on top and pointed on the bottom of an analog EEG trace (i.e., a wicket rhythm) that differentiates it from the alpha waveform. The mu rhythm is also identified by its location over the sensorimotor strip. It can be recorded at C3 and C4 in a minority of subjects and appears when the person is awake and at rest. Actual, visualized, or observed movement suppresses it (Thompson & Thompson, 2015). Mu rhythms appear to index sensorimotor cortex activity, and mu suppression has been linked to the mirror neuron system of the premotor and inferior parietal cortex.

These mirror neuron circuits may play a critical role in imitation learning and our ability to understand the actions of others. Mu rhythms facilitate the conversion of visual and auditory input into integrated skill-building functions, and attenuation of the mu rhythm appears to be associated with the activation of this function (Pineda, n.d.). The mu rhythm is highlighted below.

This second example of the mu rhythm shows a classic 10-11 Hz and 19-20 Hz "Owl Eye" presentation. The mu rhythm has an arciform, comb-like shape that produces two spectral peaks in a nearly harmonic relationship: a fundamental near 10 Hz and a beta harmonic near 20 Hz (Tiihonen, Kajola, & Hari, 1989). In the single-hertz topographic maps below, the mu fundamental near 10-11 Hz and its beta component near 19-20 Hz each appear as a pair of left and right central hot spots that look like an owl's eyes on the head map, which is the source of the name. The term is informal field usage rather than a published descriptor.

Synchronous "Alpha"

Various sensory systems (auditory, somatosensory, and visual) produce localized and semi-independent "alpha" activity. However, synchronous, distributed alpha integrates perception and facilitates action across broader cortical networks. Synchronous "alpha" appears to block localized alpha-like patterns such as mu and the posterior rhythm in favor of more broadly distributed network integration during tasks requiring global processing.

Sensorimotor Rhythm (12-15 Hz)

The sensorimotor rhythm (SMR), also called beta 1, is located on the sensorimotor strip (C3, Cz, C4). SMR amplitude increases when the motor circuitry is idle; it increases with stillness and decreases with movement. Deficient SMR may be observed in movement-spectrum complaints like hyperactivity and tics. SMR appears as sleep spindles during stage-2 sleep and is associated with reduced blood perfusion and glucose metabolism in the brain as it transitions to deeper sleep stages.

Clinicians typically reward increased SMR amplitude to calm hyperactivity and during theta/beta ratio training. For practitioners working with athletes or military personnel, SMR training can promote the calm, focused stillness essential for precision tasks like marksmanship or surgical procedures.

The following 19-channel BioTrace+ /NeXus-32 display of 12-15 Hz activity © John S. Anderson.

Beta (over 12 Hz)

Beta consists of rhythmic activity between 12-38 Hz in four ranges: beta 1 (12-15 Hz), beta 2 (15-18 Hz), beta 3 (18-25 Hz), and beta 4 (25-38 Hz). However, writers may define beta subranges somewhat differently.

Beta shows a gradient of activity from occipital to frontal lobes, with more beta occurring frontally where it is associated with focus, analysis, and relaxed thinking (Thompson & Thompson, 2015). Excessive beta is observed in anxiety, depression (reversed asymmetry), insomnia, OCD, and sleep disorders, while deficient beta is seen in ADHD, cognitive decline, and learning disorders.

Since beta overlaps with the EMG range, clinicians must be careful when up-training this rhythm and should use an EMG inhibit, (a high-beta EEG proxy for EMG), to avoid inadvertently reinforcing muscle artifact. Beta is generated by the brainstem and cortex and is associated with hyper-perfusion and increased glucose metabolism.

Normal 16-20+ Hz Beta Amplitudes

Beta amplitudes are minimal in children up to 12 years, with a significant increase in beta amplitude and organization between 12 and 30 years. Beta is commonly seen in nearly all adults with amplitudes of 20 μV or less. Interhemispheric amplitude asymmetries exceeding 35% are abnormal.

The following 19-channel BioTrace+ /NeXus-32 display of 13-21 Hz activity © John S. Anderson.

Fast or High Beta Rhythms (20-35 Hz)

Fast 20-35-Hz oscillations are generated by activation of the mesencephalic reticular formation. Thalamocortical, rostral thalamic intralaminar, and cortical neurons spontaneously oscillate in this range. This activity is primarily seen in the frontal lobes and is associated with hyper-perfusion and increased glucose metabolism, though persistent excessive activity can lead to metabolic exhaustion.

Fast beta may be associated with peak performance and cognitive processing, particularly with specificity and precision in information processing. However, excessive high beta is associated with alcoholism, anxiety, OCD, rumination, and worry. Clinicians often inhibit high beta activity but rarely reward it. In clinical practice, persistent high beta at frontal sites, particularly if it shows a spindling appearance, is one of the most common EEG signatures of anxiety disorders.

The following 19-channel BioTrace+ /NeXus-32 display of eyes-closed approximately 25 Hz fast beta activity © John S. Anderson.

Gamma Rhythms (28-80 Hz)

Because this unit ends beta at 38 Hz and begins gamma at 28 Hz, the two bands overlap between 28 and 38 Hz; clinical electroencephalography more often ends beta near 30 Hz. Any scalp band edge above roughly 30 Hz is also vulnerable to EMG contamination. Amzica and Lopes da Silva (2018) concluded that gamma oscillations might speed information distribution and processing. Gamma bursts occur during problem-solving, and the absence of gamma is associated with cognitive deficits and learning disorders. Gamma synchrony is related to cognitive processing and contributes specificity and precision to information processing. Gamma is theorized to serve as a "binding rhythm" that integrates sensory inputs into unified perception and consciousness.

The following 19-channel BioTrace+ /NeXus-32 display of eyes-open 36-44 Hz activity in a 10-year-old boy © John S. Anderson.

Gamma rhythms are linked with SCPs. The following BioTrace+ /NeXus-32 display of SCP and gamma activity © John S. Anderson.

In summary, the brain generates EEG rhythms through an interplay of thalamic pacemakers, cortical resonant loops, and subcortical modulators. Each frequency band reflects distinct physiological processes and clinical states, from delta's association with sleep and injury to gamma's role in cognitive binding. Understanding these generators equips clinicians to make informed decisions about which rhythms to train and why.

General Cortical and Subcortical Anatomy

This section provides an overview of the nervous system's major divisions, from the central and peripheral nervous systems to the brain's subdivisions, protective structures, and vascular supply. These anatomical foundations are essential for understanding where EEG signals originate and how they are altered before reaching scalp electrodes.

Major Divisions

The human nervous system consists of the central nervous system and peripheral nervous system. The central nervous system (CNS) consists of the brain, spinal cord, and retina. Central nervous system graphic © SciePro/Shutterstock.

The 3-pound brain consists of approximately 86 billion neurons (Azevedo et al., 2009; Voytek, 2013). Graphic © Jasada Sabai/Shutterstock.com.

The cylindrical spinal cord extends from the medulla (brainstem) to the lumbar (lower back) segment of the vertebral column. It distributes sensory information from the body to the brain and CNS commands from the brain to the body, and also contains networks that control reflexes and central pattern generators. Graphic © Silver Place/Shutterstock.com.

The peripheral nervous system (PNS) consists of neurons and nerves outside of the brain and spinal cord and is comprised of the autonomic nervous system and somatic nervous system. Peripheral nervous system graphic adapted from © Elena Ladanovskaya/Shutterstock.com.

Nerves

Nerves are bundles of axons that lie outside of the central nervous system. Motor nerves distribute instructions from the CNS to the rest of the body, while sensory nerves transmit information from sensory receptors to the CNS.

There are three major systems of nerves: cranial nerves, spinal nerves, and the autonomic nervous system.

The 12 pairs of cranial nerves distribute sensory and motor information. Three are exclusively sensory pathways to the brain: olfactory (I), optic (II), and vestibulocochlear (VIII). Five are exclusively motor pathways from the brain: oculomotor (III), trochlear (IV), abducens (VI), spinal accessory (XI), and hypoglossal (XII). Four cranial nerves carry both sensory and motor information: trigeminal (V), facial (VII), glossopharyngeal (IX), and vagus (X). Graphic adapted from © Alila Medical Media/Shutterstock.com.

Thirty-one pairs of spinal nerves, each member serving one side of the body, leave the spinal cord through openings in the backbone. Spinal nerve graphic © SciePro/Shutterstock.com.

Each spinal nerve carries sensory projections from the body (dorsal root) and motor commands from the spinal cord to skeletal muscles (ventral root). Graphic adapted from © Designua/Shutterstock.com.

Autonomic Nervous System

The autonomic nervous system regulates cardiac and smooth muscle and glands, transmits sensory information to the CNS, and innervates muscle spindles. It is the brain's main system for monitoring and controlling major organs.

While we normally exercise little intentional, conscious autonomic control, self-regulation disciplines like yoga and extensive research in biofeedback have demonstrated that we can learn voluntary autonomic control. Clinicians can train clients to regulate heart rate variability, peripheral blood flow to the fingers, toes, and scalp, and finger sweat gland activity to treat disorders and achieve optimal performance.

The autonomic nervous system is divided into three main systems: sympathetic, parasympathetic, and enteric. Check out the YouTube video, The Autonomic Nervous System.

We activate the sympathetic nervous system when we encounter a threat that we can fight or flee, but we also activate this branch when we get up from the couch or exercise. The parasympathetic system can oppose or complement sympathetic activity. When we feel safe, it allows us to self-regulate (through meditation or neurofeedback skills), socially engage with others, and engage in executive functions like planning. When we feel endangered and cannot fight or flee, this system produces freezing, fainting, or dissociation responses.

The enteric system consists of over 100 million neurons that release over 30 neurotransmitters to control the gut under CNS supervision, helping to maintain fluid and nutrient balance.

Somatic Nervous System

The somatic nervous system is comprised of spinal nerves that innervate somatosensory receptors in the skin, joints, and skeletal muscles. While somatic motoneuron cell bodies lie in the CNS, most of their axons are in the PNS. The cell bodies of somatic sensory neurons are in the PNS dorsal root ganglia. Dorsal root graphic adapted from © stihii/Shutterstock.com.

Lecture: Neuroanatomy Part 2

Navigating the Brain

Orientations

Three customary planes for viewing the body and brain are sagittal, coronal, and horizontal.

The sagittal plane divides the body into right and left halves. The coronal plane separates the body into front and back parts. The horizontal (transverse) plane divides the brain into upper and lower parts (Breedlove & Watson, 2023). These planes are used in neuroimaging and help clinicians interpret brain scans and localize areas of interest for neurofeedback training. Graphic adapted from Blausen.com staff "Blausen gallery 2014," Wikiversity Journal of Medicine.

Directional Terms

Important directional terms include medial (toward the middle) and lateral (toward the side), ipsilateral (same side) and contralateral (opposite side), superior (above) and inferior (below), anterior/rostral (toward the head) and caudal (posterior, toward or at the back), proximal (near the center) and distal (toward the periphery), and dorsal (toward or at the back) and ventral (toward the belly) (Breedlove & Watson, 2023). Graphic adapted from Blausen.com staff "Blausen gallery 2014," Wikiversity Journal of Medicine.

Cortical Features

The adult human brain has a volume of roughly 1,100 to 1,300 cm³, varying with sex and body size, and requires convolutions to fit within the skull (Bear, Connors, & Paradiso, 2020). If the cortex were flattened into a sheet, its surface area would be about 2,000 to 2,500 cm², roughly a quarter of a square meter or 2 to 2.7 square feet, with about two-thirds of the cortical surface lying within these folds (Breedlove & Watson, 2023). Anatomists distinguish three topographical features of the cerebral cortex: gyrus, sulcus, and fissure.

A gyrus is a ridged area of the brain. The precentral gyrus, anterior to the central sulcus, is the primary motor cortex (controlling muscles and movements). The postcentral gyrus, posterior to the central sulcus, is the primary somatosensory cortex (receiving somatosensory information).

A sulcus is a groove in the cortical surface. The central sulcus separates the primary motor cortex from the primary somatosensory cortex. A fissure is a deep groove; for example, the Sylvian fissure (also called the lateral fissure or lateral sulcus) forms the upper boundary of the temporal lobe (Breedlove & Watson, 2023). These features serve as reference landmarks for navigating brain anatomy.

The Unfixed Brain

This video was produced by Suzanne Stensaas, PhD, Department of Neurobiology and Anatomy, and the Spencer S. Eccles Health Sciences Library, University of Utah.

Dissecting Brains

This video is courtesy of the Wellcome Collection.

Lateral and Medial Brain Landmarks

Subdivisions of the Brain

The brain is divided into three major subdivisions: forebrain, midbrain, and hindbrain. Brain landmark graphic adapted from © snapgalleria/Shutterstock.com.

Medial brain section graphic adapted from © NatthapongSachan/Shutterstock.com.

The forebrain consists of the telencephalon (cerebral hemispheres) and the diencephalon. The telencephalon encompasses the cerebral cortex and the deeper structures of the basal ganglia and limbic system. Limbic system graphic © SciePro/Shutterstock.com.

The diencephalon in the posterior forebrain contains the thalamus and hypothalamus. Thalamus graphic © SciePro/Shutterstock.com.

The midbrain consists of the mesencephalon, which includes the inferior colliculi, superior colliculi, and substantia nigra. The degeneration of the substantia nigra is a key step in developing Parkinson's disease. Substantia nigra graphic © Kateryna Kon/Shutterstock.com.

The hindbrain contains the metencephalon and myelencephalon. The metencephalon is comprised of the cerebellum and pons. The cerebellum plays a role in higher-level functions like emotional and cognitive regulation, influencing the speed, capacity, consistency, and appropriateness of cognitive and emotional processes. Damage to the cerebellum can impair cognitive and affective performance as well as movement.

The cerebellum provides coordination and fine-tuning of balance and movement, addressing the rate, rhythm, and force of movement as well as analogous qualities in thinking and emotional expression. Cerebellum graphic with highlighted Purkinje neuron © Kateryna Kon/Shutterstock.com.

The myelencephalon consists of the medulla, which plays a critical role in the speeding and slowing of the heart across each breathing cycle, a phenomenon called respiratory sinus arrhythmia (RSA). This process is a key target in heart rate variability (HRV) biofeedback training. Alcohol, opioids, and sedative-hypnotics can fatally depress brainstem respiratory centers, slowing and halting breathing. Medulla graphic © mkfilm/Shutterstock.com.

The Skull

The human skull is a complex anatomical structure that plays a significant role in protecting the brain and influencing EEG signal measurement. Skull anatomy graphic adapted from © Magic mine/Shutterstock.com.

Comprising 22 bones, the skull is divided into the cranium, which houses the brain, and the facial bones. The cranium is composed of several major bones, including the frontal, parietal, temporal, and occipital bones, fused together by sutures. This bony framework provides a rigid protective case for the brain while also anchoring the meninges and other protective layers (Niedermeyer & Lopes da Silva, 2004).

The skull's primary function is to protect the brain from physical damage. Its bones have an average thickness of about 6.5 mm in adults, which significantly impacts EEG signal transmission. The skull acts as a low-pass filter, attenuating high-frequency components of the brain's electrical activity while allowing lower-frequency components to pass through. The skull can reduce signal amplitude by approximately 85% (He & Li, 2010), primarily due to its low conductivity compared to brain and scalp tissues. This filtering effect is a crucial consideration in EEG signal analysis and interpretation (Sanei & Chambers, 2013).

For example, if a skull defect leaves an opening, then fast-frequency EEG will be seen over the defect (i.e., breach rhythm).

The skull's high impedance means that much of the electrical activity generated by neurons is dissipated before reaching scalp electrodes, making it more challenging to detect subtle neural oscillations. Additionally, the varying thickness and composition of skull bones can introduce spatial distortions in EEG signals, complicating the localization of neural activity sources (Lopes da Silva, 2010).

The skull's heterogeneous structure, including both dense cortical bone (dense bone that forms a cortex or “bark” around the bone) and less dense cancellous bone (porous bone in the marrow-filled medullary cavity of bones), causes anisotropic attenuation, meaning that the degree of signal reduction varies depending on the direction of electrical currents (i.e., the skull conducts current more readily along some directions than others, so the degree of attenuation depends on the orientation of the current path and not on distance alone). This anisotropy must be accounted for in advanced EEG analysis techniques such as source localization and brain connectivity studies (Nunez & Srinivasan, 2006).

In addition to the bones, the skull's sutures and foramina (openings) influence EEG signal propagation. Sutures can act as additional barriers or channels for electrical signals, while foramina may create localized points of less attenuation. Individual variability in skull anatomy also significantly influences EEG signals: children's skulls are generally thinner and less dense than those of adults, potentially resulting in less signal attenuation (Schoffelen & Gross, 2009). The scalp and meninges add further layers of impedance that electrical signals must traverse, each with distinct electrical properties. Understanding the combined effect of these tissues is essential for accurate EEG interpretation and for the development of advanced EEG techniques (Niedermeyer & Lopes da Silva, 2004).

Meninges

Three meninges protect the brain and spinal cord, which are housed within the skull and vertebrae. The choroid plexus of the ventricles produces cerebrospinal fluid, which then circulates through the ventricles and the subarachnoid space of the meninges. These membranes include the dura mater, pia mater, and middle arachnoid (Breedlove & Watson, 2023). Graphic adapted from © Alilia Medical Media/Shutterstock.com.

Cerebral Ventricles

The cerebral ventricles are a network of fluid-filled chambers that protect the brain from trauma due to abrupt head movements and facilitate the exchange of nutrients and wastes between blood vessels and the brain. These cavities, found within all four lobes of each hemisphere, include the lateral, third, and fourth ventricles.

The brain contains four interconnected ventricles. A pair of lateral ventricles occupies the two cerebral hemispheres, the third ventricle sits in the midline between the left and right halves of the thalamus and hypothalamus, and the fourth ventricle lies between the pons and upper medulla in front and the cerebellum behind. Narrow channels connect these cavities: the paired interventricular foramina (foramen is the singular, meaning opening) join each lateral ventricle to the third ventricle, and the cerebral aqueduct joins the third ventricle to the fourth (Breedlove & Watson, 2023). Graphic adapted from © joshya/Shutterstock.com.

Glymphatic System

The glymphatic system is a recently discovered lymphatic-like system in the brain. It provides a flow of CSF through the brain's interior that helps clear cellular debris, proteins, and other wastes. Glymphatic system graphic © Claus Lunau/Science Photo Library.

Also known as the glymphatic clearance pathway or the paravascular system, this system clears waste and fluid from the vertebrate central nervous system (CNS). Interstitial fluid is removed via the cerebrospinal fluid (CSF). It is similar to the lymphatic system, but functions to remove waste products from the brain and spinal cord. This view shows the subarachnoid space (across top) between the brain and its membranes. The blue arrows show the movement of interstitial fluid and solutes.

By removing harmful substances such as the amyloid-beta and tau proteins implicated in Alzheimer's disease and the alpha-synuclein implicated in Parkinson's disease, the glymphatic flow may protect us from various neurological disorders (Breedlove & Watson, 2023). The glymphatic system removes most of its waste during stage-3 sleep (slow-wave sleep), which underscores the clinical importance of healthy sleep, a factor biofeedback practitioners should assess in every client.

The Brain's Vascular System

The resting brain consumes over 20% of the body's energy. The internal carotid artery's anterior and middle cerebral arterial branches deliver blood to about two-thirds of the cerebral hemispheres, while the paired vertebral arteries merge to form the basilar artery, whose left and right posterior cerebral arterial branches supply blood to the posterior cerebral hemispheres, cerebellum, and brainstem (Breedlove & Watson, 2023).

The effects of a stroke due to blood vessel blockage or rupture may be limited because paired arteries supply each brain hemisphere. The circle of Willis, a vascular network at the base of the brain comprised of the carotid and basilar arteries, may provide an alternate route for delivering blood when a major artery is compromised by disease or traumatic injury. The veins and sinuses drain deoxygenated blood, completing the circulatory loop to the heart via the jugular vein. Graphic adapted from © Alilia Medical Media/Shutterstock.com.

The figure below shows areas of the cortex that may be affected by strokes affecting the three major cerebral arteries.

After perfusing the brain, blood depleted of oxygen, glucose, and other nutrients drains into a network of cerebral veins that differs strikingly from the venous anatomy found elsewhere in the body. Unlike most veins, cerebral veins are thin-walled, lack valves, and do not travel alongside their companion arteries, so drainage depends on pressure gradients and posture rather than on one-way valves. Superficial cortical veins collect blood from the outer surface of the cerebrum and empty into the dural venous sinuses, most notably the superior sagittal sinus, while deep veins gather blood from the basal ganglia, thalamus, and deep white matter and channel it through the great cerebral vein of Galen into the straight sinus. These sinuses converge at the confluence of the sinuses, then course through the transverse and sigmoid sinuses before exiting the skull as the internal jugular veins, which carry the blood toward the superior vena cava and the right atrium.

The same dural sinuses also house meningeal lymphatic vessels, a discovery that overturned the long-held belief that the central nervous system lacked lymphatic drainage and now links cerebral venous anatomy to waste clearance and immune surveillance in the brain (Aspelund et al., 2015; Louveau et al., 2015).

Blood-Brain Barrier

The blood-brain barrier (BBB) is a highly selective, semipermeable interface formed by the endothelial cells that line the brain's microvasculature, where continuous tight junctions seal the spaces between adjacent cells and force most substances to move through the cells rather than between them. This barrier is not the work of endothelial cells alone but of a coordinated neurovascular unit that also includes pericytes embedded in the capillary wall, the endfeet of astrocytes that ensheath the vessels, microglia, and the surrounding basement membrane.

Together these components induce and maintain the barrier's low permeability, minimal pinocytosis, and dense expression of transport proteins that set brain capillaries apart from those elsewhere in the body (Abbott et al., 2010). The result is a living border that behaves less like a passive wall and more like a tightly regulated gatekeeper for the central nervous system (Daneman & Prat, 2015).

Functionally, the BBB shields neural tissue from circulating pathogens, toxins, and swings in blood composition while precisely controlling the traffic of ions, nutrients, and signaling molecules that keep the neuronal microenvironment stable. Small lipid-soluble gases such as oxygen and carbon dioxide diffuse across freely, whereas glucose, amino acids, and other essential polar molecules depend on specific carrier and receptor-mediated systems, and efflux pumps actively return many foreign compounds to the blood (Abbott et al., 2010).

This same protective selectivity is a double-edged property, because it excludes the vast majority of small-molecule drugs and nearly all large-molecule therapeutics, making the BBB one of the central obstacles in treating neurological and psychiatric disorders. When the barrier breaks down, as it does in conditions ranging from stroke and multiple sclerosis to Alzheimer's disease, the loss of this regulation contributes directly to disease progression, which is why BBB integrity remains a priority in both neuroscience and drug development (Daneman & Prat, 2015).

Interim Summary

The nervous system's architecture (from its major divisions to the protective skull, meninges, and vascular supply) directly affects how we record and interpret brain signals. Skull thickness, meningeal layers, and vascular dynamics all influence the EEG data you collect in clinical sessions.

Major Functions of Cortical Lobes and Major Subcortical Structures and Brodmann Areas

This section surveys the functional roles of the brain's major cortical lobes, the insular cortex, the mirror neuron system, key subcortical structures, and the fiber tracts that connect them. For biofeedback practitioners, understanding these structure-function relationships is fundamental to interpreting EEG patterns and selecting training protocols.

Cortical Lobes

The cortical lobes are named for the overlying bones of the skull (Breedlove & Watson, 2023). Graphic © Sebastian Kaulitzki/Shutterstock.com.

The cortex is required for executive functions like attention, planning, and problem-solving.

Without a cerebral cortex, a person would be blind, deaf, dumb, and unable to initiate voluntary movement (Bear, Connors, & Paradiso, 2020, p. 205).

The five major cortical regions include the frontal, parietal, temporal, and occipital lobes, and the insula (not shown). Cortical lobes graphic adapted from © Madrock24/Shutterstock.com.

Frontal Lobes

The frontal lobes (Fp1, Fp2, F7, F3, Fz, F8, F4) consist of the cortex anterior to the central sulcus and include the primary motor cortex, motor association cortex, Broca's area, and prefrontal cortex. These structures collectively support everything from fine motor control to the highest-level executive functions.

Frontal lobe damage may result in impaired flexibility and problem solving, increased risk-taking, changes in social behavior, an inability to use external cues, and deficits in emotional self-regulation. Graphic © ART-ur/Shutterstock.com.

The primary motor cortex is located in the precentral gyrus (Brodmann area 4, BA 4). It organizes the opposite side of the body's muscles and movements required for fine motor coordination in tasks like writing. Lesions can result in loss of motor control, including rigid paralysis. The graphic below, which shows the motor and sensory homunculi, was retrieved from the nccpbwikiproject.

The motor association cortex (premotor cortex), rostral to the primary motor cortex (BA 6), helps program and execute movements. Think of the motor association cortex as the piano player and the primary motor cortex as the keyboard (Carlson & Birkett, 2017). The primary and motor association cortex collectively appear to map behaviors rather than specific muscles or movements (Breedlove & Watson, 2023).

Broca's area, located in the inferior frontal gyrus (BA 44 and 45) of the dominant hemisphere (F7), is concerned with speech production, grammar, language comprehension, and sequencing (Caplan, 2006). Lesions to Broca's area can produce Broca's aphasia, an inability to produce fluent speech despite relatively intact comprehension. Broca's area receives input from Wernicke's area via the arcuate fasciculus (Breedlove & Watson, 2023). Graphic courtesy of Blausen.com staff "Blausen gallery 2014," Wikiversity Journal of Medicine.

The prefrontal cortex (PFC) (BA 9, 10, 11, 12, 25, 32, 44, 45, 46, 47) is rostral to the motor association area. The PFC participates in executive functions, including attention, working memory, outcome prediction for current and hypothetical actions, goal-directed behavior, problem-solving, planning, and the ability to suppress actions that could lead to unwanted outcomes (Diamond, 2013). The PFC integrates emotion and reward in decision-making (Fuster, 2015).

Important subdivisions of the PFC include the orbitofrontal cortex, ventromedial PFC, and dorsolateral PFC.

The orbitofrontal cortex (OFC) comprises Brodmann areas 10, 11, and 47 in Brodmann's human map, subdivided in the Walker scheme as areas 11, 13, 14, and 47/12 (Kringelbach, 2005); areas 9 and 46 belong to the dorsolateral prefrontal cortex, not the OFC. The OFC aids planning by evaluating the consequences (rewards and punishments) of our actions and helps generate the motivation to ingest drugs. The profound personality changes suffered by Phineas Gage resulted from damage to this subdivision and the ventromedial PFC. The OFC adjusts decision-making based on the stakes involved, enabling us to switch between significant (investments) and trivial (snacks) choices. It compares current options with recent ones, while the anterior cingulate cortex registers our predictions and prediction errors (Kennerley et al., 2011).

The ventromedial prefrontal cortex (VMPFC) corresponds to the ventromedial reward network (Öngür & Price, 2000) and includes BA 10, 25, 32, and parts of 11, and 12. The VMPFC is implicated in decisions where outcomes are uncertain and moral values must be applied to real situations. Patients with VMPFC damage choose options that lead to immediate reward regardless of future cost and do not learn from their mistakes. Since they have difficulty reading social cues, they may not recognize deception, irony, or sarcasm (Zald & Andreotti, 2010) and may struggle to control emotional reactions in social situations, particularly anger and violence (Carlson & Birkett, 2017).

The dorsolateral prefrontal cortex (DLPFC) is located in the middle frontal gyrus and includes BA 9 and 46. The DLPFC shares responsibility with cortical and subcortical networks for executive functions like abstract reasoning, cognitive flexibility, decision-making, inhibition, planning, and working memory (Miller & Cummings, 2007). It exercises the highest cortical level of motor control (Hale & Fiorello, 2004).

The left DLPFC is concerned with approach behavior and positive affect, helping us select positive goals and organize behavior to achieve them. The right DLPFC organizes withdrawal-related behavior and negative affect and mediates threat-related vigilance, playing a role in working memory for object location. In unipolar depression and premenstrual dysphoric disorder, the right DLPFC may be more active than the left, producing the alpha asymmetry pattern that is one of the most commonly targeted findings in neurofeedback for depression.

Anterior Cingulate Cortex (ACC)

The cingulate cortex has reciprocal connections with the parahippocampal gyri, integrates limbic functions, and is part of the salience network. Cingulate cortical functions include nurturing, grooming, play, and organizing and managing input/output functions.

The anterior cingulate cortex (ACC) (Fpz and Fz) lies above the corpus callosum (BA 24, 32, 33). The dorsal ACC connects to both the PFC and parietal cortex. The ACC plays a vital role in attention, is activated during working memory, and mediates both emotional and physical pain. It has cognitive (dorsal anterior cingulate) and affective (ventral anterior cingulate) conflict-monitoring components. Graphic courtesy of Geoff B. Hall in Wikimedia Commons.

The Stroop test illustrates a cognitive monitoring task where color and name information conflict, while discrepancies between facial and vocal cues present an affective conflict. The anterior cingulate recruits other brain areas to resolve these conflicts.

The anterior cingulate gyrus helps us allocate attention: focusing on a target, disengaging, perceiving options, and making adaptive choices. The anterior cingulate gyrus, prefrontal cortex, and caudate function abnormally in children diagnosed with ADHD during selective attention tasks. Importantly, fMRI evaluation showed that neurofeedback could teach children to normalize activity in these structures (Beauregard & Levesque, 2006).

The anterior cingulate gyrus is also involved in motivation and the perception of emotional and physical pain. Eisenberger, Lieberman, and Williams (2003) used fMRI to study brains of subjects who believed that two companions in Cyberball, an online ball-tossing game, had suddenly begun excluding them; their emotional distress activated the anterior cingulate cortex, the same region that evaluates physical pain. deCharms and colleagues (2005) provided real-time fMRI feedback from the rostral anterior cingulate, and subjects learned to increase and decrease its activation, with corresponding increases and decreases in the rated intensity of a noxious thermal stimulus.

Lesions to the cingulate can produce akinetic mutism, a state of markedly reduced spontaneous movement and speech despite preserved wakefulness, in which orienting responses are absent or greatly diminished. Cingulate malfunction can also result in addictive behaviors (alcohol or drug abuse, eating disorders, chronic pain), obsessive-compulsive disorder and OCD spectrum disorders, and "road rage."

Parahippocampal Gyri

The parahippocampal gyri are located within the medial temporal lobe. They form spatial and nonspatial contextual associations, which serve as building blocks for contextual processing, episodic memory, navigation, and scene processing (Aminoff, Kveraga, & Bar, 2013). They may also play a role in emotional responsiveness. Polygon data were generated by Database Center for Life Science (DBCLS). Creative Commons Attribution-Share Alike 2.1 jp.

Parietal Lobes

The parietal lobes (Pz, P3, P4) are posterior to the frontal lobes and are divided into the primary somatosensory cortex and secondary somatosensory cortex. Their main function is to process somatosensory information like pain and touch.

The primary somatosensory cortex (S1) is located in the parietal lobe's postcentral gyrus, posterior to the central sulcus (BA 3, 1, and 2). S1 maps touch and pain information from the opposite side of the body. The secondary somatosensory cortex (S2), which lies in the parietal operculum (BA 40 and 43), receives projections from it and maps touch and pain from both sides of the body (Breedlove & Watson, 2023). Graphic adapted from Paskari from Wikimedia Commons.

The parietal cortex monitors our preparation for a movement and is responsible for our subjective feeling of intending to move (Sirigu et al., 2004).

The angular gyrus, located near the superior temporal lobe (BA 39), is involved in reading, math, and copying writing.

The supramarginal gyrus (BA 40) forms part of the inferior parietal lobule and, like the neighboring angular gyrus (BA 39), functions as a convergence zone where somatosensory, auditory, and visual information are integrated. Positioned at the posterior end of the lateral sulcus, it draws on this multimodal input to support several higher-order functions.

In written language, it contributes to phonological processing during reading and writing, helping map the sounds of speech onto their corresponding letters and words. Its role in verbal working memory reflects its involvement in the phonological store, the component of the phonological loop that briefly holds speech-based information for rehearsal. The right supramarginal gyrus also supports social cognition by helping a person distinguish their own emotional state from that of others, a process central to empathy.

Both the angular gyrus and the supramarginal gyrus are in the vicinity of the P3 electrode site.

Temporal Lobes

The temporal lobes lie beneath the temporal bone at the sides of the head, below the T3 and T5 electrode sites on the left and the T4 and T6 sites on the right. They contain numerous Brodmann areas, both laterally (20, 21, 22, 37, 38, 41, and 42) and medially (20, 27, 28, 34, 35, 36, 37, and 38); note that several of these areas wrap around from the lateral to the medial cortical surface. The temporal lobes process hearing, smell, and taste information and help us understand spoken language and recognize visual objects and faces (Breedlove & Watson, 2023).

Their medial cortex is involved in emotional experience and new memory formation. In the language-dominant hemisphere (usually the left), Wernicke's area lies beneath electrode sites C3, T3, and T5 and encompasses posterior regions of Brodmann areas 22, 41, and 42.

Wernicke's area, located in the temporoparietal cortex (BA 22) of the dominant hemisphere, is specialized for the comprehension of spoken and written language. Damage can result in an inability to understand the meaning of speech and to construct meaningful sentences, a condition known as Wernicke's aphasia, in which speech output remains fluent but is empty of meaning and carries paraphasias and neologisms. Graphic adapted from Blausen.com in the Wikiversity Journal of Medicine.

Occipital Lobes

The occipital lobes (Oz, O1, O2) are posterior to the parietal lobes. The primary visual cortex (V1) is located within the calcarine sulcus (BA 17). The occipital lobes process visual information from the eyes in collaboration with the frontal, parietal, and temporal lobes. Graphic © ART-ur/Shutterstock.com.

Their primary functions are visual, including the analysis of orientation, color, spatial frequency, illusory contours, and complex patterns like concentric and radial stimuli (Breedlove & Watson, 2023). The occipital lobes are the primary source of the posterior dominant alpha rhythm, making them a key region of interest in neurofeedback assessment.

Insular Cortex

The insular cortex lies buried deep within the lateral sulcus, concealed by the frontal, parietal, and temporal opercula, and corresponds to Brodmann area 13. It supports interoception (awareness of internal bodily states), autonomic regulation, emotional processing, and social cognition, and serves as a core hub of the salience network. It detects salient events via afferent pathways and switches between other large-scale networks when such events are identified, affecting attention and working memory. The anterior and posterior insulae interact to regulate autonomic responses to salient stimuli, and interactive communication between the insula and anterior cingulate cortex facilitates motor control (Menon & Uddin, 2010). The right insula mediates awareness of our body, empathy, and understanding others' points of view (Khazan, 2019).

Increased heart rate variability strengthens the connectivity between the ACC and the insula for empathy and the ability to understand others' emotions, feel gratitude, socially connect, understand our own psychophysiological states, and restore nervous system balance. Mindfulness meditation increases insula gray matter and activation. This finding is clinically significant because it suggests that HRV biofeedback and mindfulness-based interventions may produce measurable structural changes in a brain region central to self-awareness and emotional regulation.

The insula functions as an integrative and organizational hub for the salience network, integrating interoceptive awareness, emotional experience, and external perception to facilitate our global perception of the world and our relationship with it. The insula directs specific networks in the processing of salient stimuli and in generating appropriate behavioral responses (Wiebking & Northoff, 2014).

The insula is the primary taste cortex and is activated when you see something that disgusts you or see another person's expression of disgust. Pictures of lovers also activate the anterior insula, as opposed to friends. In neuroeconomic studies, anterior insula activation predicted risk-avoidant financial strategies (choosing bonds instead of stocks), and in the Prisoner's Dilemma game, mutually cooperative decisions also activated this region.

Antonio Damasio has proposed that this region helps map visceral states associated with emotional experience and generate conscious feelings, providing the basis for somatic markers, gut feelings like the discomfort produced by a risky decision.

The insular cortex has been implicated in the experience of pain and basic emotions including anger, disgust, fear, happiness, and sadness. It receives reports of internal states like hunger and drug craving, motivating individuals to engage in consummatory behavior. The insular cortex plays a crucial role in craving and impulse control. It is stimulated by drug-related cues and may activate memories of pleasurable drug-related experiences. Remarkably, smokers whose strokes damaged the insular cortex have been found far more likely than smokers with damage elsewhere to quit easily, immediately, and without relapse, although not all of them quit.

National Institute of Drug Abuse graphic retrieved from Wikimedia Commons and adapted.

Cortical and Subcortical Connections

Neocortical zones are connected with cortical and subcortical regions by specialized fiber tracts: association bundles, projection fibers, and commissural bundles. A meta-networking model proposes that the dynamic interaction of "distributed but relatively specialized networks" mediates brain functions like language (Herbet & Duffau, 2020, p. 1181).

We adapted the figure below from Do et al. (2025), which shows major white matter tracts of the brain.

Association Bundles

Association bundles link cortical regions located in the same hemisphere. Short association fibers, called U-fibers, arch beneath a sulcus to join adjacent gyri, while long association fasciculi connect widely separated regions. The long fasciculi include the arcuate fasciculus (AF), frontal aslant tract (FAT), inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fascicle (ILF), middle longitudinal fasciculus (MdLF), superior longitudinal fasciculus (SLF), and uncinate fasciculus (UF).

Projection Fibers

Projection fibers connect the cortex with structures deep in the brain, the brainstem, and spinal cord. They include the frontostriatal tract (FST), which connects the premotor cortex with the caudate nucleus and putamen, as well as the thalamocortical, optic, and pyramidal tracts. Tractography animation Alfred Anwander, CC BY-SA 4.0, via Wikimedia Commons.

Commissural Bundles

The left and right hemispheres communicate using three commissures, or axon tracts. The corpus callosum is the largest tract and connects the left and right frontal, parietal, and occipital lobes. Certain conditions, such as prenatal exposure to alcohol and other drugs, may result in agenesis of the corpus callosum, in which part or all of this fiber bundle is missing. Graphic © decade3d - anatomy online/Shutterstock.com.

The anterior commissure, shown above the third ventricle at the bottom of the diagram, is considerably smaller than the corpus callosum and connects the left and right temporal lobes and the hippocampus and amygdala. Anterior commissure graphic adapted from Winter, T. J. & Franz, E. A., CC BY 3.0, via Wikimedia Commons.

The posterior commissure, located below the corpus callosum, connects the right and left diencephalon and mesencephalon (Breedlove & Watson, 2023). Corpus callosum graphic © Image Trading Source Ltd/Shutterstock.com.

Subcortical Structures

Subcortical regions, including the thalamus, basal ganglia, and limbic system (e.g., amygdala, hippocampus, hypothalamus), regulate fundamental functions like sensory processing, movement, and emotion. Sometimes the cerebellum is included among subcortical structures. These regions also contribute to the regulation of various qualities of thinking and emotion.

Thalamus

The thalamus consists of specialized nuclei that process and relay data to and from the telencephalon (cerebral cortex, basal ganglia, and limbic system). The thalamus analyzes all sensory data except olfaction before distributing this information to the cortex via thalamocortical afferent fibers (Breedlove & Watson, 2023). The cortex sends information back to the thalamus via corticothalamic fibers to adjust its processing, creating feedback loops that are crucial for generating several EEG rhythms. The thalamus helps regulate arousal, sleep, and wakefulness (Steriade & Llinás, 1988) and, through its functional connection to the hippocampus, plays a crucial role in episodic memory (Aggleton et al., 2010).

The thalamus contributes to SCPs, delta, theta, alpha, SMR activity, and beta-gamma activity (Thompson & Thompson, 2015). This makes the thalamus the single most important subcortical structure for understanding EEG generation. Thalamus graphic © decade3d - anatomy online/Shutterstock.com.

Basal Ganglia

The basal ganglia, comprising the caudate nucleus, putamen, globus pallidus, subthalamic nucleus, and substantia nigra, convert goals, value, and physiological state into action. Movement is the most visible product of this circuitry, but it is not the only one, since the same architecture also gates working memory updates, eye movements, and the pursuit of reward (Alexander et al., 1986; Middleton & Strick, 2000). The basal ganglia, prefrontal cortex, cingulate cortex, and parietal cortex together support self-awareness, attention, and emotional regulation. Researchers have identified several distinct prefrontal-basal ganglia-thalamic loops that are implicated in a range of psychiatric conditions. Graphic © Kateryna Kon/Shutterstock.com.

Three Core Functions: Receive, Gate, and Learn

Most clinical reasoning about these nuclei rests on three functions. The basal ganglia receive cortical input, gate which actions are released, and learn which actions were worth taking (Lanciego et al., 2012). The striatum is the input structure of the circuit. Its upper division, the dorsal striatum, consists of the caudate nucleus and the putamen, and its lower division, the ventral striatum, includes the nucleus accumbens. Together these regions collect signals from most of the cortex and from the thalamus (Alexander et al., 1986).

We adapted this graphic from Medico Plasma on Instagram.

Gating depends on two output nuclei that maintain a standing inhibitory brake on the thalamus, the internal segment of the globus pallidus and the substantia nigra pars reticulata. Releasing that brake allows a selected action to proceed, and tightening it holds an action back. The subthalamic nucleus excites those output nuclei and therefore strengthens the brake, which is one reason it has become a standard target for deep brain stimulation (Lanciego et al., 2012).

Learning depends on the substantia nigra pars compacta, which supplies dopamine to the striatum and teaches it which actions produced better outcomes than expected. That phasic dopamine burst encodes a reward prediction error, the difference between the outcome that was predicted and the outcome that arrived (Schultz, 2007). Degeneration of these dopamine neurons is the pathological hallmark of Parkinson's disease. This teaching signal is why the circuit matters to every clinician who delivers contingent feedback (Sitaram et al., 2017).

Direct and Indirect Pathways

Two routes leave the striatum. The direct pathway projects to the internal globus pallidus and the substantia nigra pars reticulata and releases the brake so that a chosen action can proceed. The indirect pathway passes through the external globus pallidus and the subthalamic nucleus, tightening the brake and suppressing competing actions (Albin et al., 1989). Generations of students learned these routes as a go switch and a stop switch. A third route, the hyperdirect pathway, carries a fast cortical signal to the subthalamic nucleus without passing through the striatum.

Recordings from identified cells have complicated that account. Both routes fire together at the moment of movement rather than opposing each other cleanly (Calabresi et al., 2014). In behaving mice, direct-pathway activity scales choice in a fairly straight line, while indirect-pathway influence depends on how strong the input is and on what the rest of the network is doing (Li & Jin, 2023). The practical implication is that treatment shifts the balance of a system in which both routes remain active rather than flipping a broken switch back into place. Describing neurofeedback gains to clients as graded and dose dependent is more accurate than describing them as a repair.

Parallel Loops and Integration Zones

Alexander et al. (1986) proposed that the basal ganglia run parallel loops with the cortex, including separate circuits for skeletomotor, oculomotor, cognitive, and limbic functions. Middleton and Strick (2000) confirmed that basal ganglia output reaches prefrontal regions that support thinking and not only motor cortex. Greene et al. (2020) tested the parallel loop model in individuals rather than group averages using precision functional mapping, which scans one person repeatedly so that individual network boundaries can be drawn with confidence. They identified integration zones, subcortical sites where two or more cortical networks converge. In the caudate nucleus, the default mode network met several control networks, which makes the caudate a place where inward-facing and outward-facing systems communicate.

Dosenbach et al. (2025) argue that the cingulo-opercular control network is better named the action-mode network because it describes a state of goal-directed engagement rather than a fixed anatomical address. A client who sits down, attends to a feedback display, and works to move a signal is holding the brain in exactly that state. Because a single striatal region participates in more than one cortical network, one protocol can plausibly influence more than one behavioral domain (Greene et al., 2020). This convergence also explains a clinical pattern you already see, in which a client referred for attention training shows low initiative, blunted response to reward, and slowed thinking as well.

The Somato-Cognitive Action Network

Gordon et al. (2023) scanned individuals repeatedly and found the motor homunculus interrupted. Woven between the hand, foot, and mouth patches lie regions that do not control any single muscle group, activate during action planning and whole-body movement, and connect to control networks and to internal organs. The authors named this system the somato-cognitive action network, or SCAN. An independent team using depth electrodes described a comparable region without body mapping in the same territory, which strengthens the case (Jensen et al., 2023). A useful image is that the body-part patches are individual instrumentalists and SCAN is the conductor, shaping timing, intensity, and fit to context rather than producing any single note.

Ren et al. (2026) mapped subcortical to cortical connectivity in 863 people, including patients with Parkinson's disease, healthy controls, and patients with other movement disorders. The deep structures implicated in Parkinson's disease, including the substantia nigra and the subthalamic nucleus, connected preferentially to SCAN nodes rather than to the hand, foot, or mouth zones. In patients, that coupling was abnormally elevated, a pattern called hyperconnectivity, which did not appear in healthy controls and was absent in essential tremor, dystonia, and amyotrophic lateral sclerosis. Deep brain stimulation, levodopa, and MRI-guided focused ultrasound each tracked or reduced that abnormal coupling, and lesions placed closer to the SCAN-defined target produced greater motor improvement. In a small randomized trial, transcranial magnetic stimulation delivered to a patient's own SCAN nodes produced roughly twice the motor improvement of stimulation delivered to that patient's own body-part zones.

One anatomical detail turns this from theory into a practical constraint. SCAN nodes do not occupy one corner of the motor strip, because they alternate with body-part zones along the central sulcus at a scale of millimeters (Ren et al., 2026). Conventional scalp EEG has spatial resolution measured in centimeters, so training at C3, Cz, or C4 cannot selectively engage a SCAN node rather than the body-part region beside it. The present relevance of these findings to scalp EEG practice is conceptual rather than evidence of spatially selective targeting, and the trial that compared two personalized targets in transcranial magnetic stimulation does not validate protocol selection in EEG. Saying that plainly to a client or a referring physician protects your credibility.

The Caudate Nucleus and Action Contingency

Ask most clinicians which structure signals reward and they will name the nucleus accumbens, yet the caudate does something different and more useful for feedback training. Tricomi et al. (2004) delivered monetary gains and losses at random, after a warning cue, and after the participant pressed a button. Caudate activity distinguished reward from punishment only when people believed their own response had produced the outcome, and money that simply arrived produced no such response. The trigger is action contingency, the perceived link between what you did and what happened next. One monetary paradigm cannot prove that the caudate never encodes pleasure, but it does show that contingency is what recruited the structure in that task.

Two further findings sharpen the clinical translation. Caudate responses are largest early in learning, while a person is still working out which choices pay (Delgado et al., 2005). In monkeys, silencing the pathway from orbitofrontal cortex to the caudate produced a reproducible loss of sensitivity to how much a cue was worth (Oyama et al., 2022). Grahn et al. (2008) placed deliberate, goal-directed selection in the caudate and automatic execution in the putamen, which supports habit learning. Any protocol that blurs the link between what the trainee's brain did and what the screen did weakens a signal that drives learning.

Effort, Vigor, and Apathy

Reward is not one thing. Berridge and Robinson (2003) separated liking from wanting and showed that dopamine matters far more for wanting. Salamone and Correa (2012) added the cost side, showing that dopamine in the nucleus accumbens supports effort-related decision-making. Animals with less accumbens dopamine still prefer the larger reward, but they stop paying a high effort price to obtain it and take the cheaper, smaller option. The failure is in mobilization rather than in preference.

That distinction changes the conversation you have with clients. Apathy in Parkinson's disease and anhedonia in depression involve a shifted calculation of cost against benefit rather than a character flaw, although neither syndrome reduces to that single computation. In the training room, this is the client who values the goal, attends every session, and still cannot start home practice. Breaking home practice into short intervals lowers the cost of starting, and setting early goals around starting rather than finishing matches the mechanism.

Gating, Working Memory, and Cognitive Flexibility

The same architecture shapes cognition. Frank et al. (2001) modeled the striatum as a gate on working memory that decides when new information enters and when current contents are protected. Opening the gate too readily produces distractibility, and opening it too rarely produces perseveration. Robbins (2007) reviewed the frontostriatal substrates of shifting and stopping, including the capacity to halt an action already underway. Da Cunha et al. (2012) added that these structures help select the actions that express both facts and skills.

This is why cognitive complaints in basal ganglia disease differ from those in cortical dementia. Clients often hold the information but cannot retrieve or switch it on demand, and they perform better with cues and structure than with open-ended prompts (Robbins, 2007). Explicit instructions, a fixed session sequence, and cued transitions substitute for a gate that no longer opens on schedule.

Striatal Contributions to Mood

Reduced ventral striatal activity has long been linked to anhedonia, the loss of pleasure and interest (Haber & Knutson, 2010; Price & Drevets, 2010). Lynch et al. (2024) scanned individuals with depression repeatedly over many months and reported that the frontostriatal salience network occupied nearly twice its usual cortical territory. Network size stayed stable across mood swings, which makes it a trait feature rather than a state marker, and the expansion was already present in children who later developed clinically significant depressive symptoms. Within that stable map, coupling between the nucleus accumbens and the anterior cingulate cortex weakened as anhedonia worsened in two deeply sampled individuals, although that coupling did not explain differences in anhedonia across the larger sample. The prudent reading is to treat anhedonia as a circuit-level target worth measuring rather than a residual symptom you wait out.

Disorders of the Basal Ganglia

Parkinson's disease is taught as a movement disorder, and patients do develop resting tremor, rigidity, and slowness. The disease also fragments sleep, destabilizes blood pressure control, and impairs mood and thinking, features that have never sat comfortably inside a limb-control story (Armstrong & Okun, 2020; Bloem et al., 2021). Symptoms worsen under stress and time pressure, while familiar music or a steady rhythm can temporarily restore fluent walking (Nutt et al., 2011). In one striking report, patients with advanced disease and severe gait failure escaped an earthquake unaided, and several kept the improvement for months (Bonanni et al., 2010). A network that couples movement with arousal, internal regulation, and motivation explains those oddities better than a limb-specific pathway does (Ren et al., 2026).

Huntington's disease preferentially degenerates striatal projection neurons, producing chorea, cognitive decline, and psychiatric symptoms that often precede the motor diagnosis (Ross & Tabrizi, 2011). Single-cell work explains the long silent period before onset, because the inherited repeat is unstable and keeps lengthening inside individual cells, a process called somatic CAG repeat expansion (Handsaker et al., 2025). Below roughly 150 repeats, sampled striatal projection neurons showed no abrupt disruption of gene expression, and above that length they lose their identity and die.

Obsessive-compulsive disorder implicates a loop running from orbitofrontal cortex and anterior cingulate through the striatum and thalamus, known as the cortico-striato-thalamo-cortical circuit (Pauls et al., 2014). That loop governs habit and the inhibition of unwanted action, and recent reviews argue that it cannot explain the full clinical variety without amygdala, hippocampal, and cerebellar contributions (Jijimon et al., 2026). Schizophrenia implicates different striatal territory, since the associative striatum, spanning medial caudate and dorsal putamen, shows the largest elevation of dopamine synthesis capacity (Howes & Kapur, 2009; McCutcheon et al., 2019). Blocking dopamine receptors relieves hallucinations and delusions while leaving negative and cognitive symptoms largely untouched, and the approval of a muscarinic agent showed that striatal circuits can be reached through other transmitter systems (Dean, 2024). The practical consequence is that a client's medication regimen shapes the reinforcement learning capacity your protocol depends on, so medication changes belong in the training record.

Limbic System

The limbic system is a widespread network of nuclei involved in emotion, motivation, learning, memory, and navigation. Three important limbic structures are the hippocampus, amygdala, and septal nuclei, along with the hypothalamus, anterior thalamus, and cingulate gyrus (Breedlove & Watson, 2023). Limbic system graphic © decade3d - anatomy online/Shutterstock.com.

Hippocampus

The hippocampus is a seahorse-shaped limbic structure required to form declarative memories. It plays a vital role in emotion, navigation, spatial memory, and dampening the endocrine stress response. The hippocampus simultaneously integrates emotional, auditory, and visuospatial information to create episodic memories and contains leukocyte receptors, making it part of the feedback loop for immune system regulation. Hippocampal neurons and networks that include it are important sources of the theta rhythm (Amzica & Lopes da Silva, 2018).

Hippocampal Brainwaves Travel in Two Directions

The old-school view held that hippocampal brainwaves travel in one direction, but this model could not explain how the hippocampus integrates information from various interconnected specialized systems. The new-school view, based on recording from human participants undergoing brain surgery, is that brainwaves travel through the hippocampus in both directions: from back to front and from front to back (Kleen et al., 2021). Cognitive activity differentially influences the direction of movement for low (e.g., 1.9 Hz) and high (e.g., 13.8 Hz) frequency waveforms.

Human hippocampal neuron graphic © Kateryna Kon/Shutterstock.com.

Watch Sam Kean's TED-Ed Talk, What Happens When You Remove the Hippocampus. Hippocampus graphic © decade3d - anatomy online/Shutterstock.com.

Amygdala

The amygdala is a collection of nuclei located deep within the medial temporal lobes at the end of the hippocampus. It is an essential limbic structure that includes, among others, the lateral nucleus and the central nucleus.

The lateral nucleus processes sensory information and distributes it throughout the amygdala. The central nucleus orchestrates the nervous system's response to important stimuli by activating circuits in the brainstem (autonomic arousal), basal ganglia, and periaqueductal gray (defensive behavior). The amygdala plays a crucial role in learning about the consequences of our actions and creating declarative memories for events with emotional significance (Breedlove & Watson, 2023). Understanding the amygdala's role in fear conditioning is particularly relevant for clinicians treating PTSD and anxiety disorders. Amygdala graphic © decade3d - anatomy online/Shutterstock.com.

Septal Nuclei

The septal nuclei are a limbic structure containing several nuclei involved in emotion, control of aggressive behavior, reward, and addiction (Breedlove & Watson, 2023). The septohippocampal system contributes to the theta rhythm (Amzica & Lopes da Silva, 2018). Septal nuclei graphic © MattL_Images/Shutterstock.com.

In summary, the cortical lobes and subcortical structures work together through extensive reciprocal connections to support cognition, emotion, movement, and memory. For biofeedback and neurofeedback practitioners, recognizing which structures contribute to specific EEG patterns, and which clinical disorders involve dysfunction in these regions, is the foundation of effective assessment and protocol design.

Brodmann Areas

This section covers the Brodmann classification system, its historical foundations, and its clinical relevance to biofeedback and neurofeedback practice. We will examine how specific Brodmann areas are implicated in disorders you will encounter in clinical settings, from ADHD and depression to PTSD and schizophrenia.

Historical Foundations

Brodmann areas are regions of the cerebral cortex defined by their distinct cytoarchitectonic characteristics (the organization, density, and layering of neurons), first delineated by German neurologist Korbinian Brodmann in the early twentieth century. Using Nissl staining techniques, Brodmann examined cortical cell organization across different brain regions in multiple mammalian species, including humans.

Brodmann compared the human cortex with that of a range of other mammals, including primates, rodents, and marsupials, publishing maps for humans and eight other species and enabling comparative conclusions about cortical organization (Garey, 1994). This comprehensive approach produced a map whose areas are numbered 1 through 52, each characterized by unique cytoarchitectonic features. Roughly 43 to 47 of those areas were delineated in the human cortex; the remaining numbers were defined only in non-human species, which is why numbers such as 12 through 16 and 48 through 51 are absent from most human maps. His work laid the foundation for modern functional neuroanatomy by linking structural variations in the cortex to specific sensory, motor, and cognitive functions (Brodmann, 1909). Biofeedback practitioners continue to use these divisions when interpreting qEEG findings and designing neurofeedback protocols. Brodmann graphic © sciencepics/Shutterstock.com.

The Functional Significance of Specific Brodmann Areas

The Brodmann map remains a widely used anatomical reference in both clinical and research neuroanatomy. For example, Brodmann area 4 corresponds to the primary motor cortex in the precentral gyrus and is critical for voluntary motor control (Penfield & Boldrey, 1937). Area 17, the primary visual cortex in the occipital lobe, is the initial cortical recipient of visual input from the lateral geniculate nucleus (Zeki, 1993). The use of Brodmann areas facilitates the identification of functional zones during neurosurgical procedures and functional imaging studies, aiding in the interpretation of brain activity and lesions.

Language Processing and Brodmann Areas

Language processing illustrates how Brodmann areas map onto clinical function. Broca's area (BA 44 and 45) in the dominant hemisphere's inferior frontal gyrus supports speech production and grammar, while Wernicke's area (BA 22) in the temporal cortex supports speech perception and comprehension. Damage to either area produces distinct aphasia syndromes that clinicians can identify through neuropsychological testing and correlate with qEEG findings. The arcuate fasciculus connecting these regions is a critical white matter tract whose integrity affects language network coherence.

Neuroimaging and Cortical Mapping

Recent advancements in neuroimaging techniques, such as fMRI and PET, have enabled researchers to refine the functional mapping of Brodmann areas with greater precision. Probabilistic cytoarchitectonic atlases, such as those developed by the Jülich Brain Atlas project, have supplemented Brodmann's static classification with data derived from multiple brains, allowing for population-level variability in cortical organization (Eickhoff et al., 2005). This evolution reflects the growing recognition that while Brodmann's map provides a valuable framework, individual differences in cortical morphology and function necessitate more dynamic and data-driven mapping approaches.

Relevance and Limitations

Brodmann areas continue to serve as a foundational framework for understanding cortical organization and function in both clinical and research contexts, from neurosurgical planning to the study of cognitive processes and neuropsychiatric disorders. However, ongoing advances in neuroimaging and connectomics are gradually supplementing this early anatomical schema with more detailed and individualized models of brain organization. For biofeedback practitioners, Brodmann areas remain the standard language for communicating about cortical regions, but clinicians should recognize that individual brains vary and that a given Brodmann area may not occupy the exact same cortical territory in every client.

Researchers have revised the Brodmann maps and correlated areas with their functions. The Brodmann maps below were contributed by Mark Dow, Research Assistant at the Brain Development Lab, the University of Oregon to Wikimedia Commons.

Areas 3, 1, and 2: Primary Somatosensory Cortex (S1)

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Area 4: Primary Motor Cortex (M1)

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Areas 5 and 7: Somatosensory Association Cortex (SAC)

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Area 6: Supplementary Motor Cortex and Premotor Cortex

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Area 8: Frontal Eye Field (FEF)

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Areas 9 and 46: Dorsolateral Prefrontal Cortex (DLPFC)

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Area 10: Anterior Prefrontal Cortex (aPFC)

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Areas 11, 12, 13, and 47: Orbitofrontal Cortex (OFC)

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Areas 13-16 and 52: Insular Cortex (Insula)

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Area 17: Primary Visual Cortex (V1)

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Areas 18 and 19: Secondary Visual Cortex (V2)

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Areas 18, 19, 37, 21, and 22: Visual Association Cortex (V3, V4, V5)

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Areas 20 and 37: Inferior Temporal Gyrus (ITG)

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Areas 21 and 39: Middle Temporal Gyrus (MTG)

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Areas 22, 39, and 40: Superior Temporal Gyrus (STG)

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Area 23: Ventral Posterior Cingulate Cortex (vPCC)

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Areas 24 and 25: Ventral Anterior Cingulate Cortex (vACC)

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Areas 25 and 24b: Subgenual Ventromedial Prefrontal Cortex (vmPFC)

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Areas 29 and 30: Ectosplenial Retrosplenial Cerebral Cortex

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Areas 29 and 30: Retrosplenial Cingulate Cortex

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Areas 23, 24, and 31: Dorsal Posterior Cingulate Cortex (dPCC)

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Areas 24, 25, 32, and 33: Anterior Cingulate Cortex (ACC)

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Areas 24, 32, and 33: Cingulate Cortex

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Area 27: Pyriform (Piriform) Cortex

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Area 28: Ventral Entorhinal Cortex (vEC)

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Areas 28 and 34: Dorsal Entorhinal Cortex (dEC)

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Areas 29 and 30: Ectosplenial Retrosplenial Cerebral Cortex

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Areas 35 and 36: Perirhinal Cortex (PRC)

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Areas 37 and 19: Fusiform Gyrus

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Area 38: Temporopolar Area (Temporal Pole)

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Area 39: Angular Gyrus

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Area 40: Supramarginal Gyrus

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Areas 41 and 42: Auditory Cortex

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Area 43: Primary Gustatory Cortex (PGC)

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Area 44: Pars Opercularis (inferior temporal gyrus and part of Broca's area)

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Area 45: Pars Triangularis (inferior temporal gyrus and part of Broca's area)

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Areas 9, 46, 8, and 10: Dorsolateral Prefrontal Cortex (DLPFC)

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Area 47: Pars Orbitalis (part of the inferior frontal gyrus)

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Area 48: Retrosubicular Area (small medial temporal lobe area)

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Areas 13, 14, and 52: Parainsular Area (junction of the temporal lobe and insula)

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Brodmann Area Involvement in Clinical Disorders

The clinical correlations between psychiatric and neurological disorders and specific Brodmann areas provide valuable insights into the neural mechanisms of these conditions. Understanding the abnormalities in these regions can offer critical information for diagnosis, treatment, and the development of targeted therapies. This section explores the associations between specific Brodmann areas and disorders including ADHD, autism spectrum disorder, bipolar disorder, major depressive disorder, panic disorder, PTSD, schizophrenia, and substance use disorder.

Attention-Deficit Hyperactivity Disorder (ADHD)

ADHD is associated with abnormalities in multiple Brodmann areas, including BAs 44/45 (Broca's area), 8/9, 10, 11, 46 (frontal regions), 7, 39, 40 (parietal regions), 4 (motor cortex), 30 (cingulate gyrus), 21, 38 (temporal regions), and 6 (premotor cortex). These abnormalities contribute to the diverse cognitive, attentional, and motor deficits observed in individuals with ADHD.

In individuals with ADHD, Broca's area (BA 44 and 45) exhibits functional disturbances, particularly a lower fractional amplitude of low-frequency fluctuations (fALFF). This dysfunction is linked to language deficits, with different ADHD subtypes affecting distinct parts of Broca's area: Area 44 in the inattentive subtype and Area 45 in the combined subtype (Pikusa & Jończyk, 2015; Silk et al., 2005).

In the frontal regions, children with ADHD display grey matter deficits in the right superior frontal gyrus (BA 8 and 9), suggesting disruptions in attentional networks (Overmeyer et al., 2001). Adolescents with ADHD show decreased activation in the middle frontal gyrus (Area 10) and the dorsolateral prefrontal cortex (Area 46), indicating widespread frontal lobe dysfunction (Silk et al., 2005). Abnormalities in the ventromedial orbitofrontal cortex (Area 11) are linked to motivational deficits in adults with ADHD (Farré-Colomés et al., 2021).

The parietal regions, including the superior parietal lobe (Area 7) and the inferior parietal lobule (Areas 39 and 40), also show decreased activation in ADHD, implicating these areas in attentional and action-attentional systems (Silk et al., 2005). Children with ADHD exhibit decreased activation in the primary motor cortex (Area 4) during motor tasks, suggesting anomalies in motor development (Gaddis et al., 2015; Gilbert et al., 2011, 2019).

The right posterior cingulate gyrus (Area 30) shows grey matter deficits in children with ADHD, which may contribute to difficulties in attentional control (Overmeyer et al., 2001). Structural alterations are also observed in the temporal regions, with lower cortical thickness in the fusiform gyrus and temporal pole (Areas 21 and 38) in children with ADHD (Hoogman et al., 2019; Karalok et al., 2019; Lake et al., 2019; McLaughlin et al., 2014). Increased connectivity in the premotor cortex (Area 6) may be associated with challenges in motor planning and execution (Hoshi & Tanji, 2007; Oldehinkel et al., 2016; Sörös et al., 2019; Suskauer et al., 2008).

Autism Spectrum Disorder (ASD)

Research indicates that abnormalities in Brodmann areas 24, 44, 45, and 10 are associated with Autism Spectrum Disorder. These abnormalities include changes in neuron size and density, gray matter volume, and functional connectivity, which are linked to the social and communication deficits characteristic of ASD. In the anterior cingulate cortex (BA 24), there is a notable reduction in cell size and cell packing density, specifically in areas 24b and 24c, along with elevated levels of glial fibrillary acidic protein (GFAP) in the white matter, indicating increased astrocyte activation. During verbal memory tasks, decreased glucose metabolism is observed in BA24, and dysregulated DNA methylation patterns in this area impact genes related to immune functions and synaptic membranes.

In the inferior frontal cortex (BA 44 and 45), there is a decrease in the size of pyramidal neurons, which play crucial roles in language processing and social behaviors (Jacot-Descombes et al., 2012). Reduced gray matter volume in the pars opercularis (BA44) and pars triangularis (BA45) is linked to difficulties in social communication (Yamasaki et al., 2010).

The anterior prefrontal cortex (BA 10) exhibits abnormal functional connectivity between the right and left hemispheres, correlating with the severity of social deficits (Kikuchi et al., 2013). Similar to BA24, BA10 also shows dysregulated DNA methylation affecting genes involved in immune response and synaptic function (Nardone et al., 2014).

Other areas affected include the medial/cingulate regions (BAs 32, 24, and 25), where lower glucose metabolism is observed during verbal memory tasks (Deery et al., 2022; Hazlett et al., 2004, 2010). There is also a reduction in white matter volumes in the posterior frontal lobe and along the cingulate arch (Aalst et al., 2021; Gardener et al., 2016).

Bipolar Disorder (BD)

Research indicates that abnormalities in several Brodmann areas, including BAs 9, 24, 38, 41, 42, 46, and 10, are associated with bipolar disorder. These abnormalities span structural changes such as reduced glial numbers and cortical volume, as well as functional and molecular disruptions including altered gene expression and DNA methylation. In BA 9 (part of the dorsolateral prefrontal cortex), abnormalities in DNA methylation and gene expression indicate its role in the pathophysiology of BD, and this area shows decreased numbers and density of glial cells, suggesting disruptions in neurochemical regulation.

The subgenual prefrontal cortex (BA 24) exhibits reduced volume and fewer glial cells, associated with familial forms of BD. This area is significant for mood regulation and reflects neurobiological changes linked to the disorder (Öngür et al., 1998; Scarr et al., 2019).

In the temporal pole (BA 38), notable differences in DNA methylation are associated with BD, indicating involvement in the molecular mechanisms underlying the disorder (Ho et al., 2019). In the primary auditory cortex (BA 41 and 42), decreased BOLD signals in response to auditory stimuli have been identified as potential biomarkers for BD (Okamoto et al., 2022).

BA 46, another region of the dorsolateral prefrontal cortex, shows altered gene expression with specific genes exhibiting differential expression in BD, suggesting disruptions in neuronal network functions (Nakatani et al., 2006; Vizueta et al., 2012). The prefrontal cortex (BA 10) also presents changes in gene expression in BD, highlighting complex regional-specific changes in cortical gene expression (Scarr et al., 2019; Vizueta et al., 2012).

Major Depressive Disorder (MDD)

Research consistently implicates several Brodmann areas in the pathology of major depressive disorder, including the anterior cingulate cortex (BA 24 and BA 32), dorsolateral prefrontal cortex (BA 9 and BA 46), ventromedial prefrontal cortex (BA 10), orbitofrontal cortex (BA 13 and BA 47/12), and subgenual cingulate cortex (BA 25). In the anterior cingulate cortex, structural abnormalities and reduced volume in the subgenual part of BA 24 are linked to familial forms of MDD, and elevated levels of tumor necrosis factor (TNF) have been observed in BA 24 among MDD patients, suggesting the involvement of pro-inflammatory pathways. Abnormalities in BA 32 have been associated with antidepressant treatment.

In the dorsolateral prefrontal cortex (BA 9 and 46), both structural and functional abnormalities have been connected to MDD. In BA 9, changes in connectivity and increased fractional amplitude of low-frequency fluctuation (fALFF) are noted (Gao et al., 2021; Lai & Wu, 2015; Ye et al., 2012; Vasic et al. 2008; Zhukovsky et al., 2020). Elevated TNF levels in BA 46 indicate a role in the disorder's pathophysiology (Dean et al., 2010).

The ventromedial prefrontal cortex (BA 10) shows abnormal functional connectivity linked to emotional regulation deficits in MDD patients (Almeida et al., 2011; Johnstone et al., 2007; Wackerhagen et al., 2017; Young et al., 2016). Epigenetic modifications, such as methylation changes, have been identified in BA 9 and BA 38 (Ho et al., 2019).

In the orbitofrontal cortex (BA 13 and BA 47/12), reduced functional connectivity in BA 13 is associated with depressive symptoms, while increased functional connectivity in BA 47/12 correlates with negative self-perception in MDD (Cheng et al., 2016). The subgenual cingulate cortex (BA 25) exhibits reduced functional connectivity with regions involved in emotional regulation (Peng et al., 2020), and methylation changes in BA 25 have been consistently found in independent brain samples (Åberg et al., 2018).

Panic Disorder

Research indicates that abnormalities in Brodmann areas 11, 25, 32, and 15, as well as regions within the prefrontal cortex and parahippocampal gyrus, are associated with panic disorder. During panic attacks, there is a noticeable decrease in regional cerebral blood flow (rCBF) in the right orbitofrontal cortex (BA 11) and the prelimbic cortex (BA 25). This reduction is also observed in the anterior cingulate cortex (BA 32), which exhibits mixed patterns of hyperactivation and hypoactivation during emotional processing.

The parahippocampal gyrus in panic disorder patients shows significant abnormal asymmetry in cerebral blood flow. The anterior temporal cortex (BA 15) experiences decreased rCBF during panic attacks (Hasler et al., 2007). Key regions within the prefronto-limbic network, particularly areas within the PFC, show selective deficits in emotional processing among panic disorder patients (Hasler et al., 2007; Shang et al., 2014). Dysfunctional communication within frontotemporal structures is indicated by decreased coherence imaging values (Shang et al., 2014; Speer et al., 2003).

Increased resting-state functional connectivity between the thalamus and insula suggests excessive sensitivity to external information in panic disorder patients, highlighting a potential neural mechanism underlying their heightened responsiveness to stimuli (Feldker et al., 2016, 2019; Zhou et al., 2022).

Post-Traumatic Stress Disorder (PTSD)

PTSD is associated with abnormalities in the anterior cingulate cortex (BA 32 and BA 24), medial prefrontal cortex (BA 10 and BA 11), dorsolateral prefrontal cortex (BA 46), insula (BA 13), orbitofrontal cortex (BA 25), and sensorimotor areas (BA 4/6). These regions are involved in emotional regulation, memory processing, and response to trauma-related stimuli. In individuals with PTSD, the DLPFC (BA 46) shows decreased activity and signs of mitochondrial dysfunction, and the anterior cingulate gyrus (BA 32) exhibits less activation compared to those without PTSD.

The medial prefrontal cortex (BA 10 and 11) shows reduced activation in PTSD subjects (Etkin & Wager, 2007; Herringa et al., 2012; Manthey et al., 2021; Sartory et al., 2013). The activation levels in BA 10 correlate with PTSD symptoms during threat processing. The insula (BA 13) demonstrates increased delta slow waves linked to worsening PTSD symptoms over time (Harricharan et al., 2019; Herringa et al., 2012; Rabinak et al., 2011), and differences in functional connectivity in the insula are observed between PTSD and non-PTSD individuals (Rabinak et al., 2011; Sripada et al., 2012; Zhang et al., 2016).

During symptom provocation in PTSD patients, there is increased regional cerebral blood flow (rCBF) in the right sensorimotor areas (BA 4 and 6), while lowered rCBF is observed in the right retrosplenial cortex (BA 26, 29, and 30) (Pissiota et al., 2000). Structural and functional changes in the hippocampus and amygdala are consistently observed in PTSD, highlighting their crucial roles in memory and emotional processing (Chen et al., 2018; Hull, 2002).

Schizophrenia

Abnormalities in frontal (BAs 4, 6, 8, 9, 10, 44, 46, 47), temporal (BAs 20, 21, 22, 37, 39, 42), and cingulate (BAs 24, 25, 29, 30, 31) cortices are associated with schizophrenia. These include disrupted intercorrelations, altered receptor binding, gene expression changes, and structural deficits. Significant reductions in gray matter volume have been observed in the left anterior hippocampus-amygdala, left parahippocampal gyrus, and left superior temporal gyrus, with correlations between the volume of the left posterior superior temporal gyrus and the severity of thought disorders.

Disruptions in D2 dopamine receptor patterns have been identified in the perirhinal, superior, and inferior temporal cortices (BA 20, 22, 37, 39, and 42). These disruptions are distinct to the temporal lobe and are not attributable to long-term antipsychotic treatment, suggesting a specific role in auditory hallucinations and other positive symptoms (Goldsmith et al., 1997; Joyce et al., 1997).

In schizotypal personality disorder, lower fractional anisotropy (FA) in the left temporal lobe (BA 20, 21, and 22) indicates alterations in white matter microstructure (Chan et al., 2018; Ellison-Wright & Bullmore, 2009; Hazlett et al., 2011; Lee et al., 2016; Szeszko et al., 2008). Schizophrenia is also associated with a thinner cortex and reduced surface area in the temporal lobe, with the most significant cortical thickness reductions at the temporal pole (Kaur et al., 2020; McCarley et al., 1999; Shenton et al., 1992). Progressive volumetric changes over time, particularly decreased temporal white matter volume, indicate ongoing structural abnormalities (Kaur et al., 2020; Mathew et al., 2014; Olabi et al., 2011).

Enhanced functional connectivity between the left DLPFC and the left mid-posterior temporal lobe has been identified in patients experiencing their first episode of schizophrenia (Zhou et al., 2007), a connectivity pattern that may contribute to the cognitive and perceptual disturbances characteristic of the disorder.

Substance Use Disorder (SUD)

Abnormalities in specific Brodmann areas, particularly BA 10, BA 24, BA 30, BA 18, BA 21/22, and BA 19, are associated with substance use disorder. These areas are involved in critical functions such as self-reflection, emotional regulation, memory, and executive function, which are often impaired in individuals with SUD.

In adolescents with SUD, there is reduced activity in BA 10 (superior, medial, and middle frontal gyrus), suggesting difficulties in self-referential evaluation and future planning (Dalwani et al., 2014). The anterior cingulate cortex (BA 24) shows abnormal activity, impacting emotional behavior and executive function in individuals with SUD.

Conclusion

The examination of specific Brodmann areas reveals significant correlations with various psychiatric and neurological disorders, underscoring the importance of these brain regions in disease pathology. ADHD features disruptions in regions related to attention and executive function. Autism spectrum disorder is characterized by changes in areas affecting social and communication skills. Bipolar disorder involves alterations in areas associated with mood regulation.

Panic disorder and PTSD both involve the prefronto-limbic network, impacting emotional and stress responses. Schizophrenia is associated with widespread disruptions affecting cognition and perception, and substance use disorder involves regions critical for executive function and emotional regulation. For biofeedback practitioners, these Brodmann area findings provide a neuroanatomical framework for understanding the EEG patterns and connectivity abnormalities observed in clinical assessment.

Connectivity, Phase, and Coherence

This final section introduces the connectivity, phase, and coherence concepts that underlie EEG network analysis. These measures are central to quantitative EEG (qEEG) assessment and connectivity-based neurofeedback protocols. We will cover neural network connectivity, phase reset mechanisms, EEG synchrony, coherence measurement, and co-modulation.

Neural networks are systems of interconnected ensembles of neurons that collaborate to achieve a goal (Thompson & Thompson, 2015). Networks communicate and perform functions via hub- or node-based communication systems. The image below shows dorsal and lateral views of the connectivity backbone of the human brain, with nodes (individual ROIs) coded according to strength and edges coded according to connection weight.

Hagmann, P., Cammoun, L., Gigandet, X., Meuli, R., Honey, C. J., Wedeen, V. J., & Sporns, O. (2008) Mapping the structural core of human cerebral cortex. PLoS Biology, 6(7), e159, Wikimedia Commons, licensed under the Creative Commons Attribution 3.0 Unported license.

Connectivity

Networks like the Affect, Attention, Default, Executive, and Salience systems synchronize the activity of cortical and subcortical regions to perform functions. Connectivity is the degree of synchrony between the oscillations of specialized brain regions (nodes) within a network (Bastos & Schoffelen, 2016). Strongly connected brain regions are called hubs, and hubs can be primarily connected to nodes (vertices) within their local modules (sets of interconnected nodes) or to nodes in more distant modules (Bullmore & Sporns, 2009).

Neurofeedback training can increase or decrease connectivity using a normative database. For example, BrainMaster's BrainAvatar software allows clinicians to train specific networks, like the Default Mode Network (DMN).

See the Assumptions unit for an in-depth discussion of the Affective, Default Mode, Executive, Motor, Network, Oculomotor, Salience, and Social Networks.

Phase Reset Coordination of Neural Networks

Phase refers to the degree to which the peaks and valleys of EEG waveforms coincide. Phase measures the time shift between EEG activity in two brain regions and represents the number of elements in a network times the delay in that network. Phase graphic © petrroudny43/Shutterstock.com.

Phase reset (PR) is defined by a sudden change in phase difference (phase shift duration or SD) followed by a period of phase locking (lock duration or LD), expressed as PR = SD + LD (Thatcher et al., 2009). Gap junction coupling explains both phase locking and phase shifting (Hughes & Crunelli, 2007).

Resetting the phase of ongoing oscillatory activity to endogenous (internal) or exogenous (environmental) cues facilitates coordinated information transfer within circuits and between distributed brain areas. Phase resetting is a critical marker of dynamic state changes within functional networks (Voloh & Womelsdorf, 2016). Phase resets create a neural context, a narrow band of frequencies that uniquely characterize the activated circuits, and impose coherent low-frequency phases to which high-frequency activations can synchronize.

These identifiable cross-frequency correlations span large distances and are critical for neural coding models that depend on phase, increasing the informational content of neural representations. Phase resets likely originate from the dynamics of canonical excitatory-inhibitory (E-I) circuits that are anatomically ubiquitous. They reorganize oscillations in diverse task contexts: attentional stimulus selection, classical conditioning, cross-modal integration, sensory perception, and spatial navigation, and can drive changes in ensemble organization, functional networks, neural excitability, and overt behavior.

The frequency graphic © Ali DM/Shutterstock.com. Low- and high-frequency oscillations result from phase reset decreases and increases in neural activity, respectively.

EEG Synchrony and Phase

Networks of neurons generating the EEG activity at different sites can produce signals that are identical in amplitude, frequency, and phase, or that are entirely unrelated. Understanding the distinctions between different types of synchrony is essential for interpreting qEEG connectivity measures.

Synchrony means that the firing of pools of neurons is coordinated. EEG signals can display three types of synchrony. Local synchrony occurs when the coordinated firing of cortical neurons produces high-amplitude EEG signals. For example, an alpha amplitude of 20-60 μV detected at O₁-A₁ is produced by the synchronous firing of pools of neurons, while beta activity at the same site is lower in amplitude due to desynchronized firing. This is analogous to a choir: when performers sing in unison, they produce a louder sound than when singing separately.

Frequency synchrony occurs when identical EEG frequencies are detected at two or more electrode sites, for example, 12 Hz simultaneously detected at O₁-A₁ and O₂-A₂. Phase synchrony reflects the degree of alignment of oscillatory activity across regions. If the peaks of theta waves occur at the same instant at two cortical regions, then there is zero phase lag between them.

The phase alignment of two EEG signals of the same frequency reflects the speed of information transmission, with lower phase lag (greater synchrony) reflecting faster communication between sites. High synchrony within frequency bands, such as alpha or beta, supports efficient communication, while cross-frequency synchrony between different EEG bands plays a role in the integration of brain functions.

However, increased phase synchrony does not always indicate active communication between two regions. In some cases, it simply reflects two areas receiving input from the same rhythmic generators. Increased phase synchrony can also result from damage to interactive communication, particularly with delta activity in TBI, where damaged regions independently produce delta oscillations due to a lack of other input, sometimes with increased synchrony.

EEG training may produce phase-synchronous 12-Hz alpha waves at O₁-A₁ and O₂-A₂.

Coherence

Coherence represents the degree of coupling between separate cortical regions and reflects neural network connectivity and dynamics (Bullmore & Sporns, 2009). Coherence evaluates the linear association or correlation between EEG waveforms recorded from two different scalp locations using a two-channel referential montage, as shown below.

Coherence measures the degree to which two areas have consistent phase relationships at a designated frequency. When the phase difference between two signals is constant, coherence = 1; when the phase difference is random, coherence = 0.

Hyper-coherence means too much coupling, involving a failure to activate cortical regions selectively, and may interfere with multitasking and rapid decision-making. Hypo-coherence, which often results from traumatic brain injuries, means too little coupling and involves a breakdown in communication between regions that should normally coordinate (Wilson et al., 2011).

Coherence is a correlation coefficient (squared) that estimates relative amplitude and phase consistency between any pair of signals in each frequency band (Bendat & Piersol, 2010). The key component is consistency: coherence is based on phase, and phase measures the timing relationship of two waveforms at a specific EEG frequency band.

The image below shows five identical wave patterns shifted in time relative to each other. Starting with the first waveform at the bottom, each subsequent wave is shifted in time, known as phase shift or phase angle. The angle is represented in degrees: a wave beginning one-fourth of the way through the original wave's cycle has a 90-degree phase angle (example B), while one beginning at the halfway point has a 180-degree phase angle, meaning the waves are exactly opposite (example C).

As previously noted, coherence measures the consistency of these phase relationships. Waveforms do not have to be in phase (zero phase angle) to be coherent; they only need to maintain a consistent phase relationship. Coherence values range from 0 to 1, with zero representing a random relationship and 1 representing signals that remain in the same phase relationship for the entire measurement period (usually a minimum of 2 seconds).

Because signals can be out of phase and still highly coherent, coherence should not be confused with phase synchrony, which describes two waves oscillating with the same timing (zero phase angle). This distinction matters clinically.

In heart rate variability (HRV) training, for example, a common goal is to synchronize respiration and heart rate waveforms. This is an example of phase synchrony. When this alignment is consistent, the two waves are also highly coherent. However, a true coherence calculation could show high coherence even when waveforms are significantly offset, as long as they remain in a consistent phase relationship.

In practice, many commercial HRV displays report a correlation- or spectrum-based index of relative phase synchrony rather than the full coherence calculation, which combines the cross-spectral density and the auto-spectral density between two signals. Practitioners should check what a given instrument actually computes before calling its output coherence.

EEG coherence estimates interaction between neural systems through amplitude and phase consistency in each frequency band between two scalp sensor locations. Two signals can be asynchronous but have high coherence if they are consistently in the same asynchronous relationship, implying some coordinating mechanism between the two locations related to communication and interaction (Nunez & Srinivasan, 2006).

The history of coherence measures in EEG began with Donald Walter (Walter, 1963), and since then many studies have used EEG coherence to identify factors in cognition, brain maturation, heritability, gender differences, and a variety of clinical disorders (Thatcher, 2012). There are several methods for estimating coherence, and each has important limitations that clinicians must understand.

Thatcher (2012) states that the linked ears montage or a common reference is necessary to correctly calculate phase differences because other montage arrangements distort the original time series and the relationships between individual sensor locations. Thatcher (2004) claims that the reliability of coherence measures using common average reference or Laplacian montages, though generally quite high, is irrelevant because these montaging methods render the resulting calculations uninterpretable. He argues that these montages involve the "mixing" of signals from multiple electrodes and provides examples using artificially-generated signals showing that only the linked-ear or common reference correctly represents changes in source signals as noise increases.

However, the linked ear and common references in Thatcher's study were necessarily neutral, without signal content, and therefore do not reflect real-world conditions. On the other hand, Nunez and Srinivasan (2006) demonstrate that coherence using a common reference (such as linked-ear or linked-mastoid sensors) elevates all coherence measures for all frequencies and electrode combinations because this method adds a common signal to each channel.

The idea of a "neutral" reference without any EEG or other electrical activity is not valid in real-world recordings. Ear and mastoid reference channels frequently show rhythmic alpha activity, particularly in the eyes-closed condition, and are often contaminated by EMG artifacts from masseter muscle contractions. Similarly, a common reference such as Cz or Fcz would add real EEG signal characteristics to the resulting calculation, influencing phase and coherence calculations, particularly for frontal electrode locations.

For a complete discussion of differential amplifier functions, please see the Instrumentation and Electronics section. For our purposes, it is sufficient to understand the concept of common-mode rejection, which eliminates common or similar signals between two inputs (positive and negative). The initial purpose was to eliminate "mains" artifact (60 Hz in North America, 50 Hz elsewhere), but common-mode rejection also removes any electrical signal, including EEG, from active/reference pairs when the signals are identical in frequency and, to a lesser extent, amplitude.

When the reference channel derived from ear or mastoid sites contains substantial alpha activity and is compared to frontal "active" channels that generally do not contain substantial alpha, the resulting signal retains the alpha from the reference. This creates the appearance of rhythmic, highly synchronous frontal alpha activity and produces artificially elevated alpha coherence values. Compared to a normative database, these values will generate falsely elevated z-scores, and neurofeedback training may be implemented to "correct" what is actually an artifact of the reference choice.

The same epoch is shown twice: as raw traces in a linked-ears referential montage (upper panel, note the A1-LE and A2-LE channels) and in a bipolar montage (lower panel), with an alpha-band connectivity head map inset at the upper right. A burst of alpha rises to prominence over the posterior channels in both montages.

The head map is labeled Alpha (8.0-12.0 Hz), and each line joins a pair of electrodes whose coherence departs from the normative mean: red marks pairs above the mean and blue marks pairs below it. The map therefore reports how consistently two sites hold a phase relationship over time. It does not report how much alpha either site produces, and it does not report whether their amplitudes rise and fall together, which is co-modulation.

Read alongside the discussion above, the dense red lattice reaching well into the frontal channels is exactly the pattern a linked-ear reference can manufacture when the ear channels themselves carry alpha. It should be confirmed in a second montage before it is treated as a clinical finding.

Nunez and Srinivasan (2006) suggest that the common average reference method shows coherence results more similar to experimental, reference-independent calculations, though they note that many sensors (their example used 111) are needed for an effective average reference, far more than the typical 19 used in most normative databases.

Another approach is the surface Laplacian method, which removes some issues associated with reference contamination though it tends to increase noise at each electrode location (Nunez & Srinivasan, 2006). It also reduces the problem of volume conduction, the conduction of bioelectric signals through neural tissues that appear in adjacent sensor locations not directly above the signal generator. Volume conduction decreases with distance, so closely spaced electrode pairs show higher coherence disproportionately affected by common sources. Widely spaced electrode pairs more accurately reflect actual communication between areas. Because the Laplacian operator uses the average of surrounding electrodes as the reference, common signals are minimized and coherence may be more accurate for closely spaced pairs.

The eventual answer to which coherence measure is better must await further studies using real-world models. Current practice with either method will produce results that require an understanding of the benefits and limitations of each approach. Excess frontal alpha coherence derived from linked ear reference data should be reviewed cautiously, and the raw EEG signal should always be viewed using multiple montages to determine the accuracy of frontal alpha displays.

Other factors influencing coherence include pervasive EMG artifacts that may not be evident to beginning practitioners. When such artifacts contaminate the record, excessive hypercoherence in beta and fast beta frequencies can result, as shown in the example below.

A Z-scored FFT summary recorded in a linked-ears montage (AA1 LE). Five columns run across the frequency bands from delta to high beta, and five rows step through absolute power, relative power, amplitude asymmetry, coherence, and phase lag, so reading across a row shows one measure at every band and reading down a column shows one band across every measure.

No cell shows raw microvolts. Every value is a Z score, the distance from a normative mean expressed in standard deviations, with warm colors above the mean, cool colors below it, and gray marking the unremarkable middle. The top two rows are power maps. The lower three are pairwise measures drawn as webs between electrode pairs; coherence and phase lag are connectivity measures, while amplitude asymmetry compares power at two sites rather than their coupling. The thresholds printed beneath the connectivity rows, Z of at least 1.96, 2.58, and 3.09, determine which pairs are drawn at all.

Note the combination the text above describes: elevated frontal and temporal high-beta power together with a dense red coherence lattice in beta and high beta. That pairing is a common signature of EMG contamination rather than of cortical connectivity, and the raw record should be inspected in multiple montages before these deviations are read as findings.

With these cautions in mind, coherence remains a useful tool that can be quite revealing, particularly in cases of traumatic brain injury, stroke, lesion, and other evaluations. With experience, clinicians can identify which coherence values represent actual findings and correlate them with client history and presenting symptoms.

Simple phase measurements alone are not particularly useful because they are not directional; they simply show the timing relationship between two sensor locations without revealing which location may be dysfunctional or what the causal factors may be (Nunez & Srinivasan, 2006). Additionally, a common reference distorts phase in the same way described for coherence. Nunez (1974) argues that using a bipolar montage for phase calculation substantially reduces problems of volume conduction and reference contamination, though this is not suggested as a viable montage for subsequent coherence calculation.

Phase values range from -1 to +1, and statistical calculations can be made based on normative samples. However, experimental data (Nunez, 1995; Silberstein et al., 1993) show that only about 8% of phase data could be identified as associated with traveling waves; the rest was too complex to identify source relationships. More recent work has examined phase slope, which provides a measure of effective connectivity, the directionality of influence between two EEG sources.

Co-Modulation

Co-modulation is the degree of association in the magnitude of signals detected from two sources (sites). Co-modulation, which can be measured using the Pearson Product-Moment Correlation Coefficient, shows the degree to which signals strengthen and weaken in a correlated manner (Collura, 2014). Co-modulation does not measure phase or coherence, although it may reflect phase effects (Sterman & Kaiser, 2001). It represents a complementary approach to understanding brain connectivity that avoids some of the reference-related limitations of traditional coherence measures.

In summary, connectivity, phase, and coherence are powerful tools for understanding brain network dynamics, but each measure has specific limitations that clinicians must understand. Reference montage selection, volume conduction, and EMG artifacts can all distort these measures. Effective clinical practice requires viewing raw EEG data with multiple montages and interpreting connectivity findings in the context of client history and symptoms.

Cutting-Edge Topics in Neuroanatomy

Glossary

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Assignment

Now that you have completed this unit, explain the importance of slow cortical potentials. How does 8-10 Hz alpha differ from 10-12 Hz alpha?

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