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Journal of Neuroscience
Vol. 3, pp. 1–5, 2014
Electroencephalogram Mapping of Brain States
German Torres∗, Michael P. Cinelli, Alexander T. Hynes, Ian S. Kaplan, and Joerg R. Leheste
Department of Biomedical Sciences, New York Institute of Technology,
College of Osteopathic Medicine Old Westbury, New York, 11568 USA
Neurons of the nervous system continuously generate output signals that can be gauged indirectly by quan-
titative electroencephalogram readouts. This recording procedure measures changes in depolarization pulses
from cortical and thalamic circuits in response to streams of abstract information provided by sensory receptors.
In this brief review, we discuss the electroencephalograph in terms of its use in detecting regional differences
in brain electrical activity, and describe a wide range of clinical phenomena revealed by the application of
quantitative electroencephalogram mapping.
KEYWORDS: Action Potentials, Anesthetics, Brain Pathologies, Neuronal Cell Types, Sleep-Wake Cycles.
Action potentials are the information-processing elements
of the nervous system. Although the sequence of events
underlying action potentials is relatively understood at
the microscopic level, its functional signiﬁcance at the
macroscopic level is far from clear. Nevertheless, action
potentials are usually viewed as two regenerative elec-
trochemical cycles (i.e., depolarization and hyperpolariza-
tion cycles) conveying graded information to the neuron,
synapse, neural circuit and eventually to the entire brain.
Action potentials can be gauged indirectly at the macro-
scopic level through the use of brain imaging and
quantitative electroencephalogram (EEG) readouts. For
example, EEGs measure summations of excitatory (i.e.,
depolarizing) and inhibitory (i.e., hyperpolarizing) postsy-
naptic action potentials across cortical cells, more specif-
ically, pyramidal neurons of the external (Layer III) and
internal (Layer V) layers of the cerebral cortex . As
pyramidal neurons represent the primary output for the
cerebral cortex to the ipsilateral or contralateral hemi-
sphere , EEG readouts are thought to translate local
streams of abstract information to subcortical targets in the
forebrain, brainstem or spinal cord. Because of its non-
invasive nature, and adequate temporal and spatial resolu-
tions, the EEG has become an excellent experimental tool
for deciphering global patterns of neural activity regulating
∗Author to whom correspondence should be addressed.
Received: xx Xxxx xxxx
Accepted: xx Xxxx xxxx
MECHANISMS OF THE
The EEG, as ﬁrst described by the German psychiatrist
Hans Berger, measures voltage or electrical potential (V )
differences between two electrodes placed on the scalp
of a human subject . The mechanism behind the EEG
is based upon the theory of volume conduction which
describes the passage of ion currents from a biological sys-
tem (i.e., the brain) to a source of measurement. It should
be noted that summation of ion currents from thousands of
pyramidal neurons represents the primary source of V as
cortical interneurons (e.g., -amino-butyric acid, GABA)
or glial cells (e.g., astrocytes) provide little or no con-
tribution to voltage differences. The synaptic activity of
all pyramidal neurons having the same approximate ver-
tical orientation to the scalp is eventually relayed to the
EEG machine as a synchronous signal ampliﬁed approx-
imately 10,000×(Fig. 1). Current EEG systems measure
V differences between 4 to 256 electrodes, with most
laboratories using a 21-electrode tracing system . Elec-
trodes normally detect synchronous signals ranging from
20–150 V elapsed over intervals of 0.5 to 60 Hz (cycles
per second). Electrode placement on the human scalp is
now a rigorously standardized procedure aimed to provide
reliability across studies and to develop valid hypotheses
with internal and external validity (Fig. 2). In general, the
EEG allows scientists to gauge the overall conscious state
of a patient, as each state of consciousness (e.g., asleep,
wake, anesthetized) is correlated with particular elec-
troencephalographic wave patterns. However, electroen-
cephalographic recordings do not reveal brain structures,
nor can they indicate the functioning of speciﬁc brain
J. Neurosci. Neuroeng. 2014, Vol. 3, No. 2 2168-2011/2014/3/001/005 doi:10.1166/jnsne.2014.1098 1
Electroencephalogram Mapping of Brain States Torres et al.
Fig. 1. A schematic diagram depicting an electroencephalographic
design for gauging neural activity during a state of consciousness. Elec-
trodes made of a silver/silver chloride moiety are placed on the scalp
of a human subject. Action potentials generated by pyramidal neurons
residing within cortical structures (e.g., F3, left frontal cortex; T4, right
temporal lobe) are ampliﬁed (2×) and ﬁltered (2×) against potential
EEG artifacts (e.g., EMG, EOG, rhythmic patterns of respiratory inspi-
ration/expiration indices). The use of additional electrodes signiﬁcantly
allows for the increased resolution of synchronous signals from the brain
parenchyma. A reference (A1/A2; pink) and ground (Fpz; yellow) elec-
trodes are anatomically placed on each ear to provide baseline features of
physiological activity. Eventually, the synchronous signal is transformed
to a digital index via an analog-to-digital converter. The ﬁnal electroen-
cephalographic pattern depicts differences in V over time (cycles per
second; ms, milliseconds). A1, left earlobe; A2, right earlobe.
A neural activity commonly studied by the EEG is sleep-
wake cycles. From this particular technique, we know
that sleep cycles between two states, rapid-eye-movement
(REM) and non-REM sleep that occur at regular 90-minute
intervals. Non-REM sleep has three distinct EEG stages,
whereas REM sleep is characterized by skeletal-muscle
hypotonia . It should be noted that the brain is active
during both sleep states with different bouts of neu-
ronal activity traced to each sleep state. For example,
before a person goes to sleep (i.e., eyes closed and qui-
etly resting), the brain shows prominent alpha waves
(∼10 Hz), whereas during non-REM sleep, the brain
exhibits EEG tracings of delta waves (∼1 to 4 Hz). Thus
brain activity during a relaxed, awake state is quite dif-
ferent from that of the non-REM phase of sleep where
the EEG shows high-voltage, slow wave epochs . The
fact that switches of brain activity corresponds to changes
in behavioral states indicates that sleep-awake transitions
are regulated by different populations of neurons that
promote behavioral arousal or sleep . For example,
acetylcholine-, norepinephrine-, serotonin-, histamine- and
dopamine-containing neurons from the ascending reticular
activating system and hypothalamus promote wakefulness,
whereas GABA- and galanin-containing neurons from the
ventro-lateral preoptic nucleus of the hypothalamus pro-
mote sleep [8, 9]. In addition, orexin (hypocretin) neurons
housed in the lateral hypothalamus maintain wakefulness
as degeneration of these neurons leads to narcolepsy with
Based upon EEG tracings, a desynchronized state (low
voltage, fast EEG) is associated with behavioral arousal,
whereas a synchronized state (high voltage, slow EEG)
is linked to sleep. This pattern of brain activity is com-
plemented by measuring muscle tone activity through the
use of electromyography (EMG) recordings. During non-
REM sleep, skeletal muscle is reduced, whereas during
REM sleep, there is complete loss of skeletal-muscle tone
despite the EEG showing a desynchronized pattern of
neural activity that is remarkable similar to the wake
state [6, 11]. Another commonly used technique to map
sleep bouts is the electro-oculogram (EOG) which records
eye position and movement. When the brain enters a REM
state of sleep, the EOG shows bilateral eye movements
which dominate this particular state of sleep, further allow-
ing a clear-cut distinction from the wake state (Fig. 3).
Other encephalographic patterns observed during sleep
cycles, include sleep spindles (or sigma thalamic-derived
wavebands), K complexes and theta waves (∼4–7 Hz)
which are seen during non-REM sleep. Despite consid-
erable knowledge about the mechanisms underlying the
aforementioned brain wave patterns, their functional sig-
niﬁcance to sleep behavior remains poorly understood.
The EEG is also used as a diagnostic tool for predicting
signs of brain pathology . For instance, EEG technol-
ogy has been used for detecting abnormal neural activ-
ity in prion-based diseases such as Creutzfeldt-Jakob and
in patients with debilitating deﬁciencies in motor func-
tion such as those seen in hepatic encephalopathy .
EEG readouts from these patients often show tri-phasic
wave activity which is thought to reﬂect abnormalities
in cortical-thalamic connections . It should be noted
that tri-phasic waves are also detected in peripheral condi-
tions, including individuals with uremia, hyponatremia and
autoimmune thyroiditis . In general, tri-phasic waves
are of high-amplitude (≥70 V) with three negative-
positive-negative phases that repeat periodically at a lower
amplitude and at the rate of ∼1–2 Hz. Thus, neural activ-
ity patterns in the form of tri-phasic waves appear to occur
as abnormalities in electrical circuits with different clinical
Predicting awareness outcome in patients who survive
acute brain damage but have slipped into a comatose state
is an additional strength of EEG technology. For instance,
EEGs can conﬁrm clinical diagnoses of brain death which
are deﬁned as neural activity below the 2 V range. How-
ever, for patients in a permanent vegetative state, EEG
readouts cannot conﬁrm diagnosis nor predict chances of
recovery because conscious awareness is absent from pur-
poseful motor behavior . In this regard, EEGs are
2J. Neurosci. Neuroeng., 3, 1–5, 2014
Torres et al. Electroencephalogram Mapping of Brain States
Fig. 2. A semi-schematic diagram depicting dorsal and sagittal views of the human skull and brain framed with a 21-electrode tracing system.
Standardized electrode placement distribution is based on the International 10–20 EEG system as described by Khazi et al. . Electrodes on the
right side of the brain are denoted with even numbered electrodes, whereas electrodes on the left size of the brain are denoted with odd numbered
electrodes. Nomenclature of brain structures is shown on adjacent table. The denotation “z” is for zero or midline electrode placement. In addition to
the EEG, optical coherence tomography and functional near-infrared spectroscopy (speciﬁc spectra: 700–1000 nm) are also used to gauge brain activity
in terms of oxygenation and blood volume at micrometer (m) resolutions . Diagram adapted and modiﬁed from 3D4 Medical .
more powerful gauges of consciousness than magnetic res-
onance imaging (MRI) or computed tomographic (CT)
scanning as these imaging techniques cannot detects signs
of conscious awareness; they only visualized structural
damage to the brain parenchyma. In general, EEGs from
comatose patients frequently resemble the high-amplitude,
low-frequency activity (∼13–25 Hz; paradoxical excita-
tion) seen during propofol-induced anesthesia .
The EEG is also isoelectric (a completely ﬂat EEG read-
out) during the most profound state of general anesthesia
(i.e., Phase 4). During Phase 1 of general anesthesia, the
EEG readout shows a signiﬁcant decrease of beta waves
(∼13–30 Hz) and increases of delta waves (∼1–4 Hz).
This light state of general anesthesia is followed by Phase
2 which is characterized by increases in alpha and delta
waves, a phenomenon known as anteriorization [17, 18].
Of interest, the EEG in this particular Phase of gen-
eral anesthesia (the intermediate state) resembles that of
stage 3 of the non-REM sleep cycle. Phase 3 is a deeper
state of general anesthesia and the EEG is characterized
by isoelectric periods intermingled with periods of alpha
and beta waves, a phenomenon known as burst suppres-
sion . Surgery is usually performed during Phases 2
and 3 . From these sequences of brain EEG events, it is
clear that general anesthesia is a reversible state of drug-
Another brain disorder in which EEGs provide
information on certain aspects of pathogenesis and patho-
physiology is epilepsy. Although there are more than
a dozen clinical phenotypes of epilepsy (e.g., absence
seizures), they are generally classiﬁed as generalized
epilepsy (e.g., tonic-clonic epilepsy), partial epilepsy (usu-
ally limited to a speciﬁc brain region), frontal-lobe
epilepsy and temporal-lobe epilepsy [20, 21]. Regard-
less of pathogenesis, epilepsy is characterized by neurons
whose resting potential parameters are closely aligned to
thresholds of depolarization. Under these aberrant con-
ditions, the probability of action potentials signiﬁcantly
increases causing overtly-excited glutamate neurons to ﬁre
action potentials uncontrollably. Alternatively, a decline
in GABAAreceptor signaling could also trigger hyper-
active states of depolarization cycles. The end result of
unimpeded action potentials is an epileptic seizure with a
synchronized, high frequency “spike wave” pattern across
broad populations of cortical and thalamic neurons .
It should be noted that an isoelectric EEG is often induced
by the administration of a barbiturate (e.g., pentobarbital),
J. Neurosci. Neuroeng., 3, 1–5, 2014 3
Electroencephalogram Mapping of Brain States Torres et al.
Fig. 3. Representative EEG, EMG and EOG readouts during an awake
and sleep cycle. Beta waves (∼15–40 Hz) occur during a wake state,
whereas alpha waves (∼10 Hz) occur during a drowsy-like state. Stage 1
of the sleep cycle often shows theta waves in the range of ∼3–7 Hz,
whereas stage 2 exhibits brain waves in the range of ∼12–14 Hz. Stage 2
of the sleep cycle is characterized by the presence of sleep spindles and K
complexes. Delta waves in the range of ∼1–4 Hz predominates stages 3
and 4 of the sleep cycle. Note that during REM sleep, the EEG and EOG
readouts resemble the wave patterns of the wake state. The EMG trac-
ing is highest during waking and lowest during REM sleep. In general,
periods of non-REM and REM sleep are interwoven during a sleep bout.
propofol or etomidate to minimize cell damage during neu-
rosurgery or to stop generalized seizures .
The striking changes of ensemble neural activity
observed in epilepsy, unfortunately, are not seen in other
brain disorders such as Alzheimer’s disease (AD), Parkin-
son’s disease (PD) or clinical depression. In severely
demented patients, the EEG is dominated by slow wave
activity (e.g., delta wave, ∼1 to 4 Hz) over frontal and
temporal lobes . It should be noted, however, that AD
appears to be caused by multiple pathological processes
and therefore electroencephalographic readouts may vary
in terms of etiologies and mechanisms underlying each
pathological process. This complexity also extends to clin-
ical depression where the deﬁnition of pathology, source
of pathology (e.g., genomes, epigenetic reprogramming
and/or environments) and mechanisms of disease are par-
ticularly challenging as well. Regardless, frontal and pari-
etal electroencephalographic band asymmetries (<50 V,
∼8–13 Hz) are considered biomarkers of vulnerability to
endogenous depression and generalized anxiety . How-
ever, longitudinal studies are required to determine more
precisely whether band asymmetries can serve as abso-
lute biomarkers for affective disorders, particularly during
pre-clinical stages of the disease. This EEG information
could have enormous diagnostic and prognostic value for
selecting appropriate therapeutic interventions for the ail-
The EEG is also an important diagnostic instrument
for studying REM sleep parasomnias, in particularly REM
sleep behavior disorder (RBD). In this syndrome, somatic
muscle atonia, which is the deﬁning feature of REM sleep,
is lost from the sleep cycle thus allowing the acting out
of dream mentation often with violent or injurious con-
sequences to the patient or the bed-partner . Interest-
ingly, chronic forms of RBD are associated with PD and
dementia with Lewy body disease as well as in vascular
dementia and fronto-temporal lobar degeneration [27, 28].
At the EEG and EMG level, RBD is characterized by
alpha wave patterns (∼10 Hz), prominent muscle activity
and body movements, which are accompanied by REM as
measured by EOG readouts . The association between
RBD and PD suggests that degeneration of particular auto-
nomic neurons that promote behavioral arousal or sleep
often precede the motor component of PD. Regardless,
idiopathic RBD may foreshadow neurodegenerative dis-
eases in newly diagnosed, unmedicated patients. EEG-
driven analysis of sleep may contribute to the evaluation
of neurodegenerative patients, and it may have potential
sensitivity as a clinical biomarker of the premotor phase
of PD .
In conclusion, quantitative EEG studies have revealed
that brain electrical activity is a regulated and dynamic
process that can be reorganized as a function of con-
sciousness, disease or anesthesia for surgery. These stud-
ies also conﬁrm that the generation and propagation of
action potentials, synaptic transmission and the production
of graded sensory information is a hierarchical processing
theme used by the brain for its own functional purposes.
A major new challenge is to understand how brain electri-
cal activity can be used for objective methods of diagnosis
Conﬂict of Interest
The authors report no conﬂict of interest. Some sections
from the Sleep-Wake Cycles section have been previ-
ously published in non-peered review form (Torres and
Horowitz, Kopf Carrier #81, 2014).
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