History of the Medical EEG

1925 - Hans Berger, a neuro-psychiatrist, recorded the first human EEG on his son Klaus. An EEG records brain electrical activity over time. Berger named the 10 cycles/second rhythms "alpha" waves.1

1 sec
of alpha

Alpha wave - 9-10 cycles/sec. - the first regular brainwave described.
The first neurologists and neuro-psychiatrists to use EEG saw that the rate, amplitude and constancy of their alpha waves were different.2

1 sec
of beta

Beta wave [17-19 cycles/sec.] - the second regular brainwave described.
Early research also found that some EEGs show mostly beta waves.

1 sec
of delta

Delta wave wave [2-3 cycles/sec.] - the third regular brainwave described.

1 sec
of theta

Theta wave [5-7 cycles/sec.] - the fourth regular brainwave described.
(Other regular rhythms are omitted for simplicity).

1930s - Neurologists discovered transient, irregular activity in the EEG of patients with seizures or epilepsy. Like the short-lived nature of an observable seizure, irregular EEG activity was rapid in onset and offset, easy to see and looked like a glitch in an electrical circuit. Irregular EEG activity was objective evidence of brain dysfunction that a doctor could not know from a medical exam.

Differences in alpha waves meant human neurophysiology is different, but the meaning and utility of this observation would only emerge half a century later.

Leaving the medical significance of brainwave variations for others to pursue, neurologists applied their EEG work to diagnosing and treating patients with seizures or epilepsy.1

Irregular EEG activity
1950s - Neurologists and neurosurgeons at major medical centers were using EEG to identify irregular activity and to monitor the effects of medical treatment on individual brain function. EEG also evolved as a tool to detect brainwave patterns indicating coma or brain death, to study sleep and monitor sensory and motoric pathways.

1930s-1940s - A few neuro-psychiatrists carefully studied the regular brainwaves in healthy adults and saw that they remained distinct and stable over time. The conclusion: an EEG is characteristic of a person.3

Three neuro-psychiatrists noted subtle differences in their usual brainwave pattern. Then, each submitted to brief physical challenges over five years, including inadequate oxygen, stomach distension, decompression sickness, low blood sugar, excess alcohol, low carbon dioxide, a high dose of anti-malaria medication and other noxious challenges. An EEG was done during and after each distressing event.

Each doctor's brainwaves were temporarily altered by the stressors, but two of them suffered visual defects and migraine headaches, during which their regular brainwaves distorted into irregular, slow waves before returning to their usual pattern.

EEG had served as a neurological gauge in real time, tracking brain physiology in health, during a medical illness and back to health.

After the study, each doctor's regular EEG brainwaves looked the same as five years earlier.4

Mid-20th Century - Brainwave pattern recognition had showed:
  • Brainwaves are individually distinct and stable over time.
  • Brainwave variations among persons mean neurological differences.
  • Neurological differences mean different brain physiology.
  • EEG tracks brain physiology during health and physical distress.

Advances in psychology increasingly influenced neuro-psychiatry and psychiatry by substituting psychological theories and terms for lack of neurophysiologic knowledge. An example is that medical EEG researchers repeatedly tried to link brainwave variations [neurophysiology] with personality [a bio-psycho-social concept]. They were not successful.

The first edition of Diagnostic & Statistical Manual of Mental Disorders [DSM] was published in the 1950s. The manual's main purpose was to organize particular symptoms and behaviors into categories of disordered mentation. The DSM was not intended to predict response to medication; however, the absence of a neurological gauge to show the differential effects of medicinal agents on individual brain activity, doctors used DSM symptoms and signs for this purpose.

1970s - The availability of high-speed computers provided digitized EEG processing with efficient recording and data storage. Additionally, quantified features, of the regular brainwaves which were not detectable by visible inspection were available for the first time.

Pioneering neuroscientists constructed quantitative EEG databases in asymptomatic persons from childhood to old age.5-8

For the first time, neuro-psychiatrists and psychiatrists could compare a symptomatic patient's EEG & QEEG values with those of asymptomatic persons the same age.

1986 - Hamlin Emory, M.D. and Stephen Suffin, M.D. were dissatisfied with their patients' outcomes from traditional psychiatric treatment. Convinced that persistent mental disorders were symptoms and signs of medical illnesses, they thought that EEG/QEEG data might reveal how medications affected individual brain function and help them improve patients' therapeutic outcomes.

1987 - Today - Dr. Emory has applied procedures used in general medical practice to improve the therapeutic outcomes of his psychiatric patients:
  • Physiology is primary, collect and monitor atypical physical/cognitive/mental status findings.
  • Obtain each patient's relevant lab values, including baseline EEG/QEEG data.
  • Atypical physical/cognitive findings and variant EEG/QEEG data are factual clues about the presence of unique brain activity.
  • Dr. Emory selects allopathic and/or naturopathic treatment based on the normative outcomes of prior patients with similar EEG/QEEG data.
2010 - An automated version of Dr. Emory's EEG medication predictor was shown more effective than the traditional psychiatric approach in guiding medical treatment for patients with major depressive disorder [MDD]. Psychiatrists at 5 prestigious U.S. medical centers achieved a 68% success rate when they used Dr. Emory's EEG pattern recognition to individualize each patient's medicinal regimen. By contrast, when they used the traditional approach - choosing medication from a patient's symptoms and behaviors - their success rate was only 39%.

Published in The Journal of Psychiatric Research.9 (Jan. 2011), this research showed that individual EEG/QEEG data provided sufficient evidence to markedly improve the usual rate of successful medical outcomes in patients with Major Depressive Disorder. The superior result from sorting patients by neurophysiologic differences was a breakthrough event in treating MDD and makes obvious the need to convert psychiatric therapeutics to the medical model.

Dr. Emory stated, "A majority of patients with serious, persistent disorders such as Major Depression do not achieve physical health and mental wellbeing; instead, they suffer from being physically diminished and mentally impaired. I am pleased that an automated version of my EEG medication selection was superior to best psychiatric practice in this study."

  • Neidermeyer E, Lopes da Silva, F. Electroencephalography. 5th ed. Philadelphia, PA: Lippincott Williams & Wilkins; 2005.
  • Adrian ED, Yamagiwa K. The origin of the Berger rhythm. Brain. 1935;58:323-351.
  • Lemere F. The significance of individual differences in the Berger rhythm. Brain. 1936;59:366-375.
  • Engel GL, Romano J, Ferris EB. Variations in the normal electroencephalogram during a five year period. Science. 1947;105(2736):600-601.
  • John ER, Karmel BZ, Corning WC, et al. Neurometrics. Science. 1977;196(4297):1393-1410.
  • John ER, Prichep LS, Almas M. Toward a quantitative electrophysiological classification system in psychiatry. In: Racagni G, Brunello N., Fukuda T, eds. Biological Psychiatry, Amsterdam: Elsevier. 1991;2:401-406.
  • Prichep LS, John ER, Essig-Peppard T, Alper KR. Neurometric subtyping of depressive disorders. In: Cassullo CL, Invernizzi G, Sacchetti E, Vita A, eds. Plasticity and Morphology of the Central Nervous System. London: MTP Press. 1990.
  • Prichep LS, Mas F, Hollander E, et al. Quantitative electroencephalographic subtyping of obsessive compulsive disorder. Psychiatric Res: Neuroimaging. 1993;50(1):25-32.
  • DeBattista C, Gustavo K, Hoffman D, et al. The use of referenced-EEG (rEEG) in assisting medication selection for the treatment of depression. J Psychiatr Res. 2011;45(1):64-75.
Latest News

April 2017

Lecture: Inclusive Medical Approach with EEG & QEEG Features Predict Catecholamine Response in Idiopathic Genetic Epilepsies (IGE);
SBMT Annual Meeting, Los Angeles Millennial Biltmore, April 18, 2017

Lecture: Neuroplasticity in Medical Illnesses and Psychiatric Syndromes;;
SBMT Annual Meeting, Los Angeles Millennial Biltmore, April 20, 2017

November 2016

Glycaemic Co< (Journal of Diabetes & Vascular Research Disease. DOI: 10.1177/1479164116675492)

March 2016

Monoamine Oxidase Inhibition in a Patient With Type I Diabetes and Depression Emory H. and Mizrahi, N, // (Journal of Diabetes Science and Technology. DOI: 10.1177/1932296816638106)

January 2016

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Fall 2015

Actor Dick Van Dyke publishes a book entitled, "Keep Moving and Other Tips and Truths About Aging," in which he describes his treatment by Dr. Hamlin Emory.

Spring 2015

Quantitative EEG and Current Source Density Analysis of Combined Antiepileptic Drugs and Dopaminergic Agents in Genetic Epilepsy W. Hamlin Emory, Christopher Wells and Neptune Mizrahi. // (Accepted for publication Spring 2015)

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