In the past several years, there has been a great deal of interest in using oscillations of the electroencephalogram (EEG) to understand the neural substrates of neuropsychiatric disorders. These EEG oscillations represent the coordinated activity of large populations of neurons, and oscillations in different frequency bands of the EEG are generated by distinct neural circuitries. For example, oscillations in the gamma band of the EEG (30–100 Hz) can be produced by reciprocal interactions between pyramidal cells and fast-spiking inhibitory interneurons, whereas beta (13–30 Hz) oscillations can be produced by interactions between gap junction–connected bursting pyramidal cells (
1). The identification of some of the generating circuits of particular oscillations has indicated that EEG oscillations may become a promising central tool in translational neuroscience for two reasons. First, the generating circuits of at least some oscillations appear to be conserved across species (
- Kopell N.
- Kramer M.A.
- Malerba P.
- Whittington M.A.
Are different rhythms good for different functions?.
Front Hum Neurosci. 2010; 4: 187
2). It may be possible to draw inferences about the effects of a treatment on an oscillation in a human patient based on the effects of that treatment in an animal model. Second, progress in neuropathology research has led to the identification of abnormal elements of neural circuits in neuropsychiatric disorders. The best examples are in schizophrenia (SZ), in which abnormalities of inhibitory interneurons have been characterized, especially in the parvalbumin-expressing, fast-spiking interneurons that are required for gamma generation (
- Buzsáki G.
- Logothetis N.
- Singer W.
Scaling brain size, keeping timing: Evolutionary preservation of brain rhythms.
Neuron. 2013; 80: 751-764
3). Knowing how particular cells are disturbed in a disorder could lead to precise models of these disturbances in animal models using genetic approaches. These two avenues of progress could be united with measures of EEG oscillations in humans, which provide noninvasive measures of the activity of distinct neural circuits. Using animal and computational models of neural circuit abnormalities derived from neuropathologic studies, it may be possible to determine the source of oscillation abnormalities in patients with neuropsychiatric disorders.
- Lewis D.A.
- Curley A.A.
- Glausier J.R.
- Volk D.W.
Cortical parvalbumin interneurons and cognitive dysfunction in schizophrenia.
Trends Neurosci. 2012; 35: 57-67
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- Are different rhythms good for different functions?.Front Hum Neurosci. 2010; 4: 187
- Scaling brain size, keeping timing: Evolutionary preservation of brain rhythms.Neuron. 2013; 80: 751-764
- Cortical parvalbumin interneurons and cognitive dysfunction in schizophrenia.Trends Neurosci. 2012; 35: 57-67
- Resting state electroencephalogram oscillatory abnormalities in schizophrenia and psychotic bipolar patients and their relatives from the bipolar and schizophrenia network on intermediate phenotypes study.Biol Psychiatry. 2014; 76: 456-465
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- Gamma-band auditory steady-state responses are impaired in first episode psychosis.Biol Psychiatry. 2008; 64: 369-375
- A thalamo-hippocampal-ventral tegmental area loop may produce the positive feedback that underlies the psychotic break in schizophrenia.Biol Psychiatry. 2010; 68: 17-24
- Baseline gamma power during auditory steady-state stimulation in schizophrenia.Front Hum Neurosci. 2012; 5: 190
- Altered global brain signal in schizophrenia.Proc Natl Acad Sci U S A. 2014; 111: 7438-7443
Accepted: July 8, 2014
Received: July 7, 2014
Published by Elsevier Inc.
ScienceDirectAccess this article on ScienceDirect
- Resting State Electroencephalogram Oscillatory Abnormalities in Schizophrenia and Psychotic Bipolar Patients and Their Relatives from the Bipolar and Schizophrenia Network on Intermediate Phenotypes StudyBiological PsychiatryVol. 76Issue 6
- PreviewAbnormal resting state electroencephalogram (EEG) oscillations are reported in schizophrenia (SZ) and bipolar disorder, illnesses with overlapping symptoms and genetic risk. However, less evidence exists on whether similar EEG spectral abnormalities are present in individuals with both disorders or whether these abnormalities are present in first-degree relatives, possibly representing genetic predisposition for these disorders.