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Mechanisms of gamma oscillations.

ABSTRACT: Gamma rhythms are commonly observed in many brain regions during both waking and sleep states, yet their functions and mechanisms remain a matter of debate. Here we review the cellular and synaptic mechanisms underlying gamma oscillations and outline empirical questions and controversial conceptual issues. Our main points are as follows: First, gamma-band rhythmogenesis is inextricably tied to perisomatic inhibition. Second, gamma oscillations are short-lived and typically emerge from the coordinated interaction of excitation and inhibition, which can be detected as local field potentials. Third, gamma rhythm typically concurs with irregular firing of single neurons, and the network frequency of gamma oscillations varies extensively depending on the underlying mechanism. To document gamma oscillations, efforts should be made to distinguish them from mere increases of gamma-band power and/or increased spiking activity. Fourth, the magnitude of gamma oscillation is modulated by slower rhythms. Such cross-frequency coupling may serve to couple active patches of cortical circuits. Because of their ubiquitous nature and strong correlation with the "operational modes" of local circuits, gamma oscillations continue to provide important clues about neuronal population dynamics in health and disease.

SUBMITTER: Buzsaki G

PROVIDER: S-EPMC4049541 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Mechanisms of gamma oscillations.

Buzsáki György G Wang Xiao-Jing XJ

Annual review of neuroscience 20120320

Gamma rhythms are commonly observed in many brain regions during both waking and sleep states, yet their functions and mechanisms remain a matter of debate. Here we review the cellular and synaptic mechanisms underlying gamma oscillations and outline empirical questions and controversial conceptual issues. Our main points are as follows: First, gamma-band rhythmogenesis is inextricably tied to perisomatic inhibition. Second, gamma oscillations are short-lived and typically emerge from the coordi ...[more]

PMID: 22443509

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Project description:Certain visual images, even in the absence of motion or flicker, can trigger seizures in patients with photosensitive epilepsy. As of yet, there is no systematic explanation as to why some static images are likely to provoke seizures, while others pose little or no risk. Here, we examined the neurophysiology literature to assess whether the pattern of neural responses in healthy visual cortex is predictive of the pathological responses in photosensitive epilepsy. Previous studies have suggested that gamma oscillations (30-80 Hz) measured in human visual cortex may play a role in seizure generation [1,2]. Recently, we and others have shown that increases in gamma band power can come from two very different cortical signals, one that is oscillatory (with a narrow peak between 30 Hz and 80 Hz), and another that is broadband[3]. The oscillatory signal arises from neuronal synchrony in the local population, while the broadband signal reflects the level of asynchronous neuronal activity, and is correlated with multiunit spiking [4]. These two responses have different biological origins and different selectivity for image properties. Here, we followed up on the previous proposals [1,2] to ask whether the image features that increase seizure likelihood in photosensitive epilepsy are linked to narrowband gamma oscillations specifically, or are associated with any kind of increase in visual activity. Based on published work, we compared pairs of image classes on a number of dimensions, and show that the type of image that elicits larger narrowband gamma oscillations in healthy visual cortex is also more likely to provoke seizures or pre-seizure activity in patients with photosensitive epilepsy. In contrast, images that elicit larger broadband, multiunit, or fMRI responses are much less predictive of seizure activity. We propose that a risk factor for seizures in patients with photosensitive epilepsy is engagement of the circuitry that produces gamma oscillations.

Dataset Information

Mechanisms of gamma oscillations.

Publications

Mechanisms of gamma oscillations.

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