Gamma, alpha, delta, and theta oscillations govern cognitive processes

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Abstract

The increased interest in gamma oscillations, now widely regarded as functionally relevant signals of the brain, underlines the importance of the concept of event-related oscillations for bridging the gap between single neurons and neural assemblies. Taking this concept further, we review experiments showing that oscillatory phenomena such as alpha, theta, and delta responses to events are, just as the gamma band, strongly interwoven with sensory and cognitive functions. This review argues that selectively distributed delta, theta, alpha and gamma oscillatory systems act as resonant communication networks through large populations of neurons. Thus, oscillatory processes might play a major role in functional communication in the brain in relation to memory and integrative functions.

Section snippets

Why this special issue

A great change has taken place in Neuroscience. Brain scientists have recognized the importance of oscillatory phenomena and the functional EEG. This new development will not only govern improvements in Neuroscience within the next two or three decades, it will probably create the basic approach for the biophysical understanding of brain machinery. At the beginning of the 1970s only few research scientists emphasized the importance of oscillatory brain activity. Now this branch of Neuroscience

Oscillations and functions: introductory synopsis

“During the ‘Decade of the Brain’ neuroscience is coming to terms with its ultimate problem: understanding the mechanisms by which the immense number of neurons in the human brain interact to produce higher cognitive functions” (Freeman, 1998). As one of the candidate mechanisms, oscillatory neuroelectric activity has recently attracted much interest. In particular, this holds for synchronous gamma activity in spatially distributed cells. In this framework, the present review has several aims,

Selectively distributed oscillatory systems

To end this survey of experimental data, it is suggested that event-related oscillations might help us to understand what Fessard called ‘principles that govern the most general transformations — or transfer functions — of multiunit homogeneous messages during their progression through neuronal networks’ (Fessard, 1961). The transfer function describes the ability of a network to increase or impede transmission of signals in given frequency channels. The transfer function, represented

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