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Book review of Electrophysiological Recording Techniques, edited by Robert P Vertes and Robert W Stackman, Jr

DOI: 10.1186/1475-925x-10-63

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Abstract:

The book "Electrophysiological Recording Techniques" published recently by Humana Press is an important collection of articles devoted to an issue that has gained increasing attention in modern neuroscience research. Several sources of this interest exist.Since the discovery of biological signals in the brain, the question of the neural codes of information processing has remained a challenging one. Current models of information processing and communication in the brain recognize three different levels: (a) microscopic, where ion channels, spiking neurons and neuronal assemblies are the neural substrate of information processing and transmission; (b) mesoscopic, where oscillatory electroencephalographic (EEG) activity is detected at different scales reflecting the formation and functioning of distributed neural networks, and (c) macroscopic, where regional large-scale activation and synchronization support the integrative information processes. Electrophysiological techniques have made it possible to measure and analyze in detail the bioelectric signals at each level - in single neurons, in neuronal ensembles, and integrated spatially distributed neural structures. However, modern neuroscience still confronts the problem of how neural codes are transferred and communicate across different levels and how multi-scale information processing is organized. The collection of research issues in the current book is a contributing step to this long-standing question.Neuroscience researchers were and still are attracted by the electrophysiologically recorded signals due to their major property - good time resolution, which allows one to describe precisely the temporal dynamics of neurophysiological events. Electrophysiological signals may be recorded with a time resolution of less than 1 ms, which makes it possible to follow both fast and slow processes of information processing. These signals can therefore capture with high fidelity a variety of neural mechanisms operating a

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