Observed Brain Dynamics Review

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(More customer reviews)Since the discovery of the kimograph, the statement, "Method ist Alles", is much appreciated in neuroscience. Progress depends on innovation, and progress in a particular discipline depends strongly on methods developed in related fields. The study of brain dynamics requires data collection and, perhaps even more so, data analysis. The author is a leading expert on many areas related to signal analysis and as a co-organizer of the now famous "Analysis of Neural Data" annual course, has trained and influenced many young minds. However, most of this knowledge was only available in notebooks and references linked to the vast jungle of statistics, non-linear dynamics and math. Now, we have a 'recipe' book. Mitra's book contains and discusses virtually all major contemporary methods used in analyzing continuous and point process data, with a strong emphasis on the strengths of frequency domain analysis. Although the chapters are quite demanding and require much more than the usual '101' intros to the topics, each of them are patiently and scholarly introduced with ample examples to guide the reader. This volume should be available for frequent consultation in every lab serious about neuroscience data processing.

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The biomedical sciences have recently undergone revolutionary change, due to the ability to digitize and store large data sets. In neuroscience, the data sources include measurements of neural activity measured using electrode arrays, EEG and MEG, brain imaging data from PET, fMRI, and optical imaging methods. Analysis, visualization, and management of these time series data sets is a growing field of research that has become increasingly important both for experimentalists and theorists interested in brain function. Written by investigators who have played an important role in developing the subject and in its pedagogical exposition, the current volume addresses the need for a textbook in this interdisciplinary area.The book is written for a broad spectrum of readers ranging from physical scientists, mathematicians, and statisticians wishing to educate themselves about neuroscience, to biologists who would like to learn time series analysis methods in particular and refresh their mathematical and statistical knowledge in general, through self-pedagogy. It may also be used as a supplement for a quantitative course in neurobiology or as a textbook for instruction on neural signal processing.The first part of the book contains a set of essays meant to provide conceptual background which are not technical and shall be generally accessible. Salient features include the adoption of an active perspective of the nervous system, an emphasis on function, and a brief survey of different theoretical accounts in neuroscience. The second part is the longest in the book, and contains a refresher course in mathematics and statistics leading up to time series analysis techniques. The third part contains applications of data analysis techniques to the range of data sources indicated above (also available as part of the Chronux data analysis platform from http://chronux.org), and the fourth part contains special topics.

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