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The Dynamic Brain – An Exploration of Neuronal Variability and Its Functional Significance | Oxford Scholarship Online
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The Dynamic Brain: An Exploration of Neuronal Variability and Its Functional Significance

Mingzhou Ding, PhD and Dennis Glanzman,PhD

Abstract

Neuronal responses to identically presented stimuli are extremely variable. This variability has in the past often been regarded as “noise.” At the single neuron level, interspike interval (ISI) histograms constructed during either spontaneous or stimulus-evoked activity reveal a Poisson type distribution. These observations have been taken as evidence that neurons are intrinsically “noisy” in their firing properties. More recent attempts to measure the information content of single neuron spike trains have revealed that a surprising amount of information can be coded in spike trains even in ... More

Keywords: neuronal variability, neural spike trains, electroencephalography, brain activity networks, noise, fMRI, brain disorders, computational modeling, cognition, Poisson model

Bibliographic Information

Print publication date: 2011 Print ISBN-13: 9780195393798
Published to Oxford Scholarship Online: September 2011 DOI:10.1093/acprof:oso/9780195393798.001.0001

Authors

Affiliations are at time of print publication.

Mingzhou Ding, PhD, editor
Department of Biomedical Engineering, University of Florida

Dennis Glanzman,PhD, editor
National Institute of Mental Health

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Contents

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Part 1: Characterizing Neuronal Variability

3 Neural Coding: Variability and Information

Richard B. Stein and Dirk G. Everaert

Part 2: Dynamics of Neuronal Ensembles

5 Inherent Biases in Spontaneous Cortical Dynamics

Chou P. Hung, Benjamin M. Ramsden, and Anna Wang Roe

6 Phase Resetting in the Presence of Noise and Heterogeneity

Srisairam Achuthan, Fred H. Sieling, Astrid A. Prinz, and Carmen C. Canavier

7 Understanding Animal-to-Animal Variability in Neuronal and Network Properties

Astrid A. Prinz, Tomasz G. Smolinski, and Amber E. Hudson

8 Dynamical Parameter and State Estimation in Neuron Models

Henry D. I. Abarbanel, Paul H. Bryant, Philip E. Gill, Mark Kostuk, Justin Rofeh, Zakary Singer, Bryan Toth, and Elizabeth Wong

Part 3: Neuronal Variability and Cognition

10 Linking Neuronal Variability to Perceptual Decision Making via Neuroimaging

Paul Sajda, Marios G. Philiastides, Hauke Heekeren, and Roger Ratcliff

Part 4: Neuronal Variability and Brain Disorders

End Matter