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MATLAB for Neuroscientists, 2nd Edition by Nicholas G. Hatsopoulos, Adam Seth Dickey, Tanya I. Baker, Marc D. Benayoun, Michael E. Lusignan, Pascal Wallisch

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Index

Note: Page numbers followed by “f” and “t” refer to figures and tables, respectively.

A

Action potential, See Fitzhugh-Nagumo (FN) model; Neuron action potential modeling
Active neurons, 481–482, 482f, 483, 485
Addition, 9
matrix, 61
addpath, 369
allchild, 148
alpha, 511
Alpha error, 211, 211t
Alpha rhythm, 419
Amplitude spectrum, analysis, 233–234
Analysis of variance, 95–97, 168, 169t, 170
anova1, 168, 168, 170
anova2, 170
anovan, 170
ans =, 9–12
Arrays, 58
operations versus matrix operations, 21
Artificial neural network, See Neural network
Attention, See Posner paradigm
axes_props, 148

B

Backpropagation, neural networks, 504, 511–512
Band-pass filter, 350–351
bar, 28, 29b, 30
Baum-Welch algorithm, 456–457
Bayesian analysis, 100–102

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