Information theoretic methods are now widely used for the analysis of spike train data. However, developing robust implementations of these methods can be tedious and time-consuming. In order to facilitate further adoption of these methods, the Spike Train Analysis Toolkit implements several information-theoretic spike train analysis techniques.

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“The sensory-triggered activity of a neuron is typically characterized in terms of a tuning curve, which describes the neuron’s average response as a function of a parameter that characterizes a physical stimulus. What determines the shapes of tuning curves in a neuronal population?”

Optimal Tuning Curves for Four Classes of Downstream Functions

by Emilio Salinas
Department of Neurobiology and Anatomy, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA

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Information theory quantifies how much information a neural response carries about the stimulus. This can be compared to the information transferred in particular models of the stimulus-response function and to maximum possible information transfer. Such comparisons are crucial because they validate assumptions present in any neurophysiological analysis.
An example of reverse reconstruction
The authors review information-theory basics before demonstrating its use in neural coding, validating simple stimulus-response models of neural coding of dynamic stimuli.
By Alexander Borst & Frederic E. Theunissen
Nature Neuroscience 2, 947 – 957 (1999)
doi:10.1038/14731

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The nervous system represents time-dependent signals in sequences of discrete action potentials or spikes, all spikes are identical so that information is carried only in the spike arrival times.
Entropy
A scientific paper by Steven P. Strong, Roland Koberle, Rob R. de Ruyter van Steveninck, and William Bialek
-NEC Research Institute, Princeton, New Jersey
-Department of Physics, Princeton University, Princeton, New Jersey

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