|
|
|
Data
|
Fisher and Shannon information in finite neural populations (Yarrow et al. 2012)
|
|
|
|
|
|
|
Here we model populations of rate-coding neurons with bell-shaped tuning curves and multiplicative Gaussian noise. This Matlab code supports the calculation of information theoretic (mutual information, stimulus-specific information, stimulus-specific surprise) and Fisher-based measures (Fisher information, I_Fisher, SSI_Fisher) in these population models. The information theoretic measures are computed by Monte Carlo integration, which allows computationally-intensive decompositions of the mutual information to be computed for relatively large populations (hundreds of neurons).
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
-
Yarrow S, Challis E, Seriès P (2012) Show
Other
|
|
|
|
|
|
|
|
|
|
-
Yarrow, Stuart [s.yarrow at ed.ac.uk] Show
Other
|
s.yarrow@ed.ac.uk
|
Generic rate-coding neuron
|
|
|
|
|
|
|
|
|
Coding population
|
|
|
|
|
Yarrow, Stuart <s.yarrow@ed.ac.uk>
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
