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Dynamic macroscopic analysis of neural populations with Bayesian Approximate Inference

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ssll_lib

This code implements approximate inference methods for State-Space Analysis of Spike Correlations (Shimazaki et al. PLoS Comp Bio 2012). It is an extension of the existing code from repository https://github.com/tomxsharp/ssll (For Matlab Code refer to http://github.com/shimazaki/dynamic_corr).

Copyright (C) 2016 Christian Donner (christian.donner@bccn-berlin.de) Hideaki Shimazaki (shimazaki@brain.riken.jp)

Exact Model: See the original paper for mathematical details, and example_exact.py for a demonstration of how to use the program.

Approximation Methods: See arxiv publication http://arxiv.org/abs/1607.08840 (not peer reviewed) for mathematical details on approximation methods. Demonstration of approximation methods in example_approx.py.

Contact for queries: Christian Donner

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