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From brain activities to mathematical models. The TempUnit model, a study case for GPU computing in scientific computation. What part of the brain?. How to study it ?. First attempt: use of a MLP. What is a MLP?. First Attempt: MLP (2). Results (1). Results (2). Crack the code !!.
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From brain activities to mathematical models The TempUnit model, a study case for GPU computing in scientific computation.
First attempt: use of a MLP • What is a MLP?
Crack the code !! • Frequency code (Number of spikes in a time lap) ? • Spatial coding (distributed trough the network) ? • Temporal code (Precise binary pattern) ? • Spatio-temporal code (Synchronies) ? • Something else ?
The model Xt x
Learn the parameters vi • Solving a system of linear equation oversized. • Much faster and straightforward than backpropagation for the MLP Example of a learned basis function
Graph of Neuronal Activity • The output activity of a TempUnit neural network can be described by a graph directly related to its connectivity • You determine the topology of your graph easily • Allow to determine the input activity for a particular desired output
EPSP from the integrate-and-fire model • From the integrate and fire, the α function: time (Gerstner & Kistler, 2002) To find the position of the maximum (peak), one has to resolve the following equation:
The new equation of the TempUnit model: p=0 p=6 p : position of the synapse time With μ, the maximum value: