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Brain
Simulations With Spiking Neurons
Student:
Kuangwa Zziwa
Project
Outcomes
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To
summarize various learning mechanisms for supervised neural networks with
spiking neurons using temporal coding and develop a suitable monosynaptic
modification of the Hebb learning rule, where the weight change depends on
the time difference of single presynaptic and postsynaptic firing times.
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To
propose the architecture of SPIN OB simulator based on single neuron for
modeling the information processing performed by the olfactory bulb. The
model will be used as a valuable tool in further studies of cortical
associative memory.
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To
write the code of this simulator and build a graphical user interface using
C++ and Matlab.
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To
analyze the results and compare to those received by GENESIS simulator.
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