Výsledky vyhledávání - "DePasquale, Brian"

Dissertation/ Thesis

Methods for Building Network Models of Neural Circuits

Autor: DePasquale, Brian David

Artificial recurrent neural networks (RNNs) are powerful models for understanding and modeling dynamic computation in neural circuits. As such, RNNs that have been constructed to perform tasks analogous to typical behaviors studied in systems neurosc

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full-FORCE: A Target-Based Method for Training Recurrent Networks

Autor: DePasquale, Brian, Cueva, Christopher J., Rajan, Kanaka, Escola, G. Sean, Abbott, L. F.

Trained recurrent networks are powerful tools for modeling dynamic neural computations. We present a target-based method for modifying the full connectivity matrix of a recurrent network to train it to perform tasks involving temporally complex input

Externí odkaz: http://arxiv.org/abs/1710.03070

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Akademický článek

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Using Firing-Rate Dynamics to Train Recurrent Networks of Spiking Model Neurons

Autor: DePasquale, Brian, Churchland, Mark M., Abbott, L. F.

Recurrent neural networks are powerful tools for understanding and modeling computation and representation by populations of neurons. Continuous-variable or "rate" model networks have been analyzed and applied extensively for these purposes. However,

Externí odkaz: http://arxiv.org/abs/1601.07620

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