Colloquium, October 16th, 2014 -- The Dynamics of Firing-Rate and Spiking Neural Networks
Автор: NYU Physics
Загружено: 2014-10-16
Просмотров: 5379
Larry Abbott
Columbia University
The Dynamics of Firing-Rate and Spiking Neural Networks
Large, strongly coupled neural networks tend to produce chaotic spontaneous activity. This might appear to make them unsuitable for generating reliable sensory responses or repeatable motor patterns. However, this is not the case. Inputs can induce a phase transition, leading to responses uncontaminated by chaotic "noise". Likewise, appropriately trained feedback units can control the chaos, resulting in a wide variety of repeatable output patterns. I will discuss applications of these idea to modeling how context-dependent tasks are performed by neural circuits and how long sequences can be generated.
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