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Processing of sounds by population spikes in a model of primary auditory cortex
 

Summary: Processing of sounds by population spikes in a model
of primary auditory cortex
Alex Loebel1
, Israel Nelken2
and Misha Tsodyks1,
1. Department of Neurobiology, Weizmann Institute of Science, Rehovot, Israel.
2. Department of Neurobiology, Silberman Institute of Life Sciences, and The Interdisciplinary Center for Neural Computation, Safra
Campus, Givat Ram, Hebrew University, Jerusalem, Israel.
Review Editors: Larry Abbott, Center for Neurobiology and Behavior, Columbia University, USA
Terry Sejnowsky, Howard Hughes Medical Institute, The Salk Institute for Biological Studies, USA
We propose a model of the primary auditory cortex (A1), in which each iso-frequency column is represented by a recurrent neural network
with short-term synaptic depression. Such networks can emit Population Spikes, in which most of the neurons fire synchronously for a
short time period. Different columns are interconnected in a way that reflects the tonotopic map in A1, and population spikes can propagate
along the map from one column to the next, in a temporally precise manner that depends on the specific input presented to the network.
The network, therefore, processes incoming sounds by precise sequences of population spikes that are embedded in a continuous
asynchronous activity, with both of these response components carrying information about the inputs and interacting with each other.
With these basic characteristics, the model can account for a wide range of experimental findings. We reproduce neuronal frequency
tuning curves, whose width depends on the strength of the intracortical inhibitory and excitatory connections. Non-simultaneous two-
tone stimuli show forward masking depending on their temporal separation, as well as on the duration of the first stimulus. The model
also exhibits non-linear suppressive interactions between sub-threshold tones and broad-band noise inputs, similar to the hypersensitive

  

Source: Andrzejak, Ralph Gregor - Departament de Tecnologia, Universitat Pompeu Fabra

 

Collections: Computer Technologies and Information Sciences