ArticlePloS one2014
Distribution of orientation selectivity in recurrent networks of spiking neurons with different random topologies.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Propagation of orientation selectivity in a spiking network model of layered primary visual cortex.PLoS computational biology · 2019Article
- Dynamical patterns underlying response properties of cortical circuits.Journal of the Royal Society, Interface · 2018Article
- Emergence of Functional Specificity in Balanced Networks with Synaptic Plasticity.PLoS computational biology · 2015Article
- Orientation selectivity in inhibition-dominated networks of spiking neurons: effect of single neuron properties and network dynamics.PLoS computational biology · 2015Article
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2 authors.
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Abstract
Neurons in the primary visual cortex are more or less selective for the orientation of a light bar used for stimulation. A broad distribution of individual grades of orientation selectivity has in fact been reported in all species. A possible reason for emergence of broad distributions is the recurrent network within which the stimulus is being processed. Here we compute the distribution of orientation selectivity in randomly connected model networks that are equipped with different spatial patterns of connectivity. We show that, for a wide variety of connectivity patterns, a linear theory based on firing rates accurately approximates the outcome of direct numerical simulations of networks of spiking neurons. Distance dependent connectivity in networks with a more biologically realistic structure does not compromise our linear analysis, as long as the linearized dynamics, and hence the uniform asynchronous irregular activity state, remain stable. We conclude that linear mechanisms of stimulus processing are indeed responsible for the emergence of orientation selectivity and its distribution in recurrent networks with functionally heterogeneous synaptic connectivity.
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