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An Efficient Coding Hypothesis Links Sparsity and Selectivity of Neural Responses

Overview of attention for article published in PLOS ONE, October 2011
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Title
An Efficient Coding Hypothesis Links Sparsity and Selectivity of Neural Responses
Published in
PLOS ONE, October 2011
DOI 10.1371/journal.pone.0025506
Pubmed ID
Authors

Florian Blättler, Richard H. R. Hahnloser

Abstract

To what extent are sensory responses in the brain compatible with first-order principles? The efficient coding hypothesis projects that neurons use as few spikes as possible to faithfully represent natural stimuli. However, many sparsely firing neurons in higher brain areas seem to violate this hypothesis in that they respond more to familiar stimuli than to nonfamiliar stimuli. We reconcile this discrepancy by showing that efficient sensory responses give rise to stimulus selectivity that depends on the stimulus-independent firing threshold and the balance between excitatory and inhibitory inputs. We construct a cost function that enforces minimal firing rates in model neurons by linearly punishing suprathreshold synaptic currents. By contrast, subthreshold currents are punished quadratically, which allows us to optimally reconstruct sensory inputs from elicited responses. We train synaptic currents on many renditions of a particular bird's own song (BOS) and few renditions of conspecific birds' songs (CONs). During training, model neurons develop a response selectivity with complex dependence on the firing threshold. At low thresholds, they fire densely and prefer CON and the reverse BOS (REV) over BOS. However, at high thresholds or when hyperpolarized, they fire sparsely and prefer BOS over REV and over CON. Based on this selectivity reversal, our model suggests that preference for a highly familiar stimulus corresponds to a high-threshold or strong-inhibition regime of an efficient coding strategy. Our findings apply to songbird mirror neurons, and in general, they suggest that the brain may be endowed with simple mechanisms to rapidly change selectivity of neural responses to focus sensory processing on either familiar or nonfamiliar stimuli. In summary, we find support for the efficient coding hypothesis and provide new insights into the interplay between the sparsity and selectivity of neural responses.

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Geographical breakdown

Country Count As %
Germany 2 3%
United Kingdom 2 3%
France 1 1%
Canada 1 1%
United States 1 1%
Poland 1 1%
Unknown 66 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 46%
Researcher 11 15%
Student > Master 9 12%
Professor 5 7%
Student > Doctoral Student 3 4%
Other 7 9%
Unknown 5 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 38%
Computer Science 9 12%
Neuroscience 7 9%
Psychology 5 7%
Engineering 5 7%
Other 14 19%
Unknown 6 8%