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Frequency-Invariant Representation of Interaural Time Differences in Mammals

Overview of attention for article published in PLoS Computational Biology, March 2011
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Title
Frequency-Invariant Representation of Interaural Time Differences in Mammals
Published in
PLoS Computational Biology, March 2011
DOI 10.1371/journal.pcbi.1002013
Pubmed ID
Authors

Hannes Lüling, Ida Siveke, Benedikt Grothe, Christian Leibold

Abstract

Interaural time differences (ITDs) are the major cue for localizing low-frequency sounds. The activity of neuronal populations in the brainstem encodes ITDs with an exquisite temporal acuity of about 10 μs. The response of single neurons, however, also changes with other stimulus properties like the spectral composition of sound. The influence of stimulus frequency is very different across neurons and thus it is unclear how ITDs are encoded independently of stimulus frequency by populations of neurons. Here we fitted a statistical model to single-cell rate responses of the dorsal nucleus of the lateral lemniscus. The model was used to evaluate the impact of single-cell response characteristics on the frequency-invariant mutual information between rate response and ITD. We found a rough correspondence between the measured cell characteristics and those predicted by computing mutual information. Furthermore, we studied two readout mechanisms, a linear classifier and a two-channel rate difference decoder. The latter turned out to be better suited to decode the population patterns obtained from the fitted model.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 6 15%
United States 3 7%
Unknown 32 78%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 29%
Student > Ph. D. Student 12 29%
Student > Master 4 10%
Professor 3 7%
Student > Postgraduate 2 5%
Other 5 12%
Unknown 3 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 37%
Neuroscience 7 17%
Physics and Astronomy 4 10%
Psychology 3 7%
Computer Science 3 7%
Other 6 15%
Unknown 3 7%