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A Neurocomputational Model of Stimulus-Specific Adaptation to Oddball and Markov Sequences

Overview of attention for article published in PLoS Computational Biology, August 2011
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Title
A Neurocomputational Model of Stimulus-Specific Adaptation to Oddball and Markov Sequences
Published in
PLoS Computational Biology, August 2011
DOI 10.1371/journal.pcbi.1002117
Pubmed ID
Authors

Robert Mill, Martin Coath, Thomas Wennekers, Susan L. Denham

Abstract

Stimulus-specific adaptation (SSA) occurs when the spike rate of a neuron decreases with repetitions of the same stimulus, but recovers when a different stimulus is presented. It has been suggested that SSA in single auditory neurons may provide information to change detection mechanisms evident at other scales (e.g., mismatch negativity in the event related potential), and participate in the control of attention and the formation of auditory streams. This article presents a spiking-neuron model that accounts for SSA in terms of the convergence of depressing synapses that convey feature-specific inputs. The model is anatomically plausible, comprising just a few homogeneously connected populations, and does not require organised feature maps. The model is calibrated to match the SSA measured in the cortex of the awake rat, as reported in one study. The effect of frequency separation, deviant probability, repetition rate and duration upon SSA are investigated. With the same parameter set, the model generates responses consistent with a wide range of published data obtained in other auditory regions using other stimulus configurations, such as block, sequential and random stimuli. A new stimulus paradigm is introduced, which generalises the oddball concept to Markov chains, allowing the experimenter to vary the tone probabilities and the rate of switching independently. The model predicts greater SSA for higher rates of switching. Finally, the issue of whether rarity or novelty elicits SSA is addressed by comparing the responses of the model to deviants in the context of a sequence of a single standard or many standards. The results support the view that synaptic adaptation alone can explain almost all aspects of SSA reported to date, including its purported novelty component, and that non-trivial networks of depressing synapses can intensify this novelty response.

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Geographical breakdown

Country Count As %
United States 4 4%
Germany 2 2%
Switzerland 1 <1%
Australia 1 <1%
Netherlands 1 <1%
United Kingdom 1 <1%
Poland 1 <1%
Unknown 94 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 31 30%
Researcher 18 17%
Student > Master 12 11%
Student > Bachelor 8 8%
Professor 6 6%
Other 14 13%
Unknown 16 15%
Readers by discipline Count As %
Neuroscience 27 26%
Agricultural and Biological Sciences 22 21%
Psychology 13 12%
Computer Science 7 7%
Engineering 5 5%
Other 11 10%
Unknown 20 19%