Gamma oscillations of spiking neural populations enhance signal discrimination

Naoki Masuda*, Brent Doiron

*この研究の対応する著者

研究成果: Article査読

25 被引用数 (Scopus)

抄録

Selective attention is an important filter for complex environments where distractions compete with signals. Attention increases both the gamma-band power of cortical local field potentials and the spike-field coherence within the receptive field of an attended object. However, the mechanisms by which gamma-band activity enhances, if at all, the encoding of input signals are not well understood. We propose that gamma oscillations induce binomial-like spike-count statistics across noisy neural populations. Using simplified models of spiking neurons, we show how the discrimination of static signals based on the population spike-count response is improved with gamma induced binomial statistics. These results give an important mechanistic link between the neural correlates of attention and the discrimination tasks where attention is known to enhance performance. Further, they show how a rhythmicity of spike responses can enhance coding schemes that are not temporally sensitive.

本文言語English
ページ(範囲)2348-2355
ページ数8
ジャーナルPLoS Computational Biology
3
11
DOI
出版ステータスPublished - 2007 11
外部発表はい

ASJC Scopus subject areas

  • 生態、進化、行動および分類学
  • モデリングとシミュレーション
  • 生態学
  • 分子生物学
  • 遺伝学
  • 細胞および分子神経科学
  • 計算理論と計算数学

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