2011年2月24日木曜日

A reservoir of time constants for memory traces in cortical neurons.

Nat Neurosci. 2011 Feb 13.
Bernacchia A, Seo H, Lee D, Wang XJ.

適切な学習のためには、報酬を適切な時間スケールで評価することが重要。環境変動が激しい(激しくない)ときは短い(長い)スケールで評価すべき。

ACC、dlPFC、LIP、の三つの部位全てに、異なる時間スケールで報酬情報を保持するニューロンが存在する。そしてその分布は「べき分布」に従う。

According to reinforcement learning theory of decision making, reward expectation is computed by integrating past rewards with a fixed timescale. In contrast, we found that a wide range of time constants is available across cortical neurons recorded from monkeys performing a competitive game task. By recognizing that reward modulates neural activity multiplicatively, we found that one or two time constants of reward memory can be extracted for each neuron in prefrontal, cingulate and parietal cortex. These timescales ranged from hundreds of milliseconds to tens of seconds, according to a power law distribution, which is consistent across areas and reproduced by a 'reservoir' neural network model. These neuronal memory timescales were weakly, but significantly, correlated with those of monkey's decisions. Our findings suggest a flexible memory system in which neural subpopulations with distinct sets of long or short memory timescales may be selectively deployed according to the task demands.

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