Ensemble accumulator modeling of speed-accuracy tradeoff in visual search

 描述（由申请人提供）：本提案的目标是开展研究培训，以开发受神经生理学启发和约束的认知建模方面的新专业知识。我以前在人类群体决策方面的工作，以及赞助商最近制定的一个新的建模框架来探索神经集成决策，为新的培训和跨学科合作提供了一个极好的机会。目标1将系统地研究神经元之间的关系，实例化的证据，和集体行为的神经元的合奏在决策选择任务;预测的选择行为和动力学合奏将比较观察到的眼跳选择行为和测量的清醒行为猴子的神经动力学。目标2将显着扩展这项工作，探索替代计算机制，在合奏中的聚合，从其他领域的群体决策的替代聚合方案的假设。训练潜力很大，因为这项工作将开发新的神经元集合决策的计算模型，这是一个我以前没有经验的研究领域，但它为我之前关于群体智慧的工作提供了令人兴奋的新方向。在我的新博士后工作和我以前的博士工作之间建立新的联系将为我未来作为独立研究者的研究奠定基础。这些发现具有潜在的广泛兴趣和适用性，因为它可能揭示神经元集合如何在大脑中集体做出决策。

 DESCRIPTION (provided by applicant): The goal of this proposal is to carry out research training to develop new expertise in cognitive modeling that is inspired and constrained by neurophysiology. My previous work in human group decision making, and the sponsors' recent formulation of a novel modeling framework to explore neural ensemble decision making, yields an excellent opportunity for new training and interdisciplinary collaboration. Aim 1 will systematically investigate the relationship between neurons, instantiated as evidence accumulators, and the collective behavior of ensembles of neural accumulators in decision choice tasks; predicted choice behavior and dynamics of ensembles will be compared to observed saccade choice behavior and measured neural dynamics of awake behaving monkeys. Aim 2 will significantly extend this work by exploring alternative computational mechanisms for aggregation across accumulators in an ensemble, with hypotheses for alternative aggregation schemes drawn from other domains of group decision making. Training potential is high because the work will develop new computational models of decisions made by ensembles of neurons, an area of research in which I have no prior experience, but which offers exciting new directions for linking to my prior work on the Wisdom of Crowds. Forging novel connections between my new postdoctoral work and my previous PhD work will form a basis for my future research as an independent investigator. The findings have potential wide interest and applicability, as it may shed insight into how ensembles of neurons collectively make decisions in the brain.