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Dynamic Excitatory and Inhibitory Gain Modulation Can Produce Flexible Robust and Optimal Decision-making

机译:动态的兴奋性和抑制性增益调制可以产生灵活稳健和最佳的决策

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摘要

Behavioural and neurophysiological studies in primates have increasingly shown the involvement of urgency signals during the temporal integration of sensory evidence in perceptual decision-making. Neuronal correlates of such signals have been found in the parietal cortex, and in separate studies, demonstrated attention-induced gain modulation of both excitatory and inhibitory neurons. Although previous computational models of decision-making have incorporated gain modulation, their abstract forms do not permit an understanding of the contribution of inhibitory gain modulation. Thus, the effects of co-modulating both excitatory and inhibitory neuronal gains on decision-making dynamics and behavioural performance remain unclear. In this work, we incorporate time-dependent co-modulation of the gains of both excitatory and inhibitory neurons into our previous biologically based decision circuit model. We base our computational study in the context of two classic motion-discrimination tasks performed in animals. Our model shows that by simultaneously increasing the gains of both excitatory and inhibitory neurons, a variety of the observed dynamic neuronal firing activities can be replicated. In particular, the model can exhibit winner-take-all decision-making behaviour with higher firing rates and within a significantly more robust model parameter range. It also exhibits short-tailed reaction time distributions even when operating near a dynamical bifurcation point. The model further shows that neuronal gain modulation can compensate for weaker recurrent excitation in a decision neural circuit, and support decision formation and storage. Higher neuronal gain is also suggested in the more cognitively demanding reaction time than in the fixed delay version of the task. Using the exact temporal delays from the animal experiments, fast recruitment of gain co-modulation is shown to maximize reward rate, with a timescale that is surprisingly near the experimentally fitted value. Our work provides insights into the simultaneous and rapid modulation of excitatory and inhibitory neuronal gains, which enables flexible, robust, and optimal decision-making.
机译:在灵长类动物中的行为和神经生理学研究越来越表明,在感觉性证据的时间整合中,紧急信号参与了感知决策。已经在顶叶皮层中发现了这种信号的神经元相关性,并且在单独的研究中,证明了注意力诱导的兴奋性和抑制性神经元的增益调节。尽管以前的决策计算模型已经包含了增益调制,但是它们的抽象形式无法理解抑制性增益调制的作用。因此,尚不清楚调节兴奋性和抑制性神经元增益对决策动力学和行为表现的影响。在这项工作中,我们将兴奋性和抑制性神经元的增益随时间变化的协调制合并到我们以前的基于生物学的决策电路模型中。我们基于在动物中执行的两个经典运动区分任务来进行计算研究。我们的模型表明,通过同时增加兴奋性神经元和抑制​​性神经元的增益,可以复制观察到的多种动态神经元放电活动。特别是,模型可以展现出更高的触发率,并且在明显更稳健的模型参数范围内表现出“赢家通吃”的决策行为。即使在动态分叉点附近操作,它也表现出短时的反应时间分布。该模型进一步表明,神经元增益调制可以补偿决策神经电路中较弱的循环激励,并支持决策形成和存储。与对任务的固定延迟版本相比,在对认知的要求更高的反应时间中也建议更高的神经元增益。使用来自动物实验的确切时间延迟,显示了快速募集增益共调制可最大程度地提高回报率,其时标令人惊讶地接近实验拟合值。我们的工作提供了对兴奋性和抑制性神经元增益同时快速调节的见解,从而可以灵活,强大和最佳地进行决策。

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