Rombouts Jaldert O, Bohte Sander M, Roelfsema Pieter R
Department of Life Sciences, Centrum Wiskunde & Informatica, Amsterdam, The Netherlands.
Department of Vision & Cognition, Netherlands Institute for Neurosciences, an institute of the Royal Netherlands Academy of Arts and Sciences (KNAW), Amsterdam, The Netherlands; Department of Integrative Neurophysiology, Centre for Neurogenomics and Cognitive Research, VU University, Amsterdam, The Netherlands; Psychiatry Department, Academic Medical Center, Amsterdam, The Netherlands.
PLoS Comput Biol. 2015 Mar 5;11(3):e1004060. doi: 10.1371/journal.pcbi.1004060. eCollection 2015 Mar.
Intelligence is our ability to learn appropriate responses to new stimuli and situations. Neurons in association cortex are thought to be essential for this ability. During learning these neurons become tuned to relevant features and start to represent them with persistent activity during memory delays. This learning process is not well understood. Here we develop a biologically plausible learning scheme that explains how trial-and-error learning induces neuronal selectivity and working memory representations for task-relevant information. We propose that the response selection stage sends attentional feedback signals to earlier processing levels, forming synaptic tags at those connections responsible for the stimulus-response mapping. Globally released neuromodulators then interact with tagged synapses to determine their plasticity. The resulting learning rule endows neural networks with the capacity to create new working memory representations of task relevant information as persistent activity. It is remarkably generic: it explains how association neurons learn to store task-relevant information for linear as well as non-linear stimulus-response mappings, how they become tuned to category boundaries or analog variables, depending on the task demands, and how they learn to integrate probabilistic evidence for perceptual decisions.
智能是我们学习对新刺激和新情况做出适当反应的能力。联合皮层中的神经元被认为对这种能力至关重要。在学习过程中，这些神经元会被调整到相关特征，并在记忆延迟期间开始用持续活动来表征它们。这个学习过程尚未得到充分理解。在这里，我们开发了一种生物学上合理的学习方案，解释了试错学习如何诱导神经元选择性以及对任务相关信息的工作记忆表征。我们提出，反应选择阶段向早期处理水平发送注意力反馈信号，在负责刺激 - 反应映射的那些连接上形成突触标签。然后，全局释放的神经调质与标记的突触相互作用以确定它们的可塑性。由此产生的学习规则赋予神经网络创建与任务相关信息的新工作记忆表征作为持续活动的能力。它非常通用：它解释了联合神经元如何学习为线性以及非线性刺激 - 反应映射存储任务相关信息，它们如何根据任务需求调整到类别边界或模拟变量，以及它们如何学习整合用于感知决策的概率证据。
