Spatial learning and action planning in a prefrontal cortical network model.
Spatial learning and action planning in a prefrontal cortical network model.
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DOI：
10.1371/journal.pcbi.1002045
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发表时间：
2011-05
影响因子：
4.3
通讯作者：
Arleo A
中科院分区：
文献类型：
--
作者：
Martinet LE;Sheynikhovich D;Benchenane K;Arleo A
海马和前额叶皮层（PFC）之间的相互作用是空间认知的基础。作为海马位置编码的补充，前额叶表征提供了更抽象和层次化的记忆，适用于决策。我们模拟了一个前额叶网络，它介导了空间学习和行动规划的分布式信息处理。特定的连接性和突触适应原则塑造了排列在皮质微柱中的网络的经常性动态。我们展示了如何PFC柱状组织是适合学习稀疏的拓扑度量表示从冗余的海马输入。网络的循环性支持多级空间处理，允许对环境的结构特征进行编码。激活扩散机制将神经活动传播通过列群体，从而导致轨迹规划。该模型提供了一个功能框架，用于解释在导航任务中记录的PFC神经元的活动。我们说明了从单个单元活动到行为反应的联系。结果表明，合理的神经机制subserving认知“洞察力”的能力最初归因于啮齿动物的托尔曼和Honzik。我们的神经反应的时间过程分析表明，海马和PFC之间的相互作用如何产生编码的多方面的信息有关的空间规划，包括前瞻性编码和距离目标的相关性。我们研究空间认知，一个高层次的大脑功能的基础上的能力，阐述支持目标导向的导航环境的心理表征。空间认知涉及在相互关联的大脑区域的分布式网络中进行并行信息处理。根据空间导航任务的复杂性，可能主要涉及不同的神经回路，对应于不同的行为策略。导航规划，最灵活的策略之一，是基于前瞻性地评估替代序列的行动，以推断最佳的轨迹到一个目标的能力。海马结构和前额叶皮质是可能参与导航计划的两个神经基质。我们采用计算建模的方法来显示这两个大脑区域之间的相互作用可能会导致学习的拓扑表示适合调解行动规划。我们的模型表明，合理的神经机制subserving归因于啮齿动物的认知空间能力。我们提供了一个功能框架，解释活动的前额叶和海马神经元记录在导航任务。类似于整合神经科学的方法，我们说明了从单个单元活动的联系，行为反应，而解决空间学习任务。
The interplay between hippocampus and prefrontal cortex (PFC) is fundamental to spatial cognition. Complementing hippocampal place coding, prefrontal representations provide more abstract and hierarchically organized memories suitable for decision making. We model a prefrontal network mediating distributed information processing for spatial learning and action planning. Specific connectivity and synaptic adaptation principles shape the recurrent dynamics of the network arranged in cortical minicolumns. We show how the PFC columnar organization is suitable for learning sparse topological-metrical representations from redundant hippocampal inputs. The recurrent nature of the network supports multilevel spatial processing, allowing structural features of the environment to be encoded. An activation diffusion mechanism spreads the neural activity through the column population leading to trajectory planning. The model provides a functional framework for interpreting the activity of PFC neurons recorded during navigation tasks. We illustrate the link from single unit activity to behavioral responses. The results suggest plausible neural mechanisms subserving the cognitive “insight” capability originally attributed to rodents by Tolman & Honzik. Our time course analysis of neural responses shows how the interaction between hippocampus and PFC can yield the encoding of manifold information pertinent to spatial planning, including prospective coding and distance-to-goal correlates. We study spatial cognition, a high-level brain function based upon the ability to elaborate mental representations of the environment supporting goal-oriented navigation. Spatial cognition involves parallel information processing across a distributed network of interrelated brain regions. Depending on the complexity of the spatial navigation task, different neural circuits may be primarily involved, corresponding to different behavioral strategies. Navigation planning, one of the most flexible strategies, is based on the ability to prospectively evaluate alternative sequences of actions in order to infer optimal trajectories to a goal. The hippocampal formation and the prefrontal cortex are two neural substrates likely involved in navigation planning. We adopt a computational modeling approach to show how the interactions between these two brain areas may lead to learning of topological representations suitable to mediate action planning. Our model suggests plausible neural mechanisms subserving the cognitive spatial capabilities attributed to rodents. We provide a functional framework for interpreting the activity of prefrontal and hippocampal neurons recorded during navigation tasks. Akin to integrative neuroscience approaches, we illustrate the link from single unit activity to behavioral responses while solving spatial learning tasks.
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影响因子：
3.2
作者：
Becker, S;Lim, J
通讯作者：
Lim, J
DOI：
10.1073/pnas.94.24.13293
发表时间：
1997-11-25
影响因子：
11.1
作者：
Dehaene, S;Changeux, JP
通讯作者：
Changeux, JP
影响因子：
3.4
作者：
Botvinick MM;Niv Y;Barto AG
通讯作者：
Barto AG
影响因子：
16.2
作者：
Asaad, WF;Rainer, G;Miller, EK
通讯作者：
Miller, EK
影响因子：
3.7
作者：
Doeller, CF;Opitz, B;Reith, W
通讯作者：
Reith, W