Neural dynamics and information representation in microcircuits of motor cortex.
Neural dynamics and information representation in microcircuits of motor cortex.
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DOI：
10.3389/fncir.2013.00085
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发表时间：
2013
影响因子：
3.5
通讯作者：
Fukai T
中科院分区：
文献类型：
--
作者：
Tsubo Y;Isomura Y;Fukai T
大脑必须分析和响应外部事件，这些事件可能会不时快速变化，这表明大脑的信息处理可能基本上是动态的而不是静态的。神经计算的动力学特征在控制运动产生和学习过程的运动皮层中具有重要意义。在本文中，我们讨论这些功能的基础上，我们最近的研究结果主要是神经动力学和信息编码的微电路的大鼠运动皮层。事实上，皮层神经元表现出各种各样的动力学行为，从不同频段的节律活动到高度不规则的尖峰放电。特别感兴趣的是运动皮层不同层的神经元反应特性的相似性和相异性。通过在脑片制备过程中进行电生理记录，我们报告了不同皮层层神经元的相位响应曲线（PRCs），以证明它们的层依赖性同步特性。然后，我们研究了运动皮层如何招募任务相关的神经元在不同的层自愿手臂运动的行为大鼠的同时，单细胞和多单位的记录。结果表明，表层和深层之间的功能活动谱存在有趣的差异。此外，任务相关的活动记录从不同的层表现出幂律分布的尖峰间期（ISI），在一般认为，ISI服从泊松或伽玛分布在皮层神经元。我们提出了一个理论论据，在体内神经元的这种幂律可能代表了最大化的熵的放电率与有限的能量消耗的尖峰产生。虽然需要进一步的研究来充分阐明这种编码原则的功能含义，但它可能会为运动皮层神经元和回路的信息表征提供新的线索。
The brain has to analyze and respond to external events that can change rapidly from time to time, suggesting that information processing by the brain may be essentially dynamic rather than static. The dynamical features of neural computation are of significant importance in motor cortex that governs the process of movement generation and learning. In this paper, we discuss these features based primarily on our recent findings on neural dynamics and information coding in the microcircuit of rat motor cortex. In fact, cortical neurons show a variety of dynamical behavior from rhythmic activity in various frequency bands to highly irregular spike firing. Of particular interest are the similarity and dissimilarity of the neuronal response properties in different layers of motor cortex. By conducting electrophysiological recordings in slice preparation, we report the phase response curves (PRCs) of neurons in different cortical layers to demonstrate their layer-dependent synchronization properties. We then study how motor cortex recruits task-related neurons in different layers for voluntary arm movements by simultaneous juxtacellular and multiunit recordings from behaving rats. The results suggest an interesting difference in the spectrum of functional activity between the superficial and deep layers. Furthermore, the task-related activities recorded from various layers exhibited power law distributions of inter-spike intervals (ISIs), in contrast to a general belief that ISIs obey Poisson or Gamma distributions in cortical neurons. We present a theoretical argument that this power law of in vivo neurons may represent the maximization of the entropy of firing rate with limited energy consumption of spike generation. Though further studies are required to fully clarify the functional implications of this coding principle, it may shed new light on information representations by neurons and circuits in motor cortex.
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