Plasticity and the Decoding of Temporal Information

说明（由申请人提供）： 神经元活动的模式是神经处理的基础。起源 时间信息的本质通常是刺激 例如，语音的时间特征，但也可能是神经上的， 产生于感觉加工的早期阶段。时间信息 被神经系统解码了吗是什么样的神经机制 神经元对时间尺度上的时间模式产生选择性反应 几十到几百毫秒引导电流的假设 一种观点认为，局部皮层网络本质上能够解码 时间信息具体来说，短期的可塑性 兴奋性和抑制性平衡的时间依赖性变化 事件，并且这些网络状态的时间依赖性变化允许神经元 对刺激的不同时间特征有不同的反应。 神经元对时变刺激的反应不仅取决于神经元对时变刺激的反应。 他们的兴奋性输入的强度，但通过兴奋性和 抑制性输入，其中每一个都是由短期形式的 可塑性这里描述的项目旨在了解多个 突触和细胞机制相互作用，以及控制的学习规则 每个过程的长期塑性，包括短期塑性 本身为实现这一目标，本提案的具体目标将 包括：（1）描述短期和长期之间的相互作用 兴奋性突触的关联可塑性;（2）确定是否相同 诱导EPSP可塑性的方案，产生长期的可塑性， IPSPs和/或突触前介导的短时程神经元形式的变化 可塑性;（3）计算分析是否协调调节 如在目标1和2中所观察到的， 间隔选择神经元的产生;（4）间隔选择神经元的实验分析 新皮层回路的动力学和嵌入的单个神经元的能力 在这些电路中表现出时间选择性响应。 这些研究应该有助于理解大脑是如何 时间事件，以及理解认知缺陷，可能涉及 时间处理（如某些形式的阅读障碍），并产生 能够识别复杂模式的人工系统。

DESCRIPTION (provided by the applicant): Information contained in the temporal patterns of neuronal activity is fundamental to neural processing. The origin of the temporal information is generally in the nature of the stimuli themselves, such as the temporal features of speech, but may also be neurally generated at early stages of sensory processing. How is temporal information decoded by the nervous system? What are the neural mechanisms that permit neurons to develop selective responses to temporal patterns on the time scale of tens to hundreds of milliseconds? The hypothesis guiding the current proposal is that local cortical networks are intrinsically capable of decoding temporal information. Specifically, that short-term plasticity produces time-dependent changes in the balance of opposing excitatory and inhibitory events, and that these time-dependent changes in network state allow neurons to respond differentially to the distinct temporal features of stimuli. Neuronal responses to time-varying stimuli are determined not only by the strength of their excitatory inputs, but by a balance of excitatory and inhibitory inputs, each of which is modulated by short-term forms of plasticity. The projects described here are aimed at understanding how multiple synaptic and cellular mechanisms interact, and the learning rules that govern the long-term plasticity of each process, including short-term plasticity itself. Towards this goal the Specific Aims of the current proposal will include: (1) Characterizing the interaction between short and long-term associative plasticity of excitatory synapses; (2) Determining whether the same protocols that induce plasticity of EPSPs, produce long-term plasticity of IPSPs and/or changes in presynaptically mediated forms of short-term plasticity; (3) Computational analysis of whether the orchestrated regulation of multiple synapse types in parallel - as observed in Aims 1 & 2 - may underlie the generation of interval selective neurons; (4) Experimental analysis of the dynamics of neocortical circuits and the ability of individual neurons embedded in these circuits to exhibit temporally selective responses. Together these studies should contribute to the understanding of how the brain times events, as well as to understanding cognitive deficits that may involve temporal processing (such as some forms of dyslexia), and to the generation of artificial systems capable of complex pattern recognition.