Plasticity and the Decoding of Temporal Information

描述(由申请人提供)：临时文件中包含的信息 神经元活动的模式是神经处理的基础。它的起源 的时间信息通常是在刺激的性质 自身，如语音的时间特征，也可能是神经性的 在感觉加工的早期阶段产生的。时间信息是如何 被神经系统破译？是什么神经机制允许 神经元在时间尺度上对时间模式产生选择性反应 几十到几百毫秒？引领潮流的假说 认为局部大脑皮层网络本质上具有解码的能力 时间信息。具体地说，这种短期可塑性会产生 兴奋性与抑制性对立平衡的时间依赖性变化 事件，网络状态的这些依赖于时间的变化允许神经元 对刺激的不同时间特征做出不同的反应。 神经元对时变刺激的反应不仅由 兴奋性输入的强度，但取决于兴奋性和 抑制性输入，每一种都受到短期形式的 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，以及支配学习规则 每个过程的长期塑性，包括短期塑性 它本身。为实现这一目标，目前提案的具体目标将 包括：(1)表征短期和长期之间的相互作用 兴奋性突触的联想可塑性；(2)确定是否相同 诱导EPSP可塑性的方案，产生长期可塑性 IPSP和/或突触前介导的短时程增强的变化 可塑性；(3)计算分析是否协调调节 如目标1和目标2中所观察到的那样，多种突触类型的并行可能是基础 间期选择神经元的产生；(4)实验分析。 新皮质环路的动力学和单个嵌入神经元的能力 在这些电路中表现出时间选择性的反应。 总之，这些研究应该有助于理解大脑如何 时代事件，以及理解可能涉及的认知缺陷 时间加工(如某些形式的阅读困难)，并对产生 能够进行复杂模式识别的人工系统。

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.