Biophysical mechanisms regulating synchrony transfer in somatosensory cortex

描述（由申请人提供）：感觉输入可以唤起非常不同的感知，这取决于神经系统如何处理信息。神经处理的基本方面仍然知之甚少。有证据表明，神经元之间的尖峰相关性可能是一种神经编码机制，特别是在感觉系统中。例如，感觉信息最有效地传输到皮层时，尖峰是在丘脑皮层神经元同步，现有的证据表明，同步活动继续传播到下游皮层层。突触前和突触后神经元之间的这种同步传递（即同步传递）是至关重要的，以免同步尖峰信号携带的信息丢失。一个重要但尚未解决的问题是，皮层各层之间的同步性转移有多好，以及一般来说，同步性转移是如何调节的。有一件事很清楚：只有当神经元组自身以同步尖峰响应同步输入时，它们才将同步输入传递到它们的突触后目标。那么，是什么生物物理机制控制了接受同步输入的一组神经元之间的尖峰同步呢？破译同步传递的细胞和突触基础已被证明是极具挑战性的，因为同步是一种多神经元的网络级现象，难以使用标准实验技术测量或控制。因此，这项任务就落到了计算机建模上。但是，尽管建模提供了有价值的见解，实验的需要仍然存在。我们解决这一挑战的方法是通过将电生理学与数学建模相结合，将真实的神经元嵌入虚拟网络中。这将使我们能够在大鼠躯体感觉皮层切片制备中实验研究调节同步传递的生物物理机制。简而言之，我们将通过结合动态钳位和数学建模来模拟突触连接模式，使得单独记录的神经元就像它们是传播同步活动的网络的一部分一样操作（并将被分析）。同步转移将通过比较输出同步（通过记录的输出尖峰序列的互相关计算）与输入同步（在构建我们的模拟突触输入时指定）来量化。我们将使用这种创新的方法来测试我们的中心假设，即在单个神经元，微电路和突触可塑性水平上的生物物理机制可以实现皮质层之间的良好同步传输。我们已经确定了尖峰产生，前馈抑制，尖峰时间依赖可塑性作为候选机制的基础上，从我们以前的工作的理论见解。将同步等网络级现象与其潜在的生物物理机制联系起来，对于理解感觉处理的神经生物学基础至关重要。通过将数学建模与电生理学相结合来研究嵌入虚拟网络中的真实的神经元，我们提出的研究将在网络水平的同步与调节同步传递的细胞和突触机制之间建立直接联系。

DESCRIPTION (provided by applicant): Sensory input can evoke very different percepts depending on how information is processed by the nervous system. Fundamental aspects of that neural processing remain poorly understood. Evidence points to correlation of spiking across neurons as a possible neural coding mechanism, especially in sensory systems. For example, sensory information is most effectively transmitted to the cortex when spiking is synchronized across thalamocortical neurons, and available evidence suggests that synchronous activity continues to be propagated to downstream cortical layers. This transfer of synchrony between pre- and postsynaptic neurons (i.e. synchrony transfer) is crucial, lest the information carried by synchronous spiking be lost. An important yet unresolved issue is how well synchrony is transferred between layers of cortex and, in general, how synchrony transfer is regulated. One thing is clear: sets of neurons transfer synchronous input to their postsynaptic targets only if they themselves respond to synchronous inputs with synchronous spiking. What, then, are the biophysical mechanisms that control spike synchrony across a set of neurons receiving synchronous input? Deciphering the cellular and synaptic bases for synchrony transfer has proven extremely challenging because synchrony is a multi-neuron, network-level phenomenon that is difficult to measure or control using standard experimental techniques. Consequently, the task has fallen to computer modeling. But although modeling has provided valuable insights, the need for experimentation persists. Our solution to this challenge is to embed real neurons in virtual networks by integrating electrophysiology with mathematical modeling. This will enable us to experimentally investigate the biophysical mechanisms regulating synchrony transfer in a slice preparation of rat somatosensory cortex. In brief, we will simulate synaptic connectivity patterns by combining dynamic clamp and mathematical modeling such that individually recorded neurons operate (and will be analyzed) as if they are part of a network propagating synchronous activity. Synchrony transfer will be quantified by comparing output synchrony, calculated by cross-correlation of recorded output spike trains, with input synchrony, specified when constructing our simulated synaptic input. We will use this innovative approach to test our central hypothesis that biophysical mechanisms at the level of single neurons, microcircuits, and synaptic plasticity can enable good synchrony transfer between cortical layers. We have identified spike generation, feedforward inhibition, and spike time dependent plasticity as candidate mechanisms based on theoretical insights derived from our previous work. Relating network-level phenomena like synchrony with their underlying biophysical mechanisms is essential for understanding the neurobiological basis of sensory processing. By combining mathematical modeling with electrophysiology to study real neurons embedded in virtual networks, our proposed study will establish direct links between network-level synchrony and the cellular and synaptic mechanisms regulating synchrony transfer.