Biophysical mechanisms regulating synchrony transfer in somatosensory cortex

描述（由申请人提供）：根据神经系统如何处理信息，感觉输入可以唤起非常不同的感知。神经处理的基本方面仍然知之甚少。有证据表明，神经元间的脉冲相关可能是一种神经编码机制，尤其是在感觉系统中。例如，感觉信息最有效地传递到皮质，当脉冲在丘脑皮质神经元之间同步时，现有证据表明，同步活动继续传播到下游皮质层。这种突触前和突触后神经元之间的同步转移（即同步转移）是至关重要的，以免同步尖峰所携带的信息丢失。一个重要但尚未解决的问题是，同步在皮层层之间的转移有多好，以及同步转移是如何被调节的。有一件事是明确的：只有当神经元自身对同步输入产生同步尖峰反应时，它们才会将同步输入传递给突触后目标。那么，控制一组接受同步输入的神经元之间的脉冲同步的生物物理机制是什么呢？由于同步是一种多神经元、网络级的现象，很难用标准的实验技术来测量或控制，因此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。因此，这项任务落在了计算机建模上。但是，尽管建模提供了有价值的见解，对实验的需求仍然存在。我们的解决方案是将电生理学与数学建模相结合，将真实神经元嵌入虚拟网络中。这将使我们能够通过实验研究大鼠体感觉皮层切片制备中调节同步转移的生物物理机制。简而言之，我们将通过结合动态箝位和数学建模来模拟突触连接模式，这样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运行（并将被分析）。同步传输将通过比较输出同步（由记录的输出尖峰序列的相互关联计算）与输入同步（在构建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验证我们的中心假设，即单个神经元，微电路和突触可塑性水平的生物物理机制可以实现皮层之间良好的同步转移。我们已经确定了尖峰产生、前馈抑制和尖峰时间依赖的可塑性作为候选机制，这些机制基于我们之前工作的理论见解。将网络级现象（如同步性）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神经元，我们提出的研究将建立网络级同步与调节同步转移的细胞和突触机制之间的直接联系。

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.