Spontaneous activity in gustatory cortex

描述(由申请人提供)：这位PI是石溪大学神经生物学和行为系的一名教员。他的研究重点是味觉皮质的自发和诱发神经活动。这位候选人最近从理论物理背景过渡到神经科学。这项奖励将为候选人提供必要的五年保护期，以便在拟议的指导委员会的监督下，接受系统和理论神经科学和电生理技术方面的培训。在期限结束时，候选人将实现他的长期职业目标，成功申请独立研究资金，并成为理论神经科学领域的独立研究员。这项拟议的研究计划的目标是阐明味觉皮质自发活动和诱发活动之间的关系，以及预期线索对其调节作用。感觉皮层的自发神经活动，传统上被认为是一个嘈杂的基线，正日益引起人们的注意：它可以预测试验的变异性；它包含关于神经网络功能架构的信息；它的特征要么是可能的网络活动的“全套”，要么是对感觉刺激预期的储存，由发育塑造。然而，在味觉加工的背景下，它几乎没有受到关注。这项建议的目的是阐明味觉皮质自发活动的特性。这是一个理想的系统，因为对味觉刺激的反应具有丰富的时间动力学，表现为在整个神经群体中同步的味觉特定活动模式序列。拟议计划的第一个目标是使用最先进的机器学习技术来阐明自发活动与诱发活动相关的特征。这将通过引入时间动力学的新特征，为描述自发活动的特征提供新的分析工具，并在单一框架内调和目前文献中持有的不同观点。作为拟议项目的第二个目标，将阐明预期线索在调节自发活动和诱发活动之间的关系中所起的作用，并澄清反应时间对自发活动的依赖。一个生物学上看似合理的味觉皮质自发活动模型将被引入，该模型基于尖峰神经元网络。通过对电生理数据的分析，该模型将从机制上理解自发活动的特征。

DESCRIPTION (provided by applicant): The PI is a faculty member of the Department of Neurobiology and Behavior at Stony Brook. His research focuses on spontaneous and evoked neural activity in the gustatory cortex. The candidate recently transitioned to neuroscience from a theoretical physics background. This award will provide the necessary five-year protected period for the candidate to receive training in systems and theoretical neuroscience and electrophysiological techniques, under the supervision of the proposed mentorship committee. By the end of the termed period, the candidate will achieve his long term career goals of successfully applying for independent research funding and becoming an independent investigator in the field of theoretical neuroscience. The goal of the proposed research plan is elucidating the relation between spontaneous and evoked activity in the gustatory cortex, and its modulation by anticipatory cues. Spontaneous neural activity in sensory cortices, traditionally regarded as a noisy baseline, is increasingly drawing attention: it can predict trial to trial variability; it contains information on the functional architecture of neural networks; and it was characterized as either a "repertoire" of possible network activities or a storage of expectations of sensory stimuli, shaped by development. In the context of taste processing, however, it has received little to no attention. The aim of this proposal is to elucidate the properties of spontaneous activity in the gustatory cortex. This is an ideal system, due to the rich temporal dynamics of responses to taste stimuli, represented in terms of taste-specific sequences of patterns of activity, synchronized across the whole neural population. The first goal of the proposed plan is to employ state-of-the-art machine learning techniques to elucidate the features of spontaneous activity in relation to evoked activity. This will provide new analytical tools for the characterization of spontaneous activity and reconcile within a single framework the different views currently held in the literature, by introducing the new feature of temporal dynamics. As a second goal of the proposed project, the role played by anticipatory cues in modulating the relation between spontaneous and evoked activity will be elucidated, and the dependence of reaction times on spontaneous activity will be clarified. A biologically plausible model of spontaneous activity in the gustatory cortex will be introduced, based on networks of spiking neurons. This model will yield a mechanistic understanding of the feature of spontaneous activity as revealed by the analysis of electrophysiological data.