Crowd coding in the brain:3D imaging and control of collective neuronal dynamics

 描述（由申请人提供）：皮层是一种分层结构，被认为是顺序信息处理的基础。感觉输入进入第4层（L4），活动从第4层迅速扩散到浅层2/3（L2/3）和深层5/6（L5/6）以及其他皮层区域，最终导致适当的运动反应。感觉反应本身取决于持续的，即自发的皮层活动，通常以来自内部或远处皮层区域的反射活动的形式，以及动物的状态和行为背景。 当动物从事行为任务时，神经元的感受场特性可以快速地自适应地重塑，这表明刺激的编码依赖于任务或上下文依赖的状态。反应也依赖于正在进行的皮层动力学在一个层依赖的方式和清醒和麻醉状态之间的差异。行为背景、持续活动和感觉刺激之间复杂的神经元相互作用是未知的。 具体来说，我们不知道神经元回路如何在皮层内部和皮层之间塑造这些涌现的动力学，我们也不知道哪些神经元编码感觉刺激的哪个方面。所有先前对感觉处理的研究的一个缺点是，只有少数神经元被采样，因此缺乏关于神经元之间以及神经元与全局大脑状态之间的相互作用的信息。 在这里，我们通过开发新的体内双光子成像技术来解决这些挑战，该技术允许在多个焦平面中快速成像和刺激，以及新的计算和信息理论技术来提取单个神经元和群体水平的网络动态。这些措施超越了配对措施，并考虑到神经元之间的协同作用。我们使用这些新技术来研究小鼠听觉皮层中的3D单细胞和群体活动模式。我们研究了单个神经元相对于 特定的神经元群体（群体）对网络动力学和最终动物行为的协同影响。

 DESCRIPTION (provided by applicant): The cortex is a laminated structure that is thought to underlie sequential information processing. Sensory input enters layer 4 (L4) from which activity quickly spreads to superficial layers 2/3 (L2/3) and deep layers 5/6 (L5/6) and other cortical areas eventually leading to appropriate motor responses. Sensory responses themselves depend on ongoing, i.e. spontaneous cortical activity, usually in the form of reverberating activit from within or distant cortical regions, as well as the state and behavioral context of the animal. Receptive field properties of neurons can rapidly and adaptively be reshaped when an animal is engaged in a behavioral task, indicating that encoding of stimuli is dependent on task- or context-dependent state. Responses also depend on ongoing cortical dynamics in a lamina-dependent fashion and differ between the awake and anesthetized state. The intricate neuronal interplay between behavioral context, ongoing activity, and sensory stimulus underlying cortical representations is unknown. Specifically, we do not know how neuronal circuits shape these emergent dynamics within and between laminae, and we do not know which neurons encode which aspect of a sensory stimulus. One shortcoming of all prior studies of sensory processing is that only a few neurons are sampled, and thus information about the interactions between neurons, and between neuron and global brain state is lacking. Here we address these challenges by developing new in vivo 2-photon imaging technology that allows rapid imaging and stimulation in multiple focal planes and new computational and information theoretic techniques to extract network dynamics at the single neuron and population level. These measures go beyond paired measures and take synergistic interactions between neurons into account. We use these new techniques to investigate the 3D single cell and population activity patterns in the auditory cortex in mice. We investigate the influence of single neurons relative to the synergistic influence of specific groups of neurons (the crowd) on network dynamics and ultimately behavior of the animal.