Multiscale models of neural population control in spinal cord

 描述（由申请人提供）：大脑记录技术的日益复杂性还没有被类似复杂的数学方法所匹配，该方法允许对神经系统深处的细胞群体的行为和活性之间的关系进行建模和预测。对于运动系统尤其如此，其中主要目标是控制环境的动态。我们的目标是创建脊髓运动组件的多尺度模型，该模型可以连接至少四个尺度：（1）单个神经元放电，（2）局部神经群体活动，（3）整个脊髓活动的地形图，以及（4）行为。我们建议使用脊髓化的青蛙作为我们的试验台，因为生物力学是很好的理解，本体感觉反馈被简化，脊髓可以从皮层控制中孤立地进行研究，并且可以在没有皮层控制的情况下产生可重复的复杂运动。我们将使用和进一步发展一个新的数学框架的基础上叠加的随机动态运营商。将神经活动视为引起系统动力学的修改是适当的，使得所产生的动力学（包括运动、顺应性和振荡行为）实现期望的结果。新的框架使我们能够模拟对动态环境的反应，顺应性控制，反射行为，单个尖峰的影响，以及群体中多个神经元的综合影响。我们可以检查振荡活动（如在中央模式发生器（CPG）中发现的运动）和本体感受反馈的作用。由于该理论在单个尖峰水平上运行，并且所有神经表征都是局部的，并且可以使用局部学习规则，因此它提供了与实际生物计算更紧密的联系，并且可以提供对脊髓用于产生复杂和多样运动的机制的洞察。为了测试我们对脊髓中间层神经元群体行为的理解，我们将（1）读出正在进行的运动的动力学，包括扰动反应和顺应性，（2）修改正在进行的运动的动力学，（3）创建显示控制功能在脊髓中分布的地形图。这些实验将使我们能够详细地了解神经群体对运动动力学的控制，将神经尺度与群体尺度联系起来，再到运动行为尺度。这个数学框架为理解神经元群体的功能和预测它们对行为的影响提供了一个新的模型。它还提供了一个定量模型，允许预测的影响，修改火灾或伤害的行为。最后，它将为脊髓损伤的新治疗提供基础，通过了解功能性电刺激，不仅可以用于在目标肌肉中产生力，而且可以用于以身体自然使用的方式产生平滑的顺应性动力学控制。

 DESCRIPTION (provided by applicant): Increasing sophistication of brain recording technology has not been matched by a similarly sophisticated mathematical approach that permits modeling and prediction of the relation between behavior and the activity of populations of cells deep within the nervous system. This is particularly true for motor systems, where the primary goal is control of the dynamics of the environment. Our goal is to create multiscale models of motor components of the spinal cord that can link at least four scales: (1) individual neuron firing, (2) local neural population activity, (3) topographic maps of activity across the spinal cord, and (4) behavior. We propose to use the spinalized frog as our testbed, because the biomechanics are well understood, proprioceptive feedback is simplified, the cord can be studied in isolation from cortical control, and repeatable complex movements can be generated in the absence of cortical control. We will use and further develop a new mathematical framework based upon superposition of stochastic dynamic operators. It is appropriate to consider neural activity as causing a modification of the system dynamics, so that the resulting dynamics (including movement, compliance, and oscillatory behavior) achieve a desired result. The new framework allows us to model the response to dynamic environments, compliant control, reflex behavior, the effect of single spikes, and the combined effect of multiple neurons in a population. We can examine oscillatory activity (such as found in the central pattern generator (CPG) for locomotion) and the role of proprioceptive feedback. Because this theory operates at the level of single spikes and all neural representations are local and can use local learning rules, it provides a much closer link to the actual biological computations and could provide insight into the mechanisms used by the spinal cord to generate complex and varied movement. To test our understanding of the behavior of populations of neurons in the intermediate layers of spinal cord, we will (1) read out the dynamics of ongoing movement including perturbation responses and compliance, (2) modify the dynamics of ongoing movement, (3) create topographic maps showing the distribution of control functions across the cord. These experiments will allow us to understand control by neural populations of the dynamics of movement in a detailed way that links the neural scale to the population scale to the motor behavioral scale. The mathematical framework provides a new model for understanding the function of populations of neurons and predicting their effect on behavior. It also provides a quantitative model that allows the prediction of the effect of modification of firig or injury on behavior. Finally, it will provide the basis for new treatments for spinal cord injuryby giving an understanding of functional electrical stimulation that can be used not just to generate forces in target muscles, but can be used to generate smooth compliant control of dynamics in the way naturally used by the body.