Effects of Intracortical Microstimulation on Neural Activity in Distant Cortical Regions

电刺激已被证明是一种将信息传递给大脑的有用技术 来自脑机接口技术。大脑非常有能力学习解释这样的事情 信息，最显著的例子是人工耳蜗术的成功。学习如何将刺激转化为 转化为有用的信息可以归因于神经的可塑性，但人们对两者之间的关系知之甚少 局部电刺激及其对远离模拟部位的大脑区域的后续影响。在 刺激皮质灰质或皮质内微刺激(ICMS)的特定背景，常见的 假设刺激后效应仍局限于刺激附近的小体积神经元。 电极。然而，有证据表明，这种影响可能会扩散到相当远的地方。 我实验室之前的工作表明，受试者可以学习理解向四个不同的人提供的ICMS 初级躯体感觉皮层(S1)中的电极作为指令执行四种不同的任意- 指定的动作。我使用该数据集进行的初步研究表明，在S1交付的ICMS可能具有 对远侧大脑皮层神经元的两种影响：1)ICMS脉冲可以直接在神经元中诱发棘波 来自腹侧运动前皮质(PMV)和初级运动皮质(M1)--或者反向地， 单通道，或多通道--我称之为“直接驱动”。2)其他神经元不是由 然而，ICMS脉冲在仅使用火车指示相同运动的试验之间可能会有不同的发射 ICMS脉冲与仅有视觉提示的对比，我将其称为“指令模式依赖的调制”。因此， ICMS的影响可能延伸到比先前估计的更远的皮质网络部分。 我建议调查ICMS指令对任意关联动作的影响 在S1中的几个远距离皮质区域参与运动控制。具体地说，我将研究七个方面的影响 顶区：前辅助运动区、背侧运动前皮质、腹侧运动前皮质、吻侧 初级运动皮质、尾侧初级运动皮质、顶内前区和顶后背侧 大脑皮层。目的我将检查这些皮质区域中哪些包含由ICMS脉冲直接驱动的神经元 在S1交付。AIM II将检查这些皮质区域中哪些包含显示指令的神经元- 依赖于模式的调制。拟议的研究将显示S1中的ICMS调节的程度 大脑皮层网络的遥远部分，以及当受试者学习使用 ICM作为执行任意关联动作的指令。这些信息可以用来设计 大脑-机器接口技术对大脑皮质的输入对受试者更清晰，并鼓励 健康的可塑性，以减少训练过程中的认知需求。这些改进将使人们受益 可用脑机接口技术治疗的神经系统疾病患者 包括中风、感觉神经病或头部创伤。

Electrical stimulation has been shown to be a useful technique for delivering information to the brain from brain-machine interfacing technology. The brain is remarkably capable of learning to interpret such information, most notably demonstrated by the success of cochlear implants. Learning to translate stimulation into useful information can be attributed to neural plasticity, yet little is known about the relationship between localized electrical stimulation and subsequent effects on brain regions distant from the simulation site. In the specific context of stimulating cortical gray matter, or intracortical microstimulation (ICMS), a common assumption is that post-stimulation effects remain localized to a small volume of neurons near the stimulating electrode. However, there is evidence that suggests the effects can spread substantial distances. Prior work in my lab has shown that subjects can learn to interpret ICMS delivered to four different electrodes in the primary somatosensory cortex (S1) as instructions to perform four different arbitrarily- assigned movements. My preliminary studies using that dataset suggest that ICMS delivered in S1 can have two types of effects on neurons in distant cortical areas: 1) ICMS pulses can directly elicit spikes in neurons from both ventral premotor cortex (PMv) and primary motor cortex (M1) – either antidromically, monosynaptically, or oligosynaptically – which I term “direct driving”. 2) Other neurons not directly driven by the ICMS pulses may nevertheless fire differently between trials instructing the same movements with only trains of ICMS pulses versus with only visual cues, which I term “instruction-modality dependent modulation”. Thus, the effects of ICMS may extend to parts of the cortical network more distant than previously appreciated. I propose to investigate the effects of ICMS instructions for arbitrarily-associated movements delivered in S1 on several distant cortical areas involved in motor control. Specifically, I will study effects in seven frontal and parietal regions: pre-supplementary motor area, dorsal premotor cortex, ventral premotor cortex, rostral primary motor cortex, caudal primary motor cortex, anterior intraparietal area, and dorsal posterior parietal cortex. Aim I will examine which of those cortical areas contain neurons that are directly driven by ICMS pulses delivered in S1. Aim II will examine which of those cortical areas contain neurons that show instruction- modality dependent modulation. The proposed studies will show the extent to which ICMS in S1 modulates distant parts of the cortical network, and how such modulation develops over time as subjects learn to use the ICMS as instructions to perform arbitrarily-associated movements. That information can be used to design inputs to cortex from brain-machine interfacing technology that is clearer to the subject and encourages healthy plasticity to reduce cognitive demand during the training process. Those improvements serve to benefit patients with diseases of the nervous system that can be treated with brain-machine interfacing technology including stroke, sensory neuropathies, or head trauma.