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首页> 美国卫生研究院文献>Frontiers in Neuroengineering >Short-term dynamics of causal information transfer in thalamocortical networks during natural inputs and microstimulation for somatosensory neuroprosthesis
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Short-term dynamics of causal information transfer in thalamocortical networks during natural inputs and microstimulation for somatosensory neuroprosthesis

机译：在自然输入和体刺激神经假体的微刺激期间丘脑皮质网络中因果信息传递的短期动态

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摘要

Recording the activity of large populations of neurons requires new methods to analyze and use the large volumes of time series data thus created. Fast and clear methods for finding functional connectivity are an important step toward the goal of understanding neural processing. This problem presents itself readily in somatosensory neuroprosthesis (SSNP) research, which uses microstimulation (MiSt) to activate neural tissue to mimic natural stimuli, and has the capacity to potentiate, depotentiate, or even destroy functional connections. As the aim of SSNP engineering is artificially creating neural responses that resemble those observed during natural inputs, a central goal is describing the influence of MiSt on activity structure among groups of neurons, and how this structure may be altered to affect perception or behavior. In this paper, we demonstrate the concept of Granger causality, combined with maximum likelihood methods, applied to neural signals recorded before, during, and after natural and electrical stimulation. We show how these analyses can be used to evaluate the changing interactions in the thalamocortical somatosensory system in response to repeated perturbation. Using LFPs recorded from the ventral posterolateral thalamus (VPL) and somatosensory cortex (S1) in anesthetized rats, we estimated pair-wise functional interactions between functional microdomains. The preliminary results demonstrate input-dependent modulations in the direction and strength of information flow during and after application of MiSt. Cortico-cortical interactions during cortical MiSt and baseline conditions showed the largest causal influence differences, while there was no statistically significant difference between pre- and post-stimulation baseline causal activities. These functional connectivity changes agree with physiologically accepted communication patterns through the network, and their particular parameters have implications for both rehabilitation and brain—machine interface SSNP applications.
机译：记录大量神经元的活动需要新的方法来分析和使用由此创建的大量时间序列数据。快速而清晰的查找功能连接的方法是朝着理解神经处理目标迈出的重要一步。这个问题在体感神经假体（SSNP）研究中很容易出现，该研究使用微刺激（MiSt）激活神经组织来模仿自然刺激，并且具有增强，减弱甚至破坏功能连接的能力。由于SSNP工程的目的是人为地创建类似于自然输入过程中观察到的神经反应，因此一个主要目标是描述MiSt对神经元组之间的活动结构的影响，以及如何改变这种结构以影响感知或行为。在本文中，我们展示了Granger因果关系的概念，并结合最大似然方法，将其应用于在自然和电刺激之前，之中和之后记录的神经信号。我们展示了如何使用这些分析来评估响应反复扰动的丘脑皮层体感系统中不断变化的相互作用。使用从麻醉大鼠的腹侧后外侧丘脑（VPL）和体感皮层（S1）记录的LFP，我们估计功能性微区之间的成对功能相互作用。初步结果表明，在应用MiSt期间和之后，信息流的方向和强度取决于输入调制。皮质MiSt和基线条件期间的皮质-皮质相互作用显示最大的因果影响差异，而刺激前后基线因果活动之间无统计学显着差异。这些功能的连接性变化与通过网络的生理上可接受的通信模式一致，并且它们的特定参数对康复和脑机接口SSNP应用都有影响。

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