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Deep-brain electrical microstimulation is an effective tool to explore functional characteristics of somatosensory neurons in the rat brain.

ABSTRACT: In neurophysiology researches, peripheral stimulation is used along with recordings of neural activities to study the processing of somatosensory signals in the brain. However, limited precision of peripheral stimulation makes it difficult to activate the neuron with millisecond resolution and study its functional properties in this scale. Also, tissue/receptor damage that could occur in some experiments often limits the amount of responses that can be recorded and hence reduces data reproducibility. To overcome these limitations, electrical microstimulation (ES) of the brain could be used to directly and more precisely evoke neural responses. For this purpose, a deep-brain ES protocol for rat somatosensory relay neurons was developed in this study. Three male Wistar rats were used in the experiment. The ES was applied to the thalamic region responsive to hindpaw tactile stimulation (TS) via a theta glass microelectrode. The resulting ES-evoked cortical responses showed action potentials and thalamocortical relay latencies very similar to those evoked by TS. This result shows that the developed deep-brain ES protocol is an effective tool to bypass peripheral tissue for in vivo functional analysis of specific types of somatosensory neurons. This protocol could be readily applied in researches of nociception and other somatosensory systems to allow more extensive exploration of the neural functional networks.

SUBMITTER: Jiang HJ

PROVIDER: S-EPMC4335035 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Deep-brain electrical microstimulation is an effective tool to explore functional characteristics of somatosensory neurons in the rat brain.

Jiang Han-Jia HJ Chen Kuang-Hsuan KH Jaw Fu-Shan FS

PloS one 20150219 2

In neurophysiology researches, peripheral stimulation is used along with recordings of neural activities to study the processing of somatosensory signals in the brain. However, limited precision of peripheral stimulation makes it difficult to activate the neuron with millisecond resolution and study its functional properties in this scale. Also, tissue/receptor damage that could occur in some experiments often limits the amount of responses that can be recorded and hence reduces data reproducibi ...[more]

PMID: 25695538

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Project description:When we interact with objects, we rely on signals from the hand that convey information about the object and our interaction with it. A basic feature of these interactions, the locations of contacts between the hand and object, is often only available via the sense of touch. Information about locations of contact between a brain-controlled bionic hand and an object can be signaled via intracortical microstimulation (ICMS) of somatosensory cortex (S1), which evokes touch sensations that are localized to a specific patch of skin. To provide intuitive location information, tactile sensors on the robotic hand drive ICMS through electrodes that evoke sensations at skin locations matching sensor locations. This approach requires that ICMS-evoked sensations be focal, stable, and distributed over the hand. To systematically investigate the localization of ICMS-evoked sensations, we analyzed the projected fields (PFs) of ICMS-evoked sensations - their location and spatial extent - from reports obtained over multiple years from three participants implanted with microelectrode arrays in S1. First, we found that PFs vary widely in their size across electrodes, are highly stable within electrode, are distributed over large swaths of each participant's hand, and increase in size as the amplitude or frequency of ICMS increases. Second, while PF locations match the locations of the receptive fields (RFs) of the neurons near the stimulating electrode, PFs tend to be subsumed by the corresponding RFs. Third, multi-channel stimulation gives rise to a PF that reflects the conjunction of the PFs of the component channels. By stimulating through electrodes with largely overlapping PFs, then, we can evoke a sensation that is experienced primarily at the intersection of the component PFs. To assess the functional consequence of this phenomenon, we implemented multichannel ICMS-based feedback in a bionic hand and demonstrated that the resulting sensations are more localizable than are those evoked via single-channel ICMS.

Project description:Nowadays, high-density microelectrode arrays provide unprecedented possibilities to precisely activate spatially well-controlled central nervous system (CNS) areas. However, this requires optimizing stimulating devices, which in turn requires a good understanding of the effects of microstimulation on cells and tissues. In this context, modeling approaches provide flexible ways to predict the outcome of electrical stimulation in terms of CNS activation. In this paper, we present state-of-the-art modeling methods with sufficient details to allow the reader to rapidly build numerical models of neuronal extracellular microstimulation. These include (1) the computation of the electrical potential field created by the stimulation in the tissue, and (2) the response of a target neuron to this field. Two main approaches are described: First we describe the classical hybrid approach that combines the finite element modeling of the potential field with the calculation of the neuron's response in a cable equation framework (compartmentalized neuron models). Then, we present a "whole finite element" approach allowing the simultaneous calculation of the extracellular and intracellular potentials, by representing the neuronal membrane with a thin-film approximation. This approach was previously introduced in the frame of neural recording, but has never been implemented to determine the effect of extracellular stimulation on the neural response at a sub-compartment level. Here, we show on an example that the latter modeling scheme can reveal important sub-compartment behavior of the neural membrane that cannot be resolved using the hybrid approach. The goal of this paper is also to describe in detail the practical implementation of these methods to allow the reader to easily build new models using standard software packages. These modeling paradigms, depending on the situation, should help build more efficient high-density neural prostheses for CNS rehabilitation.

Dataset Information

Deep-brain electrical microstimulation is an effective tool to explore functional characteristics of somatosensory neurons in the rat brain.

Publications

Deep-brain electrical microstimulation is an effective tool to explore functional characteristics of somatosensory neurons in the rat brain.

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