Dataset Information

A Python Code for Simulating Single Tactile Receptors and the Spiking Responses of Their Afferents.

ABSTRACT: This work presents a pieces of Python code to rapidly simulate the spiking responses of large numbers of single cutaneous tactile afferents with millisecond precision. To simulate the spike responses of all the major types of cutaneous tactile afferents, we proposed an electromechanical circuit model, in which a two-channel filter was developed to characterize the mechanical selectivity of tactile receptors, and a spike synthesizer was designed to recreate the action potentials evoked in afferents. The parameters of this model were fitted using previous neurophysiological datasets. Several simulation examples were presented in this paper to reproduce action potentials, sensory adaptation, frequency characteristics and spiking timing for each afferent type. The results indicated that the simulated responses matched previous neurophysiological recordings well. The model allows for a real-time reproduction of the spiking responses of about 4,000 tactile units with a timing precision of <6 ms. The current work provides a valuable guidance to designing highly realistic tactile interfaces such as neuroprosthesis and haptic devices.

SUBMITTER: Ouyang Q

PROVIDER: S-EPMC6478814 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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A Python Code for Simulating Single Tactile Receptors and the Spiking Responses of Their Afferents.

Ouyang Qiangqiang Q Wu Juan J Shao Zhiyu Z Wu Miao M Cao Zhiyong Z

Frontiers in neuroinformatics 20190417

This work presents a pieces of Python code to rapidly simulate the spiking responses of large numbers of single cutaneous tactile afferents with millisecond precision. To simulate the spike responses of all the major types of cutaneous tactile afferents, we proposed an electromechanical circuit model, in which a two-channel filter was developed to characterize the mechanical selectivity of tactile receptors, and a spike synthesizer was designed to recreate the action potentials evoked in afferen ...[more]

PMID: 31057386

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Project description:C-mechanoreceptors in humans comprise a population of unmyelinated afferents exhibiting a wide range of mechanical sensitivities. C-mechanoreceptors are putatively divided into those signaling gentle touch (C-tactile afferents, CTs) and nociception (C-mechanosensitive nociceptors, CMs), giving rise to positive and negative affect, respectively. We sought to distinguish, compare, and contrast the properties of a population of human C-mechanoreceptors to see how fundamental the divisions between these putative subpopulations are. We used microneurography to record from individual afferents in humans and applied electrical and mechanical stimulation to their receptive fields. We show that C-mechanoreceptors can be distinguished unequivocally into two putative populations, comprising CTs and CMs, by electrically evoked spike latency changes (slowing). After both natural mechanical stimulation and repetitive electrical stimulation there was markedly less latency slowing in CTs compared with CMs. Electrical receptive field stimulation, which bypasses the receptor end organ, was most effective in classifying C-mechanoreceptors, as responses to mechanical receptive field stimulation overlapped somewhat, which may lead to misclassification. Furthermore, we report a subclass of low-threshold CM responding to gentle mechanical stimulation and a potential subclass of CT afferent displaying burst firing. We show that substantial differences exist in the mechanisms governing axonal conduction between CTs and CMs. We provide clear electrophysiological "signatures" (extent of latency slowing) that can be used in unequivocally identifying populations of C-mechanoreceptors in single-unit and multiunit microneurography studies and in translational animal research into affective touch. Additionally, these differential mechanisms may be pharmacologically targetable for separate modulation of positive and negative affective touch information.NEW & NOTEWORTHY Human skin encodes a plethora of touch interactions, and affective tactile information is primarily signaled by slowly conducting C-mechanoreceptive afferents. We show that electrical stimulation of low-threshold C-tactile afferents produces markedly different patterns of activity compared with high-threshold C-mechanoreceptive nociceptors, although the populations overlap in their responses to mechanical stimulation. This fundamental distinction demonstrates a divergence in affective touch signaling from the first stage of sensory processing, having implications for the processing of interpersonal touch.

Dataset Information

A Python Code for Simulating Single Tactile Receptors and the Spiking Responses of Their Afferents.

Publications

A Python Code for Simulating Single Tactile Receptors and the Spiking Responses of Their Afferents.

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