Volume 11, Issue 1 (January & February 2020)                   BCN 2020, 11(1): 121-128 | Back to browse issues page


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Saberi Moghadam S, Behroozi M. A Simulation Model of Neural Activity During Hand Reaching Movement. BCN. 2020; 11 (1) :121-128
URL: http://bcn.iums.ac.ir/article-1-1501-en.html
1- Faculty of Engineering Modern Technologies, Amol University of Special Modern Technologies, Amol, Iran.; Department of Physiology, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland.
2- Neuroscience & Neuroengineering Research Lab., Department of Biomedical Engineering, School of Electrical Engineering, Iran University of Science and Technology (IUST), Tehran, Iran.
Abstract:  
Introduction: The neural response is a noisy random process. The neural response to a sensory stimulus is completely equivalent to a list of spike times in the spike train. In previous studies, decreased neuronal response variability was observed in the cortex’s various areas during motor preparatory in reaching tasks. The reasons for the reduction in Neural Variability (NV) are unclear. It could be influenced by an increased firing rate, or it could result from the intrinsic characteristic of cells during the Reaction Time (RT).
Methods: A neural response function with an underlying deterministic instantaneous firing rate signal and a random Poisson process spike generator was simulated in this research. Neural stimulation could help us understand the relationships between the complex data structures of cortical activities and their stability in detail during motor intention in arm-reaching tasks. 
Results: Our measurements indicated a similar pattern of results to the cortex, a sharp reduction of the normalized variance of simulated spike trains across all trials. We also observed a reverse relationship between activity and normalized variance.
Conclusion: The present study findings could be applied to neural engineering and brain-machine interfaces for controlling external devices, like the movement of a robot arm.
Type of Study: Original | Subject: Computational Neuroscience
Received: 2019/05/13 | Accepted: 2019/08/14 | Published: 2020/01/1

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