Author : Lin Li
Publisher :
ISBN 13 :
Total Pages : 128 pages
Book Rating : 4.:/5 (869 download)
Book Synopsis Kernel Based Machine Learning Framework for Neural Decoding by : Lin Li
Download or read book Kernel Based Machine Learning Framework for Neural Decoding written by Lin Li and published by . This book was released on 2012 with total page 128 pages. Available in PDF, EPUB and Kindle. Book excerpt: Secondly, the precise control of the firing pattern in a population of neurons via applied electrical stimulation is a challenge due to the sparseness of spiking responses and neural system plasticity. In this work, we propose a multiple-input-multiple-output (MIMO) adaptive inverse control scheme that operates on spike trains in a RKHS. The control scheme uses an inverse controller to approximate the neural circuit's inverse. The proposed control system takes advantage of the precise timing of the neural events using the Schoenberg kernel based decoding methodology we proposed before. During operation, the adaptation of the controller minimizes a difference defined in the spike train RKHS between the system output and the target response and keeps the inverse controller close to the inverse of the current neural circuit, which enables adapting to neural perturbations. The results on a realistic synthetic neural circuit show that the inverse controller based on the Schoenberg kernel can successfully drive the elicited responses close to the original target responses even when significant perturbations occur.