Title :
A reconfigurable architecture for real-time prediction of neural activity
Author :
Li, Will X. Y. ; Cheung, Ray C. C. ; Chan, Rosa H. M. ; Dong Song ; Berger, Theodore W.
Author_Institution :
Dept. of Electr. Eng., City Univ. of Hong Kong, Hong Kong, China
Abstract :
In this paper, we propose an FPGA-based hardware architecture for conducting real-time prediction of neural activity using a second-order generalized Laguerre-Volterra model (GLVM). This architecture serves as a rapid prototype of the prediction module of the future cognitive neural prosthetic device. We validate the functionality of the hardware model by utilizing the neuronal firing data of behaving rats trained to perform the delayed nonmatch-to-sample (DNMS) memory task.
Keywords :
bioelectric phenomena; cognition; field programmable gate arrays; neural nets; neurophysiology; prosthetics; real-time systems; DNMS; FPGA-based hardware architecture; GLVM; cognitive neural prosthetic device; delayed nonmatch-to-sample memory task; hardware model; neural activity; neuronal firing data; prediction module; rapid prototype; real-time prediction; reconfigurable architecture; second-order generalized Laguerre-Volterra model; Computer architecture; Convolution; Field programmable gate arrays; Hardware; Kernel; Prosthetics; Vectors;
Conference_Titel :
Circuits and Systems (ISCAS), 2013 IEEE International Symposium on
Conference_Location :
Beijing
Print_ISBN :
978-1-4673-5760-9
DOI :
10.1109/ISCAS.2013.6572230
