Original Research ARTICLE

Front. Neuroeng., 11 June 2012 | http://dx.doi.org/10.3389/fneng.2012.00010

Adaptive proactive inhibitory control for embedded real-time applications

  • Intelligent Systems Research Centre, University of Ulster, Derry, Northern Ireland, UK

Psychologists have studied the inhibitory control of voluntary movement for many years. In particular, the countermanding of an impending action has been extensively studied. In this work, we propose a neural mechanism for adaptive inhibitory control in a firing-rate type model based on current findings in animal electrophysiological and human psychophysical experiments. We then implement this model on a field-programmable gate array (FPGA) prototyping system, using dedicated real-time hardware circuitry. Our results show that the FPGA-based implementation can run in real-time while achieving behavioral performance qualitatively suggestive of the animal experiments. Implementing such biological inhibitory control in an embedded device can lead to the development of control systems that may be used in more realistic cognitive robotics or in neural prosthetic systems aiding human movement control.

Keywords: countermanding saccade, frontal eye fields, adaptive inhibitory control, FPGA, neural network model

Citation: Yang S, McGinnity TM and Wong-Lin K (2012) Adaptive proactive inhibitory control for embedded real-time applications. Front. Neuroeng. 5:10. doi: 10.3389/fneng.2012.00010

Received: 01 February 2012; Accepted: 16 May 2012;
Published online: 11 June 2012.

Edited by:

Giovanni Mirabella, University of La Sapienza, Italy

Reviewed by:

Hari S. Sharma, Uppsala University, Sweden
Simeon A. Bamford, L’Istituto Superiore di Sanità, Italy

Copyright: © 2012 Yang, McGinnity and Wong-Lin. This is an open-access article distributed under the terms of the Creative Commons Attribution Non Commercial License, which permits non-commercial use, distribution, and reproduction in other forums, provided the original authors and source are credited.

*Correspondence: Shufan Yang, Intelligent Systems Research Centre, Magee Campus, University of Ulster, Derry, Northern Ireland BT48 7JL, UK. e-mail: s.yang@ulster.ac.uk