TY - GEN
T1 - A neuronal multisensory processing simulator
AU - Lim, H. K.
AU - Keniston, L. P.
AU - Shin, J. H.
AU - Nguyen, C.
AU - Meredith, M. A.
AU - Cios, K. J.
PY - 2010
Y1 - 2010
N2 - In general, simulation of brain function involves a serial process that includes conceptual definition and design, computational (or mathematical) modeling, testing the correlation between model output and the brain, and generation of biologically testable hypotheses. Processing simulators provide a specific simulation environment in which computational models can be custom built according to their conceptual model of interest, as well as evaluate the result of the simulation by using analytic tools in the simulator. In this paper we describe a new simulator, the Neuronal Multisensory Processing Simulator (NMPS) designed primarily to model the first requisite step of multisensory processing: multisensory convergence. The NMPS generated a network of spiking neurons and stimulated convergent inputs to those neurons. Analysis of both neurons and network revealed responses similar to biological multisensory processing, and provided insight into multisensory features currently inaccessible to observation or experimentation.
AB - In general, simulation of brain function involves a serial process that includes conceptual definition and design, computational (or mathematical) modeling, testing the correlation between model output and the brain, and generation of biologically testable hypotheses. Processing simulators provide a specific simulation environment in which computational models can be custom built according to their conceptual model of interest, as well as evaluate the result of the simulation by using analytic tools in the simulator. In this paper we describe a new simulator, the Neuronal Multisensory Processing Simulator (NMPS) designed primarily to model the first requisite step of multisensory processing: multisensory convergence. The NMPS generated a network of spiking neurons and stimulated convergent inputs to those neurons. Analysis of both neurons and network revealed responses similar to biological multisensory processing, and provided insight into multisensory features currently inaccessible to observation or experimentation.
UR - http://www.scopus.com/inward/record.url?scp=79959385856&partnerID=8YFLogxK
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U2 - 10.1109/IJCNN.2010.5596777
DO - 10.1109/IJCNN.2010.5596777
M3 - Conference contribution
AN - SCOPUS:79959385856
SN - 9781424469178
T3 - Proceedings of the International Joint Conference on Neural Networks
BT - 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
T2 - 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 International Joint Conference on Neural Networks, IJCNN 2010
Y2 - 18 July 2010 through 23 July 2010
ER -