Simulation of neocortical epileptiform activity using parallel computing Export

@article{citeulike:4861008, abstract = {A scalable network model intended for study of neocortical epileptiform activity was built on the pGENESIS neural simulator. The model included superficial and deep pyramidal cells plus four types of inhibitory neurons. An electroencephalogram (EEG) simulator was attached to the model to validate model behavior and to determine the contributions of inhibitory and excitatory neuronal populations to the EEG signal. We examined effects of overall excitation and inhibition on activity patterns in the network, and found that the network-bursting patterns occur within a narrow range of the excitation–inhibition space. Further, we evaluated synchronization effects produced by gap junctions during synchronous and asynchronous states.}, author = {Vandrongelen, W. and Clee, H. and Hereld, M. and Jones, D. and Cohoon, M. and Elsen, F. and Epapka, M. and Lstevens, R.}, citeulike-article-id = {4861008}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.neucom.2004.01.186}, citeulike-linkout-1 = {http://linkinghub.elsevier.com/retrieve/pii/S0925231204001912}, doi = {10.1016/j.neucom.2004.01.186}, issn = {09252312}, journal = {Neurocomputing}, keywords = {brain, bursting, eeg, epilepsy, excitation, inhibition, neural-modeling, neural-network, pgenesis, synchronization}, month = {June}, pages = {1203--1209}, posted-at = {2009-06-15 19:20:58}, priority = {0}, title = {Simulation of neocortical epileptiform activity using parallel computing}, url = {http://dx.doi.org/10.1016/j.neucom.2004.01.186}, volume = {58-60}, year = {2004} }

TY - JOUR ID - citeulike:4861008 L3 - citeulike-article-id:4861008 N2 - A scalable network model intended for study of neocortical epileptiform activity was built on the pGENESIS neural simulator. The model included superficial and deep pyramidal cells plus four types of inhibitory neurons. An electroencephalogram (EEG) simulator was attached to the model to validate model behavior and to determine the contributions of inhibitory and excitatory neuronal populations to the EEG signal. We examined effects of overall excitation and inhibition on activity patterns in the network, and found that the network-bursting patterns occur within a narrow range of the excitation–inhibition space. Further, we evaluated synchronization effects produced by gap junctions during synchronous and asynchronous states. JF - Neurocomputing SN - 09252312 EP - 1209 TI - Simulation of neocortical epileptiform activity using parallel computing VL - 58-60 SP - 1203 KW - brain KW - bursting KW - eeg KW - epilepsy KW - excitation KW - inhibition KW - neural-modeling KW - neural-network KW - pgenesis KW - synchronization AU - Vandrongelen, W AU - Clee, H AU - Hereld, M AU - Jones, D AU - Cohoon, M AU - Elsen, F AU - Epapka, M AU - Lstevens, R PY - 2004/06// UR - http://dx.doi.org/10.1016/j.neucom.2004.01.186 ER -