Title :
Stochastic dynamics and partial synchronization of stimulus-driven neural activity
Author_Institution :
Centre for Theor. & Comput. Neuroscience, Plymouth Univ., UK
Abstract :
We study a dynamical behaviour of neural population driven by stimulus. This dynamical response is considered in relation to the population coding. The hypothesis that neuronal code at some stages of information processing in the brain is based on synchronisation of neural activity is under intensive discussions. The dynamical regime of partial synchronisation is important and very useful for modelling of neural activity and we have found that the input driven neural assembly can demonstrate a dynamical regime of partial synchronisation. It is interesting to note that population dynamics has a stochastic nature and repetition of the same stimulus causes a synchronous activity of different sub-populations.
Keywords :
brain; dynamic response; neural nets; stochastic processes; brain information processing; dynamical response; neural population; neuronal code; partial synchronisation; partial synchronization; stimulus-driven neural activity; stochastic dynamics; Assembly; Biological neural networks; Chaos; Computational modeling; Computer architecture; Frequency synchronization; Hebbian theory; Information processing; Neurons; Stochastic processes;
Conference_Titel :
Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
Print_ISBN :
0-7803-8359-1
DOI :
10.1109/IJCNN.2004.1381152