IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5
A Dynamic Cortical Amplifier Model for Fast Information Processing
Como, Italy
July 24-July 27
ISBN: 0-7695-0619-4
We start from the observation that sensory coding is not a static mapping but a process and focus on this temporal aspect. We propose that first extracting the salient features of a stimulus and then the details is an efficient coding strategy in terms of information processing when the networks bandwidth increases with time. We show (i) by using a simple transfer function that modulating the coding strategy from an initially highly competitive to a less competitive mapping is efficient for information encoding in time and (ii) present simulation results of a detailed computational model of a cortical hyper-column in order to demonstrate that this strategy could be implemented in the primary visual cortex. We propose a dynamic cortical amplifier model and suggest fast depressing synapses at the excitatory lateral connections as a possible mechanism to modulate the level competition on a short timescale.
Citation:
Lars Schwabe, Péter Adorján, Klaus Obermayer, "A Dynamic Cortical Amplifier Model for Fast Information Processing," ijcnn, vol. 5, pp.5431, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 5, 2000