A dynamic cortical amplifier model for fast information processing

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 network bandwidth increases with time. The authors: (i) show 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 hypercolumn in order to demonstrate that this strategy could be implemented in the primary visual cortex. They 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