Biomedical subjects

Dmitri Bibitchkov

Publications and source records attributed to Dmitri Bibitchkov.

3 recordsLinked to original sources

PubMed2006

Neural network model of the primary visual cortex: from functional architecture to lateral connectivity and back.

The role of intrinsic cortical dynamics is a debatable issue. A recent optical imaging study (Kenet et al., 2003) found that activity patterns similar to orientation maps (OMs), emerge in the primary visual cortex (V1) even in the absence of sensory input, suggesting an intrinsic mechanism of OM activation. To better understand these results and shed light on the intrinsic V1 processing, we suggest a neural network model in which OMs are encoded by the intrinsic lateral connections. The proposed connectivity pattern depends on the preferred orientation and, unlike previous models, on the degree of orientation selectivity of the interconnected neurons. We prove that the network has a ring attractor composed of an approximated version of the OMs. Consequently, OMs emerge spontaneously when the network is presented with an unstructured noisy input. Simulations show that the model can be applied to experimental data and generate realistic OMs. We study a variation of the model with spatially restricted connections, and show that it gives rise to states composed of several OMs. We hypothesize that these states can represent local properties of the visual scene.

Action Potentials↗

PubMed2003

Spontaneously emerging cortical representations of visual attributes.

Spontaneous cortical activity--ongoing activity in the absence of intentional sensory input--has been studied extensively, using methods ranging from EEG (electroencephalography), through voltage sensitive dye imaging, down to recordings from single neurons. Ongoing cortical activity has been shown to play a critical role in development, and must also be essential for processing sensory perception, because it modulates stimulus-evoked activity, and is correlated with behaviour. Yet its role in the processing of external information and its relationship to internal representations of sensory attributes remains unknown. Using voltage sensitive dye imaging, we previously established a close link between ongoing activity in the visual cortex of anaesthetized cats and the spontaneous firing of a single neuron. Here we report that such activity encompasses a set of dynamically switching cortical states, many of which correspond closely to orientation maps. When such an orientation state emerged spontaneously, it spanned several hypercolumns and was often followed by a state corresponding to a proximal orientation. We suggest that dynamically switching cortical states could represent the brain's internal context, and therefore reflect or influence memory, perception and behaviour.

Algorithms↗

PubMed2002

Pattern storage and processing in attractor networks with short-time synaptic dynamics.

Neurophysiological experiments show that the strength of synaptic connections can undergo substantial changes on a short time scale. These changes depend on the history of the presynaptic input. Using mean-field techniques, we study how short-time dynamics of synaptic connections influence the performance of attractor neural networks in terms of their memory capacity and capability to process external signals. For binary discrete-time as well as for firing rate continuous-time neural networks, the fixed points of the network dynamics are shown to be unaffected by synaptic dynamics. However, the stability of patterns changes considerably. Synaptic depression turns out to reduce the storage capacity. On the other hand, synaptic depression is shown to be advantageous for processing of pattern sequences. The analytical results on stability, size of the basins of attraction and on the switching between patterns are complemented by numerical simulations.

Algorithms↗