In order to study the problem how the olfactory neural system processes the odorant molecular information for constructing the olfactory image of each object, we present a dynamic model of the olfactory bulb constructed on the basis of well-established experimental and theoretical results. The information relevant to a single odor, i.e. its constituent odorant molecules and their mixing ratios, are encoded into a spatio-temporal pattern of neural activity in the olfactory bulb, where the activity pattern corresponds to a limit cycle attractor in the mitral cell network. The spatio-temporal pattern consists of a temporal sequence of spatial firing patterns: each constituent molecule is encoded into a single spatial pattern, and the order of magnitude of the mixing ratio is encoded into the temporal sequence. The formation of a limit cycle attractor under the application of a novel odor is carried out based on the intensity-to-time-delay encoding scheme. The dynamic state of the olfactory bulb, which has learned many odors, becomes a randomly itinerant state in which the current firing state of the bulb itinerates randomly among limit cycle attractors corresponding to the learned odors. The recognition of an odor is generated by the dynamic transition in the network from the randomly itinerant state to a limit cycle attractor state relevant to the odor, where the transition is induced by the short-term synaptic changes made according to the Hebbian rule under the application of the odor stimulus.
Transitions between dynamically stable activity patterns imposed on an associative neural network are shown to be induced by self-organized infinitesimal changes in synaptic connection strength and to be a kind of phase transition. A key event for the neural process of information processing in a population coding scheme is transition between the activity patterns encoding usual entities. We propose that the infinitesimal and short-term synaptic changes based on
There has been compelling evidence that the GABA transporter is crucial not only for removing gamma-aminobutyric acid (GABA) from but also releasing it into extracellular space, thereby clamping ambient GABA (GABA in extracellular space) at a certain level. The ambient GABA is known to activate extrasynaptic GABA receptors and provide tonic inhibitory current into neurons. We investigated how the transporter regulates the level of ambient GABA, mediates tonic neuronal inhibition, and influences ongoing spontaneous neuronal activity. A cortical neural network model is proposed in which GABA transporters on lateral (L) and feedback (F) inhibitory (GABAergic) interneurons are functionally made. Principal (P) cell assemblies participate in expressing information about elemental sensory features. At membrane potentials below the reversal potential, there is net influx of GABA, whereas at membrane potentials above the reversal potential, there is net efflux of GABA. Through this transport mechanism, ambient GABA concentration is kept within a submicromolar range during an ongoing spontaneous neuronal activity time period. Here we show that the GABA transporter on L cells regulates the overall level of ambient GABA across cell assemblies, and that on F cells it does so within individual cell assemblies. This combinatorial regulation of ambient GABA allows P cells to oscillate near firing threshold during the ongoing time period, thereby reducing their reaction time to externally applied stimuli. We suggest that the GABA transporter, with its forward and reverse transport mechanism, could regulate the ambient GABA. This transporter-mediated ambient GABA regulation may contribute to establishing an ongoing subthreshold neuronal state by which the network can respond rapidly to subsequent sensory input.
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