ArticlePLoS computational biology2008
A model of stimulus-specific neural assemblies in the insect antennal lobe.
Article in PLoS computational biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Network mechanism for insect olfaction.Cognitive neurodynamics · 2021Article
- Neuronal Network Models for Sensory Discrimination.Conference record. Asilomar Conference on Signals, Systems & Computers · 2016Article
- Coding of odors by temporal binding within a model network of the locust antennal lobe.Frontiers in computational neuroscience · 2013Article
- Rapid processing of chemosensor transients in a neuromorphic implementation of the insect macroglomerular complex.Frontiers in neuroscience · 2013Article
- A model of non-elemental olfactory learning in Drosophila.Journal of computational neuroscience · 2012Article
- The laminar cortex model: a new continuum cortex model incorporating laminar architecture.PLoS computational biology · 2012Article
- Interaction of cellular and network mechanisms for efficient pheromone coding in moths.Proceedings of the National Academy of Sciences of the United States of America · 2011Article
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2 authors.
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Abstract
It has been proposed that synchronized neural assemblies in the antennal lobe of insects encode the identity of olfactory stimuli. In response to an odor, some projection neurons exhibit synchronous firing, phase-locked to the oscillations of the field potential, whereas others do not. Experimental data indicate that neural synchronization and field oscillations are induced by fast GABA(A)-type inhibition, but it remains unclear how desynchronization occurs. We hypothesize that slow inhibition plays a key role in desynchronizing projection neurons. Because synaptic noise is believed to be the dominant factor that limits neuronal reliability, we consider a computational model of the antennal lobe in which a population of oscillatory neurons interact through unreliable GABA(A) and GABA(B) inhibitory synapses. From theoretical analysis and extensive computer simulations, we show that transmission failures at slow GABA(B) synapses make the neural response unpredictable. Depending on the balance between GABA(A) and GABA(B) inputs, particular neurons may either synchronize or desynchronize. These findings suggest a wiring scheme that triggers stimulus-specific synchronized assemblies. Inhibitory connections are set by Hebbian learning and selectively activated by stimulus patterns to form a spiking associative memory whose storage capacity is comparable to that of classical binary-coded models. We conclude that fast inhibition acts in concert with slow inhibition to reformat the glomerular input into odor-specific synchronized neural assemblies.
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