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A model of stimulus-specific neural assemblies in the insect antennal lobe.

Martinez D, Montejo N - PLoS Comput. Biol. (2008)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: LORIA, Campus Scientifique, Vandoeuvre-lès-Nancy, France. dominique.martinez@loria.fr

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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Phase-locking probability with GABAA or GABAB inhibition.(A) Phase-locking probability versus probability of synaptic failure in homogeneous networks. The stars represent data estimated from the simulations in the presence of GABAA (blue stars) or GABAB (red stars). The resolution at which phase-locked spikes are determined is ε = 5 ms (B). The solid curves are for the lower bounds on the phase-locking probability (Equation 5). The constant value 2εF (horizontal lines) is for the desynchronized state corresponding to the case where the firings are uniformly distributed over the duration 1/F of the oscillatory cycle. (B) Spike rasterplot over two consecutive oscillatory cyles. Synchronized spikes are those which fall within a temporal bin of ±ε around the mean firing time T̅ of the PN population. Dots with the same color correspond to the spikes fired by the neurons receiving the same amount of inhibition (k/〈k〉). The number of inhibitory inputs received by a particular cell is k and the inhibition received on average by the neuronal population is 〈k〉. Synchronized neurons are those for which k≈〈k〉. (C) Phase-locking probability versus relative amount of received inhibition (k/〈k〉) in heterogeneous networks (probability of connection = 0.4 with GABAA and 0.9 with GABAB). The resolution at which phase-locked spikes are determined is ε = 5 ms. The lower bounds on the phase-locking probability are given by Equation 6. (D) Same conventions as in (C), except that ε = 1 ms.
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pcbi-1000139-g004: Phase-locking probability with GABAA or GABAB inhibition.(A) Phase-locking probability versus probability of synaptic failure in homogeneous networks. The stars represent data estimated from the simulations in the presence of GABAA (blue stars) or GABAB (red stars). The resolution at which phase-locked spikes are determined is ε = 5 ms (B). The solid curves are for the lower bounds on the phase-locking probability (Equation 5). The constant value 2εF (horizontal lines) is for the desynchronized state corresponding to the case where the firings are uniformly distributed over the duration 1/F of the oscillatory cycle. (B) Spike rasterplot over two consecutive oscillatory cyles. Synchronized spikes are those which fall within a temporal bin of ±ε around the mean firing time T̅ of the PN population. Dots with the same color correspond to the spikes fired by the neurons receiving the same amount of inhibition (k/〈k〉). The number of inhibitory inputs received by a particular cell is k and the inhibition received on average by the neuronal population is 〈k〉. Synchronized neurons are those for which k≈〈k〉. (C) Phase-locking probability versus relative amount of received inhibition (k/〈k〉) in heterogeneous networks (probability of connection = 0.4 with GABAA and 0.9 with GABAB). The resolution at which phase-locked spikes are determined is ε = 5 ms. The lower bounds on the phase-locking probability are given by Equation 6. (D) Same conventions as in (C), except that ε = 1 ms.

Mentions: (A) is for our type 1 model of Projection Neuron (see Methods). Left: temporal evolution of the membrane potential V with somatic injection of hyperpolarizing current pulses Iinj of different durations (6, 10, and 20 ms). The spike time jitter (bars above the spikes) is estimated as the temporal dispersion of the first spikes right after inhibition. Right: spike time jitter versus duration of the hyperpolarizing interval. Means and standard deviations are estimated over five runs; The solid curve is an exponential fit of the data (time constant = 4.1 ms). (B) is for a type 2 model of olfactory bulb Mitral Cell. Left: temporal evolution of the state variables (membrane potential V and adaptive current u) for different durations of the hyperpolarizing current (1, 10, and 25 ms). Right: spike time jitter versus duration of the hyperpolarizing interval. Same convention as in (A) (time constant of exponential fit = 9.8 ms). Figure inset represents the exponential fit of experimental data recorded in MCs in vitro (time constant = 6.8 ms), modified from [28], Figure 4A4.


A model of stimulus-specific neural assemblies in the insect antennal lobe.

Martinez D, Montejo N - PLoS Comput. Biol. (2008)

Phase-locking probability with GABAA or GABAB inhibition.(A) Phase-locking probability versus probability of synaptic failure in homogeneous networks. The stars represent data estimated from the simulations in the presence of GABAA (blue stars) or GABAB (red stars). The resolution at which phase-locked spikes are determined is ε = 5 ms (B). The solid curves are for the lower bounds on the phase-locking probability (Equation 5). The constant value 2εF (horizontal lines) is for the desynchronized state corresponding to the case where the firings are uniformly distributed over the duration 1/F of the oscillatory cycle. (B) Spike rasterplot over two consecutive oscillatory cyles. Synchronized spikes are those which fall within a temporal bin of ±ε around the mean firing time T̅ of the PN population. Dots with the same color correspond to the spikes fired by the neurons receiving the same amount of inhibition (k/〈k〉). The number of inhibitory inputs received by a particular cell is k and the inhibition received on average by the neuronal population is 〈k〉. Synchronized neurons are those for which k≈〈k〉. (C) Phase-locking probability versus relative amount of received inhibition (k/〈k〉) in heterogeneous networks (probability of connection = 0.4 with GABAA and 0.9 with GABAB). The resolution at which phase-locked spikes are determined is ε = 5 ms. The lower bounds on the phase-locking probability are given by Equation 6. (D) Same conventions as in (C), except that ε = 1 ms.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2536510&req=5

pcbi-1000139-g004: Phase-locking probability with GABAA or GABAB inhibition.(A) Phase-locking probability versus probability of synaptic failure in homogeneous networks. The stars represent data estimated from the simulations in the presence of GABAA (blue stars) or GABAB (red stars). The resolution at which phase-locked spikes are determined is ε = 5 ms (B). The solid curves are for the lower bounds on the phase-locking probability (Equation 5). The constant value 2εF (horizontal lines) is for the desynchronized state corresponding to the case where the firings are uniformly distributed over the duration 1/F of the oscillatory cycle. (B) Spike rasterplot over two consecutive oscillatory cyles. Synchronized spikes are those which fall within a temporal bin of ±ε around the mean firing time T̅ of the PN population. Dots with the same color correspond to the spikes fired by the neurons receiving the same amount of inhibition (k/〈k〉). The number of inhibitory inputs received by a particular cell is k and the inhibition received on average by the neuronal population is 〈k〉. Synchronized neurons are those for which k≈〈k〉. (C) Phase-locking probability versus relative amount of received inhibition (k/〈k〉) in heterogeneous networks (probability of connection = 0.4 with GABAA and 0.9 with GABAB). The resolution at which phase-locked spikes are determined is ε = 5 ms. The lower bounds on the phase-locking probability are given by Equation 6. (D) Same conventions as in (C), except that ε = 1 ms.
Mentions: (A) is for our type 1 model of Projection Neuron (see Methods). Left: temporal evolution of the membrane potential V with somatic injection of hyperpolarizing current pulses Iinj of different durations (6, 10, and 20 ms). The spike time jitter (bars above the spikes) is estimated as the temporal dispersion of the first spikes right after inhibition. Right: spike time jitter versus duration of the hyperpolarizing interval. Means and standard deviations are estimated over five runs; The solid curve is an exponential fit of the data (time constant = 4.1 ms). (B) is for a type 2 model of olfactory bulb Mitral Cell. Left: temporal evolution of the state variables (membrane potential V and adaptive current u) for different durations of the hyperpolarizing current (1, 10, and 25 ms). Right: spike time jitter versus duration of the hyperpolarizing interval. Same convention as in (A) (time constant of exponential fit = 9.8 ms). Figure inset represents the exponential fit of experimental data recorded in MCs in vitro (time constant = 6.8 ms), modified from [28], Figure 4A4.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: LORIA, Campus Scientifique, Vandoeuvre-lès-Nancy, France. dominique.martinez@loria.fr

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.

Show MeSH
Related in: MedlinePlus