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The role of inhibition in a computational model of an auditory cortical neuron during the encoding of temporal information.

Bendor D - PLoS Comput. Biol. (2015)

Bottom Line: Using a computational neuronal model, we find that stimulus-locked responses are generated when sound-evoked excitation is combined with strong, delayed inhibition.In contrast to this, a non-synchronized rate representation is generated when the net excitation evoked by the sound is weak, which occurs when excitation is coincident and balanced with inhibition.Together these data suggest that feedforward inhibition provides a parsimonious explanation of the neural coding dichotomy observed in auditory cortex.

View Article: PubMed Central - PubMed

Affiliation: Institute of Behavioural Neuroscience, Department of Experimental Psychology, University College London, London, United Kingdom.

ABSTRACT
In auditory cortex, temporal information within a sound is represented by two complementary neural codes: a temporal representation based on stimulus-locked firing and a rate representation, where discharge rate co-varies with the timing between acoustic events but lacks a stimulus-synchronized response. Using a computational neuronal model, we find that stimulus-locked responses are generated when sound-evoked excitation is combined with strong, delayed inhibition. In contrast to this, a non-synchronized rate representation is generated when the net excitation evoked by the sound is weak, which occurs when excitation is coincident and balanced with inhibition. Using single-unit recordings from awake marmosets (Callithrix jacchus), we validate several model predictions, including differences in the temporal fidelity, discharge rates and temporal dynamics of stimulus-evoked responses between neurons with rate and temporal representations. Together these data suggest that feedforward inhibition provides a parsimonious explanation of the neural coding dichotomy observed in auditory cortex.

No MeSH data available.


Discharge rates across mixed, synchronized, and non-synchronized neurons.Mean discharge rates for simulated (left) and real (right) neuronal populations, grouped according to their neural coding regime: synchronized (red), non-synchronized (blue), and mixed (green). Error bars indicate SEM. Wilcoxon rank sum test: * P<0.003 Bonferonni corrected, ** P<1.2x10-76 Bonferonni corrected, NS = not significant (P>0.05 uncorrected). a. Pure tone responses of simulated neurons. b. Pure tone responses of real neurons.
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pcbi.1004197.g007: Discharge rates across mixed, synchronized, and non-synchronized neurons.Mean discharge rates for simulated (left) and real (right) neuronal populations, grouped according to their neural coding regime: synchronized (red), non-synchronized (blue), and mixed (green). Error bars indicate SEM. Wilcoxon rank sum test: * P<0.003 Bonferonni corrected, ** P<1.2x10-76 Bonferonni corrected, NS = not significant (P>0.05 uncorrected). a. Pure tone responses of simulated neurons. b. Pure tone responses of real neurons.

Mentions: According to our computational model (Fig. 3), when either a synchronized neuron’s inhibitory input was reduced or a non-synchronized neuron’s excitatory input was increased, the neural coding regime changed to a mixed response (i.e. non-synchronized for short IPIs and synchronized for long IPIs). This implies that mixed response neurons had a larger net excitation than either synchronized or non-synchronized neurons, which we reasoned should manifest as a larger pure tone evoked response. We observed that for the simulated neuronal population, mixed neurons had a significantly higher discharge rate to pure tones than either non-synchronized and synchronized neurons (Fig. 7a, mixed = 29.7 spk/s, nonsync = 13.9 spk/s, sync = 3.3 spk/s; Wilcoxon rank sum test, P< 1.2 x 10-76, Bonferroni corrected). We also observed a significant difference between non-synchronized and synchronized neurons (Wilcoxon rank sum test, P< 6.9 x 10-96, Bonferroni corrected). We found a similar effect in our real neuronal population- mixed neurons had a significantly higher discharge rate to pure tones than either synchronized or non-synchronized neurons (Fig. 7b, mixed = 51.3 spk/s, nonsync = 22.5 spk/s, sync = 18.3 spk/s; Wilcoxon rank sum test, P< 0.003, Bonferroni corrected). While non-synchronized neurons had a slightly higher pure tone evoked response to pure tones than synchronized neurons, this difference was not statistically significant (Wilcoxon rank sum test, P = 0.58, uncorrected). Compared with real neurons, simulated synchronized neurons generally had lower firing rates. One potential reason for this is a higher percentage of simulated neurons receiving very strong inhibition than in our real neuronal population. However, we still observed both onset and sustained pure tone responses in simulated neurons, representative of typical real synchronizing neurons. Strong delayed inhibition (e.g. an I/E ratios of 2) typically generated onset responses with delayed suppression, while more moderate delayed inhibition (e.g. an I/E ratio of 1.4) typically generated onset responses with sustained activity (S5 Fig).


The role of inhibition in a computational model of an auditory cortical neuron during the encoding of temporal information.

Bendor D - PLoS Comput. Biol. (2015)

Discharge rates across mixed, synchronized, and non-synchronized neurons.Mean discharge rates for simulated (left) and real (right) neuronal populations, grouped according to their neural coding regime: synchronized (red), non-synchronized (blue), and mixed (green). Error bars indicate SEM. Wilcoxon rank sum test: * P<0.003 Bonferonni corrected, ** P<1.2x10-76 Bonferonni corrected, NS = not significant (P>0.05 uncorrected). a. Pure tone responses of simulated neurons. b. Pure tone responses of real neurons.
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pcbi.1004197.g007: Discharge rates across mixed, synchronized, and non-synchronized neurons.Mean discharge rates for simulated (left) and real (right) neuronal populations, grouped according to their neural coding regime: synchronized (red), non-synchronized (blue), and mixed (green). Error bars indicate SEM. Wilcoxon rank sum test: * P<0.003 Bonferonni corrected, ** P<1.2x10-76 Bonferonni corrected, NS = not significant (P>0.05 uncorrected). a. Pure tone responses of simulated neurons. b. Pure tone responses of real neurons.
Mentions: According to our computational model (Fig. 3), when either a synchronized neuron’s inhibitory input was reduced or a non-synchronized neuron’s excitatory input was increased, the neural coding regime changed to a mixed response (i.e. non-synchronized for short IPIs and synchronized for long IPIs). This implies that mixed response neurons had a larger net excitation than either synchronized or non-synchronized neurons, which we reasoned should manifest as a larger pure tone evoked response. We observed that for the simulated neuronal population, mixed neurons had a significantly higher discharge rate to pure tones than either non-synchronized and synchronized neurons (Fig. 7a, mixed = 29.7 spk/s, nonsync = 13.9 spk/s, sync = 3.3 spk/s; Wilcoxon rank sum test, P< 1.2 x 10-76, Bonferroni corrected). We also observed a significant difference between non-synchronized and synchronized neurons (Wilcoxon rank sum test, P< 6.9 x 10-96, Bonferroni corrected). We found a similar effect in our real neuronal population- mixed neurons had a significantly higher discharge rate to pure tones than either synchronized or non-synchronized neurons (Fig. 7b, mixed = 51.3 spk/s, nonsync = 22.5 spk/s, sync = 18.3 spk/s; Wilcoxon rank sum test, P< 0.003, Bonferroni corrected). While non-synchronized neurons had a slightly higher pure tone evoked response to pure tones than synchronized neurons, this difference was not statistically significant (Wilcoxon rank sum test, P = 0.58, uncorrected). Compared with real neurons, simulated synchronized neurons generally had lower firing rates. One potential reason for this is a higher percentage of simulated neurons receiving very strong inhibition than in our real neuronal population. However, we still observed both onset and sustained pure tone responses in simulated neurons, representative of typical real synchronizing neurons. Strong delayed inhibition (e.g. an I/E ratios of 2) typically generated onset responses with delayed suppression, while more moderate delayed inhibition (e.g. an I/E ratio of 1.4) typically generated onset responses with sustained activity (S5 Fig).

Bottom Line: Using a computational neuronal model, we find that stimulus-locked responses are generated when sound-evoked excitation is combined with strong, delayed inhibition.In contrast to this, a non-synchronized rate representation is generated when the net excitation evoked by the sound is weak, which occurs when excitation is coincident and balanced with inhibition.Together these data suggest that feedforward inhibition provides a parsimonious explanation of the neural coding dichotomy observed in auditory cortex.

View Article: PubMed Central - PubMed

Affiliation: Institute of Behavioural Neuroscience, Department of Experimental Psychology, University College London, London, United Kingdom.

ABSTRACT
In auditory cortex, temporal information within a sound is represented by two complementary neural codes: a temporal representation based on stimulus-locked firing and a rate representation, where discharge rate co-varies with the timing between acoustic events but lacks a stimulus-synchronized response. Using a computational neuronal model, we find that stimulus-locked responses are generated when sound-evoked excitation is combined with strong, delayed inhibition. In contrast to this, a non-synchronized rate representation is generated when the net excitation evoked by the sound is weak, which occurs when excitation is coincident and balanced with inhibition. Using single-unit recordings from awake marmosets (Callithrix jacchus), we validate several model predictions, including differences in the temporal fidelity, discharge rates and temporal dynamics of stimulus-evoked responses between neurons with rate and temporal representations. Together these data suggest that feedforward inhibition provides a parsimonious explanation of the neural coding dichotomy observed in auditory cortex.

No MeSH data available.