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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.


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Simulated synchronized neuron.a. Classification of neuron-type [non-sync (o), sync (x), mixed (+), atypical (square)] across two parameters (Excitatory input and I/E ratio), with a fixed I-E delay of 5 ms. The two arrows indicate the parameters used for the simulated neurons in Fig. 4c (left arrow) and Fig. 4d (right arrow). b. Dependence of Rayleigh statistic (at an IPI of 75 ms) on the amplitude of excitatory inputs in simulated synchronized neurons. Spearman correlation coefficient: r = 0.99, P<3.1x10-87. c-e. Examples of simulated and real synchronized neurons. Each plot is subdivided into a raster plot (left), IPI vs discharge rate plot (top right), and IPI vs vector strength plot (bottom right). The stimulus is played for 500 ms, which is indicated with the gray rectangle in the raster plot. The dashed line in the IPI vs discharge rate plot indicates a significant evoked response above the spontaneous rate (2σ). Error bars indicate SEM. c. Simulated neuron: I-E delay = 5 ms, E strength = 1.8 nS, I/E ratio = 2. d. Simulated neuron: I-E delay = 5 ms, E strength = 6 nS, I/E ratio = 2. e. Real neuron (unit m2p31.1) from awake marmoset auditory cortex.
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pcbi.1004197.g004: Simulated synchronized neuron.a. Classification of neuron-type [non-sync (o), sync (x), mixed (+), atypical (square)] across two parameters (Excitatory input and I/E ratio), with a fixed I-E delay of 5 ms. The two arrows indicate the parameters used for the simulated neurons in Fig. 4c (left arrow) and Fig. 4d (right arrow). b. Dependence of Rayleigh statistic (at an IPI of 75 ms) on the amplitude of excitatory inputs in simulated synchronized neurons. Spearman correlation coefficient: r = 0.99, P<3.1x10-87. c-e. Examples of simulated and real synchronized neurons. Each plot is subdivided into a raster plot (left), IPI vs discharge rate plot (top right), and IPI vs vector strength plot (bottom right). The stimulus is played for 500 ms, which is indicated with the gray rectangle in the raster plot. The dashed line in the IPI vs discharge rate plot indicates a significant evoked response above the spontaneous rate (2σ). Error bars indicate SEM. c. Simulated neuron: I-E delay = 5 ms, E strength = 1.8 nS, I/E ratio = 2. d. Simulated neuron: I-E delay = 5 ms, E strength = 6 nS, I/E ratio = 2. e. Real neuron (unit m2p31.1) from awake marmoset auditory cortex.

Mentions: Synchronized neurons were more common when inhibition lagged excitation, and the magnitude of inhibition was at least 40–50% stronger than the magnitude of excitation (Fig. 4a, model with an I-E delay = 5 ms). Comparing synchronized neurons with a fixed I-E delay of 5 ms, we observed a highly significant correlation (r = 0.99, P<3.1x10-87, Spearman Correlation, Fig. 4b) between the excitatory input strength and the Rayleigh statistic, the criterion we used to measure the statistical significance of stimulus-synchronization. In other words, as the strength of excitation increased, our confidence in the high fidelity of a synchronized neuron’s temporal representation improved. This can be observed by comparing the responses of two simulated synchronized neurons that differ in their excitation strength parameter (Fig. 4c-d). While both of these examples of simulated neurons differ in the robustness of their temporal representation, they closely match the general properties of real synchronized neurons (Fig. 4e).


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)

Simulated synchronized neuron.a. Classification of neuron-type [non-sync (o), sync (x), mixed (+), atypical (square)] across two parameters (Excitatory input and I/E ratio), with a fixed I-E delay of 5 ms. The two arrows indicate the parameters used for the simulated neurons in Fig. 4c (left arrow) and Fig. 4d (right arrow). b. Dependence of Rayleigh statistic (at an IPI of 75 ms) on the amplitude of excitatory inputs in simulated synchronized neurons. Spearman correlation coefficient: r = 0.99, P<3.1x10-87. c-e. Examples of simulated and real synchronized neurons. Each plot is subdivided into a raster plot (left), IPI vs discharge rate plot (top right), and IPI vs vector strength plot (bottom right). The stimulus is played for 500 ms, which is indicated with the gray rectangle in the raster plot. The dashed line in the IPI vs discharge rate plot indicates a significant evoked response above the spontaneous rate (2σ). Error bars indicate SEM. c. Simulated neuron: I-E delay = 5 ms, E strength = 1.8 nS, I/E ratio = 2. d. Simulated neuron: I-E delay = 5 ms, E strength = 6 nS, I/E ratio = 2. e. Real neuron (unit m2p31.1) from awake marmoset auditory cortex.
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pcbi.1004197.g004: Simulated synchronized neuron.a. Classification of neuron-type [non-sync (o), sync (x), mixed (+), atypical (square)] across two parameters (Excitatory input and I/E ratio), with a fixed I-E delay of 5 ms. The two arrows indicate the parameters used for the simulated neurons in Fig. 4c (left arrow) and Fig. 4d (right arrow). b. Dependence of Rayleigh statistic (at an IPI of 75 ms) on the amplitude of excitatory inputs in simulated synchronized neurons. Spearman correlation coefficient: r = 0.99, P<3.1x10-87. c-e. Examples of simulated and real synchronized neurons. Each plot is subdivided into a raster plot (left), IPI vs discharge rate plot (top right), and IPI vs vector strength plot (bottom right). The stimulus is played for 500 ms, which is indicated with the gray rectangle in the raster plot. The dashed line in the IPI vs discharge rate plot indicates a significant evoked response above the spontaneous rate (2σ). Error bars indicate SEM. c. Simulated neuron: I-E delay = 5 ms, E strength = 1.8 nS, I/E ratio = 2. d. Simulated neuron: I-E delay = 5 ms, E strength = 6 nS, I/E ratio = 2. e. Real neuron (unit m2p31.1) from awake marmoset auditory cortex.
Mentions: Synchronized neurons were more common when inhibition lagged excitation, and the magnitude of inhibition was at least 40–50% stronger than the magnitude of excitation (Fig. 4a, model with an I-E delay = 5 ms). Comparing synchronized neurons with a fixed I-E delay of 5 ms, we observed a highly significant correlation (r = 0.99, P<3.1x10-87, Spearman Correlation, Fig. 4b) between the excitatory input strength and the Rayleigh statistic, the criterion we used to measure the statistical significance of stimulus-synchronization. In other words, as the strength of excitation increased, our confidence in the high fidelity of a synchronized neuron’s temporal representation improved. This can be observed by comparing the responses of two simulated synchronized neurons that differ in their excitation strength parameter (Fig. 4c-d). While both of these examples of simulated neurons differ in the robustness of their temporal representation, they closely match the general properties of real synchronized neurons (Fig. 4e).

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.


Related in: MedlinePlus