Limits...
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.


Temporal dynamics of synchronized and non-synchronized neurons.a. Net excitation (excitatory-inhibitory conductance) for a single acoustic pulse in a simulated synchronized neuron. I-E delay = 5 ms, E strength = 3 nS, I/E ratio = 1.5. b. Net excitation (excitatory-inhibitory conductance) for a single acoustic pulse in a simulated non-synchronized neuron. I-E delay = 0 ms, E strength = 0.6 nS, I/E ratio = 0.9. c. Minimum latency distribution for acoustic pulse train responses in simulated neurons. Mean: sync = 10.8 ms, nonsync = 16.6 ms, Wilcoxon rank sum test: P < 1.4 x 10-89. d. Minimum latency distribution for acoustic pulse train responses in real neurons. Mean: sync = 18.1 ms, nonsync = 51.1 ms, Wilcoxon rank sum test: P<4.6 x 10-9. e. Onset/sustained ratio distribution for pure tone responses in simulated neurons. Mean: sync = 0.69, nonsync = 0.18, Wilcoxon rank sum test: P < 6.1 x 10-124. f. Onset/sustained ratio distribution for pure tone responses in real neurons. Mean: sync = 0.60, nonsync = 0.25, Wilcoxon rank sum test: P<2.3 x 10-9.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4400160&req=5

pcbi.1004197.g006: Temporal dynamics of synchronized and non-synchronized neurons.a. Net excitation (excitatory-inhibitory conductance) for a single acoustic pulse in a simulated synchronized neuron. I-E delay = 5 ms, E strength = 3 nS, I/E ratio = 1.5. b. Net excitation (excitatory-inhibitory conductance) for a single acoustic pulse in a simulated non-synchronized neuron. I-E delay = 0 ms, E strength = 0.6 nS, I/E ratio = 0.9. c. Minimum latency distribution for acoustic pulse train responses in simulated neurons. Mean: sync = 10.8 ms, nonsync = 16.6 ms, Wilcoxon rank sum test: P < 1.4 x 10-89. d. Minimum latency distribution for acoustic pulse train responses in real neurons. Mean: sync = 18.1 ms, nonsync = 51.1 ms, Wilcoxon rank sum test: P<4.6 x 10-9. e. Onset/sustained ratio distribution for pure tone responses in simulated neurons. Mean: sync = 0.69, nonsync = 0.18, Wilcoxon rank sum test: P < 6.1 x 10-124. f. Onset/sustained ratio distribution for pure tone responses in real neurons. Mean: sync = 0.60, nonsync = 0.25, Wilcoxon rank sum test: P<2.3 x 10-9.

Mentions: Using our computational model, we could make several predictions concerning how stimulus-evoked responses may differ between synchronized, non-synchronized, and mixed-response neurons, which were testable in our dataset of real neurons. In our model, delayed inhibition in synchronized neurons led to a positive net excitation concentrated at the onset of the synaptic input (Fig. 6a), while balanced excitation and inhibition in non-synchronized neurons led to weaker net excitation that was spread out over a longer time duration (Fig. 6b). Because of this difference, an evoked response from a synchronized neuron only required a single acoustic pulse, while the evoked response of a non-synchronized neuron required the temporal summation of inputs from multiple acoustic pulses. We reasoned that this difference should also be reflected in the temporal dynamics of the neuron’s response to acoustic pulse trains, with a synchronizing neuron having a shorter latency to the onset of its response (minimum latency) than a non-synchronizing neuron. We measured the minimum latency of acoustic pulse train responses (see Methods), and found a statistically significant difference between synchronized and non-synchronized neurons, within both our simulated and real neuronal populations (Fig. 6c,d). In the simulated neuronal population, synchronized neurons had a mean minimum latency of 10.8 ms, while non-synchronized neurons had a mean minimum latency of 16.6 ms (Wilcoxon rank sum test, P < 1.4 x 10-89). A similar difference occurred in the real neuronal population; synchronized neurons had a mean minimum latency of 18.1 ms, while non-synchronized neurons had a mean minimum latency of 51.1 ms (Wilcoxon rank sum test, P < 4.6 x 10-9). Like synchronized neurons, mixed response neurons are also capable of envelope locking, with only a single acoustic pulse required to evoke a response. Based on this similarity, we reasoned that the minimum latency should be similar between synchronized and mixed response. We observed that mixed neurons had a mean minimum latency (simulated neurons: 8.0 ms, real neurons: 16.2 ms) not significantly different from synchronized neurons (Wilcoxon rank sum test, P = 0.053 (simulated), P = 0.30 (real)) and significantly different from non-synchronized neurons (Wilcoxon rank sum test, P<3.1x10-75 (simulated), P<1.1x10-5 (real)).


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)

Temporal dynamics of synchronized and non-synchronized neurons.a. Net excitation (excitatory-inhibitory conductance) for a single acoustic pulse in a simulated synchronized neuron. I-E delay = 5 ms, E strength = 3 nS, I/E ratio = 1.5. b. Net excitation (excitatory-inhibitory conductance) for a single acoustic pulse in a simulated non-synchronized neuron. I-E delay = 0 ms, E strength = 0.6 nS, I/E ratio = 0.9. c. Minimum latency distribution for acoustic pulse train responses in simulated neurons. Mean: sync = 10.8 ms, nonsync = 16.6 ms, Wilcoxon rank sum test: P < 1.4 x 10-89. d. Minimum latency distribution for acoustic pulse train responses in real neurons. Mean: sync = 18.1 ms, nonsync = 51.1 ms, Wilcoxon rank sum test: P<4.6 x 10-9. e. Onset/sustained ratio distribution for pure tone responses in simulated neurons. Mean: sync = 0.69, nonsync = 0.18, Wilcoxon rank sum test: P < 6.1 x 10-124. f. Onset/sustained ratio distribution for pure tone responses in real neurons. Mean: sync = 0.60, nonsync = 0.25, Wilcoxon rank sum test: P<2.3 x 10-9.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4400160&req=5

pcbi.1004197.g006: Temporal dynamics of synchronized and non-synchronized neurons.a. Net excitation (excitatory-inhibitory conductance) for a single acoustic pulse in a simulated synchronized neuron. I-E delay = 5 ms, E strength = 3 nS, I/E ratio = 1.5. b. Net excitation (excitatory-inhibitory conductance) for a single acoustic pulse in a simulated non-synchronized neuron. I-E delay = 0 ms, E strength = 0.6 nS, I/E ratio = 0.9. c. Minimum latency distribution for acoustic pulse train responses in simulated neurons. Mean: sync = 10.8 ms, nonsync = 16.6 ms, Wilcoxon rank sum test: P < 1.4 x 10-89. d. Minimum latency distribution for acoustic pulse train responses in real neurons. Mean: sync = 18.1 ms, nonsync = 51.1 ms, Wilcoxon rank sum test: P<4.6 x 10-9. e. Onset/sustained ratio distribution for pure tone responses in simulated neurons. Mean: sync = 0.69, nonsync = 0.18, Wilcoxon rank sum test: P < 6.1 x 10-124. f. Onset/sustained ratio distribution for pure tone responses in real neurons. Mean: sync = 0.60, nonsync = 0.25, Wilcoxon rank sum test: P<2.3 x 10-9.
Mentions: Using our computational model, we could make several predictions concerning how stimulus-evoked responses may differ between synchronized, non-synchronized, and mixed-response neurons, which were testable in our dataset of real neurons. In our model, delayed inhibition in synchronized neurons led to a positive net excitation concentrated at the onset of the synaptic input (Fig. 6a), while balanced excitation and inhibition in non-synchronized neurons led to weaker net excitation that was spread out over a longer time duration (Fig. 6b). Because of this difference, an evoked response from a synchronized neuron only required a single acoustic pulse, while the evoked response of a non-synchronized neuron required the temporal summation of inputs from multiple acoustic pulses. We reasoned that this difference should also be reflected in the temporal dynamics of the neuron’s response to acoustic pulse trains, with a synchronizing neuron having a shorter latency to the onset of its response (minimum latency) than a non-synchronizing neuron. We measured the minimum latency of acoustic pulse train responses (see Methods), and found a statistically significant difference between synchronized and non-synchronized neurons, within both our simulated and real neuronal populations (Fig. 6c,d). In the simulated neuronal population, synchronized neurons had a mean minimum latency of 10.8 ms, while non-synchronized neurons had a mean minimum latency of 16.6 ms (Wilcoxon rank sum test, P < 1.4 x 10-89). A similar difference occurred in the real neuronal population; synchronized neurons had a mean minimum latency of 18.1 ms, while non-synchronized neurons had a mean minimum latency of 51.1 ms (Wilcoxon rank sum test, P < 4.6 x 10-9). Like synchronized neurons, mixed response neurons are also capable of envelope locking, with only a single acoustic pulse required to evoke a response. Based on this similarity, we reasoned that the minimum latency should be similar between synchronized and mixed response. We observed that mixed neurons had a mean minimum latency (simulated neurons: 8.0 ms, real neurons: 16.2 ms) not significantly different from synchronized neurons (Wilcoxon rank sum test, P = 0.053 (simulated), P = 0.30 (real)) and significantly different from non-synchronized neurons (Wilcoxon rank sum test, P<3.1x10-75 (simulated), P<1.1x10-5 (real)).

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.