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Roles for Coincidence Detection in Coding Amplitude-Modulated Sounds.

Ashida G, Kretzberg J, Tollin DJ - PLoS Comput. Biol. (2016)

Bottom Line: Previous physiological recordings in vivo found considerable variations in monaural AM-tuning across neurons.Unlike monaural AM coding, temporal factors, such as the coincidence window and the effective duration of inhibition, played a major role in determining the trough positions of simulated binaural phase-response curves.These modeling results suggest that coincidence detection of excitatory and inhibitory synaptic inputs is essential for LSO neurons to encode both monaural and binaural AM sounds.

View Article: PubMed Central - PubMed

Affiliation: Cluster of Excellence "Hearing4all", Department for Neuroscience, Faculty 6, University of Oldenburg, Oldenburg, Germany.

ABSTRACT
Many sensory neurons encode temporal information by detecting coincident arrivals of synaptic inputs. In the mammalian auditory brainstem, binaural neurons of the medial superior olive (MSO) are known to act as coincidence detectors, whereas in the lateral superior olive (LSO) roles of coincidence detection have remained unclear. LSO neurons receive excitatory and inhibitory inputs driven by ipsilateral and contralateral acoustic stimuli, respectively, and vary their output spike rates according to interaural level differences. In addition, LSO neurons are also sensitive to binaural phase differences of low-frequency tones and envelopes of amplitude-modulated (AM) sounds. Previous physiological recordings in vivo found considerable variations in monaural AM-tuning across neurons. To investigate the underlying mechanisms of the observed temporal tuning properties of LSO and their sources of variability, we used a simple coincidence counting model and examined how specific parameters of coincidence detection affect monaural and binaural AM coding. Spike rates and phase-locking of evoked excitatory and spontaneous inhibitory inputs had only minor effects on LSO output to monaural AM inputs. In contrast, the coincidence threshold of the model neuron affected both the overall spike rates and the half-peak positions of the AM-tuning curve, whereas the width of the coincidence window merely influenced the output spike rates. The duration of the refractory period affected only the low-frequency portion of the monaural AM-tuning curve. Unlike monaural AM coding, temporal factors, such as the coincidence window and the effective duration of inhibition, played a major role in determining the trough positions of simulated binaural phase-response curves. In addition, empirically-observed level-dependence of binaural phase-coding was reproduced in the framework of our minimalistic coincidence counting model. These modeling results suggest that coincidence detection of excitatory and inhibitory synaptic inputs is essential for LSO neurons to encode both monaural and binaural AM sounds.

No MeSH data available.


Related in: MedlinePlus

Effects of excitatory inputs.A: Effects of non-uniform input intensities. (Black curve: uniform intensity) The default input intensity of λ0 = 180 spikes/sec (at zero modulation frequency) was used for all input fibers. (Gray curves: varied intensity) The input intensity λ0 of each fiber was randomly chosen from a uniform distribution between 80 and 280 spikes/sec. Results for ten simulation trials are shown. B: Effects of input parameters on spike rates. In the 'constant rate' condition, the average input rate  was fixed at 180 spikes/sec. In the 'constant VS' condition, VS was fixed to 0.65. Otherwise, these parameters were varied with the modulation frequency (see Materials and Methods). C: Effects of input parameters on the modulation gain. Line types in C correspond to those in B.
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pcbi.1004997.g003: Effects of excitatory inputs.A: Effects of non-uniform input intensities. (Black curve: uniform intensity) The default input intensity of λ0 = 180 spikes/sec (at zero modulation frequency) was used for all input fibers. (Gray curves: varied intensity) The input intensity λ0 of each fiber was randomly chosen from a uniform distribution between 80 and 280 spikes/sec. Results for ten simulation trials are shown. B: Effects of input parameters on spike rates. In the 'constant rate' condition, the average input rate was fixed at 180 spikes/sec. In the 'constant VS' condition, VS was fixed to 0.65. Otherwise, these parameters were varied with the modulation frequency (see Materials and Methods). C: Effects of input parameters on the modulation gain. Line types in C correspond to those in B.

Mentions: First, we tested how variations in input parameters may alter the rate-MTF (Fig 3). Variations of the intensity λ0 of excitatory input fibers slightly modified the overall output rate of the model LSO, but the shape of the rate-MTF curve was not greatly affected (Fig 3A). Therefore, in our following simulations, we assumed that all input fibers have the same rate λ0 (see Materials and Methods for equations). The modulation-frequency dependence of input spike rate and phase-locking also did not generally affect the shape of the rate-MTF curve (Fig 3B). Fixing the input vector strength (VS) at the maximum value (Fig 3B, gray curve) had only limited effects. Additional fixation of the input rate to the maximum value (Fig 3B, thin curve) led to a spike rate increase without much altering the curve shape. In this case, the output spike rate slightly increased for fm > 1000 Hz, which resulted from the combination of the fixed high degree of phase-locking and the entry of the second modulation cycle into the 0.8-ms coincidence window. The phase-locking output of the model LSO was not affected by the fm-dependence on input rates or phase-locking (Fig 3C). In sum, the monaural AM-tuning of LSO was relatively insensitive to input parameters, which lends support to the suggestion that the observed low-pass properties of LSO neurons should originate from synaptic and membrane factors [36]. Possible effects of spontaneous inhibition will be examined separately in a later subsection.


Roles for Coincidence Detection in Coding Amplitude-Modulated Sounds.

Ashida G, Kretzberg J, Tollin DJ - PLoS Comput. Biol. (2016)

Effects of excitatory inputs.A: Effects of non-uniform input intensities. (Black curve: uniform intensity) The default input intensity of λ0 = 180 spikes/sec (at zero modulation frequency) was used for all input fibers. (Gray curves: varied intensity) The input intensity λ0 of each fiber was randomly chosen from a uniform distribution between 80 and 280 spikes/sec. Results for ten simulation trials are shown. B: Effects of input parameters on spike rates. In the 'constant rate' condition, the average input rate  was fixed at 180 spikes/sec. In the 'constant VS' condition, VS was fixed to 0.65. Otherwise, these parameters were varied with the modulation frequency (see Materials and Methods). C: Effects of input parameters on the modulation gain. Line types in C correspond to those in B.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4920552&req=5

pcbi.1004997.g003: Effects of excitatory inputs.A: Effects of non-uniform input intensities. (Black curve: uniform intensity) The default input intensity of λ0 = 180 spikes/sec (at zero modulation frequency) was used for all input fibers. (Gray curves: varied intensity) The input intensity λ0 of each fiber was randomly chosen from a uniform distribution between 80 and 280 spikes/sec. Results for ten simulation trials are shown. B: Effects of input parameters on spike rates. In the 'constant rate' condition, the average input rate was fixed at 180 spikes/sec. In the 'constant VS' condition, VS was fixed to 0.65. Otherwise, these parameters were varied with the modulation frequency (see Materials and Methods). C: Effects of input parameters on the modulation gain. Line types in C correspond to those in B.
Mentions: First, we tested how variations in input parameters may alter the rate-MTF (Fig 3). Variations of the intensity λ0 of excitatory input fibers slightly modified the overall output rate of the model LSO, but the shape of the rate-MTF curve was not greatly affected (Fig 3A). Therefore, in our following simulations, we assumed that all input fibers have the same rate λ0 (see Materials and Methods for equations). The modulation-frequency dependence of input spike rate and phase-locking also did not generally affect the shape of the rate-MTF curve (Fig 3B). Fixing the input vector strength (VS) at the maximum value (Fig 3B, gray curve) had only limited effects. Additional fixation of the input rate to the maximum value (Fig 3B, thin curve) led to a spike rate increase without much altering the curve shape. In this case, the output spike rate slightly increased for fm > 1000 Hz, which resulted from the combination of the fixed high degree of phase-locking and the entry of the second modulation cycle into the 0.8-ms coincidence window. The phase-locking output of the model LSO was not affected by the fm-dependence on input rates or phase-locking (Fig 3C). In sum, the monaural AM-tuning of LSO was relatively insensitive to input parameters, which lends support to the suggestion that the observed low-pass properties of LSO neurons should originate from synaptic and membrane factors [36]. Possible effects of spontaneous inhibition will be examined separately in a later subsection.

Bottom Line: Previous physiological recordings in vivo found considerable variations in monaural AM-tuning across neurons.Unlike monaural AM coding, temporal factors, such as the coincidence window and the effective duration of inhibition, played a major role in determining the trough positions of simulated binaural phase-response curves.These modeling results suggest that coincidence detection of excitatory and inhibitory synaptic inputs is essential for LSO neurons to encode both monaural and binaural AM sounds.

View Article: PubMed Central - PubMed

Affiliation: Cluster of Excellence "Hearing4all", Department for Neuroscience, Faculty 6, University of Oldenburg, Oldenburg, Germany.

ABSTRACT
Many sensory neurons encode temporal information by detecting coincident arrivals of synaptic inputs. In the mammalian auditory brainstem, binaural neurons of the medial superior olive (MSO) are known to act as coincidence detectors, whereas in the lateral superior olive (LSO) roles of coincidence detection have remained unclear. LSO neurons receive excitatory and inhibitory inputs driven by ipsilateral and contralateral acoustic stimuli, respectively, and vary their output spike rates according to interaural level differences. In addition, LSO neurons are also sensitive to binaural phase differences of low-frequency tones and envelopes of amplitude-modulated (AM) sounds. Previous physiological recordings in vivo found considerable variations in monaural AM-tuning across neurons. To investigate the underlying mechanisms of the observed temporal tuning properties of LSO and their sources of variability, we used a simple coincidence counting model and examined how specific parameters of coincidence detection affect monaural and binaural AM coding. Spike rates and phase-locking of evoked excitatory and spontaneous inhibitory inputs had only minor effects on LSO output to monaural AM inputs. In contrast, the coincidence threshold of the model neuron affected both the overall spike rates and the half-peak positions of the AM-tuning curve, whereas the width of the coincidence window merely influenced the output spike rates. The duration of the refractory period affected only the low-frequency portion of the monaural AM-tuning curve. Unlike monaural AM coding, temporal factors, such as the coincidence window and the effective duration of inhibition, played a major role in determining the trough positions of simulated binaural phase-response curves. In addition, empirically-observed level-dependence of binaural phase-coding was reproduced in the framework of our minimalistic coincidence counting model. These modeling results suggest that coincidence detection of excitatory and inhibitory synaptic inputs is essential for LSO neurons to encode both monaural and binaural AM sounds.

No MeSH data available.


Related in: MedlinePlus