A biophysical modelling platform of the cochlear nucleus and other auditory circuits: From channels to networks

Manis, Paul B.; Campagnola, Luke

doi:10.1016/j.heares.2017.12.017

Cited by 20 publications

(35 citation statements)

References 140 publications

(209 reference statements)

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“…Neuro-physiologically parameterized auditory models mimic the dynamics of the basilar membrane, the mechano-electrical coupling of inner hair cells to it, and the membrane voltage regulated vesicle rate kinetics into the synaptic cleft between them and the associated auditory nerve fibers (Baumgarte, 1997;Sumner et al, 2002;Yu et al, 2009;Meaud and Grosh, 2012;Harczos et al, 2013a;Zilany et al, 2014;Cerezuela-Escudero et al, 2015;Lee et al, 2015;Ó'Maoiléidigh and Hudspeth, 2015;Saremi et al, 2016;Rudnicki and Hemmert, 2017;Manis and Campagnola, 2018;Saremi and Lyon, 2018;Xu et al, 2018;Liu et al, 2019).…”

Section: Methodsmentioning

confidence: 99%

Periodicity Pitch Perception

Klefenz

Harczos

2020

Front. Neurosci.

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This study presents a computational model to reproduce the biological dynamics of "listening to music." A biologically plausible model of periodicity pitch detection is proposed and simulated. Periodicity pitch is computed across a range of the auditory spectrum. Periodicity pitch is detected from subsets of activated auditory nerve fibers (ANFs). These activate connected model octopus cells, which trigger model neurons detecting onsets and offsets; thence model interval-tuned neurons are innervated at the right interval times; and finally, a set of common interval-detecting neurons indicate pitch. Octopus cells rhythmically spike with the pitch periodicity of the sound. Batteries of interval-tuned neurons stopwatch-like measure the inter-spike intervals of the octopus cells by coding interval durations as first spike latencies (FSLs). The FSL-triggered spikes synchronously coincide through a monolayer spiking neural network at the corresponding receiver pitch neurons.

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Section: Methodsmentioning

confidence: 99%

Periodicity Pitch Perception

Klefenz

Harczos

2020

Front. Neurosci.

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“…However, since our present GBC model framework lacks inhibitory inputs, the FRA of the simulated GBC does not have an inhibitory sideband (Fig 14B). Broadband inhibition (putatively from D-stellate cells [54]) would be necessary to simulate such sideband effects in GBCs.…”

Section: Resultsmentioning

confidence: 99%

“…Further experimental and theoretical studies are required to fully understand the physiological roles of these inhibitory inputs to GBCs. A recently developed model framework that simulates ipsilateral inhibitory connections from D-stellate cells and tuberculoventral cells to bushy cells [54] might be useful towards this end.…”

Section: Discussionmentioning

confidence: 99%

“…Physiological single neuron models can be classified into several categories (see [43,44] for reviews of representative classes). Prior models of bushy cells include shot-noise models that have a simplified description of synaptic inputs and focus primarily on the input-output relations [25,45–48], integrate-and-fire-type models that have a membrane potential and an abstracted spike-generation mechanism [33,47,49,50], and more complex Hodgkin-Huxley-type models that deal with detailed biophysical functions of ionic conductances [30,31,46,51–54]. Simple models are generally suitable for computationally efficient simulations and mathematical analyses, while complex models are often required for the investigation of detailed mechanisms underlying spiking phenomena [44,55].…”

Section: Introductionmentioning

confidence: 99%

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Neuronal population model of globular bushy cells covering unit-to-unit variability

Ashida

Heinermann²,

Kretzberg³

2019

PLoS Comput Biol

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Computations of acoustic information along the central auditory pathways start in the cochlear nucleus. Bushy cells in the anteroventral cochlear nucleus, which innervate monaural and binaural stations in the superior olivary complex, process and transfer temporal cues relevant for sound localization. These cells are categorized into two groups: spherical and globular bushy cells (SBCs/GBCs). Spontaneous rates of GBCs innervated by multiple auditory nerve (AN) fibers are generally lower than those of SBCs that receive a small number of large AN synapses. In response to low-frequency tonal stimulation, both types of bushy cells show improved phase-locking and entrainment compared to AN fibers. When driven by high-frequency tones, GBCs show primary-like-with-notch or onset-L peristimulus time histograms and relatively irregular spiking. However, previous in vivo physiological studies of bushy cells also found considerable unit-to-unit variability in these response patterns. Here we present a population of models that can simulate the observed variation in GBCs. We used a simple coincidence detection model with an adaptive threshold and systematically varied its six parameters. Out of 567000 parameter combinations tested, 7520 primary-like-with-notch models and 4094 onset-L models were selected that satisfied a set of physiological criteria for a GBC unit. Analyses of the model parameters and output measures revealed that the parameters of the accepted model population are weakly correlated with each other to retain major GBC properties, and that the output spiking patterns of the model are affected by a combination of multiple parameters. Simulations of frequency-dependent temporal properties of the model GBCs showed a reasonable fit to empirical data, supporting the validity of our population modeling. The computational simplicity and efficiency of the model structure makes our approach suitable for future large-scale simulations of binaural information processing that may involve thousands of GBC units.

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“…Although we used Q 10 to approximate temperature-dependent shifts in model parameters, as has been done in similar experiments (Manis and Campagnola 2018;Rothman and Manis 2003c), these Q 10 values were only estimates. More importantly, even with an accurate Q 10 value it is possible that temperature-dependent changes would be revealed at physiological temperature, such as action potential kinetics and reliability (Hong et al 2016).…”

Section: Discussionmentioning

confidence: 99%

Intrinsic physiological properties underlie auditory response diversity in the avian cochlear nucleus

Brown

Hyson

2019

Journal of Neurophysiology

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Sensory systems exploit parallel processing of stimulus features to enable rapid, simultaneous extraction of information. Mechanisms that facilitate this differential extraction of stimulus features can be intrinsic or synaptic in origin. A subdivision of the avian cochlear nucleus, nucleus angularis (NA), extracts sound intensity information from the auditory nerve and contains neurons that exhibit diverse responses to sound and current injection. NA neurons project to multiple regions ascending the auditory brain stem including the superior olivary nucleus, lateral lemniscus, and avian inferior colliculus, with functional implications for inhibitory gain control and sound localization. Here we investigated whether the diversity of auditory response patterns in NA can be accounted for by variation in intrinsic physiological features. Modeled sound-evoked auditory nerve input was applied to NA neurons with dynamic clamp during in vitro whole cell recording at room temperature. Temporal responses to auditory nerve input depended on variation in intrinsic properties, and the low-threshold K+ current was implicated as a major contributor to temporal response diversity and neuronal input-output functions. An auditory nerve model of acoustic amplitude modulation produced synchrony coding of modulation frequency that depended on the intrinsic physiology of the individual neuron. In Primary-Like neurons, varying low-threshold K+ conductance with dynamic clamp altered temporal modulation tuning bidirectionally. Taken together, these data suggest that intrinsic physiological properties play a key role in shaping auditory response diversity to both simple and more naturalistic auditory stimuli in the avian cochlear nucleus. NEW & NOTEWORTHY This article addresses the question of how the nervous system extracts different information in sounds. Neurons in the cochlear nucleus show diverse responses to acoustic stimuli that may allow for parallel processing of acoustic features. The present studies suggest that diversity in intrinsic physiological features of individual neurons, including levels of a low voltage-activated K+ current, play a major role in regulating the diversity of auditory responses.

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A biophysical modelling platform of the cochlear nucleus and other auditory circuits: From channels to networks

Cited by 20 publications

References 140 publications

Periodicity Pitch Perception

Periodicity Pitch Perception

Neuronal population model of globular bushy cells covering unit-to-unit variability

Intrinsic physiological properties underlie auditory response diversity in the avian cochlear nucleus

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