Strong energy component is more important than spectral selectivity in modeling responses of midbrain auditory neurons to wide-band environmental sounds

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11110%2F22%3A10450831" target="_blank" >RIV/00216208:11110/22:10450831 - isvavai.cz</a>

Výsledek na webu

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=8qIeMGj0Ll" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=8qIeMGj0Ll</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.biosystems.2022.104752" target="_blank" >10.1016/j.biosystems.2022.104752</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Strong energy component is more important than spectral selectivity in modeling responses of midbrain auditory neurons to wide-band environmental sounds

Popis výsledku v původním jazyce

Modeling central auditory neurons in response to complex sounds not only helps understanding neural pro-cessing of speech signals but can also provide insights for biomimetics in neuro-engineering. While modeling responses of midbrain auditory neurons to synthetic tones is rather good, modeling those to environmental sounds is less satisfactory. Environmental sounds typically contain a wide range of frequency components, often with strong and transient energy. These stimulus features have not been examined in the conventional approach of auditory modeling centered on spectral selectivity. To this end, we firstly compared responses to an envi-ronmental sound of auditory midbrain neurons across 3 subpopulations of neurons with frequency selectivity in the low, middle and high ranges; secondly, we manipulated the sound energy, both in power and in spectrum, and compared across these subpopulations how their modeled responses were affected. The environmental sound was recorded when a rat was drinking from a feeding bottle (called the &apos;drinking sound&apos;). The sound spectrum was divided into 20 non-overlapping frequency bands (from 0 to 20 kHz, at 1 kHz width) and presented to an artificial neural model built on a committee machine with parallel spectral inputs to simulate the known tonotopic organization of the auditory system. The model was trained to predict empirical response probability profiles of neurons to the repeated sounds. Results showed that model performance depended more on the strong energy components than on the spectral selectivity. Findings were interpreted to reflect general sensitivity to rapidly changing sound intensities at the auditory midbrain and in the cortex.

Název v anglickém jazyce

Strong energy component is more important than spectral selectivity in modeling responses of midbrain auditory neurons to wide-band environmental sounds

Popis výsledku anglicky

Modeling central auditory neurons in response to complex sounds not only helps understanding neural pro-cessing of speech signals but can also provide insights for biomimetics in neuro-engineering. While modeling responses of midbrain auditory neurons to synthetic tones is rather good, modeling those to environmental sounds is less satisfactory. Environmental sounds typically contain a wide range of frequency components, often with strong and transient energy. These stimulus features have not been examined in the conventional approach of auditory modeling centered on spectral selectivity. To this end, we firstly compared responses to an envi-ronmental sound of auditory midbrain neurons across 3 subpopulations of neurons with frequency selectivity in the low, middle and high ranges; secondly, we manipulated the sound energy, both in power and in spectrum, and compared across these subpopulations how their modeled responses were affected. The environmental sound was recorded when a rat was drinking from a feeding bottle (called the &apos;drinking sound&apos;). The sound spectrum was divided into 20 non-overlapping frequency bands (from 0 to 20 kHz, at 1 kHz width) and presented to an artificial neural model built on a committee machine with parallel spectral inputs to simulate the known tonotopic organization of the auditory system. The model was trained to predict empirical response probability profiles of neurons to the repeated sounds. Results showed that model performance depended more on the strong energy components than on the spectral selectivity. Findings were interpreted to reflect general sensitivity to rapidly changing sound intensities at the auditory midbrain and in the cortex.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

30103 - Neurosciences (including psychophysiology)

Projekt

—

Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Bio Systems

ISSN

0303-2647

e-ISSN

1872-8324

Svazek periodika

221

Číslo periodika v rámci svazku

November

Stát vydavatele periodika

IE - Irsko

Počet stran výsledku

9

Strana od-do

104752

Kód UT WoS článku

000883256400003

EID výsledku v databázi Scopus

2-s2.0-85137293145