Neurons in the inferior colliculus use multiplexing to encode features of frequency-modulated sweeps DOI Creative Commons
Audrey C. Drotos,

Sarah Z. Wajdi,

Michael Malina

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 11, 2025

Within the central auditory pathway, inferior colliculus (IC) is a critical integration center for ascending sound information. Previous studies have shown that many IC neurons exhibit receptive fields individual features of stimuli, such as frequency, intensity, and location, but growing evidence suggests some may multiplex sound. Here, we used in vivo juxtacellular recordings awake, head-fixed mice to examine how responded frequency-modulated sweeps varied speed, direction, frequency range. We then applied machine learning methods determine encode FM sweeps. found sweep using various strategies including spike timing, distribution inter-spike intervals, first latency. In addition, decoding accuracy direction can vary with speed range, suggesting presence mixed selectivity single neurons. Accordingly, static alone yielded poor predictions neuron responses vocalizations contain simple changes. Lastly, showed encoding across neurons, resulting highly informative population response features. Together, our results suggest multiplexing common mechanism by represent complex sounds.

Language: Английский

Neurons in the inferior colliculus use multiplexing to encode features of frequency-modulated sweeps DOI Creative Commons
Audrey C. Drotos,

Sarah Z. Wajdi,

Michael Malina

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 11, 2025

Within the central auditory pathway, inferior colliculus (IC) is a critical integration center for ascending sound information. Previous studies have shown that many IC neurons exhibit receptive fields individual features of stimuli, such as frequency, intensity, and location, but growing evidence suggests some may multiplex sound. Here, we used in vivo juxtacellular recordings awake, head-fixed mice to examine how responded frequency-modulated sweeps varied speed, direction, frequency range. We then applied machine learning methods determine encode FM sweeps. found sweep using various strategies including spike timing, distribution inter-spike intervals, first latency. In addition, decoding accuracy direction can vary with speed range, suggesting presence mixed selectivity single neurons. Accordingly, static alone yielded poor predictions neuron responses vocalizations contain simple changes. Lastly, showed encoding across neurons, resulting highly informative population response features. Together, our results suggest multiplexing common mechanism by represent complex sounds.

Language: Английский

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