Sparse high-dimensional decomposition of non-primary auditory cortical receptive fields.

Characterizing neuronal responses to natural stimuli remains a central goal in sensory neuroscience. In auditory cortical neurons, the stimulus selectivity of elicited spiking activity is summarized by a spectrotemporal receptive field (STRF) that relates neuronal responses to the stimulus spectrogr...

Full description

Saved in:
Bibliographic Details
Main Authors: Shoutik Mukherjee, Behtash Babadi, Shihab Shamma
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2025-01-01
Series:PLoS Computational Biology
Online Access:https://doi.org/10.1371/journal.pcbi.1012721
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832540363514970112
author Shoutik Mukherjee
Behtash Babadi
Shihab Shamma
author_facet Shoutik Mukherjee
Behtash Babadi
Shihab Shamma
author_sort Shoutik Mukherjee
collection DOAJ
description Characterizing neuronal responses to natural stimuli remains a central goal in sensory neuroscience. In auditory cortical neurons, the stimulus selectivity of elicited spiking activity is summarized by a spectrotemporal receptive field (STRF) that relates neuronal responses to the stimulus spectrogram. Though effective in characterizing primary auditory cortical responses, STRFs of non-primary auditory neurons can be quite intricate, reflecting their mixed selectivity. The complexity of non-primary STRFs hence impedes understanding how acoustic stimulus representations are transformed along the auditory pathway. Here, we focus on the relationship between ferret primary auditory cortex (A1) and a secondary region, dorsal posterior ectosylvian gyrus (PEG). We propose estimating receptive fields in PEG with respect to a well-established high-dimensional computational model of primary-cortical stimulus representations. These "cortical receptive fields" (CortRF) are estimated greedily to identify the salient primary-cortical features modulating spiking responses and in turn related to corresponding spectrotemporal features. Hence, they provide biologically plausible hierarchical decompositions of STRFs in PEG. Such CortRF analysis was applied to PEG neuronal responses to speech and temporally orthogonal ripple combination (TORC) stimuli and, for comparison, to A1 neuronal responses. CortRFs of PEG neurons captured their selectivity to more complex spectrotemporal features than A1 neurons; moreover, CortRF models were more predictive of PEG (but not A1) responses to speech. Our results thus suggest that secondary-cortical stimulus representations can be computed as sparse combinations of primary-cortical features that facilitate encoding natural stimuli. Thus, by adding the primary-cortical representation, we can account for PEG single-unit responses to natural sounds better than bypassing it and considering as input the auditory spectrogram. These results confirm with explicit details the presumed hierarchical organization of the auditory cortex.
format Article
id doaj-art-faf29affbccb45efaaf6d149b175b89a
institution Kabale University
issn 1553-734X
1553-7358
language English
publishDate 2025-01-01
publisher Public Library of Science (PLoS)
record_format Article
series PLoS Computational Biology
spelling doaj-art-faf29affbccb45efaaf6d149b175b89a2025-02-05T05:30:42ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582025-01-01211e101272110.1371/journal.pcbi.1012721Sparse high-dimensional decomposition of non-primary auditory cortical receptive fields.Shoutik MukherjeeBehtash BabadiShihab ShammaCharacterizing neuronal responses to natural stimuli remains a central goal in sensory neuroscience. In auditory cortical neurons, the stimulus selectivity of elicited spiking activity is summarized by a spectrotemporal receptive field (STRF) that relates neuronal responses to the stimulus spectrogram. Though effective in characterizing primary auditory cortical responses, STRFs of non-primary auditory neurons can be quite intricate, reflecting their mixed selectivity. The complexity of non-primary STRFs hence impedes understanding how acoustic stimulus representations are transformed along the auditory pathway. Here, we focus on the relationship between ferret primary auditory cortex (A1) and a secondary region, dorsal posterior ectosylvian gyrus (PEG). We propose estimating receptive fields in PEG with respect to a well-established high-dimensional computational model of primary-cortical stimulus representations. These "cortical receptive fields" (CortRF) are estimated greedily to identify the salient primary-cortical features modulating spiking responses and in turn related to corresponding spectrotemporal features. Hence, they provide biologically plausible hierarchical decompositions of STRFs in PEG. Such CortRF analysis was applied to PEG neuronal responses to speech and temporally orthogonal ripple combination (TORC) stimuli and, for comparison, to A1 neuronal responses. CortRFs of PEG neurons captured their selectivity to more complex spectrotemporal features than A1 neurons; moreover, CortRF models were more predictive of PEG (but not A1) responses to speech. Our results thus suggest that secondary-cortical stimulus representations can be computed as sparse combinations of primary-cortical features that facilitate encoding natural stimuli. Thus, by adding the primary-cortical representation, we can account for PEG single-unit responses to natural sounds better than bypassing it and considering as input the auditory spectrogram. These results confirm with explicit details the presumed hierarchical organization of the auditory cortex.https://doi.org/10.1371/journal.pcbi.1012721
spellingShingle Shoutik Mukherjee
Behtash Babadi
Shihab Shamma
Sparse high-dimensional decomposition of non-primary auditory cortical receptive fields.
PLoS Computational Biology
title Sparse high-dimensional decomposition of non-primary auditory cortical receptive fields.
title_full Sparse high-dimensional decomposition of non-primary auditory cortical receptive fields.
title_fullStr Sparse high-dimensional decomposition of non-primary auditory cortical receptive fields.
title_full_unstemmed Sparse high-dimensional decomposition of non-primary auditory cortical receptive fields.
title_short Sparse high-dimensional decomposition of non-primary auditory cortical receptive fields.
title_sort sparse high dimensional decomposition of non primary auditory cortical receptive fields
url https://doi.org/10.1371/journal.pcbi.1012721
work_keys_str_mv AT shoutikmukherjee sparsehighdimensionaldecompositionofnonprimaryauditorycorticalreceptivefields
AT behtashbabadi sparsehighdimensionaldecompositionofnonprimaryauditorycorticalreceptivefields
AT shihabshamma sparsehighdimensionaldecompositionofnonprimaryauditorycorticalreceptivefields