Music-selective neural populations arise without musical training

Recent work has shown that human auditory cortex contains neural populations anterior and posterior to primary auditory cortex that respond selectively to music. However, it is unknown how this selectivity for music arises. To test whether musical training is necessary, we measured fMRI responses to 192 natural sounds in 10 people with almost no musical training. When voxel responses were decomposed into underlying components, this group exhibited a music-selective component that was very similar in response profile and anatomical distribution to that previously seen in individuals with moderate musical training. We also found that musical genres that were less familiar to our participants (e.g., Balinese gamelan) produced strong responses within the music component, as did drum clips with rhythm but little melody, suggesting that these neural populations are broadly responsive to music as a whole. Our findings demonstrate that the signature properties of neural music selectivity do not require musical training to develop, showing that the music-selective neural populations are a fundamental and widespread property of the human brain.

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Music-selective neural populations arise without musical training

10.1101/2020.01.10.902189 ◽

2020 ◽

Cited By ~ 1

Author(s):

Dana Boebinger ◽

Sam Norman-Haignere ◽

Josh McDermott ◽

Nancy Kanwisher

Keyword(s):

Auditory Cortex ◽

Human Brain ◽

Recent Work ◽

Musical Training ◽

Primary Auditory Cortex ◽

Natural Sounds ◽

Anatomical Distribution ◽

Neural Populations ◽

Response Profile ◽

Musical Genres

ABSTRACTRecent work has shown that human auditory cortex contains neural populations anterior and posterior to primary auditory cortex that respond selectively to music. However, it is unknown how this selectivity for music arises. To test whether musical training is necessary, we measured fMRI responses to 192 natural sounds in 10 people with almost no musical training. When voxel responses were decomposed into underlying components, this group exhibited a music-selective component that was very similar in response profile and anatomical distribution to that previously seen in individuals with moderate musical training. We also found that musical genres that were less familiar to our participants (e.g., Balinese gamelan) produced strong responses within the music component, as did drum clips with rhythm but little melody, suggesting that these neural populations are broadly responsive to music as a whole. Our findings demonstrate that the signature properties of neural music selectivity do not require musical training to develop, demonstrating the music-selective neural populations are a fundamental and widespread property of the human brain.

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Dissociation of task engagement and arousal effects in auditory cortex and midbrain

eLife ◽

10.7554/elife.60153 ◽

2021 ◽

Vol 10 ◽

Author(s):

Daniela Saderi ◽

Zachary P Schwartz ◽

Charles R Heller ◽

Jacob R Pennington ◽

Stephen V David

Keyword(s):

Auditory Cortex ◽

Auditory Processing ◽

Generalized Linear Model ◽

Pupil Size ◽

Primary Auditory Cortex ◽

Task Engagement ◽

State Variables ◽

Neural Populations ◽

Evoked Activity ◽

Sensory Neural

Both generalized arousal and engagement in a specific task influence sensory neural processing. To isolate effects of these state variables in the auditory system, we recorded single-unit activity from primary auditory cortex (A1) and inferior colliculus (IC) of ferrets during a tone detection task, while monitoring arousal via changes in pupil size. We used a generalized linear model to assess the influence of task engagement and pupil size on sound-evoked activity. In both areas, these two variables affected independent neural populations. Pupil size effects were more prominent in IC, while pupil and task engagement effects were equally likely in A1. Task engagement was correlated with larger pupil; thus, some apparent effects of task engagement should in fact be attributed to fluctuations in pupil size. These results indicate a hierarchy of auditory processing, where generalized arousal enhances activity in midbrain, and effects specific to task engagement become more prominent in cortex.

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Spatial band-pass filtering aids decoding musical genres from auditory cortex 7T fMRI

F1000Research ◽

10.12688/f1000research.13689.1 ◽

2018 ◽

Vol 7 ◽

pp. 142 ◽

Cited By ~ 3

Author(s):

Ayan Sengupta ◽

Stefan Pollmann ◽

Michael Hanke

Keyword(s):

Auditory Cortex ◽

Brain Activity ◽

Activity Patterns ◽

Primary Auditory Cortex ◽

Sensory Stimulation ◽

Spatial Filtering ◽

Visual Orientation ◽

Fine Grained ◽

Musical Genres ◽

7T Fmri

Spatial filtering strategies, combined with multivariate decoding analysis of BOLD images, have been used to investigate the nature of the neural signal underlying the discriminability of brain activity patterns evoked by sensory stimulation -- primarily in the visual cortex. Reported evidence indicates that such signals are spatially broadband in nature, and are not primarily comprised of fine-grained activation patterns. However, it is unclear whether this is a general property of the BOLD signal, or whether it is specific to the details of employed analyses and stimuli. Here we performed an analysis of publicly available, high-resolution 7T fMRI on the response BOLD response to musical genres in primary auditory cortex that matches a previously conducted study on decoding visual orientation from V1. The results show that the pattern of decoding accuracies with respect to different types and levels of spatial filtering is comparable to that obtained from V1, despite considerable differences in the respective cortical circuitry.

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Dissociation of task engagement and arousal effects in auditory cortex and midbrain

10.1101/2020.06.16.155432 ◽

2020 ◽

Author(s):

Daniela Saderi ◽

Zachary P. Schwartz ◽

Charlie R. Heller ◽

Jacob R. Pennington ◽

Stephen V. David

Keyword(s):

Auditory Cortex ◽

Neural Activity ◽

Auditory Processing ◽

Neural Coding ◽

Primary Auditory Cortex ◽

Task Engagement ◽

State Variables ◽

Neural Populations ◽

Global Fluctuations ◽

Specific Control

AbstractThe brain’s representation of sound is influenced by multiple aspects of internal behavioral state. Following engagement in an auditory discrimination task, both generalized arousal and task-specific control signals can influence auditory processing. To isolate effects of these state variables on auditory processing, we recorded single-unit activity from primary auditory cortex (A1) and the inferior colliculus (IC) of ferrets as they engaged in a go/no-go tone detection task while simultaneously monitoring arousal via pupillometry. We used a generalized linear model to isolate the contributions of task engagement and arousal on spontaneous and evoked neural activity. Fluctuations in pupil-indexed arousal were correlated with task engagement, but these two variables could be dissociated in most experiments. In both A1 and IC, individual units could be modulated by task and/or arousal, but the two state variables affected independent neural populations. Arousal effects were more prominent in IC, while arousal and engagement effects occurred with about equal frequency in A1. These results indicate that some changes in neural activity attributed to task engagement in previous studies should in fact be attributed to global fluctuations in arousal. Arousal effects also explain some persistent changes in neural activity observed in passive conditions post-behavior. Together, these results indicate a hierarchy in the auditory system, where generalized arousal enhances activity in the midbrain and cortex, while task-specific changes in neural coding become more prominent in cortex.

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Spectral Resolution of Monkey Primary Auditory Cortex (A1) Revealed With Two-Noise Masking

Journal of Neurophysiology ◽

10.1152/jn.00124.2006 ◽

2006 ◽

Vol 96 (3) ◽

pp. 1105-1115 ◽

Cited By ~ 7

Author(s):

Yonatan I. Fishman ◽

Mitchell Steinschneider

Keyword(s):

Auditory Cortex ◽

Spectral Resolution ◽

Goodness Of Fit ◽

Auditory Evoked Potentials ◽

Current Source ◽

Primary Auditory Cortex ◽

Frequency Separation ◽

Frequency Resolution ◽

Noise Masking ◽

Neural Populations

An important function of the auditory nervous system is to analyze the frequency content of environmental sounds. The neural structures involved in determining psychophysical frequency resolution remain unclear. Using a two-noise masking paradigm, the present study investigates the spectral resolution of neural populations in primary auditory cortex (A1) of awake macaques and the degree to which it matches psychophysical frequency resolution. Neural ensemble responses (auditory evoked potentials, multiunit activity, and current source density) evoked by a pulsed 60-dB SPL pure-tone signal fixed at the best frequency (BF) of the recorded neural populations were examined as a function of the frequency separation (ΔF) between the tone and two symmetrically flanking continuous 80-dB SPL, 50-Hz-wide bands of noise. ΔFs ranged from 0 to 50% of the BF, encompassing the range typically examined in psychoacoustic experiments. Responses to the signal were minimal for ΔF = 0% and progressively increased with ΔF, reaching a maximum at ΔF = 50%. Rounded exponential functions, used to model auditory filter shapes in psychoacoustic studies of frequency resolution, provided excellent fits to neural masking functions. Goodness-of-fit was greatest for response components in lamina 4 and lower lamina 3 and least for components recorded in more superficial cortical laminae. Physiological equivalent rectangular bandwidths (ERBs) increased with BF, measuring nearly 15% of the BF. These findings parallel results of psychoacoustic studies in both monkeys and humans, and thus indicate that a representation of perceptual frequency resolution is available at the level of A1.

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Selective effects of arousal on population coding of natural sounds in auditory cortex

10.1101/2020.08.31.276584 ◽

2020 ◽

Author(s):

Charles R. Heller ◽

Zachary P. Schwartz ◽

Daniela Saderi ◽

Stephen V. David

Keyword(s):

Auditory Cortex ◽

Primary Auditory Cortex ◽

Population Coding ◽

Response Magnitude ◽

Correlated Noise ◽

Natural Sounds ◽

Dimensional Changes ◽

Neural Populations ◽

Evoked Activity ◽

Low Dimensional

AbstractThe ability to discriminate between complex natural sounds is critical for survival. Changes in arousal and other aspects of behavioral state can impact the accuracy of sensory coding, affecting both the reliability of single neuron responses and the degree of correlated noise between neurons. However, it is unclear how these effects interact to influence coding of diverse natural stimuli. We recorded the spiking activity of neural populations in primary auditory cortex (A1) evoked by a large library of natural sounds while monitoring changes in pupil size as an index of arousal. Heightened arousal increased response magnitude and reduced noise correlations between neurons, improving coding accuracy on average. Rather than suppressing shared noise along all dimensions of neural activity, the change in noise correlations occurred via coherent, low-dimensional modulation of response variability in A1. The modulation targeted a different group of neurons from those undergoing changes in response magnitude. Thus, changes in response magnitude and correlation are mediated by distinct mechanisms. The degree to which these low-dimensional changes were aligned with the high-dimensional natural sound-evoked activity was variable, resulting in stimulus-dependent improvements in coding accuracy.

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Music-selective cortex is sensitive to structure in both pitch and time

10.1101/2021.12.17.473232 ◽

2021 ◽

Author(s):

Dana L Boebinger ◽

Sam V Norman-Haignere ◽

Josh H McDermott ◽

Nancy G Kanwisher

Keyword(s):

Auditory Cortex ◽

Primary Auditory Cortex ◽

Acoustic Properties ◽

Musical Structure ◽

Synthetic Control ◽

Neural Responses ◽

Wide Range ◽

Neural Populations ◽

Cortical Regions ◽

High Level

Converging evidence suggests that neural populations within human non-primary auditory cortex respond selectively to music. These neural populations respond strongly to a wide range of music stimuli, and weakly to other natural sounds and to synthetic control stimuli matched to music in many acoustic properties, suggesting that they are driven by high-level musical features. What are these features? Here we used fMRI to test the extent to which musical structure in pitch and time contribute to music-selective neural responses. We used voxel decomposition to derive music-selective response components in each of 15 participants individually, and then measured the response of these components to synthetic music clips in which we selectively disrupted musical structure by scrambling either the note pitches and/or onset times. Both types of scrambling produced lower responses compared to when melodic or rhythmic structure was intact. This effect was much stronger in the music-selective component than in the other response components, even those with substantial spatial overlap with the music component. We further found no evidence for any cortical regions sensitive to pitch but not time structure, or vice versa. Our results suggest that the processing of melody and rhythm are intertwined within auditory cortex.

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Spatial band-pass filtering aids decoding musical genres from auditory cortex 7T fMRI

F1000Research ◽

10.12688/f1000research.13689.2 ◽

2018 ◽

Vol 7 ◽

pp. 142

Author(s):

Ayan Sengupta ◽

Stefan Pollmann ◽

Michael Hanke

Keyword(s):

Auditory Cortex ◽

Brain Activity ◽

Activity Patterns ◽

Primary Auditory Cortex ◽

Sensory Stimulation ◽

Spatial Filtering ◽

Visual Orientation ◽

Analysis Strategy ◽

Musical Genres ◽

7T Fmri

Spatial filtering strategies, combined with multivariate decoding analysis of BOLD images, have been used to investigate the nature of the neural signal underlying the discriminability of brain activity patterns evoked by sensory stimulation – primarily in the visual cortex. Previous research indicates that such signals are spatially broadband in nature, and are not primarily comprised of fine-grained activation patterns. However, it is unclear whether this is a general property of the BOLD signal, or whether it is specific to the details of employed analyses and stimuli. Here we applied an analysis strategy from a previous study on decoding visual orientation from V1 to publicly available, high-resolution 7T fMRI on the response BOLD response to musical genres in primary auditory cortex. The results show that the pattern of decoding accuracies with respect to different types and levels of spatial filtering is comparable to that obtained from V1, despite considerable differences in the respective cortical circuitry.

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