The sensation of groove engages motor and reward networks

Matthews, Tomas E.; Witek, Maria A. G.; Lund, Torben Ellegaard; Vuust, Peter; Penhune, Virginia B.

doi:10.1016/j.neuroimage.2020.116768

Cited by 98 publications

(139 citation statements)

References 90 publications

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“…One possibility is that the underlying neural circuits extract temporally local representations of melody and rhythm motifs that are assembled elsewhere into the representations of contour, key, meter, groove etc. that are the basis of music cognition (Janata et al, 2002;Brett and Grahn, 2007;Fedorenko et al, 2012;Matthews et al, 2020).…”

Section: What Does Cortical Music Selectivity Represent?mentioning

confidence: 99%

Music-selective neural populations arise without musical training

Boebinger

Norman-Haignere

McDermott

et al. 2021

Journal of Neurophysiology

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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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Section: What Does Cortical Music Selectivity Represent?mentioning

confidence: 99%

Music-selective neural populations arise without musical training

Boebinger

Norman-Haignere

McDermott

et al. 2021

Journal of Neurophysiology

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“…From the study of groove, we know that frontoparietal networks also play an important role in connecting music perception and movement (Matthews et al, 2020). While prefrontal activity is associated with the accuracy of predictions of sensory events (Bengtsson et al, 2009), parietal areas integrate sensory input from different sources to provide a framework of actually perceived feedback combinations.…”

Section: The Anatomy Of Motor Control: Retrieval and Adaptation Of Momentioning

confidence: 99%

Multimodal Sensory-Spatial Integration and Retrieval of Trained Motor Patterns for Body Coordination in Musicians and Dancers

2020

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Dancers and musicians are experts in spatial and temporal processing, which allows them to coordinate movement with music. This high-level processing has been associated with structural and functional adaptation of the brain for high performance sensorimotor integration. For these integration processes, adaptation does not only take place in primary and secondary sensory and motor areas but also in tertiary brain areas, such as the lateral prefrontal cortex (lPFC) and the intraparietal sulcus (IPS), providing vital resources for highly specialized performance. Here, we review evidence for the role of these brain areas in multimodal training protocols and integrate these findings into a new model of sensorimotor processing in complex motor learning.

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“…Cross-cultural perceptual priors may exist for some aspects of rhythm perception and production ( Jacoby and McDermott, 2017 ), while other aspects are shaped by encluturation within a certain musical niche ( Cameron et al, 2015 ; van der Weij et al, 2017 ; Polak et al, 2018 ). In particular, the experience of musical groove, that property of ‘wanting to move’ to the music, is proposed to be related to the balance between prediction and prediction errors generated by rhythmic properties of the music ( Janata et al, 2012 ; Matthews et al, 2019 , 2020 ). Active Inference formulations account for not only predictions related to expected stimulus input, but also predictions related to the expected accuracy–the precision , or uncertainty–of the original sensory prediction, in addition to counterfactual predictions related to how these prediction errors and their precision would change in response to active motor engagement with the sensory stimulus.…”

Section: Introductionmentioning

confidence: 99%

Motor and Predictive Processes in Auditory Beat and Rhythm Perception

Proksch

Comstock

Médé

et al. 2020

Front. Hum. Neurosci.

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In this article, we review recent advances in research on rhythm and musical beat perception, focusing on the role of predictive processes in auditory motor interactions. We suggest that experimental evidence of the motor system's role in beat perception, including in passive listening, may be explained by the generation and maintenance of internal predictive models, concordant with the Active Inference framework of sensory processing. We highlight two complementary hypotheses for the neural underpinnings of rhythm perception: The Action Simulation for Auditory Prediction hypothesis (Patel and Iversen, 2014) and the Gradual Audiomotor Evolution hypothesis (Merchant and Honing, 2014) and review recent experimental progress supporting each of these hypotheses. While initial formulations of ASAP and GAE explain different aspects of beat-based timing-the involvement of motor structures in the absence of movement, and physical entrainment to an auditory beat respectively-we suggest that work under both hypotheses provide converging evidence toward understanding the predictive role of the motor system in the perception of rhythm, and the specific neural mechanisms involved. We discuss future experimental work necessary to further evaluate the causal neural mechanisms underlying beat and rhythm perception.

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The sensation of groove engages motor and reward networks

Cited by 98 publications

References 90 publications

Music-selective neural populations arise without musical training

Music-selective neural populations arise without musical training

Multimodal Sensory-Spatial Integration and Retrieval of Trained Motor Patterns for Body Coordination in Musicians and Dancers

Motor and Predictive Processes in Auditory Beat and Rhythm Perception

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