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The pleasurable urge to move to music (PLUMM) activates motor and reward areas of the brain and is thought to be driven by predictive processes. Dopamine in motor and limbic networks is implicated in beat-based timing and music-induced pleasure, suggesting a central role of basal ganglia (BG) dopaminergic systems in PLUMM. This study tested this hypothesis by comparing PLUMM in participants with Parkinson's disease (PD), age-matched controls, and young controls. Participants listened to musical sequences with varying rhythmic and harmonic complexity (low, medium and high), and rated their experienced pleasure and urge to move to the rhythm. In line with previous results, healthy younger participants showed an inverted U-shaped relationship between rhythmic complexity and ratings, with preference for medium complexity rhythms, while age-matched controls showed a similar, but weaker, inverted U-shaped response. Conversely, PD showed a significantly flattened response for both the urge to move and pleasure. Crucially, this flattened response could not be attributed to differences in rhythm discrimination and did not reflect an overall decrease in ratings. For harmonic complexity, PD showed a negative linear pattern for both the urge to move and pleasure while healthy age-matched controls showed the same pattern for pleasure and an inverted U for the urge to move. This contrasts with the pattern observed in young healthy controls in previous studies, suggesting that both healthy aging and PD also influence affective responses to harmonic complexity. Together, these results support the role of dopamine within cortico-striatal circuits in the predictive processes that form the link between the perceptual processing of rhythmic patterns and the affective and motor responses to rhythmic music., (© 2023 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Background: Insomnia is a common problem in modern society. It is associated with reduced quality of life and impairments in physical and mental health. Listening to music is widely used as a sleep aid, but it remains unclear if it can actually improve insomnia in adults. This Cochrane Review is an update of a review published in 2015., Objectives: To assess the effects of listening to music on sleep in adults with insomnia and to assess the influence of specific variables that may moderate the effect., Search Methods: For this update, we searched CENTRAL, MEDLINE, Embase, nine other databases and two trials registers up to December 2021. In addition, we handsearched reference lists of included studies, and contacted authors of published studies to identify additional studies eligible for inclusion, including any unpublished or ongoing trials., Selection Criteria: Randomised controlled trials comparing the effects of listening to music with no treatment or treatment as usual (TAU) in adults complaining of sleep difficulties., Data Collection and Analysis: Two review authors independently screened records for eligibility, selected studies for inclusion, extracted data and assessed risk of bias of the included studies. We assessed the certainty of the evidence using GRADE. The primary outcomes were sleep quality, insomnia severity, sleep-onset latency, total sleep time, sleep interruption, sleep efficiency and adverse events. Data on the predefined outcome measures were included in meta-analyses when consistently reported by at least two studies that were homogeneous in terms of participants, interventions and outcomes. We undertook meta-analyses using random-effects models., Main Results: We included 13 studies (eight studies new to this update) comprising 1007 participants. The studies examined the effect of listening to prerecorded music daily, for 25 to 60 minutes, for a period of three days to three months. The risk of bias within the studies varied, with all studies being at high risk of performance bias, because of limited possibilities to blind participants to the music intervention. Some studies were at high risk of detection bias or other bias. Four studies reported funding from national research councils, three studies reported financial support from university sources and one study reported a grant from a private foundation. Five studies did not report any financial support. At the end of the intervention, we found moderate-certainty evidence for improved sleep quality measured with the Pittsburgh Sleep Quality Index (PSQI) in themusic groups compared to no intervention or TAU (mean difference (MD) -2.79, 95% confidence interval (CI) -3.86 to -1.72; 10 studies, 708 participants). The PSQI scale ranges from 0 to 21 with higher scores indicating poorer sleep. The size of the effect indicates an increase in sleep quality of the size of about one standard deviation in favour of the intervention. We found no clear evidence of a difference in the effects of listening to music compared to no treatment or TAU on insomnia severity (MD -6.96, 95% CI -15.21 to 1.28; 2 studies, 63 participants; very low-certainty evidence). We found low-certainty evidence that, compared to no treatment or TAU, listening to music may reduce problems with sleep-onset latency (MD -0.60, 95% CI -0.83 to -0.37; 3 studies, 197 participants), total sleep time (MD -0.69, 95% CI -1.16 to -0.23; 3 studies, 197 participants) and sleep efficiency (MD -0.96, 95% CI -1.38 to -0.54; 3 studies, 197 participants), but may have no effect on perceived sleep interruption (MD -0.53, 95% CI -1.47 to 0.40; 3 studies, 197 participants). In addition, three studies (136 participants) included objective measures of sleep-onset latency, total sleep time, sleep efficiency and sleep interruption and showed that listening to music may not improve these outcomes compared to no treatment or TAU. None of the included studies reported any adverse events., Authors' Conclusions: The findings of this review provide evidence that music may be effective for improving subjective sleep quality in adults with symptoms of insomnia. More research is needed to establish the effect of listening to music on other aspects of sleep as well as the daytime consequences of insomnia., (Copyright © 2022 The Cochrane Collaboration. Published by John Wiley & Sons, Ltd.)

Groove-defined as the pleasurable urge to move to a rhythm-depends on a fine-tuned interplay between predictability arising from repetitive rhythmic patterns, and surprise arising from rhythmic deviations, for example in the form of syncopation. The perfect balance between predictability and surprise is commonly found in rhythmic patterns with a moderate level of rhythmic complexity and represents the sweet spot of the groove experience. In contrast, rhythms with low or high complexity are usually associated with a weaker experience of groove because they are too boring to be engaging or too complex to be interpreted, respectively. Consequently, the relationship between rhythmic complexity and groove experience can be described by an inverted U-shaped function. We interpret this inverted U shape in light of the theory of predictive processing and provide perspectives on how rhythmic complexity and groove can help us to understand the underlying neural mechanisms linking temporal predictions, movement, and reward. A better understanding of these mechanisms can guide future approaches to improve treatments for patients with motor impairments, such as Parkinson's disease, and to investigate prosocial aspects of interpersonal interactions that feature music, such as dancing. Finally, we present some open questions and ideas for future research., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Stupacher, Matthews, Pando-Naude, Foster Vander Elst and Vuust.)

Through long-term training, music experts acquire complex and specialized sensorimotor skills, which are paralleled by continuous neuro-anatomical and -functional adaptations. The underlying neuroplasticity mechanisms have been extensively explored in decades of research in music, cognitive, and translational neuroscience. However, the absence of a comprehensive review and quantitative meta-analysis prevents the plethora of variegated findings to ultimately converge into a unified picture of the neuroanatomy of musical expertise. Here, we performed a comprehensive neuroimaging meta-analysis of publications investigating neuro-anatomical and -functional differences between musicians (M) and non-musicians (NM). Eighty-four studies were included in the qualitative synthesis. From these, 58 publications were included in coordinate-based meta-analyses using the anatomic/activation likelihood estimation (ALE) method. This comprehensive approach delivers a coherent cortico-subcortical network encompassing sensorimotor and limbic regions bilaterally. Particularly, M exhibited higher volume/activity in auditory, sensorimotor, interoceptive, and limbic brain areas and lower volume/activity in parietal areas as opposed to NM. Notably, we reveal topographical (dis-)similarities between the identified functional and anatomical networks and characterize their link to various cognitive functions by means of meta-analytic connectivity modelling. Overall, we effectively synthesized decades of research in the field and provide a consistent and controversies-free picture of the neuroanatomy of musical expertise., (© 2022. The Author(s).)

A remarkable feature of the human brain is its ability to integrate information from the environment with internally generated content. The integration of top-down and bottom-up processes during complex multi-modal human activities, however, is yet to be fully understood. Music provides an excellent model for understanding this since music listening leads to the urge to move, and music making entails both playing and listening at the same time (i.e., audio-motor coupling). Here, we conducted activation likelihood estimation (ALE) meta-analyses of 130 neuroimaging studies of music perception, production and imagery, with 2660 foci, 139 experiments, and 2516 participants. We found that music perception and production rely on auditory cortices and sensorimotor cortices, while music imagery recruits distinct parietal regions. This indicates that the brain requires different structures to process similar information which is made available either by an interaction with the environment (i.e., bottom-up) or by internally generated content (i.e., top-down)., (© 2021. The Author(s).)

Substance use disorders (SUDs) are characterized by a compulsion to seek and consume one or more substances of abuse, with a perceived loss of control and a negative emotional state. Prolonged substance use seems to be associated with morphological changes of multiple neural circuits, in particular the frontal-striatal and limbic pathways. Such neuroadaptations are evident across several substance disorders, but may vary depending on the type of substance, consumption severity and/or other unknown factors. We therefore identified studies investigating the effects of SUDs using volumetric whole-brain voxel-based morphometry (VBM) in gray (GM) and white matter (WM). We performed a systematic review and meta-analysis of VBM studies using the anatomic likelihood estimation (ALE) method implemented in GingerALE (PROSPERO pre-registration CRD42017071222 ). Sixty studies met inclusion criteria and were included in the final quantitative meta-analysis, with a total of 614 foci, 94 experiments and 4938 participants. We found convergence and divergence in brain regions and volume effects (higher vs. lower volume) in GM and WM depending on the severity of the consumption pattern and type of substance used. Convergent pathology was evident across substances in GM of the insula, anterior cingulate cortex, putamen, and thalamus, and in WM of the thalamic radiation and internal capsule bundle. Divergent pathology between occasional use (cortical pathology) and addiction (cortical-subcortical pathology) provides evidence of a possible top-down neuroadaptation. Our findings indicate particular brain morphometry alterations in SUDs, which may inform our understanding of disease progression and ultimately therapeutic approaches.

Listening to self-chosen, pleasant and relaxing music reduces pain in fibromyalgia (FM), a chronic centralized pain condition. However, the neural correlates of this effect are fairly unknown. In our study, we wished to investigate the neural correlates of music-induced analgesia (MIA) in FM patients. To do this, we studied 20 FM patients and 20 matched healthy controls (HC) acquiring rs-fMRI with a 3T MRI scanner, and pain data before and after two 5-min auditory conditions: music and noise. We performed resting state functional connectivity (rs-FC) seed-based correlation analyses (SCA) using pain and analgesia-related ROIs to determine the effects before and after the music intervention in FM and HC, and its correlation with pain reports. We found significant differences in baseline rs-FC between FM and HC. Both groups showed changes in rs-FC after the music condition. FM patients reported MIA that was significantly correlated with rs-FC decrease between the angular gyrus, posterior cingulate cortex and precuneus, and rs-FC increase between amygdala and middle frontal gyrus. These areas are related to autobiographical and limbic processes, and auditory attention, suggesting MIA may arise as a consequence of top-down modulation, probably originated by distraction, relaxation, positive emotion, or a combination of these mechanisms.