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Marin MM, Gingras B. How music-induced emotions affect sexual attraction: evolutionary implications. Front Psychol 2024; 15:1269820. [PMID: 38659690 PMCID: PMC11039867 DOI: 10.3389/fpsyg.2024.1269820] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Accepted: 03/29/2024] [Indexed: 04/26/2024] Open
Abstract
More than a century ago, Darwin proposed a putative role for music in sexual attraction (i.e., sex appeal), a hypothesis that has recently gained traction in the field of music psychology. In his writings, Darwin particularly emphasized the charming aspects of music. Across a broad range of cultures, music has a profound impact on humans' feelings, thoughts and behavior. Human mate choice is determined by the interplay of several factors. A number of studies have shown that music and musicality (i.e., the ability to produce and enjoy music) exert a positive influence on the evaluation of potential sexual partners. Here, we critically review the latest empirical literature on how and why music and musicality affect sexual attraction by considering the role of music-induced emotion and arousal in listeners as well as other socio-biological mechanisms. Following a short overview of current theories about the origins of musicality, we present studies that examine the impact of music and musicality on sexual attraction in different social settings. We differentiate between emotion-based influences related to the subjective experience of music as sound and effects associated with perceived musical ability or creativity in a potential partner. By integrating studies using various behavioral methods, we link current research strands that investigate how music influences sexual attraction and suggest promising avenues for future research.
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Affiliation(s)
- Manuela M. Marin
- Department of Cognition, Emotion and Methods in Psychology, University of Vienna, Vienna, Austria
- Austrian Research Institute of Empirical Aesthetics, Innsbruck, Austria
| | - Bruno Gingras
- Austrian Research Institute of Empirical Aesthetics, Innsbruck, Austria
- Department of Cognitive Biology, Faculty of Life Sciences, University of Vienna, Vienna, Austria
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Wu S, Peng H, Deng H, Guo Z, Jiang Z, Mu Q. Insomnia disorder characterized by probabilistic metastable substates using blood-oxygenation-level-dependent (BOLD) phase signals. Sleep Breath 2024:10.1007/s11325-024-03018-z. [PMID: 38451462 DOI: 10.1007/s11325-024-03018-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 02/12/2024] [Accepted: 03/01/2024] [Indexed: 03/08/2024]
Abstract
PURPOSE From a clinical point of view, how to force a transition from insomnia brain state to healthy brain state by external driven stimulation is of great interest. This needs to define brain state of insomnia disorder as metastable substates. The current study was to identify recurrent substates of insomnia disorder in terms of probability of occurrence, lifetime, and alternation profiles by using leading eigenvector dynamics analysis (LEiDA) method. METHODS We enrolled 32 patients with insomnia disorder and 30 healthy subjects. We firstly obtained the BOLD phase coherence matrix from Hilbert transform of BOLD signals and then extracted all the leading eigenvectors from the BOLD phase coherence matrix for all subjects across all time points. Lastly, we clustered the leading eigenvectors using a k-means clustering algorithm to find the probabilistic metastable substates (PMS) and calculate the probability of occurrence and associated lifetime for substates. RESULTS The resulting 3 clusters were optimal for brain state of insomnia disorder and healthy brain state, respectively. The occurred probabilities of the PMS were significantly different between the patients with insomnia disorder and healthy subjects, with 0.51 versus 0.44 for PMS-1 (p < 0.001), 0.25 versus 0.27 for PMS-2 (p = 0.051), and 0.24 versus 0.29 for PMS-3 (p < 0.001), as well as the lifetime (in TR) of 36.65 versus 33.15 for PMS-1 (p = 0.068), 14.36 versus 15.43 for PMS-2 (p = 0.117), and 14.80 versus 16.34 for PMS-3 (p = 0.042). The values of the diagonal of the transition matrix were much higher than the probabilities of switching states, indicating the metastable nature of substates. CONCLUSION The resulted probabilistic metastable substates hint the characteristic brain dynamics of insomnia disorder. The results may lay a foundation to help determine how to force a transition from insomnia brain state to healthy brain state by external driven stimulation.
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Affiliation(s)
- Suzhou Wu
- Department of Radiology, Yilong Country Hospital of Traditional Chinese Medicine, Nanchong, 637000, Sichuan, China
| | - Huaiping Peng
- Department of Radiology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Institute of Brain Function, Nanchong, 637000, Sichuan, China
| | - Haobing Deng
- Department of Radiology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Institute of Brain Function, Nanchong, 637000, Sichuan, China
| | - Zhiwei Guo
- Department of Radiology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Institute of Brain Function, Nanchong, 637000, Sichuan, China
| | - Zhijun Jiang
- Department of Radiology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Institute of Brain Function, Nanchong, 637000, Sichuan, China
| | - Qiwen Mu
- Department of Radiology, Nanchong Central Hospital, The Second Clinical Medical College, North Sichuan Medical College, Institute of Brain Function, Nanchong, 637000, Sichuan, China.
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van der Horn HJ, Ling JM, Wick TV, Dodd AB, Robertson-Benta CR, McQuaid JR, Zotev V, Vakhtin AA, Ryman SG, Cabral J, Phillips JP, Campbell RA, Sapien RE, Mayer AR. Dynamic Functional Connectivity in Pediatric Mild Traumatic Brain Injury. Neuroimage 2024; 285:120470. [PMID: 38016527 PMCID: PMC10815936 DOI: 10.1016/j.neuroimage.2023.120470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 11/13/2023] [Accepted: 11/20/2023] [Indexed: 11/30/2023] Open
Abstract
Resting-state fMRI can be used to identify recurrent oscillatory patterns of functional connectivity within the human brain, also known as dynamic brain states. Alterations in dynamic brain states are highly likely to occur following pediatric mild traumatic brain injury (pmTBI) due to the active developmental changes. The current study used resting-state fMRI to investigate dynamic brain states in 200 patients with pmTBI (ages 8-18 years, median = 14 years) at the subacute (∼1-week post-injury) and early chronic (∼ 4 months post-injury) stages, and in 179 age- and sex-matched healthy controls (HC). A k-means clustering analysis was applied to the dominant time-varying phase coherence patterns to obtain dynamic brain states. In addition, correlations between brain signals were computed as measures of static functional connectivity. Dynamic connectivity analyses showed that patients with pmTBI spend less time in a frontotemporal default mode/limbic brain state, with no evidence of change as a function of recovery post-injury. Consistent with models showing traumatic strain convergence in deep grey matter and midline regions, static interhemispheric connectivity was affected between the left and right precuneus and thalamus, and between the right supplementary motor area and contralateral cerebellum. Changes in static or dynamic connectivity were not related to symptom burden or injury severity measures, such as loss of consciousness and post-traumatic amnesia. In aggregate, our study shows that brain dynamics are altered up to 4 months after pmTBI, in brain areas that are known to be vulnerable to TBI. Future longitudinal studies are warranted to examine the significance of our findings in terms of long-term neurodevelopment.
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Affiliation(s)
| | - Josef M Ling
- The Mind Research Network/LBERI, Albuquerque, NM 87106
| | - Tracey V Wick
- The Mind Research Network/LBERI, Albuquerque, NM 87106
| | - Andrew B Dodd
- The Mind Research Network/LBERI, Albuquerque, NM 87106
| | | | | | - Vadim Zotev
- The Mind Research Network/LBERI, Albuquerque, NM 87106
| | | | | | - Joana Cabral
- Life and Health Sciences Research Institute, University of Minho, Braga, Portugal
| | | | - Richard A Campbell
- Department of Psychiatry & Behavioral Sciences, University of New Mexico, Albuquerque, NM 87131
| | - Robert E Sapien
- Department of Emergency Medicine, University of New Mexico, Albuquerque, NM 87131
| | - Andrew R Mayer
- The Mind Research Network/LBERI, Albuquerque, NM 87106; Department of Psychiatry & Behavioral Sciences, University of New Mexico, Albuquerque, NM 87131; Department of Psychology, University of New Mexico, Albuquerque, NM 87131; Department of Neurology, University of New Mexico, Albuquerque, NM 87131
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Tuulari JJ, Rajasilta O, Cabral J, Kringelbach ML, Karlsson L, Karlsson H. Maternal prenatal distress exposure negatively associates with the stability of neonatal frontoparietal network. Stress 2024; 27:2275207. [PMID: 37877207 DOI: 10.1080/10253890.2023.2275207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 09/28/2023] [Indexed: 10/26/2023] Open
Abstract
Maternal prenatal distress (PD), frequently defined as in utero prenatal stress exposure (PSE) to the developing fetus, influences the developing brain and numerous associations between PSE and brain structure have been described both in neonates and in older children. Previous studies addressing PSE-linked alterations in neonates' brain activity have focused on connectivity analyses from predefined seed regions, but the effects of PSE at the level of distributed functional networks remains unclear. In this study, we investigated the impact of prenatal distress on the spatial and temporal properties of functional networks detected in functional MRI data from 20 naturally sleeping, term-born (age 25.85 ± 7.72 days, 11 males), healthy neonates. First, we performed group level independent component analysis (GICA) to evaluate an association between PD and the identified functional networks. Second, we searched for an association with PD at the level of the stability of functional networks over time using leading eigenvector dynamics analysis (LEiDA). No statistically significant associations were detected at the spatial level for the GICA-derived networks. However, at the dynamic level, LEiDA revealed that maternal PD negatively associated with the stability of a frontoparietal network. These results imply that maternal PD may influence the stability of frontoparietal connections in neonatal brain network dynamics and adds to the cumulating evidence that frontal areas are especially sensitive to PSE. We advocate for early preventive intervention strategies regarding pregnant mothers. Nevertheless, future research venues are required to assess optimal intervention timing and methods for maximum benefit.
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Affiliation(s)
- Jetro J Tuulari
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Clinical Medicine, Psychiatry, University of Turku and Turku University Hospital, Turku, Finland
- Turku Collegium for Science, Medicine and Technology (TCSMT), University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku Finland
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Olli Rajasilta
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Neurocenter, Turku University Hospital, Turku, Finland
| | - Joana Cabral
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B's-PT Government Associate Laboratory, Braga/Guimarães, Portugal
| | - Morten L Kringelbach
- Department of Psychiatry, University of Oxford, Oxford, UK
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK
- Centre for Music in the Brain, Aarhus University, Aarhus, Denmark
| | - Linnea Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku Finland
- Department of Clinical Medicine, Paediatrics and Adolescent Medicine, University of Turku and Turku University Hospital, Turku, Finland
| | - Hasse Karlsson
- FinnBrain Birth Cohort Study, Turku Brain and Mind Center, Department of Clinical Medicine, University of Turku, Turku, Finland
- Department of Clinical Medicine, Psychiatry, University of Turku and Turku University Hospital, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku Finland
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Faber SEM, Belden AG, Loui P, McIntosh R. Age-related variability in network engagement during music listening. Netw Neurosci 2023; 7:1404-1419. [PMID: 38144689 PMCID: PMC10713012 DOI: 10.1162/netn_a_00333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 07/31/2023] [Indexed: 12/26/2023] Open
Abstract
Listening to music is an enjoyable behaviour that engages multiple networks of brain regions. As such, the act of music listening may offer a way to interrogate network activity, and to examine the reconfigurations of brain networks that have been observed in healthy aging. The present study is an exploratory examination of brain network dynamics during music listening in healthy older and younger adults. Network measures were extracted and analyzed together with behavioural data using a combination of hidden Markov modelling and partial least squares. We found age- and preference-related differences in fMRI data collected during music listening in healthy younger and older adults. Both age groups showed higher occupancy (the proportion of time a network was active) in a temporal-mesolimbic network while listening to self-selected music. Activity in this network was strongly positively correlated with liking and familiarity ratings in younger adults, but less so in older adults. Additionally, older adults showed a higher degree of correlation between liking and familiarity ratings consistent with past behavioural work on age-related dedifferentiation. We conclude that, while older adults do show network and behaviour patterns consistent with dedifferentiation, activity in the temporal-mesolimbic network is relatively robust to dedifferentiation. These findings may help explain how music listening remains meaningful and rewarding in old age.
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Affiliation(s)
- Sarah E. M. Faber
- University of Toronto, Toronto, ON, Canada
- Simon Fraser University, Burnaby, BC, Canada
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Fan L, Li Y, Huang ZG, Zhang W, Wu X, Liu T, Wang J. Low-frequency repetitive transcranial magnetic stimulation alters the individual functional dynamical landscape. Cereb Cortex 2023; 33:9583-9598. [PMID: 37376783 DOI: 10.1093/cercor/bhad228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 06/05/2023] [Accepted: 06/06/2023] [Indexed: 06/29/2023] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive approach to modulate brain activity and behavior in humans. Still, how individual resting-state brain dynamics after rTMS evolves across different functional configurations is rarely studied. Here, using resting state fMRI data from healthy subjects, we aimed to examine the effects of rTMS to individual large-scale brain dynamics. Using Topological Data Analysis based Mapper approach, we construct the precise dynamic mapping (PDM) for each participant. To reveal the relationship between PDM and canonical functional representation of the resting brain, we annotated the graph using relative activation proportion of a set of large-scale resting-state networks (RSNs) and assigned the single brain volume to corresponding RSN-dominant or a hub state (not any RSN was dominant). Our results show that (i) low-frequency rTMS could induce changed temporal evolution of brain states; (ii) rTMS didn't alter the hub-periphery configurations underlined resting-state brain dynamics; and (iii) the rTMS effects on brain dynamics differ across the left frontal and occipital lobe. In conclusion, low-frequency rTMS significantly alters the individual temporo-spatial dynamics, and our finding further suggested a potential target-dependent alteration of brain dynamics. This work provides a new perspective to comprehend the heterogeneous effect of rTMS.
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Affiliation(s)
- Liming Fan
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Youjun Li
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Zi-Gang Huang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Wenlong Zhang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Xiaofeng Wu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Tian Liu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
| | - Jue Wang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, Institute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
- National Engineering Research Center of Health Care and Medical Devices, Guangzhou, Guangdong 510500, China
- The Key Laboratory of Neuro-Informatics & Rehabilitation Engineering of Ministry of Civil Affairs, Xi'an, Shaanxi 710049, China
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7
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Eraifej J, Cabral J, Fernandes HM, Kahan J, He S, Mancini L, Thornton J, White M, Yousry T, Zrinzo L, Akram H, Limousin P, Foltynie T, Aziz TZ, Deco G, Kringelbach M, Green AL. Modulation of limbic resting-state networks by subthalamic nucleus deep brain stimulation. Netw Neurosci 2023; 7:478-495. [PMID: 37397890 PMCID: PMC10312264 DOI: 10.1162/netn_a_00297] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 11/29/2022] [Indexed: 09/03/2023] Open
Abstract
Beyond the established effects of subthalamic nucleus deep brain stimulation (STN-DBS) in reducing motor symptoms in Parkinson's disease, recent evidence has highlighted the effect on non-motor symptoms. However, the impact of STN-DBS on disseminated networks remains unclear. This study aimed to perform a quantitative evaluation of network-specific modulation induced by STN-DBS using Leading Eigenvector Dynamics Analysis (LEiDA). We calculated the occupancy of resting-state networks (RSNs) in functional MRI data from 10 patients with Parkinson's disease implanted with STN-DBS and statistically compared between ON and OFF conditions. STN-DBS was found to specifically modulate the occupancy of networks overlapping with limbic RSNs. STN-DBS significantly increased the occupancy of an orbitofrontal limbic subsystem with respect to both DBS OFF (p = 0.0057) and 49 age-matched healthy controls (p = 0.0033). Occupancy of a diffuse limbic RSN was increased with STN-DBS OFF when compared with healthy controls (p = 0.021), but not when STN-DBS was ON, which indicates rebalancing of this network. These results highlight the modulatory effect of STN-DBS on components of the limbic system, particularly within the orbitofrontal cortex, a structure associated with reward processing. These results reinforce the value of quantitative biomarkers of RSN activity in evaluating the disseminated impact of brain stimulation techniques and the personalization of therapeutic strategies.
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Affiliation(s)
- John Eraifej
- Oxford Functional Neurosurgery Group, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Joana Cabral
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Henrique M. Fernandes
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Joshua Kahan
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Shenghong He
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Laura Mancini
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - John Thornton
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - Mark White
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - Tarek Yousry
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - Ludvic Zrinzo
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Harith Akram
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Patricia Limousin
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Tom Foltynie
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Tipu Z. Aziz
- Oxford Functional Neurosurgery Group, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats, Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Morten Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Alexander L. Green
- Oxford Functional Neurosurgery Group, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
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