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Rosso M, Fernández‐Rubio G, Keller PE, Brattico E, Vuust P, Kringelbach ML, Bonetti L. FREQ-NESS Reveals the Dynamic Reconfiguration of Frequency-Resolved Brain Networks During Auditory Stimulation. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2025; 12:e2413195. [PMID: 40211612 PMCID: PMC12120751 DOI: 10.1002/advs.202413195] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/18/2024] [Revised: 01/31/2025] [Indexed: 06/01/2025]
Abstract
The brain is a dynamic system whose network organization is often studied by focusing on specific frequency bands or anatomical regions, leading to fragmented insights, or by employing complex and elaborate methods that hinder straightforward interpretations. To address this issue, a new analytical pipeline named FREQuency-resolved Network Estimation via Source Separation (FREQ-NESS) is introduced. This pipeline is designed to estimate the activation and spatial configuration of simultaneous brain networks across frequencies by analyzing the frequency-resolved multivariate covariance between whole-brain voxel time series. In this study, FREQ-NESS is applied to source-reconstructed magnetoencephalography (MEG) data during resting state and isochronous auditory stimulation. Our results reveal simultaneous, frequency-specific brain networks during resting state, such as the default mode, alpha-band, and motor-beta networks. During auditory stimulation, FREQ-NESS detects: 1) emergence of networks attuned to the stimulation frequency, 2) spatial reorganization of existing networks, such as alpha-band networks shifting from occipital to sensorimotor areas, 3) stability of networks unaffected by auditory stimuli. Furthermore, auditory stimulation significantly enhances cross-frequency coupling, with the phase of auditory networks attuned to the stimulation modulating gamma band amplitude in medial temporal lobe networks. In conclusion, FREQ-NESS effectively maps the brain's spatiotemporal dynamics, providing a comprehensive view of brain function by revealing a landscape of simultaneous, frequency-resolved networks and their interaction.
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Affiliation(s)
- Mattia Rosso
- Center for Music in the BrainDepartment of Clinical MedicineAarhus University & The Royal Academy of MusicAarhus/AalborgAarhus8000Denmark
- IPEM Institute for Systematic MusicologyGhent UniversityGhent9000Belgium
| | - Gemma Fernández‐Rubio
- Center for Music in the BrainDepartment of Clinical MedicineAarhus University & The Royal Academy of MusicAarhus/AalborgAarhus8000Denmark
| | - Peter Erik Keller
- Center for Music in the BrainDepartment of Clinical MedicineAarhus University & The Royal Academy of MusicAarhus/AalborgAarhus8000Denmark
- MARCS Institute for Brain, Behaviour and DevelopmentWestern Sydney UniversitySydney2751Australia
| | - Elvira Brattico
- Center for Music in the BrainDepartment of Clinical MedicineAarhus University & The Royal Academy of MusicAarhus/AalborgAarhus8000Denmark
- Department of Education, Psychology, CommunicationUniversity of Bari Aldo MoroBari70121Italy
| | - Peter Vuust
- Center for Music in the BrainDepartment of Clinical MedicineAarhus University & The Royal Academy of MusicAarhus/AalborgAarhus8000Denmark
| | - Morten L Kringelbach
- Center for Music in the BrainDepartment of Clinical MedicineAarhus University & The Royal Academy of MusicAarhus/AalborgAarhus8000Denmark
- Centre for Eudaimonia and Human FlourishingLinacre CollegeUniversity of OxfordOxfordOX39BXUnited Kingdom
- Department of PsychiatryUniversity of OxfordOxfordOX37JXUnited Kingdom
| | - Leonardo Bonetti
- Center for Music in the BrainDepartment of Clinical MedicineAarhus University & The Royal Academy of MusicAarhus/AalborgAarhus8000Denmark
- Centre for Eudaimonia and Human FlourishingLinacre CollegeUniversity of OxfordOxfordOX39BXUnited Kingdom
- Department of PsychiatryUniversity of OxfordOxfordOX37JXUnited Kingdom
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Nartallo-Kaluarachchi R, Bonetti L, Fernández-Rubio G, Vuust P, Deco G, Kringelbach ML, Lambiotte R, Goriely A. Multilevel irreversibility reveals higher-order organization of nonequilibrium interactions in human brain dynamics. Proc Natl Acad Sci U S A 2025; 122:e2408791122. [PMID: 40053364 PMCID: PMC11912438 DOI: 10.1073/pnas.2408791122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Accepted: 01/28/2025] [Indexed: 03/19/2025] Open
Abstract
Information processing in the human brain can be modeled as a complex dynamical system operating out of equilibrium with multiple regions interacting nonlinearly. Yet, despite extensive study of the global level of nonequilibrium in the brain, quantifying the irreversibility of interactions among brain regions at multiple levels remains an unresolved challenge. Here, we present the Directed Multiplex Visibility Graph Irreversibility framework, a method for analyzing neural recordings using network analysis of time-series. Our approach constructs directed multilayer graphs from multivariate time-series where information about irreversibility can be decoded from the marginal degree distributions across the layers, which each represents a variable. This framework is able to quantify the irreversibility of every interaction in the complex system. Applying the method to magnetoencephalography recordings during a long-term memory recognition task, we quantify the multivariate irreversibility of interactions between brain regions and identify the combinations of regions which showed higher levels of nonequilibrium in their interactions. For individual regions, we find higher irreversibility in cognitive versus sensorial brain regions while for pairs, strong relationships are uncovered between cognitive and sensorial pairs in the same hemisphere. For triplets and quadruplets, the most nonequilibrium interactions are between cognitive-sensorial pairs alongside medial regions. Combining these results, we show that multilevel irreversibility offers unique insights into the higher-order, hierarchical organization of neural dynamics from the perspective of brain network dynamics.
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Affiliation(s)
- Ramón Nartallo-Kaluarachchi
- Mathematical Institute, University of Oxford, OxfordOX2 6GG, United Kingdom
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, OxfordOX3 9BX, United Kingdom
- The Alan Turing Institute, LondonNW1 2DB, United Kingdom
| | - Leonardo Bonetti
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, OxfordOX3 9BX, United Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus8000, Denmark
- Department of Psychiatry, University of Oxford, OxfordOX3 7JX, United Kingdom
| | - Gemma Fernández-Rubio
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus8000, Denmark
| | - Peter Vuust
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus8000, Denmark
| | - Gustavo Deco
- Centre for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona08018, Spain
- Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona08018, Spain
- Institució Catalana de la Recerca i Estudis Avancats, Barcelona08010, Spain
| | - Morten L. Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, OxfordOX3 9BX, United Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus8000, Denmark
- Department of Psychiatry, University of Oxford, OxfordOX3 7JX, United Kingdom
| | - Renaud Lambiotte
- Mathematical Institute, University of Oxford, OxfordOX2 6GG, United Kingdom
- The Alan Turing Institute, LondonNW1 2DB, United Kingdom
| | - Alain Goriely
- Mathematical Institute, University of Oxford, OxfordOX2 6GG, United Kingdom
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Greaves MD, Novelli L, Mansour L S, Zalesky A, Razi A. Structurally informed models of directed brain connectivity. Nat Rev Neurosci 2025; 26:23-41. [PMID: 39663407 DOI: 10.1038/s41583-024-00881-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/30/2024] [Indexed: 12/13/2024]
Abstract
Understanding how one brain region exerts influence over another in vivo is profoundly constrained by models used to infer or predict directed connectivity. Although such neural interactions rely on the anatomy of the brain, it remains unclear whether, at the macroscale, structural (or anatomical) connectivity provides useful constraints on models of directed connectivity. Here, we review the current state of research on this question, highlighting a key distinction between inference-based effective connectivity and prediction-based directed functional connectivity. We explore the methods via which structural connectivity has been integrated into directed connectivity models: through prior distributions, fixed parameters in state-space models and inputs to structure learning algorithms. Although the evidence suggests that integrating structural connectivity substantially improves directed connectivity models, assessments of reliability and out-of-sample validity are lacking. We conclude this Review with a strategy for future research that addresses current challenges and identifies opportunities for advancing the integration of structural and directed connectivity to ultimately improve understanding of the brain in health and disease.
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Affiliation(s)
- Matthew D Greaves
- School of Psychological Sciences, Monash University, Clayton, Victoria, Australia.
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.
| | - Leonardo Novelli
- School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia
| | - Sina Mansour L
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia
| | - Andrew Zalesky
- Department of Psychiatry, The University of Melbourne, Parkville, Victoria, Australia
| | - Adeel Razi
- School of Psychological Sciences, Monash University, Clayton, Victoria, Australia.
- Monash Biomedical Imaging, Monash University, Clayton, Victoria, Australia.
- Wellcome Centre for Human Neuroimaging, University College London, London, UK.
- CIFAR Azrieli Global Scholars Program, CIFAR, Toronto, Ontario, Canada.
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Bonetti L, Fernández-Rubio G, Lumaca M, Carlomagno F, Risgaard Olsen E, Criscuolo A, Kotz SA, Vuust P, Brattico E, Kringelbach ML. Age-related neural changes underlying long-term recognition of musical sequences. Commun Biol 2024; 7:1036. [PMID: 39209979 PMCID: PMC11362492 DOI: 10.1038/s42003-024-06587-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Accepted: 07/15/2024] [Indexed: 09/04/2024] Open
Abstract
Aging is often associated with decline in brain processing power and neural predictive capabilities. To challenge this notion, we used magnetoencephalography (MEG) and magnetic resonance imaging (MRI) to record the whole-brain activity of 39 older adults (over 60 years old) and 37 young adults (aged 18-25 years) during recognition of previously memorised and varied musical sequences. Results reveal that when recognising memorised sequences, the brain of older compared to young adults reshapes its functional organisation. In fact, it shows increased early activity in sensory regions such as the left auditory cortex (100 ms and 250 ms after each note), and only moderate decreased activity (350 ms) in medial temporal lobe and prefrontal regions. When processing the varied sequences, older adults show a marked reduction of the fast-scale functionality (250 ms after each note) of higher-order brain regions including hippocampus, ventromedial prefrontal and inferior temporal cortices, while no differences are observed in the auditory cortex. Accordingly, young outperform older adults in the recognition of novel sequences, while no behavioural differences are observed with regards to memorised ones. Our findings show age-related neural changes in predictive and memory processes, integrating existing theories on compensatory neural mechanisms in non-pathological aging.
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Affiliation(s)
- Leonardo Bonetti
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus/Aalborg, Aarhus, Denmark.
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK.
- Department of Psychiatry, University of Oxford, Oxford, UK.
| | - Gemma Fernández-Rubio
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus/Aalborg, Aarhus, Denmark
| | - Massimo Lumaca
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus/Aalborg, Aarhus, Denmark
| | - Francesco Carlomagno
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus/Aalborg, Aarhus, Denmark
- Department of Education, Psychology, Communication, University of Bari Aldo Moro, Bari, Italy
| | - Emma Risgaard Olsen
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus/Aalborg, Aarhus, Denmark
| | - Antonio Criscuolo
- Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Sonja A Kotz
- Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Peter Vuust
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus/Aalborg, Aarhus, Denmark
| | - Elvira Brattico
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus/Aalborg, Aarhus, Denmark
- Department of Education, Psychology, Communication, University of Bari Aldo Moro, Bari, Italy
| | - Morten L Kringelbach
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus/Aalborg, Aarhus, Denmark
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
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Bonetti L, Brattico E, Carlomagno F, Cabral J, Stevner A, Deco G, Whybrow PC, Pearce M, Pantazis D, Vuust P, Kringelbach ML. Spatiotemporal whole-brain activity and functional connectivity of melodies recognition. Cereb Cortex 2024; 34:bhae320. [PMID: 39110413 PMCID: PMC11304985 DOI: 10.1093/cercor/bhae320] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 07/12/2024] [Accepted: 07/26/2024] [Indexed: 08/10/2024] Open
Abstract
Music is a non-verbal human language, built on logical, hierarchical structures, that offers excellent opportunities to explore how the brain processes complex spatiotemporal auditory sequences. Using the high temporal resolution of magnetoencephalography, we investigated the unfolding brain dynamics of 70 participants during the recognition of previously memorized musical sequences compared to novel sequences matched in terms of entropy and information content. Measures of both whole-brain activity and functional connectivity revealed a widespread brain network underlying the recognition of the memorized auditory sequences, which comprised primary auditory cortex, superior temporal gyrus, insula, frontal operculum, cingulate gyrus, orbitofrontal cortex, basal ganglia, thalamus, and hippocampus. Furthermore, while the auditory cortex responded mainly to the first tones of the sequences, the activity of higher-order brain areas such as the cingulate gyrus, frontal operculum, hippocampus, and orbitofrontal cortex largely increased over time during the recognition of the memorized versus novel musical sequences. In conclusion, using a wide range of analytical techniques spanning from decoding to functional connectivity and building on previous works, our study provided new insights into the spatiotemporal whole-brain mechanisms for conscious recognition of auditory sequences.
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Affiliation(s)
- Leonardo Bonetti
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, 8000 Aarhus/Aalborg, Denmark
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, OX39BX Oxford, United Kingdom
- Department of Psychiatry, University of Oxford, OX37JX Oxford, United Kingdom
| | - Elvira Brattico
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, 8000 Aarhus/Aalborg, Denmark
- Department of Education, Psychology, Communication, University of Bari Aldo Moro, 70121 Bari, Italy
| | - Francesco Carlomagno
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, 8000 Aarhus/Aalborg, Denmark
| | - Joana Cabral
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, 8000 Aarhus/Aalborg, Denmark
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, OX39BX Oxford, United Kingdom
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057 Braga, Portugal
| | - Angus Stevner
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, 8000 Aarhus/Aalborg, Denmark
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, OX39BX Oxford, United Kingdom
| | - Gustavo Deco
- Computational and Theoretical Neuroscience Group, Center for Brain and Cognition, Universitat Pompeu Fabra, 08018 Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona, Spain
| | - Peter C Whybrow
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, 90095 Los Angeles, CA, United States
| | - Marcus Pearce
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, 8000 Aarhus/Aalborg, Denmark
| | - Dimitrios Pantazis
- McGovern Institute for Brain Research, Massachusetts Institute of Technology (MIT), 02139 Cambridge, MA, United States
| | - Peter Vuust
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, 8000 Aarhus/Aalborg, Denmark
| | - Morten L Kringelbach
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, 8000 Aarhus/Aalborg, Denmark
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, OX39BX Oxford, United Kingdom
- Department of Psychiatry, University of Oxford, OX37JX Oxford, United Kingdom
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6
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Heng JG, Zhang J, Bonetti L, Lim WPH, Vuust P, Agres K, Chen SHA. Understanding music and aging through the lens of Bayesian inference. Neurosci Biobehav Rev 2024; 163:105768. [PMID: 38908730 DOI: 10.1016/j.neubiorev.2024.105768] [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: 01/09/2024] [Revised: 06/05/2024] [Accepted: 06/10/2024] [Indexed: 06/24/2024]
Abstract
Bayesian inference has recently gained momentum in explaining music perception and aging. A fundamental mechanism underlying Bayesian inference is the notion of prediction. This framework could explain how predictions pertaining to musical (melodic, rhythmic, harmonic) structures engender action, emotion, and learning, expanding related concepts of music research, such as musical expectancies, groove, pleasure, and tension. Moreover, a Bayesian perspective of music perception may shed new insights on the beneficial effects of music in aging. Aging could be framed as an optimization process of Bayesian inference. As predictive inferences refine over time, the reliance on consolidated priors increases, while the updating of prior models through Bayesian inference attenuates. This may affect the ability of older adults to estimate uncertainties in their environment, limiting their cognitive and behavioral repertoire. With Bayesian inference as an overarching framework, this review synthesizes the literature on predictive inferences in music and aging, and details how music could be a promising tool in preventive and rehabilitative interventions for older adults through the lens of Bayesian inference.
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Affiliation(s)
- Jiamin Gladys Heng
- School of Computer Science and Engineering, Nanyang Technological University, Singapore.
| | - Jiayi Zhang
- Interdisciplinary Graduate Program, Nanyang Technological University, Singapore; School of Social Sciences, Nanyang Technological University, Singapore; Centre for Research and Development in Learning, Nanyang Technological University, Singapore
| | - Leonardo Bonetti
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus, Aalborg, Denmark; Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, United Kingdom; Department of Psychiatry, University of Oxford, United Kingdom; Department of Psychology, University of Bologna, Italy
| | | | - Peter Vuust
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus, Aalborg, Denmark
| | - Kat Agres
- Centre for Music and Health, National University of Singapore, Singapore; Yong Siew Toh Conservatory of Music, National University of Singapore, Singapore
| | - Shen-Hsing Annabel Chen
- School of Social Sciences, Nanyang Technological University, Singapore; Centre for Research and Development in Learning, Nanyang Technological University, Singapore; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore; National Institute of Education, Nanyang Technological University, Singapore.
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