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Barzon G, Ambrosini E, Vallesi A, Suweis S. EEG microstate transition cost correlates with task demands. PLoS Comput Biol 2024; 20:e1012521. [PMID: 39388512 DOI: 10.1371/journal.pcbi.1012521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 09/28/2024] [Indexed: 10/12/2024] Open
Abstract
The ability to solve complex tasks relies on the adaptive changes occurring in the spatio-temporal organization of brain activity under different conditions. Altered flexibility in these dynamics can lead to impaired cognitive performance, manifesting for instance as difficulties in attention regulation, distraction inhibition, and behavioral adaptation. Such impairments result in decreased efficiency and increased effort in accomplishing goal-directed tasks. Therefore, developing quantitative measures that can directly assess the effort involved in these transitions using neural data is of paramount importance. In this study, we propose a framework to associate cognitive effort during the performance of tasks with electroencephalography (EEG) activation patterns. The methodology relies on the identification of discrete dynamical states (EEG microstates) and optimal transport theory. To validate the effectiveness of this framework, we apply it to a dataset collected during a spatial version of the Stroop task, a cognitive test in which participants respond to one aspect of a stimulus while ignoring another, often conflicting, aspect. The Stroop task is a cognitive test where participants must respond to one aspect of a stimulus while ignoring another, often conflicting, aspect. Our findings reveal an increased cost linked to cognitive effort, thus confirming the framework's effectiveness in capturing and quantifying cognitive transitions. By utilizing a fully data-driven method, this research opens up fresh perspectives for physiologically describing cognitive effort within the brain.
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Affiliation(s)
- Giacomo Barzon
- Padova Neuroscience Center, University of Padova, Padova, Italy
- Fondazione Bruno Kessler, Povo, Italy
| | - Ettore Ambrosini
- Padova Neuroscience Center, University of Padova, Padova, Italy
- Department of Neuroscience, University of Padova, Padova, Italy
| | - Antonino Vallesi
- Padova Neuroscience Center, University of Padova, Padova, Italy
- Department of Neuroscience, University of Padova, Padova, Italy
| | - Samir Suweis
- Padova Neuroscience Center, University of Padova, Padova, Italy
- Department of Physics and Astronomy "Galileo Galilei", University of Padova, Padova, Italy
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2
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Li P, Zhou X, Luo N, Shen R, Zhu X, Zhong M, Huang S, He N, Lyu H, Huang Y, Yin Q, Zhou L, Lu Y, Tan Y, Liu J. Distinct patterns of electrophysiologic-neuroimaging correlations between Parkinson's disease and multiple system atrophy. Neuroimage 2024; 297:120701. [PMID: 38914210 DOI: 10.1016/j.neuroimage.2024.120701] [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: 03/14/2024] [Revised: 06/17/2024] [Accepted: 06/21/2024] [Indexed: 06/26/2024] Open
Abstract
Due to a high degree of symptom overlap in the early stages, with movement disorders predominating, Parkinson's disease (PD) and multiple system atrophy (MSA) may exhibit a similar decline in motor areas, yet they differ in their spread throughout the brain, ultimately resulting in two distinct diseases. Drawing upon neuroimaging analyses and altered motor cortex excitability, potential diffusion mechanisms were delved into, and comparisons of correlations across distinct disease groups were conducted in a bid to uncover significant pathological disparities. We recruited thirty-five PD, thirty-seven MSA, and twenty-eight matched controls to conduct clinical assessments, electromyographic recording, and magnetic resonance imaging scanning during the "on medication" state. Patients with neurodegeneration displayed a widespread decrease in electrophysiology in bilateral M1. Brain function in early PD was still in the self-compensatory phase and there was no significant change. MSA patients demonstrated an increase in intra-hemispheric function coupled with a decrease in diffusivity, indicating a reduction in the spread of neural signals. The level of resting motor threshold in healthy aged showed broad correlations with both clinical manifestations and brain circuits related to left M1, which was absent in disease states. Besides, ICF exhibited distinct correlations with functional connections between right M1 and left middle temporal gyrus in all groups. The present study identified subtle differences in the functioning of PD and MSA related to bilateral M1. By combining clinical information, cortical excitability, and neuroimaging intuitively, we attempt to bring light on the potential mechanisms that may underlie the development of neurodegenerative disease.
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Affiliation(s)
- Puyu Li
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xinyi Zhou
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Ningdi Luo
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Ruinan Shen
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xue Zhu
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Min Zhong
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Sijia Huang
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Naying He
- Radiology Department, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Haiying Lyu
- Radiology Department, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yufei Huang
- Radiology Department, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Qianyi Yin
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Liche Zhou
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yong Lu
- Radiology Department, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yuyan Tan
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Jun Liu
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
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3
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Maschke C, O'Byrne J, Colombo MA, Boly M, Gosseries O, Laureys S, Rosanova M, Jerbi K, Blain-Moraes S. Critical dynamics in spontaneous EEG predict anesthetic-induced loss of consciousness and perturbational complexity. Commun Biol 2024; 7:946. [PMID: 39103539 DOI: 10.1038/s42003-024-06613-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 07/22/2024] [Indexed: 08/07/2024] Open
Abstract
Consciousness has been proposed to be supported by electrophysiological patterns poised at criticality, a dynamical regime which exhibits adaptive computational properties, maximally complex patterns and divergent sensitivity to perturbation. Here, we investigate dynamical properties of the resting-state electroencephalogram (EEG) of healthy subjects undergoing general anesthesia with propofol, xenon or ketamine. Importantly, all participants were unresponsive under anesthesia, while consciousness was retained only during ketamine anesthesia (in the form of vivid dreams), enabling an experimental dissociation between unresponsiveness and unconsciousness. For each condition, we measure (i) avalanche criticality, (ii) chaoticity, and (iii) criticality-related metrics, revealing that states of unconsciousness are characterized by a distancing from both avalanche criticality and the edge of chaos. We then ask whether these same dynamical properties are predictive of the perturbational complexity index (PCI), a TMS-based measure that has shown remarkably high sensitivity in detecting consciousness independently of behavior. We successfully predict individual subjects' PCI values with considerably high accuracy from resting-state EEG dynamical properties alone. Our results establish a firm link between perturbational complexity and criticality, and provide further evidence that criticality is a necessary condition for the emergence of consciousness.
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Affiliation(s)
- Charlotte Maschke
- Montreal General Hospital, McGill University Health Centre, Montreal, QC, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Montreal, QC, Canada
| | - Jordan O'Byrne
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Montreal, QC, Canada
- MILA (Québec Artificial Intelligence Institute), Montréal, QC, Canada
| | | | - Melanie Boly
- Department of Neurology and Department of Psychiatry, University of Wisconsin, Madison, WI, USA
| | - Olivia Gosseries
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre du cerveau, CHU of Liège, Liège, Belgium
| | - Steven Laureys
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- CERVO Brain Research Centre, Laval University, Laval, QC, Canada
- Consciousness Science Institute, Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Karim Jerbi
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Montreal, QC, Canada
- MILA (Québec Artificial Intelligence Institute), Montréal, QC, Canada
- Centre UNIQUE (Union Neurosciences & Intelligence Artificielle), Montréal, QC, Canada
| | - Stefanie Blain-Moraes
- Montreal General Hospital, McGill University Health Centre, Montreal, QC, Canada.
- School of Physical and Occupational Therapy, McGill University, Montreal, QC, Canada.
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4
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Sorrentino P, Pathak A, Ziaeemehr A, Troisi Lopez E, Cipriano L, Romano A, Sparaco M, Quarantelli M, Banerjee A, Sorrentino G, Jirsa V, Hashemi M. The virtual multiple sclerosis patient. iScience 2024; 27:110101. [PMID: 38974971 PMCID: PMC11226980 DOI: 10.1016/j.isci.2024.110101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 03/09/2024] [Accepted: 05/22/2024] [Indexed: 07/09/2024] Open
Abstract
Multiple sclerosis (MS) diagnosis typically involves assessing clinical symptoms, MRI findings, and ruling out alternative explanations. While myelin damage broadly affects conduction speeds, traditional tests focus on specific white-matter tracts, which may not reflect overall impairment accurately. In this study, we integrate diffusion tensor immaging (DTI) and magnetoencephalography (MEG) data into individualized virtual brain models to estimate conduction velocities for MS patients and controls. Using Bayesian inference, we demonstrated a causal link between empirical spectral changes and inferred slower conduction velocities in patients. Remarkably, these velocities proved superior predictors of clinical disability compared to structural damage. Our findings underscore a nuanced relationship between conduction delays and large-scale brain dynamics, suggesting that individualized velocity alterations at the whole-brain level contribute causatively to clinical outcomes in MS.
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Affiliation(s)
- P. Sorrentino
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille, France
- Institute of Applied Sciences and Intelligent Systems, National Research Council, Pozzuoli, Italy
| | - A. Pathak
- National Brain Research Centre, Manesar, Gurgaon, Haryana, India
| | - A. Ziaeemehr
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille, France
| | - E. Troisi Lopez
- Department of Motor Sciences and Wellness, Parthenope University of Naples, Naples, Italy
- Institute for Diagnosis and Cure Hermitage Capodimonte, Naples, Italy
| | - L. Cipriano
- Department of Motor Sciences and Wellness, Parthenope University of Naples, Naples, Italy
- Institute for Diagnosis and Cure Hermitage Capodimonte, Naples, Italy
| | - A. Romano
- Department of Motor Sciences and Wellness, Parthenope University of Naples, Naples, Italy
- Institute for Diagnosis and Cure Hermitage Capodimonte, Naples, Italy
| | - M. Sparaco
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, Caserta, Italy
| | - M. Quarantelli
- Biostructure and Bioimaging Institute, National Research Council, Naples, Italy
| | - A. Banerjee
- National Brain Research Centre, Manesar, Gurgaon, Haryana, India
| | - G. Sorrentino
- Department of Motor Sciences and Wellness, Parthenope University of Naples, Naples, Italy
- Institute for Diagnosis and Cure Hermitage Capodimonte, Naples, Italy
| | - V. Jirsa
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille, France
| | - M. Hashemi
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille, France
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da Silva Castanheira J, Wiesman AI, Hansen JY, Misic B, Baillet S. The neurophysiological brain-fingerprint of Parkinson's disease. EBioMedicine 2024; 105:105201. [PMID: 38908100 PMCID: PMC11253223 DOI: 10.1016/j.ebiom.2024.105201] [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: 12/04/2023] [Revised: 05/30/2024] [Accepted: 05/30/2024] [Indexed: 06/24/2024] Open
Abstract
BACKGROUND Research in healthy young adults shows that characteristic patterns of brain activity define individual "brain-fingerprints" that are unique to each person. However, variability in these brain-fingerprints increases in individuals with neurological conditions, challenging the clinical relevance and potential impact of the approach. Our study shows that brain-fingerprints derived from neurophysiological brain activity are associated with pathophysiological and clinical traits of individual patients with Parkinson's disease (PD). METHODS We created brain-fingerprints from task-free brain activity recorded through magnetoencephalography in 79 PD patients and compared them with those from two independent samples of age-matched healthy controls (N = 424 total). We decomposed brain activity into arrhythmic and rhythmic components, defining distinct brain-fingerprints for each type from recording durations of up to 4 min and as short as 30 s. FINDINGS The arrhythmic spectral components of cortical activity in patients with Parkinson's disease are more variable over short periods, challenging the definition of a reliable brain-fingerprint. However, by isolating the rhythmic components of cortical activity, we derived brain-fingerprints that distinguished between patients and healthy controls with about 90% accuracy. The most prominent cortical features of the resulting Parkinson's brain-fingerprint are mapped to polyrhythmic activity in unimodal sensorimotor regions. Leveraging these features, we also demonstrate that Parkinson's symptom laterality can be decoded directly from cortical neurophysiological activity. Furthermore, our study reveals that the cortical topography of the Parkinson's brain-fingerprint aligns with that of neurotransmitter systems affected by the disease's pathophysiology. INTERPRETATION The increased moment-to-moment variability of arrhythmic brain-fingerprints challenges patient differentiation and explains previously published results. We outline patient-specific rhythmic brain signaling features that provide insights into both the neurophysiological signature and symptom laterality of Parkinson's disease. Thus, the proposed definition of a rhythmic brain-fingerprint of Parkinson's disease may contribute to novel, refined approaches to patient stratification. Symmetrically, we discuss how rhythmic brain-fingerprints may contribute to the improved identification and testing of therapeutic neurostimulation targets. FUNDING Data collection and sharing for this project was provided by the Quebec Parkinson Network (QPN), the Pre-symptomatic Evaluation of Novel or Experimental Treatments for Alzheimer's Disease (PREVENT-AD; release 6.0) program, the Cambridge Centre for Aging Neuroscience (Cam-CAN), and the Open MEG Archives (OMEGA). The QPN is funded by a grant from Fonds de Recherche du Québec - Santé (FRQS). PREVENT-AD was launched in 2011 as a $13.5 million, 7-year public-private partnership using funds provided by McGill University, the FRQS, an unrestricted research grant from Pfizer Canada, the Levesque Foundation, the Douglas Hospital Research Centre and Foundation, the Government of Canada, and the Canada Fund for Innovation. The Brainstorm project is supported by funding to SB from the NIH (R01-EB026299-05). Further funding to SB for this study included a Discovery grant from the Natural Sciences and Engineering Research Council of Canada of Canada (436355-13), and the CIHR Canada research Chair in Neural Dynamics of Brain Systems (CRC-2017-00311).
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Affiliation(s)
| | - Alex I Wiesman
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Justine Y Hansen
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Bratislav Misic
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Sylvain Baillet
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada.
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6
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Polverino A, Troisi Lopez E, Liparoti M, Minino R, Romano A, Cipriano L, Trojsi F, Jirsa V, Sorrentino G, Sorrentino P. Altered spreading of fast aperiodic brain waves relates to disease duration in Amyotrophic Lateral Sclerosis. Clin Neurophysiol 2024; 163:14-21. [PMID: 38663099 DOI: 10.1016/j.clinph.2024.04.003] [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: 11/27/2023] [Revised: 03/27/2024] [Accepted: 04/08/2024] [Indexed: 06/15/2024]
Abstract
OBJECTIVE To test the hypothesis that patients affected by Amyotrophic Lateral Sclerosis (ALS) show an altered spatio-temporal spreading of neuronal avalanches in the brain, and that this may related to the clinical picture. METHODS We obtained the source-reconstructed magnetoencephalography (MEG) signals from thirty-six ALS patients and forty-two healthy controls. Then, we used the construct of the avalanche transition matrix (ATM) and the corresponding network parameter nodal strength to quantify the changes in each region, since this parameter provides key information about which brain regions are mostly involved in the spreading avalanches. RESULTS ALS patients presented higher values of the nodal strength in both cortical and sub-cortical brain areas. This parameter correlated directly with disease duration. CONCLUSIONS In this work, we provide a deeper characterization of neuronal avalanches propagation in ALS, describing their spatio-temporal trajectories and identifying the brain regions most likely to be involved in the process. This makes it possible to recognize the brain areas that take part in the pathogenic mechanisms of ALS. Furthermore, the nodal strength of the involved regions correlates directly with disease duration. SIGNIFICANCE Our results corroborate the clinical relevance of aperiodic, fast large-scale brain activity as a biomarker of microscopic changes induced by neurophysiological processes.
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Affiliation(s)
- Arianna Polverino
- Institute of Diagnosis and Treatment Hermitage Capodimonte, 80131 Naples, Italy
| | - Emahnuel Troisi Lopez
- Institute of Applied Sciences and Intelligent Systems of National Research Council, 80078 Pozzuoli, Italy
| | - Marianna Liparoti
- Department of Philosophical, Pedagogical and Economic-Quantitative Sciences, University of Chieti-Pescara G. D'Annunzio, 66100 Chieti, Italy
| | - Roberta Minino
- Department of Medical, Motor and Wellness Sciences, University of Naples Parthenope, 80133 Naples, Italy
| | - Antonella Romano
- Department of Medical, Motor and Wellness Sciences, University of Naples Parthenope, 80133 Naples, Italy
| | - Lorenzo Cipriano
- Department of Medical, Motor and Wellness Sciences, University of Naples Parthenope, 80133 Naples, Italy
| | - Francesca Trojsi
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, 81100 Naples, Italy
| | - Viktor Jirsa
- Institut de Neurosciences des Systèmes, Inserm, INS, Aix-Marseille University, 13005 Marseille, France
| | - Giuseppe Sorrentino
- Institute of Diagnosis and Treatment Hermitage Capodimonte, 80131 Naples, Italy; Institute of Applied Sciences and Intelligent Systems of National Research Council, 80078 Pozzuoli, Italy; Department of Medical, Motor and Wellness Sciences, University of Naples Parthenope, 80133 Naples, Italy.
| | - Pierpaolo Sorrentino
- Institute of Applied Sciences and Intelligent Systems of National Research Council, 80078 Pozzuoli, Italy; Institut de Neurosciences des Systèmes, Inserm, INS, Aix-Marseille University, 13005 Marseille, France; Department of Biomedical Sciences, University of Sassari, 07100 Sassari, Italy
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7
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Wang HE, Triebkorn P, Breyton M, Dollomaja B, Lemarechal JD, Petkoski S, Sorrentino P, Depannemaecker D, Hashemi M, Jirsa VK. Virtual brain twins: from basic neuroscience to clinical use. Natl Sci Rev 2024; 11:nwae079. [PMID: 38698901 PMCID: PMC11065363 DOI: 10.1093/nsr/nwae079] [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: 09/25/2023] [Revised: 02/05/2024] [Accepted: 02/20/2024] [Indexed: 05/05/2024] Open
Abstract
Virtual brain twins are personalized, generative and adaptive brain models based on data from an individual's brain for scientific and clinical use. After a description of the key elements of virtual brain twins, we present the standard model for personalized whole-brain network models. The personalization is accomplished using a subject's brain imaging data by three means: (1) assemble cortical and subcortical areas in the subject-specific brain space; (2) directly map connectivity into the brain models, which can be generalized to other parameters; and (3) estimate relevant parameters through model inversion, typically using probabilistic machine learning. We present the use of personalized whole-brain network models in healthy ageing and five clinical diseases: epilepsy, Alzheimer's disease, multiple sclerosis, Parkinson's disease and psychiatric disorders. Specifically, we introduce spatial masks for relevant parameters and demonstrate their use based on the physiological and pathophysiological hypotheses. Finally, we pinpoint the key challenges and future directions.
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Affiliation(s)
- Huifang E Wang
- Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes (INS) UMR1106; Marseille 13005, France
| | - Paul Triebkorn
- Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes (INS) UMR1106; Marseille 13005, France
| | - Martin Breyton
- Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes (INS) UMR1106; Marseille 13005, France
- Service de Pharmacologie Clinique et Pharmacosurveillance, AP–HM, Marseille, 13005, France
| | - Borana Dollomaja
- Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes (INS) UMR1106; Marseille 13005, France
| | - Jean-Didier Lemarechal
- Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes (INS) UMR1106; Marseille 13005, France
| | - Spase Petkoski
- Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes (INS) UMR1106; Marseille 13005, France
| | - Pierpaolo Sorrentino
- Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes (INS) UMR1106; Marseille 13005, France
| | - Damien Depannemaecker
- Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes (INS) UMR1106; Marseille 13005, France
| | - Meysam Hashemi
- Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes (INS) UMR1106; Marseille 13005, France
| | - Viktor K Jirsa
- Aix Marseille Université, Institut National de la Santé et de la Recherche Médicale, Institut de Neurosciences des Systèmes (INS) UMR1106; Marseille 13005, France
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8
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Lu J, Zhang X, Shu Z, Han J, Yu N. A dynamic brain network decomposition method discovers effective brain hemodynamic sub-networks for Parkinson's disease. J Neural Eng 2024; 21:026047. [PMID: 38621377 DOI: 10.1088/1741-2552/ad3eb6] [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: 01/17/2024] [Accepted: 04/15/2024] [Indexed: 04/17/2024]
Abstract
Objective.Dopaminergic treatment is effective for Parkinson's disease (PD). Nevertheless, the conventional treatment assessment mainly focuses on human-administered behavior examination while the underlying functional improvements have not been well explored. This paper aims to investigate brain functional variations of PD patients after dopaminergic therapy.Approach.This paper proposed a dynamic brain network decomposition method and discovered brain hemodynamic sub-networks that well characterized the efficacy of dopaminergic treatment in PD. Firstly, a clinical walking procedure with functional near-infrared spectroscopy was developed, and brain activations during the procedure from fifty PD patients under the OFF and ON states (without and with dopaminergic medication) were captured. Then, dynamic brain networks were constructed with sliding-window analysis of phase lag index and integrated time-varying functional networks across all patients. Afterwards, an aggregated network decomposition algorithm was formulated based on aggregated effectiveness optimization of functional networks in spanning network topology and cross-validation network variations, and utilized to unveil effective brain hemodynamic sub-networks for PD patients. Further, dynamic sub-network features were constructed to characterize the brain flexibility and dynamics according to the temporal switching and activation variations of discovered sub-networks, and their correlations with differential treatment-induced gait alterations were analyzed.Results.The results demonstrated that PD patients exhibited significantly enhanced flexibility after dopaminergic therapy within a sub-network related to the improvement of motor functions. Other sub-networks were significantly correlated with trunk-related axial symptoms and exhibited no significant treatment-induced dynamic interactions.Significance.The proposed method promises a quantified and objective approach for dopaminergic treatment evaluation. Moreover, the findings suggest that the gait of PD patients comprises distinct motor domains, and the corresponding neural controls are selectively responsive to dopaminergic treatment.
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Affiliation(s)
- Jiewei Lu
- College of Artificial Intelligence, Nankai University, Tianjin, People's Republic of China
| | - Xinyuan Zhang
- College of Artificial Intelligence, Nankai University, Tianjin, People's Republic of China
| | - Zhilin Shu
- College of Artificial Intelligence, Nankai University, Tianjin, People's Republic of China
| | - Jianda Han
- College of Artificial Intelligence, Nankai University, Tianjin, People's Republic of China
- Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Nankai University, Tianjin, People's Republic of China
- Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen, People's Republic of China
| | - Ningbo Yu
- College of Artificial Intelligence, Nankai University, Tianjin, People's Republic of China
- Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Nankai University, Tianjin, People's Republic of China
- Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen, People's Republic of China
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9
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Cipriano L, Minino R, Liparoti M, Polverino A, Romano A, Bonavita S, Pirozzi MA, Quarantelli M, Jirsa V, Sorrentino G, Sorrentino P, Troisi Lopez E. Flexibility of brain dynamics is increased and predicts clinical impairment in relapsing-remitting but not in secondary progressive multiple sclerosis. Brain Commun 2024; 6:fcae112. [PMID: 38585670 PMCID: PMC10998461 DOI: 10.1093/braincomms/fcae112] [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: 07/31/2023] [Revised: 02/15/2024] [Accepted: 04/01/2024] [Indexed: 04/09/2024] Open
Abstract
Large-scale brain activity has long been investigated under the erroneous assumption of stationarity. Nowadays, we know that resting-state functional connectivity is characterized by aperiodic, scale-free bursts of activity (i.e. neuronal avalanches) that intermittently recruit different brain regions. These different patterns of activity represent a measure of brain flexibility, whose reduction has been found to predict clinical impairment in multiple neurodegenerative diseases such as Parkinson's disease, amyotrophic lateral sclerosis and Alzheimer's disease. Brain flexibility has been recently found increased in multiple sclerosis, but its relationship with clinical disability remains elusive. Also, potential differences in brain dynamics according to the multiple sclerosis clinical phenotypes remain unexplored so far. We performed a brain dynamics study quantifying brain flexibility utilizing the 'functional repertoire' (i.e. the number of configurations of active brain areas) through source reconstruction of magnetoencephalography signals in a cohort of 25 multiple sclerosis patients (10 relapsing-remitting multiple sclerosis and 15 secondary progressive multiple sclerosis) and 25 healthy controls. Multiple sclerosis patients showed a greater number of unique reconfigurations at fast time scales as compared with healthy controls. This difference was mainly driven by the relapsing-remitting multiple sclerosis phenotype, whereas no significant differences in brain dynamics were found between secondary progressive multiple sclerosis and healthy controls. Brain flexibility also showed a different predictive power on clinical disability according to the multiple sclerosis type. For the first time, we investigated brain dynamics in multiple sclerosis patients through high temporal resolution techniques, unveiling differences in brain flexibility according to the multiple sclerosis phenotype and its relationship with clinical disability.
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Affiliation(s)
- Lorenzo Cipriano
- Department of Medical, Motor and Wellness Sciences, University of Naples ‘Parthenope’, 80133 Naples, Italy
| | - Roberta Minino
- Department of Medical, Motor and Wellness Sciences, University of Naples ‘Parthenope’, 80133 Naples, Italy
| | - Marianna Liparoti
- Department of Philosophical, Pedagogical and Quantitative-Economic Sciences, University of Chieti-Pescara ‘G. d’Annunzio’, 66100 Chieti, Italy
| | - Arianna Polverino
- Institute of Diagnosis and Therapy Hermitage Capodimonte, 80145 Naples, Italy
| | - Antonella Romano
- Department of Medical, Motor and Wellness Sciences, University of Naples ‘Parthenope’, 80133 Naples, Italy
| | - Simona Bonavita
- Department of Advanced Medical and Surgical Sciences, University of Campania ‘L. Vanvitelli’, 81100 Naples, Italy
| | - Maria Agnese Pirozzi
- Department of Advanced Medical and Surgical Sciences, University of Campania ‘L. Vanvitelli’, 81100 Naples, Italy
| | | | - Viktor Jirsa
- Institut de Neurosciences des Systèmes, Inserm, INS, Aix-Marseille University, 13005 Marseille, France
| | - Giuseppe Sorrentino
- Department of Medical, Motor and Wellness Sciences, University of Naples ‘Parthenope’, 80133 Naples, Italy
- Institute of Diagnosis and Therapy Hermitage Capodimonte, 80145 Naples, Italy
- Institute of Applied Sciences and Intelligent Systems, National Research Council, 80078 Pozzuoli, Italy
| | - Pierpaolo Sorrentino
- Institut de Neurosciences des Systèmes, Inserm, INS, Aix-Marseille University, 13005 Marseille, France
- Department of Biomedical Sciences, University of Sassari, 07100 Sassari, Italy
| | - Emahnuel Troisi Lopez
- Institute of Applied Sciences and Intelligent Systems, National Research Council, 80078 Pozzuoli, Italy
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10
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van Nifterick AM, Scheijbeler EP, Gouw AA, de Haan W, Stam CJ. Local signal variability and functional connectivity: Sensitive measures of the excitation-inhibition ratio? Cogn Neurodyn 2024; 18:519-537. [PMID: 38699618 PMCID: PMC11061092 DOI: 10.1007/s11571-023-10003-x] [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: 03/16/2023] [Revised: 06/08/2023] [Accepted: 08/13/2023] [Indexed: 05/05/2024] Open
Abstract
A novel network version of permutation entropy, the inverted joint permutation entropy (JPEinv), holds potential as non-invasive biomarker of abnormal excitation-inhibition (E-I) ratio in Alzheimer's disease (AD). In this computational modelling study, we test the hypotheses that this metric, and related measures of signal variability and functional connectivity, are sensitive to altered E-I ratios. The E-I ratio in each neural mass of a whole-brain computational network model was systematically varied. We evaluated whether JPEinv, local signal variability (by permutation entropy) and functional connectivity (by weighted symbolic mutual information (wsMI)) were related to E-I ratio, on whole-brain and regional level. The hub disruption index can identify regions primarily affected in terms of functional connectivity strength (or: degree) by the altered E-I ratios. Analyses were performed for a range of coupling strengths, filter and time-delay settings. On whole-brain level, higher E-I ratios were associated with higher functional connectivity (by JPEinv and wsMI) and lower local signal variability. These relationships were nonlinear and depended on the coupling strength, filter and time-delay settings. On regional level, hub-like regions showed a selective decrease in functional degree (by JPEinv and wsMI) upon a lower E-I ratio, and non-hub-like regions showed a selective increase in degree upon a higher E-I ratio. These results suggest that abnormal functional connectivity and signal variability, as previously reported in patients across the AD continuum, can inform us about altered E-I ratios. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-023-10003-x.
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Affiliation(s)
- Anne M. van Nifterick
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Elliz P. Scheijbeler
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Alida A. Gouw
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Willem de Haan
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Cornelis J. Stam
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
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11
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Liang J, Yang Z, Zhou C. Excitation-Inhibition Balance, Neural Criticality, and Activities in Neuronal Circuits. Neuroscientist 2024:10738584231221766. [PMID: 38291889 DOI: 10.1177/10738584231221766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Neural activities in local circuits exhibit complex and multilevel dynamic features. Individual neurons spike irregularly, which is believed to originate from receiving balanced amounts of excitatory and inhibitory inputs, known as the excitation-inhibition balance. The spatial-temporal cascades of clustered neuronal spikes occur in variable sizes and durations, manifested as neural avalanches with scale-free features. These may be explained by the neural criticality hypothesis, which posits that neural systems operate around the transition between distinct dynamic states. Here, we summarize the experimental evidence for and the underlying theory of excitation-inhibition balance and neural criticality. Furthermore, we review recent studies of excitatory-inhibitory networks with synaptic kinetics as a simple solution to reconcile these two apparently distinct theories in a single circuit model. This provides a more unified understanding of multilevel neural activities in local circuits, from spontaneous to stimulus-response dynamics.
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Affiliation(s)
- Junhao Liang
- Eberhard Karls University of Tübingen and Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Zhuda Yang
- Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong
| | - Changsong Zhou
- Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong
- Life Science Imaging Centre, Hong Kong Baptist University, Kowloon Tong, Hong Kong
- Research Centre, Hong Kong Baptist University Institute of Research and Continuing Education, Shenzhen, China
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12
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Liparoti M, Cipriano L, Troisi Lopez E, Polverino A, Minino R, Sarno L, Sorrentino G, Lucidi F, Sorrentino P. Brain flexibility increases during the peri-ovulatory phase as compared to early follicular phase of the menstrual cycle. Sci Rep 2024; 14:1976. [PMID: 38263324 PMCID: PMC10805777 DOI: 10.1038/s41598-023-49588-y] [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: 06/19/2023] [Accepted: 12/09/2023] [Indexed: 01/25/2024] Open
Abstract
The brain operates in a flexible dynamic regime, generating complex patterns of activity (i.e. neuronal avalanches). This study aimed at describing how brain dynamics change according to menstrual cycle (MC) phases. Brain activation patterns were estimated from resting-state magnetoencephalography (MEG) scans, acquired from women at early follicular (T1), peri-ovulatory (T2) and mid-luteal (T3) phases of the MC. We investigated the functional repertoire (number of brain configurations based on fast high-amplitude bursts of the brain signals) and the region-specific influence on large-scale dynamics across the MC. Finally, we assessed the relationship between sex hormones and changes in brain dynamics. A significantly larger number of visited configurations in T2 as compared to T1 was specifically observed in the beta frequency band. No relationship between changes in brain dynamics and sex hormones was evident. Finally, we showed that the left posterior cingulate gyrus and the right insula were recruited more often in the functional repertoire during T2 as compared to T1, while the right pallidum was more often part of the functional repertoires during T1 as compared to T2. In summary, we showed hormone-independent increased flexibility of the brain dynamics during the ovulatory phase. Moreover, we demonstrated that several specific brain regions play a key role in determining this change.
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Affiliation(s)
- Marianna Liparoti
- Department of Philosophical, Pedagogical and Quantitative-Economic Sciences, University of Chieti-Pescara "G. d'Annunzio", 66100, Chieti, Italy
| | - Lorenzo Cipriano
- Department of Motor Sciences and Wellness, University of Naples "Parthenope", 80133, Naples, Italy
| | - Emahnuel Troisi Lopez
- Institute of Applied Sciences and Intelligent Systems, National Research Council, 80078, Pozzuoli, Italy
| | - Arianna Polverino
- Institute for Diagnosis and Cure Hermitage Capodimonte, 80131, Naples, Italy
| | - Roberta Minino
- Department of Motor Sciences and Wellness, University of Naples "Parthenope", 80133, Naples, Italy
| | - Laura Sarno
- Department of Neurosciences, Reproductive Science and Dentistry, University of Naples "Federico II", 80131, Naples, Italy
| | - Giuseppe Sorrentino
- Department of Motor Sciences and Wellness, University of Naples "Parthenope", 80133, Naples, Italy
- Institute of Applied Sciences and Intelligent Systems, National Research Council, 80078, Pozzuoli, Italy
- Institute for Diagnosis and Cure Hermitage Capodimonte, 80131, Naples, Italy
| | - Fabio Lucidi
- Department of Social and Developmental Psychology, "Sapienza" University of Rome, 00185, Rome, Italy
| | - Pierpaolo Sorrentino
- Institute of Applied Sciences and Intelligent Systems, National Research Council, 80078, Pozzuoli, Italy.
- Institut de Neurosciences Des Systèmes, Aix-Marseille Université, 13005, Marseille, France.
- Department of Biomedical Sciences, University of Sassari, 07100, Sassari, Italy.
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13
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Corsi MC, Sorrentino P, Schwartz D, George N, Gollo LL, Chevallier S, Hugueville L, Kahn AE, Dupont S, Bassett DS, Jirsa V, De Vico Fallani F. Measuring neuronal avalanches to inform brain-computer interfaces. iScience 2024; 27:108734. [PMID: 38226174 PMCID: PMC10788504 DOI: 10.1016/j.isci.2023.108734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 10/18/2023] [Accepted: 12/12/2023] [Indexed: 01/17/2024] Open
Abstract
Large-scale interactions among multiple brain regions manifest as bursts of activations called neuronal avalanches, which reconfigure according to the task at hand and, hence, might constitute natural candidates to design brain-computer interfaces (BCIs). To test this hypothesis, we used source-reconstructed magneto/electroencephalography during resting state and a motor imagery task performed within a BCI protocol. To track the probability that an avalanche would spread across any two regions, we built an avalanche transition matrix (ATM) and demonstrated that the edges whose transition probabilities significantly differed between conditions hinged selectively on premotor regions in all subjects. Furthermore, we showed that the topology of the ATMs allows task-decoding above the current gold standard. Hence, our results suggest that neuronal avalanches might capture interpretable differences between tasks that can be used to inform brain-computer interfaces.
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Affiliation(s)
- Marie-Constance Corsi
- Sorbonne Université, Institut du cerveau - Paris Brain Institute - ICM, CNRS, Inserm, APHP, Hôpital de la Pitié Salpêtrière, Paris, France
- Inria, Aramis Team, Paris, France
| | - Pierpaolo Sorrentino
- Institut de Neuroscience des Systèmes, Aix-Marseille University, Inserm, Marseille, France
| | - Denis Schwartz
- Institut du Cerveau - Paris Brain Institute, ICM, Inserm U 1127, CNRS UMR 7225, Sorbonne Université, CENIR, Centre MEG-EEG, Paris, France
| | - Nathalie George
- Sorbonne Université, Institut du cerveau - Paris Brain Institute - ICM, CNRS, Inserm, APHP, Hôpital de la Pitié Salpêtrière, Paris, France
- Institut du Cerveau - Paris Brain Institute, ICM, Inserm U 1127, CNRS UMR 7225, Sorbonne Université, CENIR, Centre MEG-EEG, Paris, France
| | - Leonardo L. Gollo
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria 3168, Australia
| | | | - Laurent Hugueville
- Institut de Neuroscience des Systèmes, Aix-Marseille University, Inserm, Marseille, France
| | - Ari E. Kahn
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, USA
| | - Sophie Dupont
- Sorbonne Université, Institut du cerveau - Paris Brain Institute - ICM, CNRS, Inserm, APHP, Hôpital de la Pitié Salpêtrière, Paris, France
| | | | - Viktor Jirsa
- Institut de Neuroscience des Systèmes, Aix-Marseille University, Inserm, Marseille, France
| | - Fabrizio De Vico Fallani
- Sorbonne Université, Institut du cerveau - Paris Brain Institute - ICM, CNRS, Inserm, APHP, Hôpital de la Pitié Salpêtrière, Paris, France
- Inria, Aramis Team, Paris, France
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14
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Dimitriadis SI, Routley B, Linden DEJ, Singh KD. Multiplexity of human brain oscillations as a personal brain signature. Hum Brain Mapp 2023; 44:5624-5640. [PMID: 37668332 PMCID: PMC10619372 DOI: 10.1002/hbm.26466] [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: 02/06/2023] [Revised: 07/11/2023] [Accepted: 08/08/2023] [Indexed: 09/06/2023] Open
Abstract
Human individuality is likely underpinned by the constitution of functional brain networks that ensure consistency of each person's cognitive and behavioral profile. These functional networks should, in principle, be detectable by noninvasive neurophysiology. We use a method that enables the detection of dominant frequencies of the interaction between every pair of brain areas at every temporal segment of the recording period, the dominant coupling modes (DoCM). We apply this method to brain oscillations, measured with magnetoencephalography (MEG) at rest in two independent datasets, and show that the spatiotemporal evolution of DoCMs constitutes an individualized brain fingerprint. Based on this successful fingerprinting we suggest that DoCMs are important targets for the investigation of neural correlates of individual psychological parameters and can provide mechanistic insight into the underlying neurophysiological processes, as well as their disturbance in brain diseases.
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Affiliation(s)
- Stavros I. Dimitriadis
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffWalesUK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of MedicineCardiff UniversityCardiffWalesUK
- Department of Clinical Psychology and PsychobiologyUniversity of BarcelonaBarcelonaSpain
| | - B. Routley
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffWalesUK
| | - David E. J. Linden
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffWalesUK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of MedicineCardiff UniversityCardiffWalesUK
- School for Mental Health and Neuroscience, Faculty of Health Medicine and Life SciencesMaastricht UniversityMaastrichtThe Netherlands
| | - Krish D. Singh
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffWalesUK
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15
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Romano A, Troisi Lopez E, Cipriano L, Liparoti M, Minino R, Polverino A, Cavaliere C, Aiello M, Granata C, Sorrentino G, Sorrentino P. Topological changes of fast large-scale brain dynamics in mild cognitive impairment predict early memory impairment: a resting-state, source reconstructed, magnetoencephalography study. Neurobiol Aging 2023; 132:36-46. [PMID: 37717553 DOI: 10.1016/j.neurobiolaging.2023.08.003] [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: 11/22/2022] [Revised: 08/08/2023] [Accepted: 08/10/2023] [Indexed: 09/19/2023]
Abstract
Functional connectivity has been used as a framework to investigate widespread brain interactions underlying cognitive deficits in mild cognitive impairment (MCI). However, many functional connectivity metrics focus on the average of the periodic activities, disregarding the aperiodic bursts of activity (i.e., the neuronal avalanches) characterizing the large-scale dynamic activities of the brain. Here, we apply the recently described avalanche transition matrix framework to source-reconstructed magnetoencephalography signals in a cohort of 32 MCI patients and 32 healthy controls to describe the spatio-temporal features of neuronal avalanches and explore their topological properties. Our results showed that MCI patients showed a more centralized network (as assessed by higher values of the degree divergence and leaf fraction) as compared to healthy controls. Furthermore, we found that the degree divergence (in the theta band) was predictive of hippocampal memory impairment. These findings highlight the role of the changes of aperiodic bursts in clinical conditions and may contribute to a more thorough phenotypical assessment of patients.
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Affiliation(s)
- Antonella Romano
- Department of Motor and Wellness Sciences, University of Naples "Parthenope", Naples, Italy
| | - Emahnuel Troisi Lopez
- Department of Motor and Wellness Sciences, University of Naples "Parthenope", Naples, Italy
| | - Lorenzo Cipriano
- Department of Motor and Wellness Sciences, University of Naples "Parthenope", Naples, Italy
| | - Marianna Liparoti
- Department of Developmental and Social Psychology, University of Rome "La Sapienza", Rome, Italy
| | - Roberta Minino
- Department of Motor and Wellness Sciences, University of Naples "Parthenope", Naples, Italy
| | - Arianna Polverino
- Institute of Diagnosis and Treatment, Hermitage Capodimonte, Naples, Italy
| | - Carlo Cavaliere
- IRCCS SYNLAB-SDN, Naples Via Emanuele Gianturco, Naples, Italy
| | - Marco Aiello
- IRCCS SYNLAB-SDN, Naples Via Emanuele Gianturco, Naples, Italy
| | - Carmine Granata
- Institute of Applied Sciences and Intelligent Systems, National Research Council, Pozzuoli, Italy
| | - Giuseppe Sorrentino
- Department of Motor and Wellness Sciences, University of Naples "Parthenope", Naples, Italy; Institute of Diagnosis and Treatment, Hermitage Capodimonte, Naples, Italy; Institute of Applied Sciences and Intelligent Systems, National Research Council, Pozzuoli, Italy.
| | - Pierpaolo Sorrentino
- Institute of Applied Sciences and Intelligent Systems, National Research Council, Pozzuoli, Italy; Institut de Neurosciences des Systèmes, Inserm, INS, Aix-Marseille University, Marseille, France
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16
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Rabus A, Curic D, Ivan VE, Esteves IM, Gruber AJ, Davidsen J. Changes in functional connectivity preserve scale-free neuronal and behavioral dynamics. Phys Rev E 2023; 108:L052301. [PMID: 38115411 DOI: 10.1103/physreve.108.l052301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 09/06/2023] [Indexed: 12/21/2023]
Abstract
Does the brain optimize itself for storage and transmission of information, and if so, how? The critical brain hypothesis is based in statistical physics and posits that the brain self-tunes its dynamics to a critical point or regime to maximize the repertoire of neuronal responses. Yet, the robustness of this regime, especially with respect to changes in the functional connectivity, remains an unsolved fundamental challenge. Here, we show that both scale-free neuronal dynamics and self-similar features of behavioral dynamics persist following significant changes in functional connectivity. Specifically, we find that the psychedelic compound ibogaine that is associated with an altered state of consciousness fundamentally alters the functional connectivity in the retrosplenial cortex of mice. Yet, the scale-free statistics of movement and of neuronal avalanches among behaviorally related neurons remain largely unaltered. This indicates that the propagation of information within biological neural networks is robust to changes in functional organization of subpopulations of neurons, opening up a new perspective on how the adaptive nature of functional networks may lead to optimality of information transmission in the brain.
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Affiliation(s)
- Anja Rabus
- Complexity Science Group, Department of Physics and Astronomy University of Calgary, Calgary, Alberta, Canada T2N 1N4
| | - Davor Curic
- Complexity Science Group, Department of Physics and Astronomy University of Calgary, Calgary, Alberta, Canada T2N 1N4
| | - Victorita E Ivan
- Canadian Centre for Behavioral Neuroscience University of Lethbridge, Lethbridge, Alberta, Canada T1K 3M4
| | - Ingrid M Esteves
- Canadian Centre for Behavioral Neuroscience University of Lethbridge, Lethbridge, Alberta, Canada T1K 3M4
| | - Aaron J Gruber
- Canadian Centre for Behavioral Neuroscience University of Lethbridge, Lethbridge, Alberta, Canada T1K 3M4
| | - Jörn Davidsen
- Complexity Science Group, Department of Physics and Astronomy University of Calgary, Calgary, Alberta, Canada T2N 1N4
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada T2N 4N1
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17
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Maschke C, O'Byrne J, Colombo MA, Boly M, Gosseries O, Laureys S, Rosanova M, Jerbi K, Blain-Moraes S. Criticality of resting-state EEG predicts perturbational complexity and level of consciousness during anesthesia. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.26.564247. [PMID: 37994368 PMCID: PMC10664178 DOI: 10.1101/2023.10.26.564247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
Consciousness has been proposed to be supported by electrophysiological patterns poised at criticality, a dynamical regime which exhibits adaptive computational properties, maximally complex patterns and divergent sensitivity to perturbation. Here, we investigated dynamical properties of the resting-state electroencephalogram of healthy subjects undergoing general anesthesia with propofol, xenon or ketamine. We then studied the relation of these dynamic properties with the perturbational complexity index (PCI), which has shown remarkably high sensitivity in detecting consciousness independent of behavior. All participants were unresponsive under anesthesia, while consciousness was retained only during ketamine anesthesia (in the form of vivid dreams)., enabling an experimental dissociation between unresponsiveness and unconsciousness. We estimated (i) avalanche criticality, (ii) chaoticity, and (iii) criticality-related measures, and found that states of unconsciousness were characterized by a distancing from both the edge of activity propagation and the edge of chaos. We were then able to predict individual subjects' PCI (i.e., PCImax) with a mean absolute error below 7%. Our results establish a firm link between the PCI and criticality and provide further evidence for the role of criticality in the emergence of consciousness.
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Affiliation(s)
- Charlotte Maschke
- Montreal General Hospital, McGill University Health Centre, Montreal, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Canada
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Québec, Canada
| | - Jordan O'Byrne
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Québec, Canada
- MILA (Québec Artificial Intelligence Institute), Montréal, Québec, Canada
| | | | - Melanie Boly
- Department of Neurology and Department of Psychiatry, University of Wisconsin, Madison, USA
| | - Olivia Gosseries
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre du cerveau, CHU of Liège, Liège, Belgium
| | - Steven Laureys
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- CERVO Brain Research Centre, Laval University, Canada
- Consciousness Science Institute, Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Karim Jerbi
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Québec, Canada
- MILA (Québec Artificial Intelligence Institute), Montréal, Québec, Canada
- Centre UNIQUE (Union Neurosciences & Intelligence Artificielle), Montréal, Québec, Canada
| | - Stefanie Blain-Moraes
- Montreal General Hospital, McGill University Health Centre, Montreal, Canada
- School of Physical and Occupational Therapy, McGill University, Montreal, Canada
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18
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Pontone GM, McDaniels B, Keener AM, Subramanian I. A Wellness Prescription for Parkinson's: Mid to Late-Stage Disease. Am J Geriatr Psychiatry 2023; 31:737-747. [PMID: 37005185 DOI: 10.1016/j.jagp.2023.02.049] [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: 01/29/2023] [Revised: 02/22/2023] [Accepted: 02/23/2023] [Indexed: 04/04/2023]
Abstract
The mid- to late-stages of Parkinson's disease (PD) bring increasing disability that may challenge independence and lower quality of life. Many people with PD struggle to remain hopeful and cope with an uncertain future due to the progression of the disease. Although disability in PD is due chiefly to motor impairment, nonmotor symptoms and psychosocial distress are also major contributors that are amenable to treatment. Interventions that address nonmotor symptoms and psychosocial distress can improve daily function and quality of life even as motor function worsens with disease progression. This manuscript proposes a patient-centered, proactive strategy to promote psychosocial adaptation to decrease the impact of motor, nonmotor, and psychosocial distress on quality of life and function in people with PD.
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Affiliation(s)
- Gregory M Pontone
- Department of Psychiatry and Neurology (GMP), Johns Hopkins University School of Medicine, Baltimore, MD.
| | - Bradley McDaniels
- Department of Rehabilitation and Health Services (BM), University of North Texas, Denton, TX
| | - Adrienne M Keener
- Department of Neurology (AMK, IS), David Geffen School of Medicine, UCLA, Los Angeles, CA; PADRECC (AMK, IS), West Los Angeles Veterans Administration, Los Angeles, CA
| | - Indu Subramanian
- Department of Neurology (AMK, IS), David Geffen School of Medicine, UCLA, Los Angeles, CA; PADRECC (AMK, IS), West Los Angeles Veterans Administration, Los Angeles, CA
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19
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Pierrieau E, Berret B, Lepage JF, Bernier PM. From Motivation to Action: Action Cost Better Predicts Changes in Premovement Beta-Band Activity than Speed. J Neurosci 2023; 43:5264-5275. [PMID: 37339875 PMCID: PMC10342222 DOI: 10.1523/jneurosci.0213-23.2023] [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: 02/04/2023] [Revised: 05/03/2023] [Accepted: 06/06/2023] [Indexed: 06/22/2023] Open
Abstract
Although premovement beta-band event-related desynchronization (β-ERD; 13-30 Hz) from sensorimotor regions is modulated by movement speed, current evidence does not support a strict monotonic association between the two. Given that β-ERD is thought to increase information encoding capacity, we tested the hypothesis that it might be related to the expected neurocomputational cost of movement, here referred to as action cost. Critically, action cost is greater both for slow and fast movements compared with a medium or "preferred" speed. Thirty-one right-handed participants performed a speed-controlled reaching task while recording their EEG. Results revealed potent modulations of beta power as a function of speed, with β-ERD being significantly greater both for movements performed at high and low speeds compared with medium speed. Interestingly, medium-speed movements were more often chosen by participants than low-speed and high-speed movements, suggesting that they were evaluated as less costly. In line with this, modeling of action cost revealed a pattern of modulation across speed conditions that strikingly resembled the one found for β-ERD. Indeed, linear mixed models showed that estimated action cost predicted variations of β-ERD significantly better than speed. This relationship with action cost was specific to beta power, as it was not found when averaging activity in the mu band (8-12 Hz) and gamma band (31-49 Hz) bands. These results demonstrate that increasing β-ERD may not merely speed up movements, but instead facilitate the preparation of high-speed and low-speed movements through the allocation of additional neural resources, thereby enabling flexible motor control.SIGNIFICANCE STATEMENT Heightened beta activity has been associated with movement slowing in Parkinson's disease, and modulations of beta activity are commonly used to decode movement parameters in brain-computer interfaces. Here we show that premovement beta activity is better explained by the neurocomputational cost of the action rather than its speed. Instead of being interpreted as a mere reflection of changes in movement speed, premovement changes in beta activity might therefore be used to infer the amount of neural resources that are allocated for motor planning.
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Affiliation(s)
- Emeline Pierrieau
- Programme de Physiologie, Faculté de Médecine et des Sciences de la Santé, Université de Sherbrooke, Sherbrooke, Québec J1H 5N4, Canada
| | - Bastien Berret
- CIAMS (Complexité, Innovation, Activités, Motrices, et Sportives), Université Paris-Saclay, 91405 Orsay, France
- CIAMS (Complexité, Innovation, Activités, Motrices, et Sportives), Université d'Orléans, 45067 Orléans, France
- Institut Universitaire de France, 75231 Paris, France
| | - Jean-François Lepage
- Programme de Physiologie, Faculté de Médecine et des Sciences de la Santé, Université de Sherbrooke, Sherbrooke, Québec J1H 5N4, Canada
- Département de Pédiatrie, Faculté de Médecine et des Sciences de la Santé, Université de Sherbrooke, Sherbrooke, Québec J1H 5N4, Canada
| | - Pierre-Michel Bernier
- Département de Kinanthropologie, Faculté des Sciences de l'Activité Physique, Université de Sherbrooke, Sherbrooke, Québec J1K 2R1, Canada
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20
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Sorrentino P, Lopez ET, Romano A, Granata C, Corsi MC, Sorrentino G, Jirsa V. Brain fingerprint is based on the aperiodic, scale-free, neuronal activity. Neuroimage 2023:120260. [PMID: 37392807 DOI: 10.1016/j.neuroimage.2023.120260] [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: 03/01/2023] [Revised: 06/13/2023] [Accepted: 06/28/2023] [Indexed: 07/03/2023] Open
Abstract
Subject differentiation bears the possibility to individualize brain analyses. However, the nature of the processes generating subject-specific features remains unknown. Most of the current literature uses techniques that assume stationarity (e.g., Pearson's correlation), which might fail to capture the non-linear nature of brain activity. We hypothesize that non-linear perturbations (defined as neuronal avalanches in the context of critical dynamics) spread across the brain and carry subject-specific information, contributing the most to differentiability. To test this hypothesis, we compute the avalanche transition matrix (ATM) from source-reconstructed magnetoencephalographic data, as to characterize subject-specific fast dynamics. We perform differentiability analysis based on the ATMs, and compare the performance to that obtained using Pearson's correlation (which assumes stationarity). We demonstrate that selecting the moments and places where neuronal avalanches spread improves differentiation (P < 0.0001, permutation testing), despite the fact that most of the data (i.e., the linear part) are discarded. Our results show that the non-linear part of the brain signals carries most of the subject-specific information, thereby clarifying the nature of the processes that underlie individual differentiation. Borrowing from statistical mechanics, we provide a principled way to link emergent large-scale personalized activations to non-observable, microscopic processes.
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Affiliation(s)
- Pierpaolo Sorrentino
- Institut de Neurosciences des Systèmes, Aix-Marseille Universitè, Marseille, France; Institute of Applied Sciences and Intelligent Systems, CNR, Naples, Italy.
| | - Emahnuel Troisi Lopez
- Institute of Applied Sciences and Intelligent Systems, CNR, Naples, Italy; Department of Motor Sciences and Wellness, University of Naples "Parthenope", Naples, Italy
| | - Antonella Romano
- Department of Motor Sciences and Wellness, University of Naples "Parthenope", Naples, Italy
| | - Carmine Granata
- Institute of Applied Sciences and Intelligent Systems, CNR, Naples, Italy
| | - Marie Constance Corsi
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière, F-75013, Paris, France
| | - Giuseppe Sorrentino
- Institute of Applied Sciences and Intelligent Systems, CNR, Naples, Italy; Department of Motor Sciences and Wellness, University of Naples "Parthenope", Naples, Italy; Institute of Diagnosis and Treatment Hermitage Capodimonte, Naples, Italy
| | - Viktor Jirsa
- Institut de Neurosciences des Systèmes, Aix-Marseille Universitè, Marseille, France
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21
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Duma GM, Danieli A, Mento G, Vitale V, Opipari RS, Jirsa V, Bonanni P, Sorrentino P. Altered spreading of neuronal avalanches in temporal lobe epilepsy relates to cognitive performance: A resting-state hdEEG study. Epilepsia 2023; 64:1278-1288. [PMID: 36799098 DOI: 10.1111/epi.17551] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 02/15/2023] [Accepted: 02/15/2023] [Indexed: 02/18/2023]
Abstract
OBJECTIVE Large aperiodic bursts of activations named neuronal avalanches have been used to characterize whole-brain activity, as their presence typically relates to optimal dynamics. Epilepsy is characterized by alterations in large-scale brain network dynamics. Here we exploited neuronal avalanches to characterize differences in electroencephalography (EEG) basal activity, free from seizures and/or interictal spikes, between patients with temporal lobe epilepsy (TLE) and matched controls. METHOD We defined neuronal avalanches as starting when the z-scored source-reconstructed EEG signals crossed a specific threshold in any region and ending when all regions returned to baseline. This technique avoids data manipulation or assumptions of signal stationarity, focusing on the aperiodic, scale-free components of the signals. We computed individual avalanche transition matrices to track the probability of avalanche spreading across any two regions, compared them between patients and controls, and related them to memory performance in patients. RESULTS We observed a robust topography of significant edges clustering in regions functionally and structurally relevant for the TLE, such as the entorhinal cortex, the inferior parietal and fusiform area, the inferior temporal gyrus, and the anterior cingulate cortex. We detected a significant correlation between the centrality of the entorhinal cortex in the transition matrix and the long-term memory performance (delay recall Rey-Osterrieth Complex Figure Test). SIGNIFICANCE Our results show that the propagation patterns of large-scale neuronal avalanches are altered in TLE during the resting state, suggesting a potential diagnostic application in epilepsy. Furthermore, the relationship between specific patterns of propagation and memory performance support the neurophysiological relevance of neuronal avalanches.
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Affiliation(s)
- Gian Marco Duma
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Treviso, Italy
| | - Alberto Danieli
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Treviso, Italy
| | - Giovanni Mento
- Department of General Psychology, University of Padova, Padova, Italy.,Padova Neuroscience Center (PNC), University of Padova, Padova, Italy
| | - Valerio Vitale
- Department of Neuroscience, Neuroradiology Unit, San Bortolo Hospital, Vicenza, Italy
| | | | - Viktor Jirsa
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille, France
| | - Paolo Bonanni
- Epilepsy Unit, IRCCS E. Medea Scientific Institute, Treviso, Italy
| | - Pierpaolo Sorrentino
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille, France
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22
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Sorrentino P, Rabuffo G, Baselice F, Troisi Lopez E, Liparoti M, Quarantelli M, Sorrentino G, Bernard C, Jirsa V. Dynamical interactions reconfigure the gradient of cortical timescales. Netw Neurosci 2023; 7:73-85. [PMID: 37334007 PMCID: PMC10270712 DOI: 10.1162/netn_a_00270] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 07/14/2022] [Indexed: 09/18/2023] Open
Abstract
The functional organization of the brain is usually presented with a back-to-front gradient of timescales, reflecting regional specialization with sensory areas (back) processing information faster than associative areas (front), which perform information integration. However, cognitive processes require not only local information processing but also coordinated activity across regions. Using magnetoencephalography recordings, we find that the functional connectivity at the edge level (between two regions) is also characterized by a back-to-front gradient of timescales following that of the regional gradient. Unexpectedly, we demonstrate a reverse front-to-back gradient when nonlocal interactions are prominent. Thus, the timescales are dynamic and can switch between back-to-front and front-to-back patterns.
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Affiliation(s)
- P. Sorrentino
- Institut de Neurosciences des Systèmes, Aix-Marseille University, Marseille, France
- Institute of Applied Sciences and Intelligent Systems, National Research Council, Pozzuoli, Italy
| | - G. Rabuffo
- Institut de Neurosciences des Systèmes, Aix-Marseille University, Marseille, France
| | - F. Baselice
- Department of Engineering, Parthenope University of Naples, Naples, Italy
| | - E. Troisi Lopez
- Department of Motor Sciences and Wellness, Parthenope University of Naples, Naples, Italy
- Institute for Diagnosis and Cure Hermitage Capodimonte, Naples, Italy
| | - M. Liparoti
- Department of Motor Sciences and Wellness, Parthenope University of Naples, Naples, Italy
- Institute for Diagnosis and Cure Hermitage Capodimonte, Naples, Italy
| | - M. Quarantelli
- Biostructure and Bioimaging Institute, National Research Council, Naples, Italy
| | - G. Sorrentino
- Institute of Applied Sciences and Intelligent Systems, National Research Council, Pozzuoli, Italy
- Institute for Diagnosis and Cure Hermitage Capodimonte, Naples, Italy
| | - C. Bernard
- Institut de Neurosciences des Systèmes, Aix-Marseille University, Marseille, France
| | - V. Jirsa
- Institut de Neurosciences des Systèmes, Aix-Marseille University, Marseille, France
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23
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Sorrentino P, Petkoski S, Sparaco M, Troisi Lopez E, Signoriello E, Baselice F, Bonavita S, Pirozzi MA, Quarantelli M, Sorrentino G, Jirsa V. Whole-Brain Propagation Delays in Multiple Sclerosis, a Combined Tractography-Magnetoencephalography Study. J Neurosci 2022; 42:8807-8816. [PMID: 36241383 PMCID: PMC9698668 DOI: 10.1523/jneurosci.0938-22.2022] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 09/13/2022] [Accepted: 09/19/2022] [Indexed: 12/29/2022] Open
Abstract
Two structurally connected brain regions are more likely to interact, with the lengths of the structural bundles, their widths, myelination, and the topology of the structural connectome influencing the timing of the interactions. We introduce an in vivo approach for measuring functional delays across the whole brain in humans (of either sex) using magneto/electroencephalography (MEG/EEG) and integrating them with the structural bundles. The resulting topochronic map of the functional delays/velocities shows that larger bundles have faster velocities. We estimated the topochronic map in multiple sclerosis patients, who have damaged myelin sheaths, and controls, demonstrating greater delays in patients across the network and that structurally lesioned tracts were slowed down more than unaffected ones. We provide a novel framework for estimating functional transmission delays in vivo at the single-subject and single-tract level.SIGNIFICANCE STATEMENT This article provides a straightforward way to estimate patient-specific delays and conduction velocities in the CNS, at the individual level, in healthy and diseased subjects. To do so, it uses a principled way to merge magnetoencephalography (MEG)/electroencephalography (EEG) and tractography.
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Affiliation(s)
- P Sorrentino
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, 13005 Marseille, France
- Institute of Applied Sciences and Intelligent Systems, National Research Council, 80078 Pozzuoli, Italy
| | - S Petkoski
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, 13005 Marseille, France
| | - M Sparaco
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, 81100 Caserta, Italy
| | - E Troisi Lopez
- Department of Motor Sciences and Wellness, Parthenope University of Naples, 80133 Naples, Italy
| | - E Signoriello
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, 81100 Caserta, Italy
| | - F Baselice
- Department of Engineering, Parthenope University of Naples, 80143 Naples, Italy
| | - S Bonavita
- Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, 81100 Caserta, Italy
| | - M A Pirozzi
- Biostructure and Bioimaging Institute, National Research Council, 80145 Naples, Italy
| | - M Quarantelli
- Biostructure and Bioimaging Institute, National Research Council, 80145 Naples, Italy
| | - G Sorrentino
- Department of Motor Sciences and Wellness, Parthenope University of Naples, 80133 Naples, Italy
- Institute for Diagnosis and Cure Hermitage Capodimonte, 80131 Naples, Italy
| | - V Jirsa
- Institut de Neurosciences des Systèmes, Aix-Marseille Université, 13005 Marseille, France
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24
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Troisi Lopez E, Minino R, Liparoti M, Polverino A, Romano A, De Micco R, Lucidi F, Tessitore A, Amico E, Sorrentino G, Jirsa V, Sorrentino P. Fading of brain network fingerprint in Parkinson's disease predicts motor clinical impairment. Hum Brain Mapp 2022; 44:1239-1250. [PMID: 36413043 PMCID: PMC9875937 DOI: 10.1002/hbm.26156] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 10/18/2022] [Accepted: 11/10/2022] [Indexed: 11/23/2022] Open
Abstract
The clinical connectome fingerprint (CCF) was recently introduced as a way to assess brain dynamics. It is an approach able to recognize individuals, based on the brain network. It showed its applicability providing network features used to predict the cognitive decline in preclinical Alzheimer's disease. In this article, we explore the performance of CCF in 47 Parkinson's disease (PD) patients and 47 healthy controls, under the hypothesis that patients would show reduced identifiability as compared to controls, and that such reduction could be used to predict motor impairment. We used source-reconstructed magnetoencephalography signals to build two functional connectomes for 47 patients with PD and 47 healthy controls. Then, exploiting the two connectomes per individual, we investigated the identifiability characteristics of each subject in each group. We observed reduced identifiability in patients compared to healthy individuals in the beta band. Furthermore, we found that the reduction in identifiability was proportional to the motor impairment, assessed through the Unified Parkinson's Disease Rating Scale, and, interestingly, able to predict it (at the subject level), through a cross-validated regression model. Along with previous evidence, this article shows that CCF captures disrupted dynamics in neurodegenerative diseases and is particularly effective in predicting motor clinical impairment in PD.
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Affiliation(s)
- Emahnuel Troisi Lopez
- Department of Motor Sciences and WellnessUniversity of Naples “Parthenope”NaplesItaly
| | - Roberta Minino
- Department of Motor Sciences and WellnessUniversity of Naples “Parthenope”NaplesItaly
| | - Marianna Liparoti
- Department of Developmental and Social PsychologyUniversity "La Sapienza" of RomeRomeItaly
| | - Arianna Polverino
- Institute for Diagnosis and Treatment Hermitage CapodimonteNaplesItaly
| | - Antonella Romano
- Department of Motor Sciences and WellnessUniversity of Naples “Parthenope”NaplesItaly
| | - Rosa De Micco
- Department of Advanced Medical and Surgical SciencesUniversity of Campania “Luigi Vanvitelli”NaplesItaly
| | - Fabio Lucidi
- Department of Developmental and Social PsychologyUniversity "La Sapienza" of RomeRomeItaly
| | - Alessandro Tessitore
- Department of Advanced Medical and Surgical SciencesUniversity of Campania “Luigi Vanvitelli”NaplesItaly
| | - Enrico Amico
- Institute of Bioengineering, Center for Neuroprosthetics, EPFLGenevaSwitzerland,Department of Radiology and Medical InformaticsUniversity of Geneva (UNIGE)GenevaSwitzerland
| | - Giuseppe Sorrentino
- Department of Motor Sciences and WellnessUniversity of Naples “Parthenope”NaplesItaly,Institute for Diagnosis and Treatment Hermitage CapodimonteNaplesItaly,Institute of Applied Sciences and Intelligent Systems, National Research CouncilNaplesItaly
| | - Viktor Jirsa
- Institut de Neurosciences des SystèmesAix‐Marseille UniversitéMarseilleFrance
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25
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Rabuffo G, Sorrentino P, Bernard C, Jirsa V. Spontaneous neuronal avalanches as a correlate of access consciousness. Front Psychol 2022; 13:1008407. [PMID: 36337573 PMCID: PMC9634647 DOI: 10.3389/fpsyg.2022.1008407] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Accepted: 10/04/2022] [Indexed: 09/03/2023] Open
Abstract
Decades of research have advanced our understanding of the biophysical mechanisms underlying consciousness. However, an overarching framework bridging between models of consciousness and the large-scale organization of spontaneous brain activity is still missing. Based on the observation that spontaneous brain activity dynamically switches between epochs of segregation and large-scale integration of information, we hypothesize a brain-state dependence of conscious access, whereby the presence of either segregated or integrated states marks distinct modes of information processing. We first review influential works on the neuronal correlates of consciousness, spontaneous resting-state brain activity and dynamical system theory. Then, we propose a test experiment to validate our hypothesis that conscious access occurs in aperiodic cycles, alternating windows where new incoming information is collected but not experienced, to punctuated short-lived integration events, where conscious access to previously collected content occurs. In particular, we suggest that the integration events correspond to neuronal avalanches, which are collective bursts of neuronal activity ubiquitously observed in electrophysiological recordings. If confirmed, the proposed framework would link the physics of spontaneous cortical dynamics, to the concept of ignition within the global neuronal workspace theory, whereby conscious access manifest itself as a burst of neuronal activity.
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Affiliation(s)
- Giovanni Rabuffo
- Institut de Neurosciences des Systemes, Aix-Marseille University, Marseille, France
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26
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Troisi Lopez E, Colonnello V, Liparoti M, Castaldi M, Alivernini F, Russo PM, Sorrentino G, Lucidi F, Mandolesi L, Sorrentino P. Brain network topology and personality traits: A source level magnetoencephalographic study. Scand J Psychol 2022; 63:495-503. [PMID: 35674278 PMCID: PMC9796445 DOI: 10.1111/sjop.12835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 04/08/2022] [Accepted: 05/04/2022] [Indexed: 01/01/2023]
Abstract
Personality neuroscience is focusing on the correlation between individual differences and the efficiency of large-scale networks from the perspective of the brain as an interconnected network. A suitable technique to explore this relationship is the magnetoencephalography (MEG), but not many MEG studies are aimed at investigating topological properties correlated to personality traits. By using MEG, the present study aims to evaluate how individual differences described in Cloninger's psychobiological model are correlated with specific cerebral structures. Fifty healthy individuals (20 males, 30 females, mean age: 27.4 ± 4.8 years) underwent Temperament and Character Inventory examination and MEG recording during a resting state condition. High harm avoidance scores were associated with a reduced centrality of the left caudate nucleus and this negative correlation was maintained in females when we analyzed gender differences. Our data suggest that the caudate nucleus plays a key role in adaptive behavior and could be a critical node in insular salience network. The clear difference between males and females allows us to suggest that topological organization correlated to personality is highly dependent on gender. Our findings provide new insights to evaluate the mutual influences of topological and functional connectivity in neural communication efficiency and disruption as biomarkers of psychopathological traits.
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Affiliation(s)
- Emahnuel Troisi Lopez
- Department of Motor Sciences and WellnessUniversity of Naples “Parthenope”NaplesItaly
| | - Valentina Colonnello
- Department of Experimental, Diagnostic and Specialty Medicine, Alma Mater StudiorumUniversity of Bologna, Policlinico S. Orsola‐MalpighiBolognaItaly
| | - Marianna Liparoti
- Department of Social and Developmental Psychology, Faculty of Medicine and PsychologyUniversity of Roma “Sapienza”RomeItaly
| | - Mauro Castaldi
- Institute for Diagnosis and Cure Hermitage CapodimonteNaplesItaly
| | - Fabio Alivernini
- Department of Social and Developmental Psychology, Faculty of Medicine and PsychologyUniversity of Roma “Sapienza”RomeItaly
| | - Paolo Maria Russo
- Department of Experimental, Diagnostic and Specialty Medicine, Alma Mater StudiorumUniversity of Bologna, Policlinico S. Orsola‐MalpighiBolognaItaly
| | - Giuseppe Sorrentino
- Department of Motor Sciences and WellnessUniversity of Naples “Parthenope”NaplesItaly,Institute for Diagnosis and Cure Hermitage CapodimonteNaplesItaly
| | - Fabio Lucidi
- Department of Social and Developmental Psychology, Faculty of Medicine and PsychologyUniversity of Roma “Sapienza”RomeItaly
| | - Laura Mandolesi
- Department of HumanitiesUniversity of Naples “Federico II”NaplesItaly
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27
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O'Byrne J, Jerbi K. How critical is brain criticality? Trends Neurosci 2022; 45:820-837. [PMID: 36096888 DOI: 10.1016/j.tins.2022.08.007] [Citation(s) in RCA: 54] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 07/27/2022] [Accepted: 08/10/2022] [Indexed: 10/31/2022]
Abstract
Criticality is the singular state of complex systems poised at the brink of a phase transition between order and randomness. Such systems display remarkable information-processing capabilities, evoking the compelling hypothesis that the brain may itself be critical. This foundational idea is now drawing renewed interest thanks to high-density data and converging cross-disciplinary knowledge. Together, these lines of inquiry have shed light on the intimate link between criticality, computation, and cognition. Here, we review these emerging trends in criticality neuroscience, highlighting new data pertaining to the edge of chaos and near-criticality, and making a case for the distance to criticality as a useful metric for probing cognitive states and mental illness. This unfolding progress in the field contributes to establishing criticality theory as a powerful mechanistic framework for studying emergent function and its efficiency in both biological and artificial neural networks.
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Affiliation(s)
- Jordan O'Byrne
- Cognitive and Computational Neuroscience Lab, Psychology Department, University of Montreal, Montreal, Quebec, Canada
| | - Karim Jerbi
- Cognitive and Computational Neuroscience Lab, Psychology Department, University of Montreal, Montreal, Quebec, Canada; MILA (Quebec Artificial Intelligence Institute), Montreal, Quebec, Canada; UNIQUE Center (Quebec Neuro-AI Research Center), Montreal, Quebec, Canada.
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28
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What lies underneath: Precise classification of brain states using time-dependent topological structure of dynamics. PLoS Comput Biol 2022; 18:e1010412. [PMID: 36067227 PMCID: PMC9481177 DOI: 10.1371/journal.pcbi.1010412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 09/16/2022] [Accepted: 07/18/2022] [Indexed: 11/19/2022] Open
Abstract
The self-organising global dynamics underlying brain states emerge from complex recursive nonlinear interactions between interconnected brain regions. Until now, most efforts of capturing the causal mechanistic generating principles have supposed underlying stationarity, being unable to describe the non-stationarity of brain dynamics, i.e. time-dependent changes. Here, we present a novel framework able to characterise brain states with high specificity, precisely by modelling the time-dependent dynamics. Through describing a topological structure associated to the brain state at each moment in time (its attractor or ‘information structure’), we are able to classify different brain states by using the statistics across time of these structures hitherto hidden in the neuroimaging dynamics. Proving the strong potential of this framework, we were able to classify resting-state BOLD fMRI signals from two classes of post-comatose patients (minimally conscious state and unresponsive wakefulness syndrome) compared with healthy controls with very high precision. Brain states emerge through continuously evolving dynamics of brain networks. The usual way of modelling these dynamics is by using stationary systems: there is one structure (attractor) which is responsible of the brain dynamics. We adopt a different approach by characterising the brain activity through a landscape of informational structures (IS) changing in time. We use a model transformation procedure to produce these structures and look at several properties related to how the different brain networks interact not in the observed resting-state fMRI signal but in the information structure underlying it. These properties provide measures strongly related with relevant characteristics of conscious activity, such as metastability, information integration or synchronisation. The distribution of IS measures is studied for healthy controls (HC) and two groups of post-comatose patients with disorders of consciousness (DOC): minimally conscious state (MCS) and unresponsive wakefulness syndrome (UWS). Based on IS measures, machine learners classifiers identify the state of consciousness with an outstanding discrimination (precision of 95.6% por HC/DOC and 86.6% for MCS/UWS).
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29
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Enhanced brain network flexibility by physical exercise in female methamphetamine users. Cogn Neurodyn 2022. [DOI: 10.1007/s11571-022-09848-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
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30
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Romano A, Trosi Lopez E, Liparoti M, Polverino A, Minino R, Trojsi F, Bonavita S, Mandolesi L, Granata C, Amico E, Sorrentino G, Sorrentino P. The progressive loss of brain network fingerprints in Amyotrophic Lateral Sclerosis predicts clinical impairment. Neuroimage Clin 2022; 35:103095. [PMID: 35764029 PMCID: PMC9241102 DOI: 10.1016/j.nicl.2022.103095] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 05/31/2022] [Accepted: 06/19/2022] [Indexed: 10/25/2022]
Abstract
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterised by functional connectivity alterations in both motor and extra-motor brain regions. Within the framework of network analysis, fingerprinting represents a reliable approach to assess subject-specific connectivity features within a given population (healthy or diseased). Here, we applied the Clinical Connectome Fingerprint (CCF) analysis to source-reconstructed magnetoencephalography (MEG) signals in a cohort of seventy-eight subjects: thirty-nine ALS patients and thirty-nine healthy controls. We set out to develop an identifiability matrix to assess the extent to which each patient was recognisable based on his/her connectome, as compared to healthy controls. The analysis was performed in the five canonical frequency bands. Then, we built a multilinear regression model to test the ability of the "clinical fingerprint" to predict the clinical evolution of the disease, as assessed by the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-r), the King's disease staging system, and the Milano-Torino Staging (MiToS) disease staging system. We found a drop in the identifiability of patients in the alpha band compared to the healthy controls. Furthermore, the "clinical fingerprint" was predictive of the ALSFRS-r (p = 0.0397; β = 32.8), the King's (p = 0.0001; β = -7.40), and the MiToS (p = 0.0025; β = -4.9) scores. Accordingly, it negatively correlated with the King's (Spearman's rho = -0.6041, p = 0.0003) and MiToS scales (Spearman's rho = -0.4953, p = 0.0040). Our results demonstrated the ability of the CCF approach to predict the individual motor impairment in patients affected by ALS. Given the subject-specificity of our approach, we hope to further exploit it to improve disease management.
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Affiliation(s)
- Antonella Romano
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy
| | - Emahnuel Trosi Lopez
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy
| | - Marianna Liparoti
- Department of Social and Developmental Psychology, University of Rome "Sapienza", Italy
| | - Arianna Polverino
- Institute of Diagnosis and Treatment Hermitage Capodimonte, via Cupa delle Tozzole 2, 80131 Naples, Italy
| | - Roberta Minino
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy
| | - Francesca Trojsi
- Department of Advanced Medical and Surgical Sciences, Division of Neurology, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Simona Bonavita
- Department of Advanced Medical and Surgical Sciences, Division of Neurology, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Laura Mandolesi
- Department of Humanistic Studies, University of Naples Federico II, via Porta di Massa 1, 80133, Naples, Italy
| | - Carmine Granata
- Institute of Applied Sciences and Intelligent Systems, CNR, via Campi Flegrei 34, 80078 Pozzuoli, NA, Italy
| | - Enrico Amico
- Institute of Bioengineering, Center for Neuroprosthetics, EPFL, Geneva, Switzerland; Department of Radiology and Medical Informatics, University of Geneva (UNIGE), Geneva, Switzerland
| | - Giuseppe Sorrentino
- Department of Motor Sciences and Wellness - University of Naples "Parthenope", via Medina 40, 80133 Naples, Italy; Institute of Diagnosis and Treatment Hermitage Capodimonte, via Cupa delle Tozzole 2, 80131 Naples, Italy; Institute of Applied Sciences and Intelligent Systems, CNR, via Campi Flegrei 34, 80078 Pozzuoli, NA, Italy.
| | - Pierpaolo Sorrentino
- Institute of Applied Sciences and Intelligent Systems, CNR, via Campi Flegrei 34, 80078 Pozzuoli, NA, Italy; Institut de Neurosciences des Systèmes, Aix-Marseille Université, Marseille, France
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Govaarts R, Beeldman E, Fraschini M, Griffa A, Engels MMA, van Es MA, Veldink JH, van den Berg LH, van der Kooi AJ, Pijnenburg YAL, de Visser M, Stam CJ, Raaphorst J, Hillebrand A. Cortical and subcortical changes in resting-state neuronal activity and connectivity in early symptomatic ALS and advanced frontotemporal dementia. Neuroimage Clin 2022; 34:102965. [PMID: 35217500 PMCID: PMC8867127 DOI: 10.1016/j.nicl.2022.102965] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 02/08/2022] [Accepted: 02/09/2022] [Indexed: 01/17/2023]
Abstract
The objective of this study was to examine if patterns of resting-state brain activity and functional connectivity in cortical and subcortical regions in patients with early symptomatic amyotrophic lateral sclerosis (ALS) resemble those of behavioural variant frontotemporal dementia (bvFTD). In a cross-sectional design, eyes-closed resting-state magnetoencephalography (MEG) data of 34 ALS patients, 18 bvFTD patients and 18 age- and gender-matched healthy controls (HCs) were projected to source-space using an atlas-based beamformer. Group differences in peak frequency, band-specific oscillatory activity and functional connectivity (corrected amplitude envelope correlation) in 78 cortical regions and 12 subcortical regions were determined. False discovery rate was used to correct for multiple comparisons. BvFTD patients, as compared to ALS and HCs, showed lower relative beta power in parietal, occipital, temporal and nearly all subcortical regions. Compared to HCs, patients with ALS and patients with bvFTD had a higher delta (0.5-4 Hz) and gamma (30-48 Hz) band resting-state functional connectivity in a high number of overlapping regions in the frontal lobe and in limbic and subcortical regions. Higher delta band connectivity was widespread in the bvFTD patients compared to HCs. ALS showed a more widespread higher gamma band functional connectivity compared to bvFTD. In conclusion, MEG in early symptomatic ALS patients shows resting-state functional connectivity changes in frontal, limbic and subcortical regions that overlap considerably with bvFTD. The findings show the potential of MEG to detect brain changes in early symptomatic phases of ALS and contribute to our understanding of the disease spectrum, with ALS and bvFTD at the two extreme ends.
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Affiliation(s)
- Rosanne Govaarts
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands.
| | - Emma Beeldman
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Matteo Fraschini
- University of Cagliari, Department of Electrical and Electronic Engineering, Cagliari, Italy
| | - Alessandra Griffa
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland; Institute of Bioengineering, Center of Neuroprosthetics, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland
| | - Marjolein M A Engels
- Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology, Magnetoencephalography Centre, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Michael A van Es
- University Medical Centre Utrecht, Department of Neurology, Brain Centre Rudolf Magnus, Utrecht, the Netherlands
| | - Jan H Veldink
- University Medical Centre Utrecht, Department of Neurology, Brain Centre Rudolf Magnus, Utrecht, the Netherlands
| | - Leonard H van den Berg
- University Medical Centre Utrecht, Department of Neurology, Brain Centre Rudolf Magnus, Utrecht, the Netherlands
| | - Anneke J van der Kooi
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Yolande A L Pijnenburg
- Amsterdam University Medical Centers, Vrije Universiteit, Alzheimer Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Marianne de Visser
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Cornelis J Stam
- Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology, Magnetoencephalography Centre, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Joost Raaphorst
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Arjan Hillebrand
- Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology, Magnetoencephalography Centre, Amsterdam Neuroscience, Amsterdam, the Netherlands
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Mavanji V, Georgopoulos AP, Kotz CM. Orexin enhances neuronal synchronization in adult rat hypothalamic culture: a model to study hypothalamic function. J Neurophysiol 2022; 127:1221-1229. [PMID: 35353632 PMCID: PMC9054260 DOI: 10.1152/jn.00041.2022] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 03/28/2022] [Indexed: 11/22/2022] Open
Abstract
The regulation of sleep/wake behavior and energy homeostasis is maintained in part by the hypothalamic neuropeptide orexin A (OXA, hypocretin). Reduction in orexin signaling is associated with sleep disorders and obesity, whereas higher lateral hypothalamic (LH) orexin signaling and sensitivity promotes obesity resistance. Similarly, dysregulation of hypothalamic neural networks is associated with onset of age-related diseases, including obesity and several neurological diseases. Despite the association of obesity and aging, and that adult populations are the target for the majority of pharmaceutical and obesity studies, conventional models for neuronal networks utilize embryonic neural cultures rather than adult neurons. Synchronous activity describes correlated changes in neuronal activity between neurons and is a feature of normal brain function, and is a measure of functional connectivity and final output from a given neural structure. Earlier studies show alterations in hypothalamic synchronicity following behavioral perturbations in embryonic neurons obtained from obesity-resistant rats and following application of orexin onto embryonic hypothalamic cultures. Synchronous network dynamics in adult hypothalamic neurons remain largely undescribed. To address this, we established an adult rat hypothalamic culture in multi-electrode-array (MEA) dishes and recorded the field potentials. Then we studied the effect of exogenous orexin on network synchronization of these adult hypothalamic cultures. In addition, we studied the wake promoting effects of orexin in vivo when directly injected into the lateral hypothalamus (LH). Our results showed that the adult hypothalamic cultures are viable for nearly 3 mo in vitro, good quality MEA recordings can be obtained from these cultures in vitro, and finally, that cultured adult hypothalamus is responsive to orexin. These results support that adult rat hypothalamic cultures could be used as a model to study the neural mechanisms underlying obesity. In addition, LH administration of OXA enhanced wakefulness in rats, indicating that OXA enhances wakefulness partly by promoting neural synchrony in the hypothalamus.NEW & NOTEWORTHY This study, for the first time, demonstrates that adult hypothalamic cultures are viable in vitro for a prolonged duration and are electrophysiologically active. In addition, the study shows that orexin enhances neural synchronization in adult hypothalamic cultures.
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Affiliation(s)
- Vijayakumar Mavanji
- Research Service, Veterans Affairs Health Care System, Minneapolis, Minnesota
| | - Apostolos P Georgopoulos
- Research Service, Veterans Affairs Health Care System, Minneapolis, Minnesota
- Brain Sciences Center, Veterans Affairs Health Care System, Minneapolis, Minnesota
- Department of Neuroscience, University of Minnesota Medical School, Minneapolis, Minnesota
- Department of Psychiatry, University of Minnesota Medical School, Minneapolis, Minnesota
- Center for Cognitive Sciences, University of Minnesota, Minneapolis, Minnesota
- Department of Neurology, University of Minnesota Medical School, Minneapolis, Minnesota
| | - Catherine M Kotz
- Research Service, Veterans Affairs Health Care System, Minneapolis, Minnesota
- Minnesota Nutrition and Obesity Research Center, St. Paul, Minnesota
- Geriatric Research Education Clinical Center, Veterans Affairs Health Care System, Minneapolis, Minnesota
- Department of Integrative Biology and Physiology, University of Minnesota, Minneapolis, Minnesota
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Montaser-Kouhsari L, Young CB, Poston KL. Neuroimaging approaches to cognition in Parkinson's disease. PROGRESS IN BRAIN RESEARCH 2022; 269:257-286. [PMID: 35248197 DOI: 10.1016/bs.pbr.2022.01.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
While direct visualization of Lewy body accumulation within the brain is not yet possible in living Parkinson's disease patients, brain imaging studies offer insights into how the buildup of Lewy body pathology impacts different regions of the brain. Unlike biological biomarkers and purely behavioral research, these brain imaging studies therefore offer a unique opportunity to relate brain localization to cognitive function and dysfunction in living patients. Magnetic resonance imaging studies can reveal physical changes in brain structure as they relate to different cognitive domains and task specific impairments. Functional imaging studies use a combination of task and resting state magnetic resonance imaging, as well as positron emission tomography and single photon emission computed tomography, and can be used to determine changes in blood flow, neuronal activation and neurochemical changes in the brain associated with PD cognition and cognitive impairments. Other unique advantages to brain imaging studies are the ability to monitor changes in brain structure and function longitudinally as patients progress and the ability to study changes in brain function when patients are exposed to different pharmacological manipulations. This is particularly true when assessing the effects of dopaminergic replacement therapy on cognitive function in Parkinson's disease patients. Together, this chapter will describe imaging studies that have helped identify structural and functional brain changes associated with cognition, cognitive impairment, and dementia in Parkinson's disease.
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Affiliation(s)
- Leila Montaser-Kouhsari
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, United States
| | - Christina B Young
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, United States
| | - Kathleen L Poston
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, United States; Department of Neurosurgery, Stanford University, Stanford, CA, United States.
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Pesoli M, Rucco R, Liparoti M, Lardone A, D'Aurizio G, Minino R, Troisi Lopez E, Paccone A, Granata C, Curcio G, Sorrentino G, Mandolesi L, Sorrentino P. A night of sleep deprivation alters brain connectivity and affects specific executive functions. Neurol Sci 2022; 43:1025-1034. [PMID: 34244891 PMCID: PMC8789640 DOI: 10.1007/s10072-021-05437-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Accepted: 06/23/2021] [Indexed: 12/29/2022]
Abstract
Sleep is a fundamental physiological process necessary for efficient cognitive functioning especially in relation to memory consolidation and executive functions, such as attentional and switching abilities. The lack of sleep strongly alters the connectivity of some resting-state networks, such as default mode network and attentional network. In this study, by means of magnetoencephalography (MEG) and specific cognitive tasks, we investigated how brain topology and cognitive functioning are affected by 24 h of sleep deprivation (SD). Thirty-two young men underwent resting-state MEG recording and evaluated in letter cancellation task (LCT) and task switching (TS) before and after SD. Results showed a worsening in the accuracy and speed of execution in the LCT and a reduction of reaction times in the TS, evidencing thus a worsening of attentional but not of switching abilities. Moreover, we observed that 24 h of SD induced large-scale rearrangements in the functional network. These findings evidence that 24 h of SD is able to alter brain connectivity and selectively affects cognitive domains which are under the control of different brain networks.
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Affiliation(s)
- Matteo Pesoli
- Department of Motor Sciences and Wellness, University of Naples "Parthenope", Naples, Italy
| | - Rosaria Rucco
- Department of Motor Sciences and Wellness, University of Naples "Parthenope", Naples, Italy
- Institute of Applied Sciences and Intelligent Systems, CNR, Pozzuoli, Italy
| | - Marianna Liparoti
- Department of Motor Sciences and Wellness, University of Naples "Parthenope", Naples, Italy
| | - Anna Lardone
- Department of Social and Developmental Psychology, University of Rome "Sapienza", Rome, Italy
| | - Giulia D'Aurizio
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Roberta Minino
- Department of Motor Sciences and Wellness, University of Naples "Parthenope", Naples, Italy
| | - Emahnuel Troisi Lopez
- Department of Motor Sciences and Wellness, University of Naples "Parthenope", Naples, Italy
| | - Antonella Paccone
- Institute for Diagnosis and Cure Hermitage Capodimonte, Naples, Italy
| | - Carmine Granata
- Institute of Applied Sciences and Intelligent Systems, CNR, Pozzuoli, Italy
| | - Giuseppe Curcio
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Giuseppe Sorrentino
- Department of Motor Sciences and Wellness, University of Naples "Parthenope", Naples, Italy
- Institute of Applied Sciences and Intelligent Systems, CNR, Pozzuoli, Italy
- Institute for Diagnosis and Cure Hermitage Capodimonte, Naples, Italy
| | - Laura Mandolesi
- Department of Humanities Studies, University Federico II, Via Porta di Massa 1, 80133, Naples, Italy.
| | - Pierpaolo Sorrentino
- Institute of Applied Sciences and Intelligent Systems, CNR, Pozzuoli, Italy
- Institut de Neurosciences Des Systèmes, Aix-Marseille Université, Marseille, France
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Chen C, Zhang S, Wei Y, Sun X. LncRNA RMST Regulates Neuronal Apoptosis and Inflammatory Response via Sponging miR-150-5p in Parkinson's Disease. Neuroimmunomodulation 2022; 29:55-62. [PMID: 34515176 DOI: 10.1159/000518212] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Accepted: 06/24/2021] [Indexed: 11/19/2022] Open
Abstract
INTRODUCTION LncRNA rhabdomyosarcoma 2-associated transcript (RMST) serves as a key regulator in neural stem cell fate and is involved in the progression of different neurological diseases. In this research, the serum level and clinical value of RMST in Parkinson's disease (PD) patients were detected, and the underlying mechanism was explored. METHODS Ninety-nine PD patients and 93 healthy individuals were collected for clinical experiments. SH-SY5Y cells were treated with the dopaminergic neurotoxin 1-methyl-4-phenylpyridinium (MPP+) to establish PD cell models. qRT-PCR was used for the detection of mRNA levels. CCK-8 and flow cytometry were used to detect neuronal viability and apoptosis. The target relationship of RMST with miR-15a-5p was confirmed applying luciferase reporter assay. RESULTS RMST was present at high levels in both serum of PD patients and PD cell models. Serum RMST had a certain clinical value for the diagnosis of PD with the AUC of 0.892 at a cutoff value of 1.225. Serum RMST was positively associated with the levels of TNF-α (r = 0.421, p < 0.001) and IL-1β (r = 0.567, p < 0.001) in PD patients. Knockdown of RMST alleviated the apoptosis and inflammatory response of SH-SY5Y cells induced by MPP+. miR-150-5p was the target gene of RMST and less expressed in the clinical serum samples and PD cell models. CONCLUSION Serum RMST serves as a promising biomarker for the diagnosis of PD. RMST downregulation may regulate the occurrence and development of PD through inhibiting neuron cell apoptosis and the release of inflammatory cytokines via targeting miR-150-5p.
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Affiliation(s)
- Chuanlei Chen
- Department of Neurology First Ward, Yidu Central Hospital of Weifang, Weifang, China
| | - Shijuan Zhang
- Department of Critical Care Medicine, Yidu Central Hospital of Weifang, Weifang, China
| | - Yuhong Wei
- Department of Gastroenterology First Ward, Yidu Central Hospital of Weifang, Weifang, China
| | - Xibo Sun
- Department of Neurology First Ward, Yidu Central Hospital of Weifang, Weifang, China
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Biondi F, Liparoti M, Lacetera A, Sorrentino P, Minino R. Risk factors for mental health in general population during SARS-COV2 pandemic: a systematic review. MIDDLE EAST CURRENT PSYCHIATRY, AIN SHAMS UNIVERSITY 2022; 29:85. [PMCID: PMC9552736 DOI: 10.1186/s43045-022-00251-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
The COVID-19 pandemic and its social restrictions have affected mental health globally. This systematic review aims to analyze the psychological responses of the general population and its related sociodemographic risk factors, excluding the most vulnerable groups (e.g., healthcare workers, COVID-19 patients and survivors, pregnant women, people with chronic diseases or preexisting psychiatric disorders). A reproducible search from June 2020 to February 2021 was conducted on PubMed and Google Scholar, following the PRISMA guidelines. Papers that (1) considered the most at-risk populations, (2) did not report sociodemographic data, and (3) did not use validated scales were excluded from our analysis. Non-English papers and review articles were also excluded. Of 1116 papers identified, 25 were included for this review (n = 162,465). The main risk factors associated with the emergence of depression, anxiety, sleep disorders, post-traumatic stress disorder, and obsessive compulsive disorder were: female gender, younger and later age, high level of education, Latino origin, free marital status, living quarantine in a house with no outdoor, negative coping strategies, close proximity to positive cases, high concern about contracting COVID-19 and living in a most affected area. High income, physical activity, resilience, family support, and a high level of knowledge about COVID-19, seems to be protective factors against the onset of psychological symptoms. In a general population, COVID-19 restrictions are linked to risk factors for psychological disorders caused by gender and sociodemographic conditions. In this regard governments should pay more attention to the public’s mental health and its risk and protective factors.
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Affiliation(s)
- Francesca Biondi
- Institute for Diagnosis and Care, Hermitage Capodimonte, Naples, Italy
| | - Marianna Liparoti
- grid.7841.aDepartment of Social and Developmental Psychology, University of Rome “Sapienza”, Rome, Italy
| | - Angelica Lacetera
- Institute for Diagnosis and Care, Hermitage Capodimonte, Naples, Italy
| | - Pierpaolo Sorrentino
- grid.5399.60000 0001 2176 4817Institut de Neuroscience Des Systemès, Aix-Marseille University, Marseille, France
| | - Roberta Minino
- grid.17682.3a0000 0001 0111 3566Department of Motor Sciences and Wellness, University of Naples “Parthenope”, Naples, Italy
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Kazemi A, Mirian MS, Lee S, McKeown MJ. Galvanic Vestibular Stimulation Effects on EEG Biomarkers of Motor Vigor in Parkinson's Disease. Front Neurol 2021; 12:759149. [PMID: 34803892 PMCID: PMC8599939 DOI: 10.3389/fneur.2021.759149] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 10/05/2021] [Indexed: 01/18/2023] Open
Abstract
Background: Impaired motor vigor (MV) is a critical aspect of Parkinson's disease (PD) pathophysiology. While MV is predominantly encoded in the basal ganglia, deriving (cortical) EEG measures of MV may provide valuable targets for modulation via galvanic vestibular stimulation (GVS). Objective: To find EEG features predictive of MV and examine the effects of high-frequency GVS. Methods: Data were collected from 20 healthy control (HC) and 18 PD adults performing 30 trials total of a squeeze bulb task with sham or multi-sine (50-100 Hz "GVS1" or 100-150 Hz "GVS2") stimuli. For each trial, we determined the time to reach maximum force after a "Go" signal, defined MV as the inverse of this time, and used the EEG data 1-sec prior to this time for prediction. We utilized 53 standard EEG features, including relative spectral power, harmonic parameters, and amplitude and phase of bispectrum corresponding to standard EEG bands from each of 27 EEG channels. We then used LASSO regression to select a sparse set of features to predict MV. The regression weights were examined, and separate band-specific models were developed by including only band-specific features (Delta, Theta, Alpha-low, Alpha-high, Beta, Gamma). The correlation between MV prediction and measured MV was used to assess model performance. Results: Models utilizing broadband EEG features were capable of accurately predicting MV (controls: 75%, PD: 81% of the variance). In controls, all EEG bands performed roughly equally in predicting MV, while in the PD group, the model using only beta band features did not predict MV well compared to other bands. Despite having minimal effects on the EEG feature values themselves, both GVS stimuli had significant effects on MV and profound effects on MV predictability via the EEG. With the GVS1 stimulus, beta-band activity in PD subjects became more closely associated with MV compared to the sham condition. With GVS2 stimulus, MV could no longer be accurately predicted from the EEG. Conclusions: EEG features can be a proxy for MV. However, GVS stimuli have profound effects on the relationship between EEG and MV, possibly via direct vestibulo-basal ganglia connections not measurable by the EEG.
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Affiliation(s)
- Alireza Kazemi
- Center for Mind and Brain, Department of Psychology, University of California, Davis, Davis, CA, United States
| | - Maryam S. Mirian
- Pacific Parkinson's Research Centre, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Soojin Lee
- Pacific Parkinson's Research Centre, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
- Wellcome Centre for Integrative Neuroimaging (FMRIB), University of Oxford, Oxford, United Kingdom
| | - Martin J. McKeown
- Pacific Parkinson's Research Centre, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
- Faculty of Medicine (Neurology), University of British Columbia, Vancouver, BC, Canada
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Li Z, Ren G, Liu C, Wang Q, Liang K, Han C, Qiao H, Zhang J, Wang Q, Meng F. Dysfunctional Brain Dynamics of Parkinson's Disease and the Effect of Acute Deep Brain Stimulation. Front Neurosci 2021; 15:697909. [PMID: 34354564 PMCID: PMC8331088 DOI: 10.3389/fnins.2021.697909] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Accepted: 06/09/2021] [Indexed: 12/25/2022] Open
Abstract
Background: Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer's disease, and deep brain stimulation (DBS) can effectively alleviate PD symptoms. Although previous studies have detected network features of PD and DBS, few studies have considered their dynamic characteristics. Objective: We tested two hypotheses. (1) Reduced brain dynamics, as evidenced by slowed microstate dynamic change, is a characteristic of PD and is related to the movement disorders of patients with PD. (2) Therapeutic acute DBS can partially reverse slow brain dynamics in PD to healthy levels. Methods: We used electroencephalography (EEG) microstate analysis based on high density (256-channel) EEG to detect the effects of PD and DBS on brain dynamic changes on a sub-second timescale. We compared 21 healthy controls (HCs) with 20 patients with PD who were in either DBS-OFF or DBS-ON states. Assessment of movement disorder using the Unified Parkinson's Disease Rating Scale III was correlated with microstate parameters. Results: Compared with HCs, patients with PD displayed a longer mean microstate duration with reduced occurrence per second, which were significantly associated with movement disorders. In patients with PD, some parameters of microstate analysis were restored toward healthy levels after DBS. Conclusions: Resting-state EEG microstate analysis is an important tool for investigating brain dynamic changes in PD and DBS. PD can slow down brain dynamic change, and therapeutic acute DBS can partially reverse this change toward a healthy level.
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Affiliation(s)
- Zhibao Li
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Guoping Ren
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Chong Liu
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Qiao Wang
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Kun Liang
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Chunlei Han
- Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neurostimulation, Beijing Neurosurgical Institute, Beijing, China
| | - Hui Qiao
- Neuroelectrophysiology Room, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Jianguo Zhang
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neurostimulation, Beijing Neurosurgical Institute, Beijing, China
| | - Qun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Fangang Meng
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.,Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neurostimulation, Beijing Neurosurgical Institute, Beijing, China.,Chinese Institute for Brain Research Beijing (CIBR), Beijing, China
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Rucco R, Lardone A, Liparoti M, Troisi Lopez E, De Micco R, Tessitore A, Granata C, Mandolesi L, Sorrentino G, Sorrentino P. Brain networks and cognitive impairment in Parkinson's disease. Brain Connect 2021; 12:465-475. [PMID: 34269602 DOI: 10.1089/brain.2020.0985] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Aim The aim of the present study is to investigate the relations between both functional connectivity and brain networks with cognitive decline, in patients with Parkinson's disease (PD). Introduction PD phenotype is not limited to motor impairment but, rather, a wide range of non-motor disturbances can occur, cognitive impairment being one of the commonest. However, how the large-scale organization of brain activity differs in cognitively impaired patients, as opposed to cognitively preserved ones, remains poorly understood. Methods Starting from source-reconstructed resting-state magnetoencephalography data, we applied the PLM to estimate functional connectivity, globally and between brain areas, in PD patients with and without cognitive impairment (respectively PD-CI and PD-NC), as compared to healthy subjects (HS). Furthermore, using graph analysis, we characterized the alterations in brain network topology and related these, as well as the functional connectivity, to cognitive performance. Results We found reduced global and nodal PLM in several temporal (fusiform gyrus, Heschl's gyrus and inferior temporal gyrus), parietal (postcentral gyrus), and occipital (lingual gyrus) areas within the left hemisphere, in the gamma band, in PD-CI patients, as compared to PD-NC and HS. With regard to the global topological features, PD-CI patients, as compared to HS and PD-NC patients, showed differences in multi frequencies bands (delta, alpha, gamma) in the Leaf fraction, Tree hierarchy (both higher in PD-CI) and Diameter (lower in PD-CI). Finally, we found statistically significant correlations between the MoCA test and both the Diameter in delta band and the Tree Hierarchy in the alpha band. Conclusion Our work points to specific large-scale rearrangements that occur selectively in cognitively compromised PD patients and correlated to cognitive impairment.
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Affiliation(s)
- Rosaria Rucco
- University of Naples - Parthenope, 18993, Department of Motor Sciences and Wellness, Napoli, Campania, Italy.,Eduardo Caianiello Institute for Applied Science and Intelligent Systems National Research Council, 96973, Pozzuoli, Campania, Italy;
| | - Anna Lardone
- University of Rome La Sapienza Department of Developmental and Social Psychology, 247818, Roma, Lazio, Italy;
| | - Marianna Liparoti
- University of Naples - Parthenope, 18993, Department of Motor Sciences and Wellness, Napoli, Campania, Italy;
| | - Emahnuel Troisi Lopez
- University of Naples - Parthenope, 18993, Department of Motor Sciences and Wellness, Napoli, Campania, Italy;
| | - Rosa De Micco
- University of Campania Luigi Vanvitelli Department of Advanced Medical and Surgical Sciences, 217742, Napoli, Campania, Italy;
| | - Alessandro Tessitore
- University of Campania Luigi Vanvitelli Department of Advanced Medical and Surgical Sciences, 217742, Napoli, Campania, Italy;
| | - Carmine Granata
- Eduardo Caianiello Institute for Applied Science and Intelligent Systems National Research Council, 96973, Pozzuoli, Campania, Italy;
| | - Laura Mandolesi
- University of Naples Federico II, 9307, Department of Humanistic Studies, Napoli, Campania, Italy;
| | - Giuseppe Sorrentino
- University of Naples - Parthenope, 18993, Department of Motor and Wellness Sciences, Via Medina 40, 3, Napoli, Italy, 80133.,Institute of Diagnosis and Treatment Hermitage Capodimont, Naples, Campania, Italy.,National Research Council Research Area Naples 3 - Pozzuoli, 462880, Institute of Applied Sciences and Intelligent Systems , Pozzuoli, Campania, Italy;
| | - Pierpaolo Sorrentino
- Eduardo Caianiello Institute for Applied Science and Intelligent Systems National Research Council, 96973, Pozzuoli, Campania, Italy.,Aix-Marseille Universite, 128791, Institut de Neurosciences des Systèmes, Marseille, France;
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Sorrentino P, Seguin C, Rucco R, Liparoti M, Troisi Lopez E, Bonavita S, Quarantelli M, Sorrentino G, Jirsa V, Zalesky A. The structural connectome constrains fast brain dynamics. eLife 2021; 10:67400. [PMID: 34240702 PMCID: PMC8294846 DOI: 10.7554/elife.67400] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 07/07/2021] [Indexed: 02/07/2023] Open
Abstract
Brain activity during rest displays complex, rapidly evolving patterns in space and time. Structural connections comprising the human connectome are hypothesized to impose constraints on the dynamics of this activity. Here, we use magnetoencephalography (MEG) to quantify the extent to which fast neural dynamics in the human brain are constrained by structural connections inferred from diffusion MRI tractography. We characterize the spatio-temporal unfolding of whole-brain activity at the millisecond scale from source-reconstructed MEG data, estimating the probability that any two brain regions will significantly deviate from baseline activity in consecutive time epochs. We find that the structural connectome relates to, and likely affects, the rapid spreading of neuronal avalanches, evidenced by a significant association between these transition probabilities and structural connectivity strengths (r = 0.37, p<0.0001). This finding opens new avenues to study the relationship between brain structure and neural dynamics.
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Affiliation(s)
- Pierpaolo Sorrentino
- Aix-Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes, Marseille, France.,Department of Motor Sciences and Wellness, Parthenope University of Naples, Naples, Italy.,Institute for Diagnosis and Cure Hermitage Capodimonte, Naples, Italy.,Institute of Applied Sciences and Intelligent Systems, National Research Council, Pozzuoli, Italy
| | - Caio Seguin
- University of Melbourne, Melbourne, Australia
| | - Rosaria Rucco
- Department of Motor Sciences and Wellness, Parthenope University of Naples, Naples, Italy.,Institute for Diagnosis and Cure Hermitage Capodimonte, Naples, Italy
| | - Marianna Liparoti
- Department of Motor Sciences and Wellness, Parthenope University of Naples, Naples, Italy.,Institute for Diagnosis and Cure Hermitage Capodimonte, Naples, Italy
| | - Emahnuel Troisi Lopez
- Department of Motor Sciences and Wellness, Parthenope University of Naples, Naples, Italy.,Institute for Diagnosis and Cure Hermitage Capodimonte, Naples, Italy
| | | | - Mario Quarantelli
- Biostructure and Bioimaging Institute, National Research Council, Naples, Italy
| | - Giuseppe Sorrentino
- Institute of Applied Sciences and Intelligent Systems, National Research Council, Pozzuoli, Italy
| | - Viktor Jirsa
- Aix-Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes, Marseille, France
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Kobeleva X, Machts J, Veit M, Vielhaber S, Petri S, Schoenfeld MA. Brain activity is contingent on neuropsychological function in a functional magnetic resonance imaging study of verbal working memory in amyotrophic lateral sclerosis. Eur J Neurol 2021; 28:3051-3060. [PMID: 34081813 DOI: 10.1111/ene.14957] [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: 02/17/2021] [Revised: 05/17/2021] [Accepted: 05/25/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND AND PURPOSE Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease that causes progressive degeneration of neurons in motor and non-motor brain regions, affecting multiple cognitive domains such as memory. A functional magnetic resonance imaging (fMRI) study was performed to explore working memory function in ALS. METHODS To contribute to the growing research field that employs structural and functional neuroimaging to investigate the effect of ALS on different working memory components, the localization and intensity of alterations in neural activity was explored using fMRI. Being the first study to specifically address verbal working memory via fMRI in the context of ALS, the verbal n-back task with 0-back and 2-back conditions was employed. RESULTS Despite ALS patients showing unimpaired accuracies (p = 0.724) and reaction times (p = 0.0785), there was significantly increased brain activity of frontotemporal and parietal regions in the 2-back minus 0-back contrast in patients compared to controls (using nonparametric statistics with 5000 permutations and a T threshold of 2.5). DISCUSSION Increased brain activity of the frontotemporal and parietal regions during working memory performance was largely associated with better neuropsychological function within the ALS group, suggesting a compensatory effect during working memory execution. This study therefore adds to the current knowledge on neural correlates of working memory in ALS and contributes to a more nuanced understanding of hyperactivity during cognitive processes in fMRI studies of ALS.
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Affiliation(s)
- Xenia Kobeleva
- Department of Neurology, University Hospital of Bonn, Bonn, Germany.,Department of Neurology and Clinical Neurophysiology, Hannover Medical School, Hannover, Germany
| | - Judith Machts
- Institute for Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University Magdeburg, Magdeburg, Germany
| | - Maria Veit
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany.,Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hannover, Germany
| | - Stefan Vielhaber
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany
| | - Susanne Petri
- Department of Neurology and Clinical Neurophysiology, Hannover Medical School, Hannover, Germany
| | - Mircea Ariel Schoenfeld
- Department of Neurology, Otto-von-Guericke University, Magdeburg, Germany.,Kliniken Schmieder, Heidelberg, Germany.,Department of behavioral neurology, Leibniz Institute for Neurobiology, Magdeburg, Germany
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