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Maddaluno O, Della Penna S, Pizzuti A, Spezialetti M, Corbetta M, de Pasquale F, Betti V. Encoding Manual Dexterity through Modulation of Intrinsic α Band Connectivity. J Neurosci 2024; 44:e1766232024. [PMID: 38538141 PMCID: PMC11097277 DOI: 10.1523/jneurosci.1766-23.2024] [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: 09/18/2023] [Revised: 01/21/2024] [Accepted: 02/20/2024] [Indexed: 05/18/2024] Open
Abstract
The human hand possesses both consolidated motor skills and remarkable flexibility in adapting to ongoing task demands. However, the underlying mechanisms by which the brain balances stability and flexibility remain unknown. In the absence of external input or behavior, spontaneous (intrinsic) brain connectivity is thought to represent a prior of stored memories. In this study, we investigated how manual dexterity modulates spontaneous functional connectivity in the motor cortex during hand movement. Using magnetoencephalography, in 47 human participants (both sexes), we examined connectivity modulations in the α and β frequency bands at rest and during two motor tasks (i.e., finger tapping or toe squeezing). The flexibility and stability of such modulations allowed us to identify two groups of participants with different levels of performance (high and low performers) on the nine-hole peg test, a test of manual dexterity. In the α band, participants with higher manual dexterity showed distributed decreases of connectivity, specifically in the motor cortex, increased segregation, and reduced nodal centrality. Participants with lower manual dexterity showed an opposite pattern. Notably, these patterns from the brain to behavior are mirrored by results from behavior to the brain. Indeed, when participants were divided using the median split of the dexterity score, we found the same connectivity patterns. In summary, this experiment shows that a long-term motor skill-manual dexterity-influences the way the motor systems respond during movements.
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Affiliation(s)
- Ottavia Maddaluno
- Department of Psychology, Sapienza University of Rome, Rome 00185, Italy
- IRCCS Santa Lucia Foundation, Rome 00179, Italy
| | - Stefania Della Penna
- Department of Neuroscience, Imaging and Clinical Sciences and ITAB - Institute of Advanced Biomedical Technologies, "G. d'Annunzio" University of Chieti and Pescara, Chieti 66013, Italy
| | - Alessandra Pizzuti
- Department of Psychology, Sapienza University of Rome, Rome 00185, Italy
- IRCCS Santa Lucia Foundation, Rome 00179, Italy
| | - Matteo Spezialetti
- Department of Psychology, Sapienza University of Rome, Rome 00185, Italy
- IRCCS Santa Lucia Foundation, Rome 00179, Italy
| | - Maurizio Corbetta
- Department of Neuroscience and Padova Neuroscience Center, University of Padua, Padua 35131, Italy
- Veneto Institute of Molecular Medicine (VIMM), Padova 35129, Italy
| | | | - Viviana Betti
- Department of Psychology, Sapienza University of Rome, Rome 00185, Italy
- IRCCS Santa Lucia Foundation, Rome 00179, Italy
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2
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Amoruso L, García AM, Pusil S, Timofeeva P, Quiñones I, Carreiras M. Decoding bilingualism from resting-state oscillatory network organization. Ann N Y Acad Sci 2024; 1534:106-117. [PMID: 38419368 DOI: 10.1111/nyas.15113] [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] [Indexed: 03/02/2024]
Abstract
Can lifelong bilingualism be robustly decoded from intrinsic brain connectivity? Can we determine, using a spectrally resolved approach, the oscillatory networks that better predict dual-language experience? We recorded resting-state magnetoencephalographic activity in highly proficient Spanish-Basque bilinguals and Spanish monolinguals, calculated functional connectivity at canonical frequency bands, and derived topological network properties using graph analysis. These features were fed into a machine learning classifier to establish how robustly they discriminated between the groups. The model showed excellent classification (AUC: 0.91 ± 0.12) between individuals in each group. The key drivers of classification were network strength in beta (15-30 Hz) and delta (2-4 Hz) rhythms. Further characterization of these networks revealed the involvement of temporal, cingulate, and fronto-parietal hubs likely underpinning the language and default-mode networks (DMNs). Complementary evidence from a correlation analysis showed that the top-ranked features that better discriminated individuals during rest also explained interindividual variability in second language (L2) proficiency within bilinguals, further supporting the robustness of the machine learning model in capturing trait-like markers of bilingualism. Overall, our results show that long-term experience with an L2 can be "brain-read" at a fine-grained level from resting-state oscillatory network organization, highlighting its pervasive impact, particularly within language and DMN networks.
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Affiliation(s)
- Lucia Amoruso
- Basque Center on Cognition, Brain and Language (BCBL), San Sebastian, Spain
- Ikerbasque, Basque Foundation for Science, Bilbao, Spain
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
| | - Adolfo M García
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina
- Global Brain Health Institute, University of California San Francisco, San Francisco, California, USA
- Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile
| | - Sandra Pusil
- Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
| | - Polina Timofeeva
- Basque Center on Cognition, Brain and Language (BCBL), San Sebastian, Spain
- Universidad del País Vasco (UPV/EHU), San Sebastian, Spain
| | - Ileana Quiñones
- Basque Center on Cognition, Brain and Language (BCBL), San Sebastian, Spain
- Ikerbasque, Basque Foundation for Science, Bilbao, Spain
| | - Manuel Carreiras
- Basque Center on Cognition, Brain and Language (BCBL), San Sebastian, Spain
- Ikerbasque, Basque Foundation for Science, Bilbao, Spain
- Universidad del País Vasco (UPV/EHU), San Sebastian, Spain
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3
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Ibáñez A, Kühne K, Miklashevsky A, Monaco E, Muraki E, Ranzini M, Speed LJ, Tuena C. Ecological Meanings: A Consensus Paper on Individual Differences and Contextual Influences in Embodied Language. J Cogn 2023; 6:59. [PMID: 37841670 PMCID: PMC10573819 DOI: 10.5334/joc.228] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 05/20/2022] [Indexed: 10/17/2023] Open
Abstract
Embodied theories of cognition consider many aspects of language and other cognitive domains as the result of sensory and motor processes. In this view, the appraisal and the use of concepts are based on mechanisms of simulation grounded on prior sensorimotor experiences. Even though these theories continue receiving attention and support, increasing evidence indicates the need to consider the flexible nature of the simulation process, and to accordingly refine embodied accounts. In this consensus paper, we discuss two potential sources of variability in experimental studies on embodiment of language: individual differences and context. Specifically, we show how factors contributing to individual differences may explain inconsistent findings in embodied language phenomena. These factors include sensorimotor or cultural experiences, imagery, context-related factors, and cognitive strategies. We also analyze the different contextual modulations, from single words to sentences and narratives, as well as the top-down and bottom-up influences. Similarly, we review recent efforts to include cultural and language diversity, aging, neurodegenerative diseases, and brain disorders, as well as bilingual evidence into the embodiment framework. We address the importance of considering individual differences and context in clinical studies to drive translational research more efficiently, and we indicate recommendations on how to correctly address these issues in future research. Systematically investigating individual differences and context may contribute to understanding the dynamic nature of simulation in language processes, refining embodied theories of cognition, and ultimately filling the gap between cognition in artificial experimental settings and cognition in the wild (i.e., in everyday life).
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Affiliation(s)
- Agustín Ibáñez
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago de Chile, Chile
- Cognitive Neuroscience Center (CNC), Universidad de San Andrés and CONICET, Buenos Aires, Argentina
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), California, US
- Trinity College Dublin (TCD), Dublin, Ireland, IE
| | - Katharina Kühne
- Potsdam Embodied Cognition Group, Cognitive Sciences, University of Potsdam, Potsdam, DE
| | - Alex Miklashevsky
- Potsdam Embodied Cognition Group, Cognitive Sciences, University of Potsdam, Potsdam, DE
| | - Elisa Monaco
- Laboratory for Cognitive and Neurological Sciences, Department of Neuroscience and Movement Science, Faculty of Science and Medicine, University of Fribourg, CH
| | - Emiko Muraki
- Department of Psychology & Hotchkiss Brain Institute, University of Calgary, CA
| | | | | | - Cosimo Tuena
- Applied Technology for Neuro-Psychology Lab, IRCCS Istituto Auxologico Italiano, Milan, IT
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4
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Amoruso L, Pusil S, García AM, Ibañez A. Decoding motor expertise from fine-tuned oscillatory network organization. Hum Brain Mapp 2022; 43:2817-2832. [PMID: 35274804 PMCID: PMC9120567 DOI: 10.1002/hbm.25818] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 01/26/2022] [Accepted: 02/15/2022] [Indexed: 01/21/2023] Open
Abstract
Can motor expertise be robustly predicted by the organization of frequency-specific oscillatory brain networks? To answer this question, we recorded high-density electroencephalography (EEG) in expert Tango dancers and naïves while viewing and judging the correctness of Tango-specific movements and during resting. We calculated task-related and resting-state connectivity at different frequency-bands capturing task performance (delta [δ], 1.5-4 Hz), error monitoring (theta [θ], 4-8 Hz), and sensorimotor experience (mu [μ], 8-13 Hz), and derived topographical features using graph analysis. These features, together with canonical expertise measures (i.e., performance in action discrimination, time spent dancing Tango), were fed into a data-driven computational learning analysis to test whether behavioral and brain signatures robustly classified individuals depending on their expertise level. Unsurprisingly, behavioral measures showed optimal classification (100%) between dancers and naïves. When considering brain models, the task-based classification performed well (~73%), with maximal discrimination afforded by theta-band connectivity, a hallmark signature of error processing. Interestingly, mu connectivity during rest outperformed (100%) the task-based approach, matching the optimal classification of behavioral measures and thus emerging as a potential trait-like marker of sensorimotor network tuning by intense training. Overall, our findings underscore the power of fine-tuned oscillatory network signatures for capturing expertise-related differences and their potential value in the neuroprognosis of learning outcomes.
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Affiliation(s)
- Lucia Amoruso
- Basque Center on Cognition, Brain and Language (BCBL), San Sebastian, Spain.,IKERBASQUE, Basque Foundation for Science, Bilbao, Spain
| | - Sandra Pusil
- Department of Experimental Psychology, Complutense University of Madrid, Madrid, Spain
| | - Adolfo Martín García
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina.,Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina.,National University of Cuyo (UNCuyo), Mendoza, Argentina.,Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, Chile.,Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, California, USA.,Trinity College Dublin (TCD), Dublin, Ireland
| | - Agustín Ibañez
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina.,Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina.,Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, California, USA.,Trinity College Dublin (TCD), Dublin, Ireland.,Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
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5
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Ibanez A, Parra MA, Butler C. The Latin America and the Caribbean Consortium on Dementia (LAC-CD): From Networking to Research to Implementation Science. J Alzheimers Dis 2021; 82:S379-S394. [PMID: 33492297 PMCID: PMC8293660 DOI: 10.3233/jad-201384] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
In comparison with other regions, dementia prevalence in Latin America is growing rapidly, along with the consequent clinical, social, and economic burden upon patients and their families. The combination of fragile health care systems, large social inequalities, and isolated clinical and research initiatives makes the coordination of efforts imperative. The Latin America and the Caribbean Consortium on Dementia (LAC-CD) is a regional organization overseeing and promoting clinical and research activities on dementia. Here, we first provide an overview of the consortium, highlighting the antecedents and current mission. Then, we present the consortium’s regional research, including the multi-partner consortium to expand dementia research in Latin America (ReDLat), which aims to identify the unique genetic, social, and economic factors that drive Alzheimer’s and frontotemporal dementia presentation in LAC relative to the US. We describe an extension of ReDLat which aims to develop affordable markers of disease subtype and severity using high density EEG. We introduce current initiatives promoting regional diagnosis, visibility, and capacity, including the forthcoming launch of the Latin American Brain Health Institute (BrainLat). We discuss LAC-CD-led advances in brain health diplomacy, including an assessment of responses to the impact of COVID-19 on people with dementia and examining the knowledge of public policies among experts in the region. Finally, we present the current knowledge-to-action framework, which paves the way for a future regional action plan. Coordinated actions are crucial to forging strong regional bonds, supporting the implementation of regional dementia plans, improving health systems, and expanding research collaborations across Latin America.
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Affiliation(s)
- Agustin Ibanez
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), San Francisco, CA, USA.,Cognitive Neuroscience Center (CNC), Universidad de San Andrés, Buenos Aires, Argentina.,National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina.,Universidad Autónoma del Caribe, Barranquilla, Barranquilla, Colombia.,Latin American Institute for Brain Health (BrainLat), Center for Social and Cognitive Neuroscience (CSCN), Universidad Adolfo Ibanez, Santiago de Chile, Chile
| | - Mario A Parra
- Universidad Autónoma del Caribe, Barranquilla, Barranquilla, Colombia.,School of Psychological Sciences and Health, University of Strathclyde, Glasgow, UK
| | - Christopher Butler
- Department of Brain Sciences, Imperial College London, UK.,Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Instituto de Neurología Cognitiva, Buenos Aires, Argentina.,Departamento de Neurología, Pontificia Universidad de Chile, Santiago, Chile
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6
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Zhang Y, Wang C, Yao Y, Zhou C, Chen F. Adaptive Reconfiguration of Intrinsic Community Structure in Children with 5-Year Abacus Training. Cereb Cortex 2021; 31:3122-3135. [PMID: 33585902 DOI: 10.1093/cercor/bhab010] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2020] [Revised: 12/17/2020] [Accepted: 01/04/2020] [Indexed: 01/21/2023] Open
Abstract
Human learning can be understood as a network phenomenon, underpinned by the adaptive reconfiguration of modular organization. However, the plasticity of community structure (CS) in resting-state network induced by cognitive intervention has never been investigated. Here, we explored the individual difference of intrinsic CS between children with 5-year abacus-based mental calculation (AMC) training (35 subjects) and their peers without prior experience in AMC (31 subjects). Using permutation-based analysis between subjects in the two groups, we found the significant alteration of intrinsic CS, with training-attenuated individual difference. The alteration of CS focused on selective subsets of cortical regions ("core areas"), predominantly affiliated to the visual, somatomotor, and default-mode subsystems. These subsystems exhibited training-promoted cohesion with attenuated interaction between them, from the perspective of individuals' CS. Moreover, the cohesion of visual network could predict training-improved math ability in the AMC group, but not in the control group. Finally, the whole network displayed enhanced segregation in the AMC group, including higher modularity index, more provincial hubs, lower participation coefficient, and fewer between-module links, largely due to the segregation of "core areas." Collectively, our findings suggested that the intrinsic CS could get reconfigured toward more localized processing and segregated architecture after long-term cognitive training.
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Affiliation(s)
- Yi Zhang
- Bio-X Laboratory, Interdisciplinary Center for Quantum Information, State Key Laboratory of Modern Optical Instrumentation, and Zhejiang Province Key Laboratory of Quantum Technology and Device, Department of Physics, Zhejiang University, Hangzhou 310027, China
| | - Chunjie Wang
- Bio-X Laboratory, Interdisciplinary Center for Quantum Information, State Key Laboratory of Modern Optical Instrumentation, and Zhejiang Province Key Laboratory of Quantum Technology and Device, Department of Physics, Zhejiang University, Hangzhou 310027, China
| | - Yuzhao Yao
- Bio-X Laboratory, Interdisciplinary Center for Quantum Information, State Key Laboratory of Modern Optical Instrumentation, and Zhejiang Province Key Laboratory of Quantum Technology and Device, Department of Physics, Zhejiang University, Hangzhou 310027, China
| | - Changsong Zhou
- Bio-X Laboratory, Interdisciplinary Center for Quantum Information, State Key Laboratory of Modern Optical Instrumentation, and Zhejiang Province Key Laboratory of Quantum Technology and Device, Department of Physics, Zhejiang University, Hangzhou 310027, China.,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, China
| | - Feiyan Chen
- Bio-X Laboratory, Interdisciplinary Center for Quantum Information, State Key Laboratory of Modern Optical Instrumentation, and Zhejiang Province Key Laboratory of Quantum Technology and Device, Department of Physics, Zhejiang University, Hangzhou 310027, China
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7
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Ibanez A, Yokoyama JS, Possin KL, Matallana D, Lopera F, Nitrini R, Takada LT, Custodio N, Sosa Ortiz AL, Avila-Funes JA, Behrens MI, Slachevsky A, Myers RM, Cochran JN, Brusco LI, Bruno MA, Brucki SMD, Pina-Escudero SD, Okada de Oliveira M, Donnelly Kehoe P, Garcia AM, Cardona JF, Santamaria-Garcia H, Moguilner S, Duran-Aniotz C, Tagliazucchi E, Maito M, Longoria Ibarrola EM, Pintado-Caipa M, Godoy ME, Bakman V, Javandel S, Kosik KS, Valcour V, Miller BL. The Multi-Partner Consortium to Expand Dementia Research in Latin America (ReDLat): Driving Multicentric Research and Implementation Science. Front Neurol 2021; 12:631722. [PMID: 33776890 PMCID: PMC7992978 DOI: 10.3389/fneur.2021.631722] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Accepted: 02/15/2021] [Indexed: 12/17/2022] Open
Abstract
Dementia is becoming increasingly prevalent in Latin America, contrasting with stable or declining rates in North America and Europe. This scenario places unprecedented clinical, social, and economic burden upon patients, families, and health systems. The challenges prove particularly pressing for conditions with highly specific diagnostic and management demands, such as frontotemporal dementia. Here we introduce a research and networking initiative designed to tackle these ensuing hurdles, the Multi-partner consortium to expand dementia research in Latin America (ReDLat). First, we present ReDLat's regional research framework, aimed at identifying the unique genetic, social, and economic factors driving the presentation of frontotemporal dementia and Alzheimer's disease in Latin America relative to the US. We describe ongoing ReDLat studies in various fields and ongoing research extensions. Then, we introduce actions coordinated by ReDLat and the Latin America and Caribbean Consortium on Dementia (LAC-CD) to develop culturally appropriate diagnostic tools, regional visibility and capacity building, diplomatic coordination in local priority areas, and a knowledge-to-action framework toward a regional action plan. Together, these research and networking initiatives will help to establish strong cross-national bonds, support the implementation of regional dementia plans, enhance health systems' infrastructure, and increase translational research collaborations across the continent.
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Affiliation(s)
- Agustin Ibanez
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- School of Psychology, Center for Social and Cognitive Neuroscience, Latin American Institute for Brain Health (BrainLat), Universidad Adolfo Ibanez, Adolfo Ibanez University, Santiago, Chile
| | - Jennifer S. Yokoyama
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, United States
| | - Katherine L. Possin
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
| | - Diana Matallana
- Psychiatry Department, School of Medicine, Aging Institute, Pontificia Universidad Javeriana, Bogotá, Colombia
- Memory and Cognition Clinic, Intellectus, Hospital Universitario San Ignacio, Bogotá, Colombia
- Mental Health Unit, Hospital Universitario Santa Fe de Bogotá, Bogotá, Colombia
| | - Francisco Lopera
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellín, Colombia
| | - Ricardo Nitrini
- Cognitive and Behavioral Neurology Unit, Hospital das Clinicas, University of São Paulo Medical School, São Paulo, Brazil
| | - Leonel T. Takada
- Cognitive and Behavioral Neurology Unit, Hospital das Clinicas, University of São Paulo Medical School, São Paulo, Brazil
| | - Nilton Custodio
- Unit Cognitive Impairment and Dementia Prevention, Cognitive Neurology Center, Peruvian Institute of Neurosciences, Lima, Perú
| | - Ana Luisa Sosa Ortiz
- Instituto Nacional de Neurologia y Neurocirugia MVS, Universidad Nacional Autonoma de Mexico, Mexico, Mexico
| | - José Alberto Avila-Funes
- Department of Geriatrics, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico, Mexico
- Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, Bordeaux, France
| | - Maria Isabel Behrens
- Centro de Investigación Clínica Avanzada, Hospital Clínico, Facultad de Medicina Universidad de Chile, Santiago, Chile
- Departamento de Neurología y Neurocirugía, Hospital Clínico Universidad de Chile, Santiago, Chile
- Departamento de Neurociencia, Facultad de Medicina Universidad de Chile, Santiago, Chile
- Clínica Alemana Santiago, Universidad del Desarrollo, Santiago, Chile
| | - Andrea Slachevsky
- Clínica Alemana Santiago, Universidad del Desarrollo, Santiago, Chile
- Geroscience Center for Brain Health and Metabolism (GERO), Santiago, Chile
- Neuropsychology and Clinical Neuroscience Laboratory, Physiopathology Department, Institute of Biomedical Sciences, Neuroscience and East Neuroscience, Santiago, Chile
- Faculty of Medicine, University of Chile, Santiago, Chile
- Memory and Neuropsychiatric Clinic (CMYN) Neurology Department, Faculty of Medicine, Hospital del Salvador, University of Chile, Santiago, Chile
| | - Richard M. Myers
- Hudson Alpha Institute for Biotechnology, Huntsville, AL, United States
| | | | - Luis Ignacio Brusco
- Facultad de Medicina, Universidad de Buenos Aires, Buenos Aires, Argentina
- ALZAR – Alzheimer, Buenos Aires, Argentina
| | - Martin A. Bruno
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Facultad Ciencias Médicas, Instituto Ciencias Biomédicas, Universidad Católica de Cuyo, San Juan, Argentina
| | - Sonia M. D. Brucki
- Cognitive and Behavioral Neurology Unit, Hospital das Clinicas, University of São Paulo Medical School, São Paulo, Brazil
- Hospital Santa Marcelina, São Paulo, São Paulo, Brazil
| | - Stefanie Danielle Pina-Escudero
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
| | - Maira Okada de Oliveira
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Cognitive and Behavioral Neurology Unit, Hospital das Clinicas, University of São Paulo Medical School, São Paulo, Brazil
- Hospital Santa Marcelina, São Paulo, São Paulo, Brazil
| | - Patricio Donnelly Kehoe
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Multimedia Signal Processing Group - Neuroimage Division, French-Argentine International Center for Information and Systems Sciences, Rosario, Argentina
| | - Adolfo M. Garcia
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
- Faculty of Education, National University of Cuyo, Mendoza, Argentina
| | | | - Hernando Santamaria-Garcia
- Memory and Cognition Clinic, Intellectus, Hospital Universitario San Ignacio, Bogotá, Colombia
- Ph.D. Program in Neuroscience, Department of Psychiatry, Physiology, Pontificia Universidad Javeriana, Bogotá, Colombia
| | - Sebastian Moguilner
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
| | - Claudia Duran-Aniotz
- School of Psychology, Center for Social and Cognitive Neuroscience, Latin American Institute for Brain Health (BrainLat), Universidad Adolfo Ibanez, Adolfo Ibanez University, Santiago, Chile
| | - Enzo Tagliazucchi
- Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
| | - Marcelo Maito
- Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina
| | | | - Maritza Pintado-Caipa
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Unit Cognitive Impairment and Dementia Prevention, Cognitive Neurology Center, Peruvian Institute of Neurosciences, Lima, Perú
| | - Maria Eugenia Godoy
- Cognitive Neuroscience Center, Universidad de San Andrés, Buenos Aires, Argentina
| | - Vera Bakman
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
| | - Shireen Javandel
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
| | - Kenneth S. Kosik
- Department of Molecular, Cellular, and Developmental Biology, Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, CA, United States
| | - Victor Valcour
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
| | - Bruce L. Miller
- The Global Brain Health Institute (GBHI), University of California, San Francisco, San Francisco, CA, United States
- The Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA, United States
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8
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Li F, Tao Q, Peng W, Zhang T, Si Y, Zhang Y, Yi C, Biswal B, Yao D, Xu P. Inter-subject P300 variability relates to the efficiency of brain networks reconfigured from resting- to task-state: Evidence from a simultaneous event-related EEG-fMRI study. Neuroimage 2020; 205:116285. [DOI: 10.1016/j.neuroimage.2019.116285] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2019] [Revised: 09/12/2019] [Accepted: 10/14/2019] [Indexed: 11/15/2022] Open
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9
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An ANOVA approach for statistical comparisons of brain networks. Sci Rep 2018; 8:4746. [PMID: 29549369 PMCID: PMC5856783 DOI: 10.1038/s41598-018-23152-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2017] [Accepted: 03/06/2018] [Indexed: 12/21/2022] Open
Abstract
The study of brain networks has developed extensively over the last couple of decades. By contrast, techniques for the statistical analysis of these networks are less developed. In this paper, we focus on the statistical comparison of brain networks in a nonparametric framework and discuss the associated detection and identification problems. We tested network differences between groups with an analysis of variance (ANOVA) test we developed specifically for networks. We also propose and analyse the behaviour of a new statistical procedure designed to identify different subnetworks. As an example, we show the application of this tool in resting-state fMRI data obtained from the Human Connectome Project. We identify, among other variables, that the amount of sleep the days before the scan is a relevant variable that must be controlled. Finally, we discuss the potential bias in neuroimaging findings that is generated by some behavioural and brain structure variables. Our method can also be applied to other kind of networks such as protein interaction networks, gene networks or social networks.
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10
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Ibáñez A, García AM, Esteves S, Yoris A, Muñoz E, Reynaldo L, Pietto ML, Adolfi F, Manes F. Social neuroscience: undoing the schism between neurology and psychiatry. Soc Neurosci 2018; 13:1-39. [PMID: 27707008 PMCID: PMC11177280 DOI: 10.1080/17470919.2016.1245214] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Multiple disorders once jointly conceived as "nervous diseases" became segregated by the distinct institutional traditions forged in neurology and psychiatry. As a result, each field specialized in the study and treatment of a subset of such conditions. Here we propose new avenues for interdisciplinary interaction through a triangulation of both fields with social neuroscience. To this end, we review evidence from five relevant domains (facial emotion recognition, empathy, theory of mind, moral cognition, and social context assessment), highlighting their common disturbances across neurological and psychiatric conditions and discussing their multiple pathophysiological mechanisms. Our proposal is anchored in multidimensional evidence, including behavioral, neurocognitive, and genetic findings. From a clinical perspective, this work paves the way for dimensional and transdiagnostic approaches, new pharmacological treatments, and educational innovations rooted in a combined neuropsychiatric training. Research-wise, it fosters new models of the social brain and a novel platform to explore the interplay of cognitive and social functions. Finally, we identify new challenges for this synergistic framework.
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Affiliation(s)
- Agustín Ibáñez
- a Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation , Favaloro University , Buenos Aires , Argentina
- b National Scientific and Technical Research Council (CONICET) , Buenos Aires , Argentina
- c Center for Social and Cognitive Neuroscience (CSCN), School of Psychology , Universidad Adolfo Ibáñez , Santiago de Chile , Chile
- d Universidad Autónoma del Caribe , Barranquilla , Colombia
- e Centre of Excellence in Cognition and its Disorders , Australian Research Council (ACR) , Sydney , Australia
| | - Adolfo M García
- a Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation , Favaloro University , Buenos Aires , Argentina
- b National Scientific and Technical Research Council (CONICET) , Buenos Aires , Argentina
- f Faculty of Elementary and Special Education (FEEyE) , National University of Cuyo (UNCuyo) , Mendoza , Argentina
| | - Sol Esteves
- a Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation , Favaloro University , Buenos Aires , Argentina
| | - Adrián Yoris
- a Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation , Favaloro University , Buenos Aires , Argentina
- b National Scientific and Technical Research Council (CONICET) , Buenos Aires , Argentina
| | - Edinson Muñoz
- g Departamento de Lingüística y Literatura, Facultad de Humanidades , Universidad de Santiago de Chile , Santiago , Chile
| | - Lucila Reynaldo
- a Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation , Favaloro University , Buenos Aires , Argentina
| | | | - Federico Adolfi
- a Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation , Favaloro University , Buenos Aires , Argentina
| | - Facundo Manes
- a Laboratory of Experimental Psychology and Neuroscience (LPEN), Institute of Cognitive and Translational Neuroscience (INCyT), INECO Foundation , Favaloro University , Buenos Aires , Argentina
- b National Scientific and Technical Research Council (CONICET) , Buenos Aires , Argentina
- e Centre of Excellence in Cognition and its Disorders , Australian Research Council (ACR) , Sydney , Australia
- i Department of Experimental Psychology , University of South Carolina , Columbia , SC , USA
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Steiner ABQ, Jacinto AF, Mayoral VFDS, Brucki SMD, Citero VDA. Mild cognitive impairment and progression to dementia of Alzheimer's disease. Rev Assoc Med Bras (1992) 2017; 63:651-655. [PMID: 28977092 DOI: 10.1590/1806-9282.63.07.651] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2017] [Accepted: 02/05/2017] [Indexed: 11/22/2022] Open
Abstract
The increase in life expectancy in the Brazilian population raises questions about the preparation of the public health system in identifying elderly patients with signs of cognitive impairment. Currently, as a consequence of the long duration of preclinical phase of Alzheimer's disease, efforts of early detection have been emphasized. Clinical dementia presents an important impact on the individual's caregivers, family, society and economy. Identifying individuals who already have some cognitive impairment, despite remaining functional, as well as analyzing associated comorbidities, constitutes an opportunity to analyze possibilities for future interventions. Dementias are clinical conditions that impose a burden on the health system with its high costs, whereas the identification of individuals with cognitive impairment without dementia can aid patients and their families to plan the future and mitigate costs. This narrative revision can provide general practitioners with more information on the subject.
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Affiliation(s)
- Ana Beatriz Quintes Steiner
- MD, Psychiatrist, Psychogeriatrist, MSc Student, Psychiatry Department, Escola Paulista de Medicina (EPM), Universidade Federal de São Paulo (Unifesp), São Paulo, SP, Brazil
| | - Alessandro Ferrari Jacinto
- MD, PhD, Geriatrist, Assistant Professor of Geriatrics, Department of Internal Medicine, Faculdade de Medicina de Botucatu (FMB), Universidade Estadual Paulista Júlio de Mesquita Filho (Unesp), Botucatu, SP, Brazil
| | | | - Sonia Maria Dozzi Brucki
- MD, Neurologist. MSc and PhD in Neurology, Unifesp. Post-Doctoral degree from Universidade de São Paulo (USP). Preceptor of the Neurology Residency Program at Hospital Santa Marcelina. Assisting Physician of the Grupo de Neurologia Cognitiva e do Comportamento e do Centro de Referência em Distúrbios Cognitivos (Ceredic), USP, São Paulo, SP, Brazil
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Towards affordable biomarkers of frontotemporal dementia: A classification study via network's information sharing. Sci Rep 2017. [PMID: 28630492 PMCID: PMC5476568 DOI: 10.1038/s41598-017-04204-8] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Developing effective and affordable biomarkers for dementias is critical given the difficulty to achieve early diagnosis. In this sense, electroencephalographic (EEG) methods offer promising alternatives due to their low cost, portability, and growing robustness. Here, we relied on EEG signals and a novel information-sharing method to study resting-state connectivity in patients with behavioral variant frontotemporal dementia (bvFTD) and controls. To evaluate the specificity of our results, we also tested Alzheimer’s disease (AD) patients. The classification power of the ensuing connectivity patterns was evaluated through a supervised classification algorithm (support vector machine). In addition, we compared the classification power yielded by (i) functional connectivity, (ii) relevant neuropsychological tests, and (iii) a combination of both. BvFTD patients exhibited a specific pattern of hypoconnectivity in mid-range frontotemporal links, which showed no alterations in AD patients. These functional connectivity alterations in bvFTD were replicated with a low-density EEG setting (20 electrodes). Moreover, while neuropsychological tests yielded acceptable discrimination between bvFTD and controls, the addition of connectivity results improved classification power. Finally, classification between bvFTD and AD patients was better when based on connectivity than on neuropsychological measures. Taken together, such findings underscore the relevance of EEG measures as potential biomarker signatures for clinical settings.
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