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Toba MN, Godefroy O, Rushmore RJ, Zavaglia M, Maatoug R, Hilgetag CC, Valero-Cabré A. Revisiting 'brain modes' in a new computational era: approaches for the characterization of brain-behavioural associations. Brain 2020; 143:1088-1098. [PMID: 31764975 DOI: 10.1093/brain/awz343] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 08/07/2019] [Accepted: 08/28/2019] [Indexed: 11/12/2022] Open
Abstract
The study of brain-function relationships is undergoing a conceptual and methodological transformation due to the emergence of network neuroscience and the development of multivariate methods for lesion-deficit inferences. Anticipating this process, in 1998 Godefroy and co-workers conceptualized the potential of four elementary typologies of brain-behaviour relationships named 'brain modes' (unicity, equivalence, association, summation) as building blocks able to describe the association between intact or lesioned brain regions and cognitive processes or neurological deficits. In the light of new multivariate lesion inference and network approaches, we critically revisit and update the original theoretical notion of brain modes, and provide real-life clinical examples that support their existence. To improve the characterization of elementary units of brain-behavioural relationships further, we extend such conceptualization with a fifth brain mode (mutual inhibition/masking summation). We critically assess the ability of these five brain modes to account for any type of brain-function relationship, and discuss past versus future contributions in redefining the anatomical basis of human cognition. We also address the potential of brain modes for predicting the behavioural consequences of lesions and their future role in the design of cognitive neurorehabilitation therapies.
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Affiliation(s)
- Monica N Toba
- Laboratory of Functional Neurosciences (EA 4559), University Hospital of Amiens and University of Picardy Jules Verne, Amiens, France
| | - Olivier Godefroy
- Laboratory of Functional Neurosciences (EA 4559), University Hospital of Amiens and University of Picardy Jules Verne, Amiens, France
| | - R Jarrett Rushmore
- Laboratory of Cerebral Dynamics, Plasticity and Rehabilitation, Boston University School of Medicine, Boston, MA 02118, USA.,Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.,Psychiatry Neuroimaging Laboratory, Brigham and Women's Hospital, Boston, MA, USA
| | - Melissa Zavaglia
- Institute of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Focus Area Health, Jacobs University Bremen, Germany
| | - Redwan Maatoug
- Cerebral Dynamics, Plasticity and Rehabilitation Group, FRONTLAB Team, Brain and Spine Institute, ICM, Paris, France.,Sorbonne Université, INSERM UMR S 1127, CNRS UMR 7225, F-75013, and IHU-A-ICM, Paris, France
| | - Claus C Hilgetag
- Institute of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.,Health Sciences Department, Boston University, 635 Commonwealth Ave. Boston, MA 02215, USA
| | - Antoni Valero-Cabré
- Laboratory of Cerebral Dynamics, Plasticity and Rehabilitation, Boston University School of Medicine, Boston, MA 02118, USA.,Cerebral Dynamics, Plasticity and Rehabilitation Group, FRONTLAB Team, Brain and Spine Institute, ICM, Paris, France.,Sorbonne Université, INSERM UMR S 1127, CNRS UMR 7225, F-75013, and IHU-A-ICM, Paris, France.,Cognitive Neuroscience and Information Technology Research Program, Open University of Catalonia (UOC), Barcelona, Catalunya, Spain
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