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Auer T, Goldthorpe R, Peach R, Hebron H, Violante IR. Functionally annotated electrophysiological neuromarkers of healthy ageing and memory function. Hum Brain Mapp 2024; 45:e26687. [PMID: 38651629 PMCID: PMC11036379 DOI: 10.1002/hbm.26687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 02/22/2024] [Accepted: 04/05/2024] [Indexed: 04/25/2024] Open
Abstract
The unprecedented increase in life expectancy presents a unique opportunity and the necessity to explore both healthy and pathological aspects of ageing. Electroencephalography (EEG) has been widely used to identify neuromarkers of cognitive ageing due to its affordability and richness in information. However, despite the growing volume of data and methodological advancements, the abundance of contradictory and non-reproducible findings has hindered clinical translation. To address these challenges, our study introduces a comprehensive workflow expanding on previous EEG studies and investigates various static and dynamic power and connectivity estimates as potential neuromarkers of cognitive ageing in a large dataset. We also assess the robustness of our findings by testing their susceptibility to band specification. Finally, we characterise our findings using functionally annotated brain networks to improve their interpretability and multi-modal integration. Our analysis demonstrates the effect of methodological choices on findings and that dynamic rather than static neuromarkers are not only more sensitive but also more robust. Consequently, they emerge as strong candidates for cognitive ageing neuromarkers. Moreover, we were able to replicate the most established EEG findings in cognitive ageing, such as alpha oscillation slowing, increased beta power, reduced reactivity across multiple bands, and decreased delta connectivity. Additionally, when considering individual variations in the alpha band, we clarified that alpha power is characteristic of memory performance rather than ageing, highlighting its potential as a neuromarker for cognitive ageing. Finally, our approach using functionally annotated source reconstruction allowed us to provide insights into domain-specific electrophysiological mechanisms underlying memory performance and ageing. HIGHLIGHTS: We provide an open and reproducible pipeline with a comprehensive workflow to investigate static and dynamic EEG neuromarkers. Neuromarkers related to neural dynamics are sensitive and robust. Individualised alpha power characterises cognitive performance rather than ageing. Functional annotation allows cross-modal interpretation of EEG findings.
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Affiliation(s)
- Tibor Auer
- School of PsychologyUniversity of SurreyGuildfordUK
| | | | | | - Henry Hebron
- School of PsychologyUniversity of SurreyGuildfordUK
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Olgiati E, Violante IR, Xu S, Sinclair TG, Li LM, Crow JN, Kapsetaki ME, Calvo R, Li K, Nayar M, Grossman N, Patel MC, Wise RJS, Malhotra PA. Targeted non-invasive brain stimulation boosts attention and modulates contralesional brain networks following right hemisphere stroke. Neuroimage Clin 2024; 42:103599. [PMID: 38608376 PMCID: PMC11019269 DOI: 10.1016/j.nicl.2024.103599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [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: 03/01/2024] [Accepted: 03/29/2024] [Indexed: 04/14/2024]
Abstract
Right hemisphere stroke patients frequently present with a combination of lateralised and non-lateralised attentional deficits characteristic of the neglect syndrome. Attentional deficits are associated with poor functional outcome and are challenging to treat, with non-lateralised deficits often persisting into the chronic stage and representing a common complaint among patients and families. In this study, we investigated the effects of non-invasive brain stimulation on non-lateralised attentional deficits in right-hemispheric stroke. In a randomised double-blind sham-controlled crossover study, twenty-two patients received real and sham transcranial Direct Current Stimulation (tDCS) whilst performing a non-lateralised attentional task. A high definition tDCS montage guided by stimulation modelling was employed to maximise current delivery over the right dorsolateral prefrontal cortex, a key node in the vigilance network. In a parallel study, we examined brain network response to this tDCS montage by carrying out concurrent fMRI during stimulation in healthy participants and patients. At the group level, stimulation improved target detection in patients, reducing overall error rate when compared with sham stimulation. TDCS boosted performance throughout the duration of the task, with its effects briefly outlasting stimulation cessation. Exploratory lesion analysis indicated that response to stimulation was related to lesion location rather than volume. In particular, reduced stimulation response was associated with damage to the thalamus and postcentral gyrus. Concurrent stimulation-fMRI revealed that tDCS did not affect local connectivity but influenced functional connectivity within large-scale networks in the contralesional hemisphere. This combined behavioural and functional imaging approach shows that brain stimulation targeted to surviving tissue in the ipsilesional hemisphere improves non-lateralised attentional deficits following stroke. This effect may be exerted via contralesional network effects.
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Affiliation(s)
- Elena Olgiati
- Imperial College London, Department of Brain Sciences, UK; Imperial College Healthcare NHS Trust, UK.
| | - Ines R Violante
- Imperial College London, Department of Brain Sciences, UK; University of Surrey, Department of Psychology, UK
| | - Shuler Xu
- Imperial College London, Department of Brain Sciences, UK; University College London, UK
| | | | - Lucia M Li
- Imperial College London, Department of Brain Sciences, UK; UK Dementia Research Institute Care Research and Technology Centre, Imperial College London and the University of Surrey, London, UK
| | - Jennifer N Crow
- Imperial College London, Department of Brain Sciences, UK; Imperial College Healthcare NHS Trust, UK
| | | | - Roberta Calvo
- UTHealth, Department of Neurobiology and Anatomy, McGovern Medical School, Houston, US
| | - Korina Li
- Imperial College London, Department of Brain Sciences, UK; University College London, UK
| | | | - Nir Grossman
- Imperial College London, Department of Brain Sciences, UK; UK Dementia Research Institute Care Research and Technology Centre, Imperial College London and the University of Surrey, London, UK
| | - Maneesh C Patel
- Imperial College London, Department of Brain Sciences, UK; Imperial College Healthcare NHS Trust, UK
| | - Richard J S Wise
- Imperial College London, Department of Brain Sciences, UK; Imperial College Healthcare NHS Trust, UK
| | - Paresh A Malhotra
- Imperial College London, Department of Brain Sciences, UK; Imperial College Healthcare NHS Trust, UK; UK Dementia Research Institute Care Research and Technology Centre, Imperial College London and the University of Surrey, London, UK
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Cohen Z, Steinbrenner M, Piper RJ, Tangwiriyasakul C, Richardson MP, Sharp DJ, Violante IR, Carmichael DW. Transcranial electrical stimulation during functional magnetic resonance imaging in patients with genetic generalized epilepsy: a pilot and feasibility study. Front Neurosci 2024; 18:1354523. [PMID: 38572149 PMCID: PMC10989273 DOI: 10.3389/fnins.2024.1354523] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 02/13/2024] [Indexed: 04/05/2024] Open
Abstract
Objective A third of patients with epilepsy continue to have seizures despite receiving adequate antiseizure medication. Transcranial direct current stimulation (tDCS) might be a viable adjunct treatment option, having been shown to reduce epileptic seizures in patients with focal epilepsy. Evidence for the use of tDCS in genetic generalized epilepsy (GGE) is scarce. We aimed to establish the feasibility of applying tDCS during fMRI in patients with GGE to study the acute neuromodulatory effects of tDCS, particularly on sensorimotor network activity. Methods Seven healthy controls and three patients with GGE received tDCS with simultaneous fMRI acquisition while watching a movie. Three tDCS conditions were applied: anodal, cathodal and sham. Periods of 60 s without stimulation were applied between each stimulation condition. Changes in sensorimotor cortex connectivity were evaluated by calculating the mean degree centrality across eight nodes of the sensorimotor cortex defined by the Automated Anatomical Labeling atlas (primary motor cortex (precentral left and right), supplementary motor area (left and right), mid-cingulum (left and right), postcentral gyrus (left and right)), across each of the conditions, for each participant. Results Simultaneous tDCS-fMRI was well tolerated in both healthy controls and patients without adverse effects. Anodal and cathodal stimulation reduced mean degree centrality of the sensorimotor network (Friedman's ANOVA with Dunn's multiple comparisons test; adjusted p = 0.02 and p = 0.03 respectively). Mean degree connectivity of the sensorimotor network during the sham condition was not different to the rest condition (adjusted p = 0.94). Conclusion Applying tDCS during fMRI was shown to be feasible and safe in a small group of patients with GGE. Anodal and cathodal stimulation caused a significant reduction in network connectivity of the sensorimotor cortex across participants. This initial research supports the feasibility of using fMRI to guide and understand network modulation by tDCS that might facilitate its clinical application in GGE in the future.
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Affiliation(s)
- Zachary Cohen
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Mirja Steinbrenner
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- Department of Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Rory J. Piper
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
- University College London Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - Chayanin Tangwiriyasakul
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
| | - Mark P. Richardson
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, United Kingdom
| | - David J. Sharp
- The Computational, Cognitive and Clinical Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, United Kingdom
| | - Ines R. Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom
| | - David W. Carmichael
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom
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Mayes WP, Gentle J, Ivanova M, Violante IR. Audio-visual multisensory integration and haptic perception are altered in adults with developmental coordination disorder. Hum Mov Sci 2024; 93:103180. [PMID: 38266441 DOI: 10.1016/j.humov.2024.103180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Revised: 12/06/2023] [Accepted: 01/13/2024] [Indexed: 01/26/2024]
Abstract
Developmental Coordination Disorder (DCD) is a movement disorder in which atypical sensory processing may underly movement atypicality. However, whether altered sensory processing is domain-specific or global in nature, are unanswered questions. Here, we measured for the first time, different aspects of sensory processing and spatiotemporal integration in the same cohort of adult participants with DCD (N = 16), possible DCD (pDCD, N = 12) and neurotypical adults (NT, N = 28). Haptic perception was reduced in both DCD and the extended DCD + pDCD groups when compared to NT adults. Audio-visual integration, measured using the sound-induced double flash illusion, was reduced only in DCD participants, and not the DCD + pDCD extended group. While low-level sensory processing was altered in DCD, the more cognitive, higher-level ability to infer temporal dimensions from spatial information, and vice-versa, as assessed with Tau-Kappa effects, was intact in DCD (and extended DCD + pDCD) participants. Both audio-visual integration and haptic perception difficulties correlated with the degree of self-reported DCD symptoms and were most apparent when comparing DCD and NT groups directly, instead of the expanded DCD + pDCD group. The association of sensory difficulties with DCD symptoms suggests that perceptual differences play a role in motor difficulties in DCD via an underlying internal modelling mechanism.
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Affiliation(s)
- William P Mayes
- School of Psychology, University of Surrey, Stag Hill, Surrey GU2 7XH, UK.
| | - Judith Gentle
- School of Psychology, University of Surrey, Stag Hill, Surrey GU2 7XH, UK.
| | - Mirela Ivanova
- School of Psychology, University of Surrey, Stag Hill, Surrey GU2 7XH, UK
| | - Ines R Violante
- School of Psychology, University of Surrey, Stag Hill, Surrey GU2 7XH, UK.
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Violante IR, Alania K, Cassarà AM, Neufeld E, Acerbo E, Carron R, Williamson A, Kurtin DL, Rhodes E, Hampshire A, Kuster N, Boyden ES, Pascual-Leone A, Grossman N. Publisher Correction: Non-invasive temporal interference electrical stimulation of the human hippocampus. Nat Neurosci 2023; 26:2252. [PMID: 37957321 PMCID: PMC10689236 DOI: 10.1038/s41593-023-01517-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Affiliation(s)
- Ines R Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.
| | - Ketevan Alania
- Department of Brain Sciences, Imperial College London, London, UK
- UK Dementia Research Institute, Imperial College London, London, UK
| | - Antonino M Cassarà
- Foundation for Research on Information Technologies in Society (IT'IS), Zurich, Switzerland
| | - Esra Neufeld
- Foundation for Research on Information Technologies in Society (IT'IS), Zurich, Switzerland
| | - Emma Acerbo
- Institut de Neurosciences des Systèmes, Aix-Marseille University, INSERM, Marseille, France
- Department of Neurology and Neurosurgery, Emory University Hospital, Atlanta, GA, USA
| | - Romain Carron
- Institut de Neurosciences des Systèmes, Aix-Marseille University, INSERM, Marseille, France
- Department of Functional and Stereotactic Neurosurgery, Timone University Hospital, Marseille, France
| | - Adam Williamson
- Institut de Neurosciences des Systèmes, Aix-Marseille University, INSERM, Marseille, France
- International Clinical Research Center, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Danielle L Kurtin
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Edward Rhodes
- Department of Brain Sciences, Imperial College London, London, UK
- UK Dementia Research Institute, Imperial College London, London, UK
| | - Adam Hampshire
- Department of Brain Sciences, Imperial College London, London, UK
| | - Niels Kuster
- Foundation for Research on Information Technologies in Society (IT'IS), Zurich, Switzerland
- Department of Information Technology and Electrical Engineering, Swiss Federal Institute of Technology, Zurich, Switzerland
| | - Edward S Boyden
- Departments of Brain and Cognitive Sciences, Media Arts and Sciences, and Biological Engineering, McGovern and Koch Institutes, Massachusetts Institute of Technology, Cambridge, MA, USA
- Howard Hughes Medical Institute, Cambridge, MA, USA
| | - Alvaro Pascual-Leone
- Hinda and Arthur Marcus Institute for Aging Research and Deanna and Sidney Wolk Center for Memory Health, Hebrew SeniorLife, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Nir Grossman
- Department of Brain Sciences, Imperial College London, London, UK.
- UK Dementia Research Institute, Imperial College London, London, UK.
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Wessel MJ, Beanato E, Popa T, Windel F, Vassiliadis P, Menoud P, Beliaeva V, Violante IR, Abderrahmane H, Dzialecka P, Park CH, Maceira-Elvira P, Morishita T, Cassara AM, Steiner M, Grossman N, Neufeld E, Hummel FC. Noninvasive theta-burst stimulation of the human striatum enhances striatal activity and motor skill learning. Nat Neurosci 2023; 26:2005-2016. [PMID: 37857774 PMCID: PMC10620076 DOI: 10.1038/s41593-023-01457-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 09/07/2023] [Indexed: 10/21/2023]
Abstract
The stimulation of deep brain structures has thus far only been possible with invasive methods. Transcranial electrical temporal interference stimulation (tTIS) is a novel, noninvasive technology that might overcome this limitation. The initial proof-of-concept was obtained through modeling, physics experiments and rodent models. Here we show successful noninvasive neuromodulation of the striatum via tTIS in humans using computational modeling, functional magnetic resonance imaging studies and behavioral evaluations. Theta-burst patterned striatal tTIS increased activity in the striatum and associated motor network. Furthermore, striatal tTIS enhanced motor performance, especially in healthy older participants as they have lower natural learning skills than younger subjects. These findings place tTIS as an exciting new method to target deep brain structures in humans noninvasively, thus enhancing our understanding of their functional role. Moreover, our results lay the groundwork for innovative, noninvasive treatment strategies for brain disorders in which deep striatal structures play key pathophysiological roles.
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Affiliation(s)
- Maximilian J Wessel
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, Clinique Romande de Réadaptation, École Polytechnique Fédérale de Lausanne, Sion, Switzerland
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Elena Beanato
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, Clinique Romande de Réadaptation, École Polytechnique Fédérale de Lausanne, Sion, Switzerland
| | - Traian Popa
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, Clinique Romande de Réadaptation, École Polytechnique Fédérale de Lausanne, Sion, Switzerland
| | - Fabienne Windel
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, Clinique Romande de Réadaptation, École Polytechnique Fédérale de Lausanne, Sion, Switzerland
| | - Pierre Vassiliadis
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, Clinique Romande de Réadaptation, École Polytechnique Fédérale de Lausanne, Sion, Switzerland
- Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium
| | - Pauline Menoud
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, Clinique Romande de Réadaptation, École Polytechnique Fédérale de Lausanne, Sion, Switzerland
| | - Valeriia Beliaeva
- Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, Zurich, Switzerland
| | - Ines R Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | | | - Patrycja Dzialecka
- Department of Brain Sciences, Imperial College London, London, UK
- United Kingdom Dementia Research Institute, Imperial College London, London, UK
| | - Chang-Hyun Park
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, Clinique Romande de Réadaptation, École Polytechnique Fédérale de Lausanne, Sion, Switzerland
| | - Pablo Maceira-Elvira
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, Clinique Romande de Réadaptation, École Polytechnique Fédérale de Lausanne, Sion, Switzerland
| | - Takuya Morishita
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, Clinique Romande de Réadaptation, École Polytechnique Fédérale de Lausanne, Sion, Switzerland
| | - Antonino M Cassara
- Foundation for Research on Information Technologies in Society, Zurich, Switzerland
| | - Melanie Steiner
- Foundation for Research on Information Technologies in Society, Zurich, Switzerland
| | - Nir Grossman
- Department of Brain Sciences, Imperial College London, London, UK
- United Kingdom Dementia Research Institute, Imperial College London, London, UK
| | - Esra Neufeld
- Foundation for Research on Information Technologies in Society, Zurich, Switzerland
| | - Friedhelm C Hummel
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland.
- Defitech Chair of Clinical Neuroengineering, Neuro-X Institute and Brain Mind Institute, Clinique Romande de Réadaptation, École Polytechnique Fédérale de Lausanne, Sion, Switzerland.
- Clinical Neuroscience, University of Geneva Medical School, Geneva, Switzerland.
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Violante IR, Alania K, Cassarà AM, Neufeld E, Acerbo E, Carron R, Williamson A, Kurtin DL, Rhodes E, Hampshire A, Kuster N, Boyden ES, Pascual-Leone A, Grossman N. Non-invasive temporal interference electrical stimulation of the human hippocampus. Nat Neurosci 2023; 26:1994-2004. [PMID: 37857775 PMCID: PMC10620081 DOI: 10.1038/s41593-023-01456-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Accepted: 09/06/2023] [Indexed: 10/21/2023]
Abstract
Deep brain stimulation (DBS) via implanted electrodes is used worldwide to treat patients with severe neurological and psychiatric disorders. However, its invasiveness precludes widespread clinical use and deployment in research. Temporal interference (TI) is a strategy for non-invasive steerable DBS using multiple kHz-range electric fields with a difference frequency within the range of neural activity. Here we report the validation of the non-invasive DBS concept in humans. We used electric field modeling and measurements in a human cadaver to verify that the locus of the transcranial TI stimulation can be steerably focused in the hippocampus with minimal exposure to the overlying cortex. We then used functional magnetic resonance imaging and behavioral experiments to show that TI stimulation can focally modulate hippocampal activity and enhance the accuracy of episodic memories in healthy humans. Our results demonstrate targeted, non-invasive electrical stimulation of deep structures in the human brain.
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Affiliation(s)
- Ines R Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.
| | - Ketevan Alania
- Department of Brain Sciences, Imperial College London, London, UK
- UK Dementia Research Institute, Imperial College London, London, UK
| | - Antonino M Cassarà
- Foundation for Research on Information Technologies in Society (IT'IS), Zurich, Switzerland
| | - Esra Neufeld
- Foundation for Research on Information Technologies in Society (IT'IS), Zurich, Switzerland
| | - Emma Acerbo
- Institut de Neurosciences des Systèmes, Aix-Marseille University, INSERM, Marseille, France
- Department of Neurology and Neurosurgery, Emory University Hospital, Atlanta, GA, USA
| | - Romain Carron
- Institut de Neurosciences des Systèmes, Aix-Marseille University, INSERM, Marseille, France
- Department of Functional and Stereotactic Neurosurgery, Timone University Hospital, Marseille, France
| | - Adam Williamson
- Institut de Neurosciences des Systèmes, Aix-Marseille University, INSERM, Marseille, France
- International Clinical Research Center, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Danielle L Kurtin
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Edward Rhodes
- Department of Brain Sciences, Imperial College London, London, UK
- UK Dementia Research Institute, Imperial College London, London, UK
| | - Adam Hampshire
- Department of Brain Sciences, Imperial College London, London, UK
| | - Niels Kuster
- Foundation for Research on Information Technologies in Society (IT'IS), Zurich, Switzerland
- Department of Information Technology and Electrical Engineering, Swiss Federal Institute of Technology, Zurich, Switzerland
| | - Edward S Boyden
- Departments of Brain and Cognitive Sciences, Media Arts and Sciences, and Biological Engineering, McGovern and Koch Institutes, Massachusetts Institute of Technology, Cambridge, MA, USA
- Howard Hughes Medical Institute, Cambridge, MA, USA
| | - Alvaro Pascual-Leone
- Hinda and Arthur Marcus Institute for Aging Research and Deanna and Sidney Wolk Center for Memory Health, Hebrew SeniorLife, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Nir Grossman
- Department of Brain Sciences, Imperial College London, London, UK.
- UK Dementia Research Institute, Imperial College London, London, UK.
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Kurtin DL, Araña‐Oiarbide G, Lorenz R, Violante IR, Hampshire A. Planning ahead: Predictable switching recruits task-active and resting-state networks. Hum Brain Mapp 2023; 44:5030-5046. [PMID: 37471699 PMCID: PMC10502652 DOI: 10.1002/hbm.26430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Revised: 06/08/2023] [Accepted: 07/05/2023] [Indexed: 07/22/2023] Open
Abstract
Switching is a difficult cognitive process characterised by costs in task performance; specifically, slowed responses and reduced accuracy. It is associated with the recruitment of a large coalition of task-positive regions including those referred to as the multiple demand cortex (MDC). The neural correlates of switching not only include the MDC, but occasionally the default mode network (DMN), a characteristically task-negative network. To unpick the role of the DMN during switching we collected fMRI data from 24 participants playing a switching paradigm that perturbed predictability (i.e., cognitive load) across three switch dimensions-sequential, perceptual, and spatial predictability. We computed the activity maps unique to switch vs. stay trials and all switch dimensions, then evaluated functional connectivity under these switch conditions by computing the pairwise mutual information functional connectivity (miFC) between regional timeseries. Switch trials exhibited an expected cost in reaction time while sequential predictability produced a significant benefit to task accuracy. Our results showed that switch trials recruited a broader activity map than stay trials, including regions of the DMN, the MDC, and task-positive networks such as visual, somatomotor, dorsal, salience/ventral attention networks. More sequentially predictable trials recruited increased activity in the somatomotor and salience/ventral attention networks. Notably, changes in sequential and perceptual predictability, but not spatial predictability, had significant effects on miFC. Increases in perceptual predictability related to decreased miFC between control, visual, somatomotor, and DMN regions, whereas increases in sequential predictability increased miFC between regions in the same networks, as well as regions within ventral attention/ salience, dorsal attention, limbic, and temporal parietal networks. These results provide novel clues as to how DMN may contribute to executive task performance. Specifically, the improved task performance, unique activity, and increased miFC associated with increased sequential predictability suggest that the DMN may coordinate more strongly with the MDC to generate a temporal schema of upcoming task events, which may attenuate switching costs.
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Affiliation(s)
- Danielle L. Kurtin
- NeuroModulation Lab, Department of Psychology, Faculty of Health and Medical SciencesUniversity of SurreyGuildfordUK
- Department of Brain Sciences, Faculty of MedicineImperial College LondonLondonUK
| | | | - Romy Lorenz
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
- The Poldrack LabStanford UniversityStanfordCaliforniaUSA
- Department of NeurophysicsMax‐Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Ines R. Violante
- NeuroModulation Lab, Department of Psychology, Faculty of Health and Medical SciencesUniversity of SurreyGuildfordUK
| | - Adam Hampshire
- Department of Brain Sciences, Faculty of MedicineImperial College LondonLondonUK
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Soleimani G, Nitsche MA, Bergmann TO, Towhidkhah F, Violante IR, Lorenz R, Kuplicki R, Tsuchiyagaito A, Mulyana B, Mayeli A, Ghobadi-Azbari P, Mosayebi-Samani M, Zilverstand A, Paulus MP, Bikson M, Ekhtiari H. Closing the loop between brain and electrical stimulation: towards precision neuromodulation treatments. Transl Psychiatry 2023; 13:279. [PMID: 37582922 PMCID: PMC10427701 DOI: 10.1038/s41398-023-02565-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 07/06/2023] [Accepted: 07/20/2023] [Indexed: 08/17/2023] Open
Abstract
One of the most critical challenges in using noninvasive brain stimulation (NIBS) techniques for the treatment of psychiatric and neurologic disorders is inter- and intra-individual variability in response to NIBS. Response variations in previous findings suggest that the one-size-fits-all approach does not seem the most appropriate option for enhancing stimulation outcomes. While there is a growing body of evidence for the feasibility and effectiveness of individualized NIBS approaches, the optimal way to achieve this is yet to be determined. Transcranial electrical stimulation (tES) is one of the NIBS techniques showing promising results in modulating treatment outcomes in several psychiatric and neurologic disorders, but it faces the same challenge for individual optimization. With new computational and methodological advances, tES can be integrated with real-time functional magnetic resonance imaging (rtfMRI) to establish closed-loop tES-fMRI for individually optimized neuromodulation. Closed-loop tES-fMRI systems aim to optimize stimulation parameters based on minimizing differences between the model of the current brain state and the desired value to maximize the expected clinical outcome. The methodological space to optimize closed-loop tES fMRI for clinical applications includes (1) stimulation vs. data acquisition timing, (2) fMRI context (task-based or resting-state), (3) inherent brain oscillations, (4) dose-response function, (5) brain target trait and state and (6) optimization algorithm. Closed-loop tES-fMRI technology has several advantages over non-individualized or open-loop systems to reshape the future of neuromodulation with objective optimization in a clinically relevant context such as drug cue reactivity for substance use disorder considering both inter and intra-individual variations. Using multi-level brain and behavior measures as input and desired outcomes to individualize stimulation parameters provides a framework for designing personalized tES protocols in precision psychiatry.
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Affiliation(s)
- Ghazaleh Soleimani
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
- Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Michael A Nitsche
- Department of Psychology and Neuroscience, Leibniz Research Center for Working Environment and Human Factors, Dortmund, Germany
- Bielefeld University, University Hospital OWL, Protestant Hospital of Bethel Foundation, University Clinic of Psychiatry and Psychotherapy, and University Clinic of Child and Adolescent Psychiatry and Psychotherapy, Bielefeld, Germany
| | - Til Ole Bergmann
- Neuroimaging Center, Focus Program Translational Neuroscience, Johannes Gutenberg University Medical Center Mainz, Mainz, Germany
- Leibniz Institute for Resilience Research, Mainz, Germany
| | - Farzad Towhidkhah
- Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Ines R Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guilford, UK
| | - Romy Lorenz
- Department of Psychology, Stanford University, Stanford, CA, USA
- MRC CBU, University of Cambridge, Cambridge, UK
- Department of Neurophysics, MPI, Leipzig, Germany
| | | | | | - Beni Mulyana
- Laureate Institute for Brain Research, Tulsa, OK, USA
- School of Electrical and Computer Engineering, University of Oklahoma, Tulsa, OK, USA
| | - Ahmad Mayeli
- University of Pittsburgh Medical Center, Pittsburg, PA, USA
| | - Peyman Ghobadi-Azbari
- Department of Biomedical Engineering, Shahed University, Tehran, Iran
- Iranian National Center for Addiction Studies, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohsen Mosayebi-Samani
- Department of Psychology and Neuroscience, Leibniz Research Center for Working Environment and Human Factors, Dortmund, Germany
| | - Anna Zilverstand
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | | | | | - Hamed Ekhtiari
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA.
- Laureate Institute for Brain Research, Tulsa, OK, USA.
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Kurtin DL, Giunchiglia V, Vohryzek J, Cabral J, Skeldon AC, Violante IR. Moving from phenomenological to predictive modelling: Progress and pitfalls of modelling brain stimulation in-silico. Neuroimage 2023; 272:120042. [PMID: 36965862 DOI: 10.1016/j.neuroimage.2023.120042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [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: 09/29/2022] [Revised: 02/06/2023] [Accepted: 03/16/2023] [Indexed: 03/27/2023] Open
Abstract
Brain stimulation is an increasingly popular neuromodulatory tool used in both clinical and research settings; however, the effects of brain stimulation, particularly those of non-invasive stimulation, are variable. This variability can be partially explained by an incomplete mechanistic understanding, coupled with a combinatorial explosion of possible stimulation parameters. Computational models constitute a useful tool to explore the vast sea of stimulation parameters and characterise their effects on brain activity. Yet the utility of modelling stimulation in-silico relies on its biophysical relevance, which needs to account for the dynamics of large and diverse neural populations and how underlying networks shape those collective dynamics. The large number of parameters to consider when constructing a model is no less than those needed to consider when planning empirical studies. This piece is centred on the application of phenomenological and biophysical models in non-invasive brain stimulation. We first introduce common forms of brain stimulation and computational models, and provide typical construction choices made when building phenomenological and biophysical models. Through the lens of four case studies, we provide an account of the questions these models can address, commonalities, and limitations across studies. We conclude by proposing future directions to fully realise the potential of computational models of brain stimulation for the design of personalized, efficient, and effective stimulation strategies.
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Affiliation(s)
- Danielle L Kurtin
- Neuromodulation Laboratory, School of Psychology, University of Surrey, Guildford, GU2 7XH, United Kingdom; Department of Brain Sciences, Imperial College London, London, United Kingdom.
| | | | - Jakub Vohryzek
- Centre for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain; Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, UK
| | - Joana Cabral
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
| | - Anne C Skeldon
- Department of Mathematics, Centre for Mathematical and Computational Biology, University of Surrey, Guildford, United Kingdom
| | - Ines R Violante
- Neuromodulation Laboratory, School of Psychology, University of Surrey, Guildford, GU2 7XH, United Kingdom
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11
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Kurtin DL, Scott G, Hebron H, Skeldon AC, Violante IR. Task-based differences in brain state dynamics and their relation to cognitive ability. Neuroimage 2023; 271:119945. [PMID: 36870433 DOI: 10.1016/j.neuroimage.2023.119945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Revised: 02/06/2023] [Accepted: 02/14/2023] [Indexed: 03/06/2023] Open
Abstract
Transient patterns of interregional connectivity form and dissipate in response to varying cognitive demands. Yet, it is not clear how different cognitive demands influence brain state dynamics, and whether these dynamics relate to general cognitive ability. Here, using functional magnetic resonance imaging (fMRI) data, we characterised shared, recurrent, global brain states in 187 participants across the working memory, emotion, language, and relation tasks from the Human Connectome Project. Brain states were determined using Leading Eigenvector Dynamics Analysis (LEiDA). In addition to the LEiDA-based metrics of brain state lifetimes and probabilities, we also computed information-theoretic measures of Block Decomposition Method of complexity, Lempel-Ziv complexity and transition entropy. Information theoretic metrics are notable in their ability to compute relationships amongst sequences of states over time, compared to lifetime and probability, which capture the behaviour of each state in isolation. We then related task-based brain state metrics to fluid intelligence. We observed that brain states exhibited stable topology across a range of numbers of clusters (K = 2:15). Most metrics of brain state dynamics, including state lifetime, probability, and all information theoretic metrics, reliably differed between tasks. However, relationships between state dynamic metrics and cognitive abilities varied according to the task, the metric, and the value of K, indicating that there are contextual relationships between task-dependant state dynamics and trait cognitive ability. This study provides evidence that the brain reconfigures across time in response to cognitive demands, and that there are contextual, rather than generalisable, relationships amongst task, state dynamics, and cognitive ability.
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Affiliation(s)
- Danielle L Kurtin
- NeuroModulation Lab, Department of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK; Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK.
| | - Gregory Scott
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London and the University of Surrey, Guildford, UK; Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Henry Hebron
- NeuroModulation Lab, Department of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK; UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London and the University of Surrey, Guildford, UK
| | - Anne C Skeldon
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London and the University of Surrey, Guildford, UK; Department of Mathematics, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, UK
| | - Ines R Violante
- NeuroModulation Lab, Department of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.
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12
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Brunoni AR, Ekhtiari H, Antal A, Auvichayapat P, Baeken C, Benseñor IM, Bikson M, Boggio P, Borroni B, Brighina F, Brunelin J, Carvalho S, Caumo W, Ciechanski P, Charvet L, Clark VP, Cohen Kadosh R, Cotelli M, Datta A, Deng ZD, De Raedt R, De Ridder D, Fitzgerald PB, Floel A, Frohlich F, George MS, Ghobadi-Azbari P, Goerigk S, Hamilton RH, Jaberzadeh SJ, Hoy K, Kidgell DJ, Zonoozi AK, Kirton A, Laureys S, Lavidor M, Lee K, Leite J, Lisanby SH, Loo C, Martin DM, Miniussi C, Mondino M, Monte-Silva K, Morales-Quezada L, Nitsche MA, Okano AH, Oliveira CS, Onarheim B, Pacheco-Barrios K, Padberg F, Nakamura-Palacios EM, Palm U, Paulus W, Plewnia C, Priori A, Rajji TK, Razza LB, Rehn EM, Ruffini G, Schellhorn K, Zare-Bidoky M, Simis M, Skorupinski P, Suen P, Thibaut A, Valiengo LCL, Vanderhasselt MA, Vanneste S, Venkatasubramanian G, Violante IR, Wexler A, Woods AJ, Fregni F. Digitalized transcranial electrical stimulation: A consensus statement. Clin Neurophysiol 2022; 143:154-165. [PMID: 36115809 PMCID: PMC10031774 DOI: 10.1016/j.clinph.2022.08.018] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 08/16/2022] [Accepted: 08/20/2022] [Indexed: 11/15/2022]
Abstract
OBJECTIVE Although relatively costly and non-scalable, non-invasive neuromodulation interventions are treatment alternatives for neuropsychiatric disorders. The recent developments of highly-deployable transcranial electric stimulation (tES) systems, combined with mobile-Health technologies, could be incorporated in digital trials to overcome methodological barriers and increase equity of access. The study aims are to discuss the implementation of tES digital trials by performing a systematic scoping review and strategic process mapping, evaluate methodological aspects of tES digital trial designs, and provide Delphi-based recommendations for implementing digital trials using tES. METHODS We convened 61 highly-productive specialists and contacted 8 tES companies to assess 71 issues related to tES digitalization readiness, and processes, barriers, advantages, and opportunities for implementing tES digital trials. Delphi-based recommendations (>60% agreement) were provided. RESULTS The main strengths/opportunities of tES were: (i) non-pharmacological nature (92% of agreement), safety of these techniques (80%), affordability (88%), and potential scalability (78%). As for weaknesses/threats, we listed insufficient supervision (76%) and unclear regulatory status (69%). Many issues related to methodological biases did not reach consensus. Device appraisal showed moderate digitalization readiness, with high safety and potential for trial implementation, but low connectivity. CONCLUSIONS Panelists recognized the potential of tES for scalability, generalizability, and leverage of digital trials processes; with no consensus about aspects regarding methodological biases. SIGNIFICANCE We further propose and discuss a conceptual framework for exploiting shared aspects between mobile-Health tES technologies with digital trials methodology to drive future efforts for digitizing tES trials.
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Affiliation(s)
- Andre R Brunoni
- Department and Institute of Psychiatry, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil; Department of Internal Medicine, Faculdade de Medicina da Universidade de São Paulo & Hospital Universitário, Universidade de São Paulo, São Paulo, Brazil; Laboratory of Neurosciences (LIM-27), Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Service of Interdisciplinary Neuromodulation (SIN), Department and Institute of Psychiatry, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.
| | - Hamed Ekhtiari
- Laureate Institute for Brain Research (LIBR), Tulsa, OK, USA
| | - Andrea Antal
- Department of Neurology, University Medical Center Göttingen, Göttingen, Germany
| | - Paradee Auvichayapat
- Department of Physiology, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand
| | - Chris Baeken
- Vrije Universiteit Brussel (VUB): Department of Psychiatry University Hospital (UZBrussel), Brussels, Belgium; Department of Head and Skin, Ghent University Hospital, Ghent University, Ghent, Belgium; Ghent Experimental Psychiatry (GHEP) Lab, Ghent, Belgium; Eindhoven University of Technology, Department of Electrical Engineering, the Netherlands
| | - Isabela M Benseñor
- Center for Clinical and Epidemiological Research, University of São Paulo, São Paulo, Brazil
| | - Marom Bikson
- The Department of Biomedical Engineering, The City College of New York, The City University of New York, NY, USA
| | - Paulo Boggio
- Social and Cognitive Neuroscience Laboratory, Center for Biological Science and Health, Mackenzie Presbyterian University, São Paulo, Brazil
| | - Barbara Borroni
- Centre for Neurodegenerative Disorders, Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Italy
| | - Filippo Brighina
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), University of Palermo, Palermo, Italy
| | - Jerome Brunelin
- Centre Hospitalier le Vinatier, Bron, France; INSERM U1028, CNRS UMR 5292, PSYR2 Team, Centre de recherche en Neurosciences de Lyon (CRNL), Université Lyon 1, Lyon, France
| | - Sandra Carvalho
- Translational Neuropsychology Lab, Department of Education and Psychology and William James Center for Research (WJCR), University of Aveiro, Campus Universitário de Santiago, Aveiro, Portugal
| | - Wolnei Caumo
- Post-Graduate Program in Medical Sciences, School of Medicine, Universidade Federal do Rio Grande do Sul (UFRGS), Brazil; Laboratory of Pain and Neuromodulation at Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, Brazil; Pain and Palliative Care Service at HCPA, Brazil; Department of Surgery, School of Medicine, UFRGS, Brazil
| | - Patrick Ciechanski
- Faculty of Medicine and Dentistry, University of Alberta, 1-002 Katz Group Centre for Pharmacy and Health Research, Edmonton, Alberta, Canada
| | - Leigh Charvet
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, USA
| | - Vincent P Clark
- Psychology Clinical Neuroscience Center, Department of Psychology, The University of New Mexico, Albuquerque, NM, USA
| | - Roi Cohen Kadosh
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Maria Cotelli
- Neuropsychology Unit, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Abhishek Datta
- Research and Development, Soterix Medical Inc., New York, USA
| | - Zhi-De Deng
- Noninvasive Neuromodulation Unit, Experimental Therapeutics & Pathophysiology Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Rudi De Raedt
- Department of Experimental Clinical and Health Psychology, Ghent University, Belgium
| | - Dirk De Ridder
- Section of Neurosurgery, Department of Surgical Sciences, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand
| | - Paul B Fitzgerald
- Epworth Centre for Innovation in Mental Health, Epworth Healthcare and Monash University Department of Psychiatry, Camberwell, Victoria, Australia
| | - Agnes Floel
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany; German Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, Germany
| | - Flavio Frohlich
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA; Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, NC, USA; Neuroscience Center, University of North Carolina, Chapel Hill, NC, USA; Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, NC, USA; Department of Biomedical Engineering, University of North Carolina, Chapel Hill, NC, USA; Department of Neurology, University of North Carolina, Chapel Hill, NC, USA
| | - Mark S George
- Department of Psychiatry, Medical University of South Carolina, Charleston, SC, USA; Ralph H. Johnson VA Medical Center, Charleston, SC, USA
| | - Peyman Ghobadi-Azbari
- Iranian National Center for Addiction Studies, Tehran University of Medical Sciences, Tehran, Iran; Department of Biomedical Engineering, Shahed University, Tehran, Iran
| | - Stephan Goerigk
- Department of Psychiatry and Psychotherapy, LMU Hospital, Munich, Germany; Department of Psychological Methodology and Assessment, LMU, Munich, Germany; Hochschule Fresenius, University of Applied Sciences, Munich, Germany
| | - Roy H Hamilton
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Shapour J Jaberzadeh
- Department of Physiotherapy, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia
| | - Kate Hoy
- Epworth Centre for Innovation in Mental Health, Epworth Healthcare and Monash University Department of Psychiatry, Camberwell, Victoria, Australia
| | - Dawson J Kidgell
- Department of Physiotherapy, School of Primary and Allied Health Care, Faculty of Medicine, Nursing and Health Science, Monash University, Melbourne, Australia
| | - Arash Khojasteh Zonoozi
- Iranian National Center for Addiction Studies, Tehran University of Medical Sciences, Tehran, Iran; Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Adam Kirton
- Department of Clinical Neurosciences and Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada
| | - Steven Laureys
- Coma Science Group, GIGA-Consciousness, GIGA Institute, University of Liège, Liege, Belgium
| | - Michal Lavidor
- Bar Ilan University, Department of Psychology, and the Gonda Brain Research Center, Israel
| | - Kiwon Lee
- Ybrain Corporation, Gyeonggi-do, Republic of Korea
| | - Jorge Leite
- INPP, Portucalense University, Porto, Portugal
| | - Sarah H Lisanby
- Noninvasive Neuromodulation Unit, Experimental Therapeutics & Pathophysiology Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Colleen Loo
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia; Black Dog Institute, Sydney, NSW, Australia
| | - Donel M Martin
- School of Psychiatry, University of New South Wales, Sydney, NSW, Australia; Black Dog Institute, Sydney, NSW, Australia
| | - Carlo Miniussi
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto, Italy
| | - Marine Mondino
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), University of Palermo, Palermo, Italy; Centre Hospitalier le Vinatier, Bron, France
| | - Katia Monte-Silva
- Applied Neuroscience Laboratory, Department of Physical Therapy, Universidade Federal de Pernambuco, UFPE, Recife, PE, Brazil; NAPeN Network (Núcleo de Assistência e Pesquisa em Neuromodulação), Brazil
| | - Leon Morales-Quezada
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA 02215, USA
| | - Michael A Nitsche
- Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany; Department of Neurology, University Medical Hospital Bergmannsheil, Bochum, Germany
| | - Alexandre H Okano
- NAPeN Network (Núcleo de Assistência e Pesquisa em Neuromodulação), Brazil; Center for Mathematics, Computation, and Cognition, Universidade Federal do ABC, São Bernardo do Campo, Brazil; Brazilian Institute of Neuroscience and Neurotechnology (BRAINN/CEPID-FAPESP), University of Campinas, Campinas, São Paulo, Brazil
| | - Claudia S Oliveira
- Master's and Doctoral Program in Health Sciences, Faculty of Medical Sciences, Santa Casa de São Paulo, São Paulo, Brazil; Master's and Doctoral Program in Human Movement and Rehabilitation, Evangelical University of Goiás, Anápolis, Brazil
| | | | - Kevin Pacheco-Barrios
- Neuromodulation Center and Center for Clinical Research Learning, Spaulding Rehabilitation Hospital and Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Universidad San Ignacio de Loyola, Vicerrectorado de Investigación, Unidad de Investigación para la Generación y Síntesis de Evidencias en Salud, Lima, Peru
| | - Frank Padberg
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Ester M Nakamura-Palacios
- Laboratory of Cognitive Sciences and Neuropsychopharmacology, Program of Post-Graduation in Physiological Sciences, Health Sciences Center, Federal University of Espirito Santo, Vitória, ES, Brazil
| | - Ulrich Palm
- Department of Psychiatry and Psychotherapy, Klinikum der Universität München, Munich, Germany; Medical Park Chiemseeblick, Rasthausstr. 25, 83233 Bernau-Felden, Germany
| | - Walter Paulus
- Department of Neurology. Ludwig Maximilians University Munich, Klinikum Großhadern, Marchioninistr, München, Germany
| | - Christian Plewnia
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), Neurophysiology and Interventional Neuropsychiatry, University of Tübingen, Tübingen, Germany
| | - Alberto Priori
- Aldo Ravelli Research Center for Neurotechnology and Experimental Neurotherapeutics, Department of Health Sciences, University of Milan, Milan, Italy
| | - Tarek K Rajji
- Centre for Addiction and Mental Health, Toronto, Canada; Temerty Faculty of Medicine, University of Toronto, Toronto, Canada; Toronto Dementia Research Alliance, Toronto, Canada
| | - Lais B Razza
- Service of Interdisciplinary Neuromodulation (SIN), Department and Institute of Psychiatry, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | | | | | | | - Mehran Zare-Bidoky
- Iranian National Center for Addiction Studies, Tehran University of Medical Sciences, Tehran, Iran; School of Medicine, Shahid-Sadoughi University of Medical Sciences, Yazd, Iran
| | - Marcel Simis
- Physical and Rehabilitation Medicine Institute, General Hospital, Medical School of the University of Sao Paulo, São Paulo, Brazil
| | | | - Paulo Suen
- Service of Interdisciplinary Neuromodulation (SIN), Department and Institute of Psychiatry, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Aurore Thibaut
- Coma Science Group, GIGA-Consciousness & Centre du Cerveau, University and University Hospital of Liège, Liège, Belgium
| | - Leandro C L Valiengo
- Laboratory of Neurosciences (LIM-27), Instituto Nacional de Biomarcadores em Neuropsiquiatria (INBioN), Service of Interdisciplinary Neuromodulation (SIN), Department and Institute of Psychiatry, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
| | - Marie-Anne Vanderhasselt
- Department of Head and Skin, Ghent University Hospital, Ghent University, Ghent, Belgium; Ghent Experimental Psychiatry (GHEP) Lab, Ghent, Belgium
| | - Sven Vanneste
- Lab for Clinical & Integrative Neuroscience, Trinity College of Neuroscience, Trinity College Dublin, Ireland
| | - Ganesan Venkatasubramanian
- Department of Psychiatry, National Institute of Mental Health and Neuro Sciences (NIMHANS), Bengaluru, India
| | - Ines R Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Anna Wexler
- Department of Medical Ethics and Health Policy, University of Pennsylvania, Philadelphia, PA, USA
| | - Adam J Woods
- Center for Cognitive Aging and Memory, McKnight Brain Institute, University of Florida, Gainesville, FL, USA; Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA; Department of Neuroscience, University of Florida, Gainesville, FL, USA
| | - Felipe Fregni
- Neuromodulation Center and Center for Clinical Research Learning, Spaulding Rehabilitation Hospital and Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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13
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Ekhtiari H, Ghobadi-Azbari P, Thielscher A, Antal A, Li LM, Shereen AD, Cabral-Calderin Y, Keeser D, Bergmann TO, Jamil A, Violante IR, Almeida J, Meinzer M, Siebner HR, Woods AJ, Stagg CJ, Abend R, Antonenko D, Auer T, Bächinger M, Baeken C, Barron HC, Chase HW, Crinion J, Datta A, Davis MH, Ebrahimi M, Esmaeilpour Z, Falcone B, Fiori V, Ghodratitoostani I, Gilam G, Grabner RH, Greenspan JD, Groen G, Hartwigsen G, Hauser TU, Herrmann CS, Juan CH, Krekelberg B, Lefebvre S, Liew SL, Madsen KH, Mahdavifar-Khayati R, Malmir N, Marangolo P, Martin AK, Meeker TJ, Ardabili HM, Moisa M, Momi D, Mulyana B, Opitz A, Orlov N, Ragert P, Ruff CC, Ruffini G, Ruttorf M, Sangchooli A, Schellhorn K, Schlaug G, Sehm B, Soleimani G, Tavakoli H, Thompson B, Timmann D, Tsuchiyagaito A, Ulrich M, Vosskuhl J, Weinrich CA, Zare-Bidoky M, Zhang X, Zoefel B, Nitsche MA, Bikson M. A checklist for assessing the methodological quality of concurrent tES-fMRI studies (ContES checklist): a consensus study and statement. Nat Protoc 2022; 17:596-617. [PMID: 35121855 PMCID: PMC7612687 DOI: 10.1038/s41596-021-00664-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Accepted: 11/12/2021] [Indexed: 11/09/2022]
Abstract
Low-intensity transcranial electrical stimulation (tES), including alternating or direct current stimulation, applies weak electrical stimulation to modulate the activity of brain circuits. Integration of tES with concurrent functional MRI (fMRI) allows for the mapping of neural activity during neuromodulation, supporting causal studies of both brain function and tES effects. Methodological aspects of tES-fMRI studies underpin the results, and reporting them in appropriate detail is required for reproducibility and interpretability. Despite the growing number of published reports, there are no consensus-based checklists for disclosing methodological details of concurrent tES-fMRI studies. The objective of this work was to develop a consensus-based checklist of reporting standards for concurrent tES-fMRI studies to support methodological rigor, transparency and reproducibility (ContES checklist). A two-phase Delphi consensus process was conducted by a steering committee (SC) of 13 members and 49 expert panelists through the International Network of the tES-fMRI Consortium. The process began with a circulation of a preliminary checklist of essential items and additional recommendations, developed by the SC on the basis of a systematic review of 57 concurrent tES-fMRI studies. Contributors were then invited to suggest revisions or additions to the initial checklist. After the revision phase, contributors rated the importance of the 17 essential items and 42 additional recommendations in the final checklist. The state of methodological transparency within the 57 reviewed concurrent tES-fMRI studies was then assessed by using the checklist. Experts refined the checklist through the revision and rating phases, leading to a checklist with three categories of essential items and additional recommendations: (i) technological factors, (ii) safety and noise tests and (iii) methodological factors. The level of reporting of checklist items varied among the 57 concurrent tES-fMRI papers, ranging from 24% to 76%. On average, 53% of checklist items were reported in a given article. In conclusion, use of the ContES checklist is expected to enhance the methodological reporting quality of future concurrent tES-fMRI studies and increase methodological transparency and reproducibility.
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Affiliation(s)
| | - Peyman Ghobadi-Azbari
- Department of Biomedical Engineering, Shahed University, Tehran, Iran
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | - Axel Thielscher
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark
- Department of Health Technology, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Andrea Antal
- Department of Neurology, University Medical Center Goettingen, Goettingen, Germany
| | - Lucia M Li
- Computational, Cognitive and Clinical Imaging Lab, Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
- UK DRI Centre for Care Research and Technology, Imperial College London, London, UK
| | - A Duke Shereen
- Advanced Science Research Center, The Graduate Center, City University of New York, New York, NY, USA
| | - Yuranny Cabral-Calderin
- Research Group Neural and Environmental Rhythms, Max Planck Institute for Empirical Aesthetics, Frankfurt, Germany
| | - Daniel Keeser
- Department of Psychiatry and Psychotherapy, University Hospital LMU Munich, Munich, Germany
- Department of Radiology, University Hospital LMU Munich, Munich, Germany
- NeuroImaging Core Unit Munich (NICUM), University Hospital LMU Munich, Munich, Germany
| | - Til Ole Bergmann
- Neuroimaging Center (NIC), Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University Medical Center, Mainz, Germany
- Leibniz Institute for Resilience Research, Mainz, Germany
- Department of Neurology and Stroke and Hertie Institute for Clinical Brain Research, Eberhard Karls University of Tübingen, Tübingen, Germany
| | - Asif Jamil
- Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
| | - Ines R Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Jorge Almeida
- Proaction Lab, Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal
- CINEICC, Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal
| | - Marcus Meinzer
- Centre for Clinical Research (UQCCR), The University of Queensland, Brisbane, Queensland, Australia
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany
| | - Hartwig R Siebner
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark
- Department of Neurology, Copenhagen University Hospital Bispebjerg and Frederiksberg, Copenhagen, Denmark
- Institute of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Adam J Woods
- Center for Cognitive Aging and Memory, McKnight Brain Institute, Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Charlotte J Stagg
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, FMRIB, John Radcliffe Hospital, Oxford, UK
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Rany Abend
- Section on Development and Affective Neuroscience, National Institute of Mental Health, Bethesda, MD, USA
| | - Daria Antonenko
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany
| | - Tibor Auer
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Marc Bächinger
- Neural Control of Movement Lab, Department of Health Sciences and Technology, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich, Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
| | - Chris Baeken
- Department of Psychiatry and Medical Psychology, University Hospital Ghent, Ghent, Belgium
- Department of Psychiatry, Vrije Universiteit Brussel, University Hospital Brussels, Brussels, Belgium
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands
| | - Helen C Barron
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, FMRIB, John Radcliffe Hospital, Oxford, UK
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Henry W Chase
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Jenny Crinion
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Abhishek Datta
- Research and Development, Soterix Medical, New York, USA
- The City College of the City University of New York, New York, USA
| | - Matthew H Davis
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Mohsen Ebrahimi
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | - Zeinab Esmaeilpour
- Department of Biomedical Engineering, The City College of New York of CUNY, New York, NY, USA
| | - Brian Falcone
- Northrop Grumman Company, Mission Systems, Falls Church, VA, USA
| | - Valentina Fiori
- Department of Clinical and Behavioral Neurology, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Iman Ghodratitoostani
- Neurocognitive Engineering Laboratory (NEL), Center for Engineering Applied to Health, Institute of Mathematics and Computer Science (ICMC), University of Sao Paulo, Sao Paulo, Brazil
| | - Gadi Gilam
- Systems Neuroscience and Pain Laboratory, Division of Pain Medicine, Department of Anesthesiology, Perioperative, and Pain Medicine, School of Medicine, Stanford University, Palo Alto, CA, USA
- The Institute of Biomedical and Oral Research, Faculty of Dental Medicine, Hebrew University of Jerusalem, Jerusalem, Israel
| | - Roland H Grabner
- Educational Neuroscience, Institute of Psychology, University of Graz, Graz, Austria
| | - Joel D Greenspan
- Department of Neural and Pain Sciences, University of Maryland School of Dentistry, Baltimore, MD, USA
| | - Georg Groen
- Department of Psychiatry, University of Ulm, Ulm, Germany
| | - Gesa Hartwigsen
- Lise Meitner Research Group Cognition and Plasticity, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Tobias U Hauser
- Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, University College London, London, UK
| | - Christoph S Herrmann
- Experimental Psychology Lab, Cluster of Excellence "Hearing4all", European Medical School, University of Oldenburg, Oldenburg, Germany
- Neuroimaging Unit, European Medical School, University of Oldenburg, Oldenburg, Germany
- Research Centre Neurosensory Science, University of Oldenburg, Oldenburg, Germany
| | - Chi-Hung Juan
- Institute of Cognitive Neuroscience, National Central University, Taoyuan, Taiwan
- Cognitive Intelligence and Precision Healthcare Research Center, National Central University, Taoyuan, Taiwan
| | - Bart Krekelberg
- Center for Molecular and Behavioral Neuroscience, Rutgers University-Newark, Newark, NJ, USA
| | - Stephanie Lefebvre
- Translational Research Centre, University Hospital of Psychiatry, University of Bern, Bern, Switzerland
| | - Sook-Lei Liew
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, USA
- USC Stevens Neuroimaging and Informatics Institute, Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Biomedical Engineering, University of Southern California, Los Angeles, CA, USA
- Division of Biokinesiology and Physical Therapy, University of Southern California, Los Angeles, CA, USA
| | - Kristoffer H Madsen
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Hvidovre, Denmark
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, K, Lyngby, Denmark
| | | | - Nastaran Malmir
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | - Paola Marangolo
- Department of Humanities Studies, University Federico II, Naples, Italy
- Aphasia Research Lab, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Andrew K Martin
- Centre for Clinical Research (UQCCR), The University of Queensland, Brisbane, Queensland, Australia
- Department of Psychology, University of Kent, Canterbury, UK
| | - Timothy J Meeker
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA
| | - Hossein Mohaddes Ardabili
- Psychiatry and Behavioral Sciences Research Center, Ibn-e-Sina Hospital, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Marius Moisa
- Zurich Center for Neuroeconomics, Department of Economics, University of Zurich, Zurich, Switzerland
| | - Davide Momi
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
| | - Beni Mulyana
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - Alexander Opitz
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Natasza Orlov
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA
- Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing, China
- Department of Psychology, Jagiellonian University, Cracow, Poland
| | - Patrick Ragert
- Institute for General Kinesiology and Exercise Science, University of Leipzig, Leipzig, Germany
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Christian C Ruff
- Zurich Center for Neuroeconomics, Department of Economics, University of Zurich, Zurich, Switzerland
| | - Giulio Ruffini
- Neuroelectrics Corporation, Cambridge, Cambridge, MA, USA
- Neuroelectrics Corporation, Barcelona, Barcelona, Spain
| | - Michaela Ruttorf
- Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Arshiya Sangchooli
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
| | | | - Gottfried Schlaug
- Neuroimaging-Neuromodulation and Stroke Recovery Laboratories, Department of Neurology, Baystate-University of Massachusetts Medical School, and Department of Biomedical Engineering, Institute of Applied Life Sciences, University of Massachusetts, Amherst, MA, USA
| | - Bernhard Sehm
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Neurology, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany
| | - Ghazaleh Soleimani
- Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Hosna Tavakoli
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
- Department of Cognitive Neuroscience, Institute for Cognitive Sciences Studies, Tehran, Iran
| | - Benjamin Thompson
- School of Optometry and Vision Science, University of Auckland, Auckland, New Zealand
- School of Optometry and Vision Science, University of Waterloo, Waterloo, Ontario, Canada
- Centre for Eye and Vision Research, Hong Kong, Hong Kong
| | - Dagmar Timmann
- Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), Essen University Hospital, University of Duisburg-Essen, Essen, Germany
| | | | - Martin Ulrich
- Department of Psychiatry, University of Ulm, Ulm, Germany
| | - Johannes Vosskuhl
- Experimental Psychology Lab, Cluster of Excellence "Hearing4all", European Medical School, University of Oldenburg, Oldenburg, Germany
| | - Christiane A Weinrich
- Department of Neurology, University Medical Center Goettingen, Goettingen, Germany
- Department of Cognitive Neurology, University Medical Center Goettingen, Goettingen, Germany
| | - Mehran Zare-Bidoky
- Iranian National Center for Addiction Studies (INCAS), Tehran University of Medical Sciences, Tehran, Iran
- Shahid-Sadoughi University of Medical Sciences, Yazd, Iran
| | - Xiaochu Zhang
- Department of Psychology, School of Humanities & Social Science, University of Science & Technology of China, Hefei, China
| | - Benedikt Zoefel
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
- Centre de Recherche Cerveau et Cognition (CerCo), CNRS, Toulouse, France
- Université Toulouse III Paul Sabatier, Toulouse, France
| | - Michael A Nitsche
- Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany
- Department of Neurology, University Medical Hospital Bergmannsheil, Bochum, Germany
| | - Marom Bikson
- Department of Biomedical Engineering, The City College of New York of CUNY, New York, NY, USA
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14
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Parkin BL, Daws RE, Das-Neves I, Violante IR, Soreq E, Faisal AA, Sandrone S, Lao-Kaim NP, Martin-Bastida A, Roussakis AA, Piccini P, Hampshire A. Dissociable effects of age and Parkinson's disease on instruction-based learning. Brain Commun 2021; 3:fcab175. [PMID: 34485905 PMCID: PMC8410985 DOI: 10.1093/braincomms/fcab175] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 04/06/2021] [Accepted: 05/10/2021] [Indexed: 12/02/2022] Open
Abstract
The cognitive deficits associated with Parkinson's disease vary across individuals and change across time, with implications for prognosis and treatment. Key outstanding challenges are to define the distinct behavioural characteristics of this disorder and develop diagnostic paradigms that can assess these sensitively in individuals. In a previous study, we measured different aspects of attentional control in Parkinson's disease using an established fMRI switching paradigm. We observed no deficits for the aspects of attention the task was designed to examine; instead those with Parkinson's disease learnt the operational requirements of the task more slowly. We hypothesized that a subset of people with early-to-mid stage Parkinson's might be impaired when encoding rules for performing new tasks. Here, we directly test this hypothesis and investigate whether deficits in instruction-based learning represent a characteristic of Parkinson's Disease. Seventeen participants with Parkinson's disease (8 male; mean age: 61.2 years), 18 older adults (8 male; mean age: 61.3 years) and 20 younger adults (10 males; mean age: 26.7 years) undertook a simple instruction-based learning paradigm in the MRI scanner. They sorted sequences of coloured shapes according to binary discrimination rules that were updated at two-minute intervals. Unlike common reinforcement learning tasks, the rules were unambiguous, being explicitly presented; consequently, there was no requirement to monitor feedback or estimate contingencies. Despite its simplicity, a third of the Parkinson's group, but only one older adult, showed marked increases in errors, 4 SD greater than the worst performing young adult. The pattern of errors was consistent, reflecting a tendency to misbind discrimination rules. The misbinding behaviour was coupled with reduced frontal, parietal and anterior caudate activity when rules were being encoded, but not when attention was initially oriented to the instruction slides or when discrimination trials were performed. Concomitantly, Magnetic Resonance Spectroscopy showed reduced gamma-Aminobutyric acid levels within the mid-dorsolateral prefrontal cortices of individuals who made misbinding errors. These results demonstrate, for the first time, that a subset of early-to-mid stage people with Parkinson's show substantial deficits when binding new task rules in working memory. Given the ubiquity of instruction-based learning, these deficits are likely to impede daily living. They will also confound clinical assessment of other cognitive processes. Future work should determine the value of instruction-based learning as a sensitive early marker of cognitive decline and as a measure of responsiveness to therapy in Parkinson's disease.
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Affiliation(s)
- Beth L Parkin
- Department of Psychology, School of Social Science, University of Westminster, 115 New Cavendish Street, London, W1W 6UW, UK
| | - Richard E Daws
- The Cognitive, Computational and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London W120NN, UK
| | - Ines Das-Neves
- The Cognitive, Computational and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London W120NN, UK
| | - Ines R Violante
- The Cognitive, Computational and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London W120NN, UK
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK
| | - Eyal Soreq
- The Cognitive, Computational and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London W120NN, UK
| | - A Aldo Faisal
- Brain and Behaviour Laboratory, Department of Bioengineering, Imperial College London, London W12 0NN, UK
- Brain and Behaviour Laboratory, Department of Computing, Imperial College London, London W12 0NN, UK
- Behaviour Analytics Lab, Data Science Institute, Imperial College London, London W12 0NN, UK
- MRC London Institute of Medical Sciences, London W12 0NN, UK
| | - Stefano Sandrone
- The Cognitive, Computational and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London W120NN, UK
| | - Nicholas P Lao-Kaim
- Neurology Imaging Unit, Division of Neurology, Imperial College London, London W12 0NN, UK
| | - Antonio Martin-Bastida
- Neurology Imaging Unit, Division of Neurology, Imperial College London, London W12 0NN, UK
- Department of Neurology and Neurosciences, Clinica Universidad de Navarra, Pamplona-Madrid 28027, Spain
| | | | - Paola Piccini
- Neurology Imaging Unit, Division of Neurology, Imperial College London, London W12 0NN, UK
| | - Adam Hampshire
- The Cognitive, Computational and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London W120NN, UK
- UK DRI Care Research & Technology Centre, Imperial College London, London W12 0NN, UK
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15
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Kurtin DL, Violante IR, Zimmerman K, Leech R, Hampshire A, Patel MC, Carmichael DW, Sharp DJ, Li LM. Investigating the interaction between white matter and brain state on tDCS-induced changes in brain network activity. Brain Stimul 2021; 14:1261-1270. [PMID: 34438046 PMCID: PMC8460997 DOI: 10.1016/j.brs.2021.08.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 07/30/2021] [Accepted: 08/05/2021] [Indexed: 11/21/2022] Open
Abstract
Background Transcranial direct current stimulation (tDCS) is a form of noninvasive brain stimulation whose potential as a cognitive therapy is hindered by our limited understanding of how participant and experimental factors influence its effects. Using functional MRI to study brain networks, we have previously shown in healthy controls that the physiological effects of tDCS are strongly influenced by brain state. We have additionally shown, in both healthy and traumatic brain injury (TBI) populations, that the behavioral effects of tDCS are positively correlated with white matter (WM) structure. Objectives In this study we investigate how these two factors, WM structure and brain state, interact to shape the effect of tDCS on brain network activity. Methods We applied anodal, cathodal and sham tDCS to the right inferior frontal gyrus (rIFG) of healthy (n = 22) and TBI participants (n = 34). We used the Choice Reaction Task (CRT) performance to manipulate brain state during tDCS. We acquired simultaneous fMRI to assess activity of cognitive brain networks and used Fractional Anisotropy (FA) as a measure of WM structure. Results We find that the effects of tDCS on brain network activity in TBI participants are highly dependent on brain state, replicating findings from our previous healthy control study in a separate, patient cohort. We then show that WM structure further modulates the brain-state dependent effects of tDCS on brain network activity. These effects are not unidirectional - in the absence of task with anodal and cathodal tDCS, FA is positively correlated with brain activity in several regions of the default mode network. Conversely, with cathodal tDCS during CRT performance, FA is negatively correlated with brain activity in a salience network region. Conclusions Our results show that experimental and participant factors interact to have unexpected effects on brain network activity, and that these effects are not fully predictable by studying the factors in isolation. We replicated the brain state and polarity dependent effects of tDCS. White matter structure influences tDCS's state-dependent changes in neural activity The parameters of tDCS may operate under a hierarchy of influence.
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Affiliation(s)
- Danielle L Kurtin
- Computational, Clinical, and Cognitive Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, United Kingdom; Neuromodulation Laboratory, School of Psychology, University of Surrey, Guildford, United Kingdom.
| | - Ines R Violante
- Neuromodulation Laboratory, School of Psychology, University of Surrey, Guildford, United Kingdom
| | - Karl Zimmerman
- Computational, Clinical, and Cognitive Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, United Kingdom
| | - Robert Leech
- Centre for Neuroimaging Science, King's College London, Denmark Hill, London, United Kingdom
| | - Adam Hampshire
- Computational, Clinical, and Cognitive Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, United Kingdom; Department of Biomedical Imaging, King's College London, 3rd Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, United Kingdom
| | - Maneesh C Patel
- Computational, Clinical, and Cognitive Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, United Kingdom
| | - David W Carmichael
- Department of Biomedical Imaging, King's College London, 3rd Floor Lambeth Wing, St Thomas' Hospital, London SE1 7EH, United Kingdom
| | - David J Sharp
- Computational, Clinical, and Cognitive Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, United Kingdom; Imperial UK Dementia Research Institute at Imperial Care Research and Technology Centre, United Kingdom
| | - Lucia M Li
- Computational, Clinical, and Cognitive Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, United Kingdom; Imperial UK Dementia Research Institute at Imperial Care Research and Technology Centre, United Kingdom.
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16
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Soreq E, Violante IR, Daws RE, Hampshire A. Neuroimaging evidence for a network sampling theory of individual differences in human intelligence test performance. Nat Commun 2021; 12:2072. [PMID: 33824305 PMCID: PMC8024400 DOI: 10.1038/s41467-021-22199-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Accepted: 02/25/2021] [Indexed: 01/07/2023] Open
Abstract
Despite a century of research, it remains unclear whether human intelligence should be studied as one dominant, several major, or many distinct abilities, and how such abilities relate to the functional organisation of the brain. Here, we combine psychometric and machine learning methods to examine in a data-driven manner how factor structure and individual variability in cognitive-task performance relate to dynamic-network connectomics. We report that 12 sub-tasks from an established intelligence test can be accurately multi-way classified (74%, chance 8.3%) based on the network states that they evoke. The proximities of the tasks in behavioural-psychometric space correlate with the similarities of their network states. Furthermore, the network states were more accurately classified for higher relative to lower performing individuals. These results suggest that the human brain uses a high-dimensional network-sampling mechanism to flexibly code for diverse cognitive tasks. Population variability in intelligence test performance relates to the fidelity of expression of these task-optimised network states.
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Affiliation(s)
- Eyal Soreq
- The Computational, Cognitive and Clinical Neuroimaging Laboratory, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK.
| | - Ines R Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Richard E Daws
- The Computational, Cognitive and Clinical Neuroimaging Laboratory, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Adam Hampshire
- The Computational, Cognitive and Clinical Neuroimaging Laboratory, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
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17
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d'Almeida OC, Violante IR, Quendera B, Moreno C, Gomes L, Castelo-Branco M. The neurometabolic profiles of GABA and Glutamate as revealed by proton magnetic resonance spectroscopy in type 1 and type 2 diabetes. PLoS One 2020; 15:e0240907. [PMID: 33120406 PMCID: PMC7595380 DOI: 10.1371/journal.pone.0240907] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 10/05/2020] [Indexed: 01/06/2023] Open
Abstract
Glucose metabolism is pivotal for energy and neurotransmitter synthesis and homeostasis, particularly in Glutamate and GABA systems. In turn, the stringent control of inhibitory/excitatory tonus is known to be relevant in neuropsychiatric conditions. Glutamatergic neurotransmission dominates excitatory synaptic functions and is involved in plasticity and excitotoxicity. GABAergic neurochemistry underlies inhibition and predicts impaired psychophysical function in diabetes. It has also been associated with cognitive decline in people with diabetes. Still, the relation between metabolic homeostasis and neurotransmission remains elusive. Two 3T proton MR spectroscopy studies were independently conducted in the occipital cortex to provide insight into inhibitory/excitatory homeostasis (GABA/Glutamate) and to evaluate the impact of chronic metabolic control on the levels and regulation (as assessed by regression slopes) of the two main neurotransmitters of the CNS in type 2 diabetes (T2DM) and type 1 diabetes (T1DM). Compared to controls, participants with T2DM showed significantly lower Glutamate, and also GABA. Nevertheless, higher levels of GABA/Glx (Glutamate+Glutamine), and lower levels of Glutamate were associated with poor metabolic control in participants with T2DM. Importantly, the relationship between GABA/Glx and HbA1c found in T2DM supports a relationship between inhibitory/excitatory balance and metabolic control. Interestingly, this neurometabolic profile was undetected in T1DM. In this condition we found strong evidence for alterations in MRS surrogate measures of neuroinflammation (myo-Inositol), positively related to chronic metabolic control. Our results suggest a role for Glutamate as a global marker of T2DM and a sensitive marker of glycemic status. GABA/Glx may provide a signature of cortical metabolic state in poorly controlled patients as assessed by HbA1c levels, which indicate long-term blood Glucose control. These findings are consistent with an interplay between abnormal neurotransmission and metabolic control in particular in type 2 diabetes thereby revealing dissimilar contributions to the pathophysiology of neural dysfunction in both types of diabetes.
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Affiliation(s)
- Otília C d'Almeida
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal.,CiBIT, Coimbra Institute for Biomedical Imaging and Translational Research, Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
| | - Ines R Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom
| | - Bruno Quendera
- CiBIT, Coimbra Institute for Biomedical Imaging and Translational Research, Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
| | - Carolina Moreno
- Department of Endocrinology, Coimbra University and Hospital Centre (CHUC), Coimbra, Portugal
| | - Leonor Gomes
- Department of Endocrinology, Coimbra University and Hospital Centre (CHUC), Coimbra, Portugal
| | - Miguel Castelo-Branco
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal.,CiBIT, Coimbra Institute for Biomedical Imaging and Translational Research, Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
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18
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Goldthorpe RA, Rapley JM, Violante IR. A Systematic Review of Non-invasive Brain Stimulation Applications to Memory in Healthy Aging. Front Neurol 2020; 11:575075. [PMID: 33193023 PMCID: PMC7604325 DOI: 10.3389/fneur.2020.575075] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 09/11/2020] [Indexed: 12/15/2022] Open
Abstract
It has long been acknowledged that memory changes over the course of one's life, irrespective of diseases like dementia. Approaches to mitigate these changes have however yielded mixed results. Brain stimulation has been identified as one novel approach of augmenting older adult's memory. Thus far, such approaches have however been nuanced, targeting different memory domains with different methodologies. This has produced an amalgam of research with an unclear image overall. This systematic review therefore aims to clarify this landscape, evaluating, and interpreting available research findings in a coherent manner. A systematic search of relevant literature was conducted across Medline, PsycInfo, Psycarticles and the Psychology and Behavioral Sciences Collection, which uncovered 44 studies employing non-invasive electrical brain stimulation in healthy older adults. All studies were of generally good quality spanning numerous memory domains. Within these, evidence was found for non-invasive brain stimulation augmenting working, episodic, associative, semantic, and procedural memory, with the first three domains having the greatest evidence base. Key sites for stimulation included the left dorsolateral prefrontal cortex (DLPFC), temporoparietal region, and primary motor cortex, with transcranial direct current stimulation (tDCS) holding the greatest literature base. Inconsistencies within the literature are highlighted and interpreted, however this discussion was constrained by potential confounding variables within the literature, a risk of bias, and challenges defining research aims and results. Non-invasive brain stimulation often did however have a positive and predictable impact on older adult's memory, and thus warrants further research to better understand these effects.
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Affiliation(s)
| | - Jessica M Rapley
- School of Psychology, University of Surrey, Guildford, United Kingdom
| | - Ines R Violante
- School of Psychology, University of Surrey, Guildford, United Kingdom
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19
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Beppi C, Violante IR, Hampshire A, Grossman N, Sandrone S. Patterns of Focal- and Large-Scale Synchronization in Cognitive Control and Inhibition: A Review. Front Hum Neurosci 2020; 14:196. [PMID: 32670035 PMCID: PMC7330107 DOI: 10.3389/fnhum.2020.00196] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Accepted: 04/30/2020] [Indexed: 01/08/2023] Open
Abstract
Neural synchronization patterns are involved in several complex cognitive functions and constitute a growing trend in neuroscience research. While synchrony patterns in working memory have been extensively discussed, a complete understanding of their role in cognitive control and inhibition is still elusive. Here, we provide an up-to-date review on synchronization patterns underlying behavioral inhibition, extrapolating common grounds, and dissociating features with other inhibitory functions. Moreover, we suggest a schematic conceptual framework and highlight existing gaps in the literature, current methodological challenges, and compelling research questions for future studies.
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Affiliation(s)
- Carolina Beppi
- Neuroscience Center Zürich (ZNZ), University of Zürich (UZH) and Swiss Federal Institute of Technology in Zürich (ETH), Zurich, Switzerland
- Department of Neurology, University Hospital Zürich, University of Zürich, Zurich, Switzerland
| | - Ines R. Violante
- Computational, Cognitive and Clinical Neuroscience Laboratory (C3NL), Department of Brain Sciences, Imperial College London, London, United Kingdom
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom
| | - Adam Hampshire
- Computational, Cognitive and Clinical Neuroscience Laboratory (C3NL), Department of Brain Sciences, Imperial College London, London, United Kingdom
| | - Nir Grossman
- Department of Brain Sciences, Imperial College London, London, United Kingdom
| | - Stefano Sandrone
- Computational, Cognitive and Clinical Neuroscience Laboratory (C3NL), Department of Brain Sciences, Imperial College London, London, United Kingdom
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Li LM, Violante IR, Zimmerman K, Leech R, Hampshire A, Patel M, Opitz A, McArthur D, Jolly A, Carmichael DW, Sharp DJ. Traumatic axonal injury influences the cognitive effect of non-invasive brain stimulation. Brain 2019; 142:3280-3293. [PMID: 31504237 PMCID: PMC6794939 DOI: 10.1093/brain/awz252] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2019] [Revised: 06/06/2019] [Accepted: 06/25/2019] [Indexed: 01/05/2023] Open
Abstract
Non-invasive brain stimulation has been widely investigated as a potential treatment for a range of neurological and psychiatric conditions, including brain injury. However, the behavioural effects of brain stimulation are variable, for reasons that are poorly understood. This is a particular challenge for traumatic brain injury, where patterns of damage and their clinical effects are heterogeneous. Here we test the hypothesis that the response to transcranial direct current stimulation following traumatic brain injury is dependent on white matter damage within the stimulated network. We used a novel simultaneous stimulation-MRI protocol applying anodal, cathodal and sham stimulation to 24 healthy control subjects and 35 patients with moderate/severe traumatic brain injury. Stimulation was applied to the right inferior frontal gyrus/anterior insula node of the salience network, which was targeted because our previous work had shown its importance to executive function. Stimulation was applied during performance of the Stop Signal Task, which assesses response inhibition, a key component of executive function. Structural MRI was used to assess the extent of brain injury, including diffusion MRI assessment of post-traumatic axonal injury. Functional MRI, which was simultaneously acquired to delivery of stimulation, assessed the effects of stimulation on cognitive network function. Anodal stimulation improved response inhibition in control participants, an effect that was not observed in the patient group. The extent of traumatic axonal injury within the salience network strongly influenced the behavioural response to stimulation. Increasing damage to the tract connecting the stimulated right inferior frontal gyrus/anterior insula to the rest of the salience network was associated with reduced beneficial effects of stimulation. In addition, anodal stimulation normalized default mode network activation in patients with poor response inhibition, suggesting that stimulation modulates communication between the networks involved in supporting cognitive control. These results demonstrate an important principle: that white matter structure of the connections within a stimulated brain network influences the behavioural response to stimulation. This suggests that a personalized approach to non-invasive brain stimulation is likely to be necessary, with structural integrity of the targeted brain networks an important criterion for patient selection and an individualized approach to the selection of stimulation parameters.
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Affiliation(s)
- Lucia M Li
- Computational, Cognitive and Clinical Imaging Lab, Division of Brain Sciences, Department of Medicine, Imperial College London, UK
- UK DRI Centre for Care Research and Technology, Imperial College London, UK
| | - Ines R Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, UK
| | - Karl Zimmerman
- Computational, Cognitive and Clinical Imaging Lab, Division of Brain Sciences, Department of Medicine, Imperial College London, UK
| | - Rob Leech
- Centre of Neuroimaging Science, Kings College London, UK
| | - Adam Hampshire
- Computational, Cognitive and Clinical Imaging Lab, Division of Brain Sciences, Department of Medicine, Imperial College London, UK
- UK DRI Centre for Care Research and Technology, Imperial College London, UK
| | - Maneesh Patel
- Department of Imaging, Charing Cross Hospital, London, UK
| | - Alexander Opitz
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - David McArthur
- David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
| | - Amy Jolly
- Computational, Cognitive and Clinical Imaging Lab, Division of Brain Sciences, Department of Medicine, Imperial College London, UK
| | | | - David J Sharp
- Computational, Cognitive and Clinical Imaging Lab, Division of Brain Sciences, Department of Medicine, Imperial College London, UK
- UK DRI Centre for Care Research and Technology, Imperial College London, UK
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21
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Lorenz R, Simmons LE, Monti RP, Arthur JL, Limal S, Laakso I, Leech R, Violante IR. Efficiently searching through large tACS parameter spaces using closed-loop Bayesian optimization. Brain Stimul 2019; 12:1484-1489. [PMID: 31289013 PMCID: PMC6879005 DOI: 10.1016/j.brs.2019.07.003] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2019] [Revised: 06/26/2019] [Accepted: 07/01/2019] [Indexed: 11/25/2022] Open
Abstract
Background Selecting optimal stimulation parameters from numerous possibilities is a major obstacle for assessing the efficacy of non-invasive brain stimulation. Objective We demonstrate that Bayesian optimization can rapidly search through large parameter spaces and identify subject-level stimulation parameters in real-time. Methods To validate the method, Bayesian optimization was employed using participants’ binary judgements about the intensity of phosphenes elicited through tACS. Results We demonstrate the efficiency of Bayesian optimization in identifying parameters that maximize phosphene intensity in a short timeframe (5 min for >190 possibilities). Our results replicate frequency-dependent effects across three montages and show phase-dependent effects of phosphene perception. Computational modelling explains that these phase effects result from constructive/destructive interference of the current reaching the retinas. Simulation analyses demonstrate the method's versatility for complex response functions, even when accounting for noisy observations. Conclusion Alongside subjective ratings, this method can be used to optimize tACS parameters based on behavioral and neural measures and has the potential to be used for tailoring stimulation protocols to individuals.
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Affiliation(s)
- Romy Lorenz
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF, UK; Max-Planck Institute for Human Cognitive and Brain Sciences, Leipzig, 04303, Germany.
| | - Laura E Simmons
- Computational, Cognitive and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London, W12 0NN, UK
| | - Ricardo P Monti
- Gatsby Computational Neuroscience Unit, University College London, London, W1T 4JG, UK
| | - Joy L Arthur
- Computational, Cognitive and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London, W12 0NN, UK
| | - Severin Limal
- Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, OX1 3PT, UK
| | - Ilkka Laakso
- Department of Electrical Engineering and Automation, Aalto University, Espoo, 02150, Finland
| | - Robert Leech
- Centre for Neuroimaging Science, King's College London, London, SE5 8AF, UK
| | - Ines R Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, GU2 7XH, UK.
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Hampshire A, Daws RE, Neves ID, Soreq E, Sandrone S, Violante IR. Probing cortical and sub-cortical contributions to instruction-based learning: Regional specialisation and global network dynamics. Neuroimage 2019; 192:88-100. [PMID: 30851447 DOI: 10.1016/j.neuroimage.2019.03.002] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Revised: 02/28/2019] [Accepted: 03/03/2019] [Indexed: 11/29/2022] Open
Abstract
Diverse cortical networks and striatal brain regions are implicated in instruction-based learning (IBL); however, their distinct contributions remain unclear. We use a modified fMRI paradigm to test two hypotheses regarding the brain mechanisms that underlie IBL. One hypothesis proposes that anterior caudate and frontoparietal regions transiently co-activate when new rules are being bound in working memory. The other proposes that they mediate the application of the rules at different stages of the consolidation process. In accordance with the former hypothesis, we report strong activation peaks within and increased connectivity between anterior caudate and frontoparietal regions when rule-instruction slides are presented. However, similar effects occur throughout a broader set of cortical and sub-cortical regions, indicating a metabolically costly reconfiguration of the global brain state. The distinct functional roles of cingulo-opercular, frontoparietal and default-mode networks are apparent from their activation throughout, early and late in the practice phase respectively. Furthermore, there is tentative evidence of a peak in anterior caudate activity mid-way through the practice stage. These results demonstrate how performance of the same simple task involves a steadily shifting balance of brain systems as learning progresses. They also highlight the importance of distinguishing between regional specialisation and global dynamics when studying the network mechanisms that underlie cognition and learning.
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Affiliation(s)
- Adam Hampshire
- Computational, Cognitive and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London W12 0NN, UK.
| | - Richard E Daws
- Computational, Cognitive and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London W12 0NN, UK
| | - Ines Das Neves
- Computational, Cognitive and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London W12 0NN, UK
| | - Eyal Soreq
- Computational, Cognitive and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London W12 0NN, UK
| | - Stefano Sandrone
- Computational, Cognitive and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London W12 0NN, UK
| | - Ines R Violante
- Computational, Cognitive and Clinical Neuroscience Laboratory, Department of Medicine, Imperial College London, London W12 0NN, UK; School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK
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23
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Li LM, Violante IR, Leech R, Hampshire A, Opitz A, McArthur D, Carmichael DW, Sharp DJ. Cognitive enhancement with Salience Network electrical stimulation is influenced by network structural connectivity. Neuroimage 2019; 185:425-433. [PMID: 30385222 PMCID: PMC6299257 DOI: 10.1016/j.neuroimage.2018.10.069] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2018] [Revised: 10/11/2018] [Accepted: 10/26/2018] [Indexed: 12/13/2022] Open
Abstract
The Salience Network (SN) and its interactions are important for cognitive control. We have previously shown that structural damage to the SN is associated with abnormal functional connectivity between the SN and Default Mode Network (DMN), abnormal DMN deactivation, and impaired response inhibition, which is an important aspect of cognitive control. This suggests that stimulating the SN might enhance cognitive control. Here, we tested whether non-invasive transcranial direct current stimulation (TDCS) could be used to modulate activity within the SN and enhance cognitive control. TDCS was applied to the right inferior frontal gyrus/anterior insula cortex during performance of the Stop Signal Task (SST) and concurrent functional (f)MRI. Anodal TDCS improved response inhibition. Furthermore, stratification of participants based on SN structural connectivity showed that it was an important influence on both behavioural and physiological responses to anodal TDCS. Participants with high fractional anisotropy within the SN showed improved SST performance and increased activation of the SN with anodal TDCS, whilst those with low fractional anisotropy within the SN did not. Cathodal stimulation of the SN produced activation of the right caudate, an effect which was not modulated by SN structural connectivity. Our results show that stimulation targeted to the SN can improve response inhibition, supporting the causal influence of this network on cognitive control and confirming it as a target to produce cognitive enhancement. Our results also highlight the importance of structural connectivity as a modulator of network to TDCS, which should guide the design and interpretation of future stimulation studies.
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Affiliation(s)
- Lucia M Li
- Computational, Cognitive and Clinical Imaging Lab, Division of Brain Sciences, Department of Medicine, Imperial College London, W12 0NN, UK
| | | | - Rob Leech
- Centre for Neuroimaging Science, Denmark Hill, SE5 8AF, UK
| | - Adam Hampshire
- Computational, Cognitive and Clinical Imaging Lab, Division of Brain Sciences, Department of Medicine, Imperial College London, W12 0NN, UK
| | - Alexander Opitz
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, 55455, USA
| | - David McArthur
- David Geffen School of Medicine, UCLA, Los Angeles, CA, 90095, USA
| | | | - David J Sharp
- Computational, Cognitive and Clinical Imaging Lab, Division of Brain Sciences, Department of Medicine, Imperial College London, W12 0NN, UK.
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24
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Li LM, Violante IR, Leech R, Ross E, Hampshire A, Opitz A, Rothwell JC, Carmichael DW, Sharp DJ. Brain state and polarity dependent modulation of brain networks by transcranial direct current stimulation. Hum Brain Mapp 2018; 40:904-915. [PMID: 30378206 PMCID: PMC6387619 DOI: 10.1002/hbm.24420] [Citation(s) in RCA: 79] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2018] [Revised: 09/04/2018] [Accepted: 10/03/2018] [Indexed: 01/03/2023] Open
Abstract
Despite its widespread use in cognitive studies, there is still limited understanding of whether and how transcranial direct current stimulation (tDCS) modulates brain network function. To clarify its physiological effects, we assessed brain network function using functional magnetic resonance imaging (fMRI) simultaneously acquired during tDCS stimulation. Cognitive state was manipulated by having subjects perform a Choice Reaction Task or being at “rest.” A novel factorial design was used to assess the effects of brain state and polarity. Anodal and cathodal tDCS were applied to the right inferior frontal gyrus (rIFG), a region involved in controlling activity large‐scale intrinsic connectivity networks during switches of cognitive state. tDCS produced widespread modulation of brain activity in a polarity and brain state dependent manner. In the absence of task, the main effect of tDCS was to accentuate default mode network (DMN) activation and salience network (SN) deactivation. In contrast, during task performance, tDCS increased SN activation. In the absence of task, the main effect of anodal tDCS was more pronounced, whereas cathodal tDCS had a greater effect during task performance. Cathodal tDCS also accentuated the within‐DMN connectivity associated with task performance. There were minimal main effects of stimulation on network connectivity. These results demonstrate that rIFG tDCS can modulate the activity and functional connectivity of large‐scale brain networks involved in cognitive function, in a brain state and polarity dependent manner. This study provides an important insight into mechanisms by which tDCS may modulate cognitive function, and also has implications for the design of future stimulation studies.
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Affiliation(s)
- Lucia M Li
- Computational, Cognitive, and Clinical Imaging Lab, Division of Brain Sciences, Department of Medicine, Imperial College, London, UK
| | - Ines R Violante
- Computational, Cognitive, and Clinical Imaging Lab, Division of Brain Sciences, Department of Medicine, Imperial College, London, UK.,Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, University College London, London, UK.,School of Psychology, University of Surrey, Guildford, UK
| | - Rob Leech
- Centre for Neuroimaging Science, Kings College London, UK
| | - Ewan Ross
- Computational, Cognitive, and Clinical Imaging Lab, Division of Brain Sciences, Department of Medicine, Imperial College, London, UK
| | - Adam Hampshire
- Computational, Cognitive, and Clinical Imaging Lab, Division of Brain Sciences, Department of Medicine, Imperial College, London, UK
| | - Alexander Opitz
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, Minnesota
| | - John C Rothwell
- Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, University College London, London, UK
| | - David W Carmichael
- Centre for Neuroimaging Science, Kings College London, UK.,Department of Biomedical Engineering, Kings College London, UK
| | - David J Sharp
- Computational, Cognitive, and Clinical Imaging Lab, Division of Brain Sciences, Department of Medicine, Imperial College, London, UK
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25
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Lorenz R, Violante IR, Monti RP, Montana G, Hampshire A, Leech R. Dissociating frontoparietal brain networks with neuroadaptive Bayesian optimization. Nat Commun 2018; 9:1227. [PMID: 29581425 PMCID: PMC5964320 DOI: 10.1038/s41467-018-03657-3] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2017] [Accepted: 02/28/2018] [Indexed: 11/08/2022] Open
Abstract
Understanding the unique contributions of frontoparietal networks (FPN) in cognition is challenging because they overlap spatially and are co-activated by diverse tasks. Characterizing these networks therefore involves studying their activation across many different cognitive tasks, which previously was only possible with meta-analyses. Here, we use neuroadaptive Bayesian optimization, an approach combining real-time analysis of functional neuroimaging data with machine-learning, to discover cognitive tasks that segregate ventral and dorsal FPN activity. We identify and subsequently refine two cognitive tasks, Deductive Reasoning and Tower of London, which maximally dissociate the dorsal from ventral FPN. We subsequently investigate these two FPNs in the context of a wider range of FPNs and demonstrate the importance of studying the whole activity profile across tasks to uniquely differentiate any FPN. Our findings deviate from previous meta-analyses and hypothesized functional labels for these FPNs. Taken together the results form the starting point for a neurobiologically-derived cognitive taxonomy.
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Affiliation(s)
- Romy Lorenz
- Department of Medicine, Computational, Cognitive and Clinical Neuroscience Laboratory (C3NL), Imperial College London, London, W12 0NN, UK.
| | - Ines R Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, GU2 7XH, UK
| | - Ricardo Pio Monti
- Gatsby Computational Neuroscience Unit, University College London, London, W1T 4JG, UK
| | - Giovanni Montana
- Department of Mathematics, Imperial College London, London, SW7 2AZ, UK
- Department of Biomedical Engineering, King's College London, London, SE1 7EH, UK
| | - Adam Hampshire
- Department of Medicine, Computational, Cognitive and Clinical Neuroscience Laboratory (C3NL), Imperial College London, London, W12 0NN, UK
| | - Robert Leech
- Centre for Neuroimaging Science, King's College London, London, SE5 8AF, UK.
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26
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Violante IR, Li LM, Carmichael DW, Lorenz R, Leech R, Hampshire A, Rothwell JC, Sharp DJ. Externally induced frontoparietal synchronization modulates network dynamics and enhances working memory performance. eLife 2017; 6. [PMID: 28288700 PMCID: PMC5349849 DOI: 10.7554/elife.22001] [Citation(s) in RCA: 111] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Accepted: 02/06/2017] [Indexed: 12/23/2022] Open
Abstract
Cognitive functions such as working memory (WM) are emergent properties of large-scale network interactions. Synchronisation of oscillatory activity might contribute to WM by enabling the coordination of long-range processes. However, causal evidence for the way oscillatory activity shapes network dynamics and behavior in humans is limited. Here we applied transcranial alternating current stimulation (tACS) to exogenously modulate oscillatory activity in a right frontoparietal network that supports WM. Externally induced synchronization improved performance when cognitive demands were high. Simultaneously collected fMRI data reveals tACS effects dependent on the relative phase of the stimulation and the internal cognitive processing state. Specifically, synchronous tACS during the verbal WM task increased parietal activity, which correlated with behavioral performance. Furthermore, functional connectivity results indicate that the relative phase of frontoparietal stimulation influences information flow within the WM network. Overall, our findings demonstrate a link between behavioral performance in a demanding WM task and large-scale brain synchronization.
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Affiliation(s)
- Ines R Violante
- The Computational, Cognitive and Clinical Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, United Kingdom.,Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, University College London, London, United Kingdom
| | - Lucia M Li
- The Computational, Cognitive and Clinical Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, United Kingdom
| | - David W Carmichael
- Developmental Imaging and Biophysics Section, UCL Institute of Child Health, University College London, London, United Kingdom
| | - Romy Lorenz
- The Computational, Cognitive and Clinical Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, United Kingdom
| | - Robert Leech
- The Computational, Cognitive and Clinical Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, United Kingdom
| | - Adam Hampshire
- The Computational, Cognitive and Clinical Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, United Kingdom
| | - John C Rothwell
- Sobell Department of Motor Neuroscience and Movement Disorders, UCL Institute of Neurology, University College London, London, United Kingdom
| | - David J Sharp
- The Computational, Cognitive and Clinical Neuroimaging Laboratory, Department of Medicine, Imperial College London, London, United Kingdom
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27
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Datta G, Violante IR, Scott G, Zimmerman K, Santos-Ribeiro A, Rabiner EA, Gunn RN, Malik O, Ciccarelli O, Nicholas R, Matthews PM. Translocator positron-emission tomography and magnetic resonance spectroscopic imaging of brain glial cell activation in multiple sclerosis. Mult Scler 2016; 23:1469-1478. [PMID: 27903933 DOI: 10.1177/1352458516681504] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
BACKGROUND Multiple sclerosis (MS) is characterised by a diffuse inflammatory response mediated by microglia and astrocytes. Brain translocator protein (TSPO) positron-emission tomography (PET) and [myo-inositol] magnetic resonance spectroscopy (MRS) were used together to assess this. OBJECTIVE To explore the in vivo relationships between MRS and PET [11C]PBR28 in MS over a range of brain inflammatory burden. METHODS A total of 23 patients were studied. TSPO PET imaging with [11C]PBR28, single voxel MRS and conventional magnetic resonance imaging (MRI) sequences were undertaken. Disability was assessed by Expanded Disability Status Scale (EDSS) and Multiple Sclerosis Functional Composite (MSFC). RESULTS [11C]PBR28 uptake and [ myo-inositol] were not associated. When the whole cohort was stratified by higher [11C]PBR28 inflammatory burden, [ myo-inositol] was positively correlated to [11C]PBR28 uptake (Spearman's ρ = 0.685, p = 0.014). Moderate correlations were found between [11C]PBR28 uptake and both MRS creatine normalised N-acetyl aspartate (NAA) concentration and grey matter volume. MSFC was correlated with grey matter volume (ρ = 0.535, p = 0.009). There were no associations between other imaging or clinical measures. CONCLUSION MRS [ myo-inositol] and PET [11C]PBR28 measure independent inflammatory processes which may be more commonly found together with more severe inflammatory disease. Microglial activation measured by [11C]PBR28 uptake was associated with loss of neuronal integrity and grey matter atrophy.
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Affiliation(s)
- Gourab Datta
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
| | - Ines R Violante
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
| | - Gregory Scott
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
| | - Karl Zimmerman
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
| | - Andre Santos-Ribeiro
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
| | - Eugenii A Rabiner
- Imanova Ltd, Imperial College London, London, UK/Centre for Neuroimaging Sciences, King's College London, London, UK
| | - Roger N Gunn
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK/manova Ltd, Imperial College London, London, UK
| | - Omar Malik
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
| | - Olga Ciccarelli
- Queen Square Multiple Sclerosis Centre, Institute of Neurology, University College London, London, UK
| | - Richard Nicholas
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
| | - Paul M Matthews
- Division of Brain Sciences, Department of Medicine, Imperial College London, London, UK
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