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Hobbs NZ, Papoutsi M, Delva A, Kinnunen KM, Nakajima M, Van Laere K, Vandenberghe W, Herath P, Scahill RI. Neuroimaging to Facilitate Clinical Trials in Huntington's Disease: Current Opinion from the EHDN Imaging Working Group. J Huntingtons Dis 2024:JHD240016. [PMID: 38788082 DOI: 10.3233/jhd-240016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/26/2024]
Abstract
Neuroimaging is increasingly being included in clinical trials of Huntington's disease (HD) for a wide range of purposes from participant selection and safety monitoring, through to demonstration of disease modification. Selection of the appropriate modality and associated analysis tools requires careful consideration. On behalf of the EHDN Imaging Working Group, we present current opinion on the utility and future prospects for inclusion of neuroimaging in HD trials. Covering the key imaging modalities of structural-, functional- and diffusion- MRI, perfusion imaging, positron emission tomography, magnetic resonance spectroscopy, and magnetoencephalography, we address how neuroimaging can be used in HD trials to: 1) Aid patient selection, enrichment, stratification, and safety monitoring; 2) Demonstrate biodistribution, target engagement, and pharmacodynamics; 3) Provide evidence for disease modification; and 4) Understand brain re-organization following therapy. We also present the challenges of translating research methodology into clinical trial settings, including equipment requirements and cost, standardization of acquisition and analysis, patient burden and invasiveness, and interpretation of results. We conclude, that with appropriate consideration of modality, study design and analysis, imaging has huge potential to facilitate effective clinical trials in HD.
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Affiliation(s)
- Nicola Z Hobbs
- HD Research Centre, UCL Institute of Neurology, UCL, London, UK
| | - Marina Papoutsi
- HD Research Centre, UCL Institute of Neurology, UCL, London, UK
- IXICO plc, London, UK
| | - Aline Delva
- Department of Neurosciences, KU Leuven, Belgium
- Department of Neurology, University Hospitals Leuven, Belgium
| | | | | | - Koen Van Laere
- Department of Imaging and Pathology, Nuclear Medicine and Molecular Imaging, KU Leuven, Belgium
- Division of Nuclear Medicine, University Hospitals Leuven, Belgium
| | - Wim Vandenberghe
- Department of Neurosciences, KU Leuven, Belgium
- Department of Neurology, University Hospitals Leuven, Belgium
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2
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Whiteside DJ, Holland N, Tsvetanov KA, Mak E, Malpetti M, Savulich G, Jones PS, Naessens M, Rouse MA, Fryer TD, Hong YT, Aigbirhio FI, Mulroy E, Bhatia KP, Rittman T, O'Brien JT, Rowe JB. Synaptic density affects clinical severity via network dysfunction in syndromes associated with frontotemporal lobar degeneration. Nat Commun 2023; 14:8458. [PMID: 38114493 PMCID: PMC10730886 DOI: 10.1038/s41467-023-44307-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 12/07/2023] [Indexed: 12/21/2023] Open
Abstract
There is extensive synaptic loss from frontotemporal lobar degeneration, in preclinical models and human in vivo and post mortem studies. Understanding the consequences of synaptic loss for network function is important to support translational models and guide future therapeutic strategies. To examine this relationship, we recruited 55 participants with syndromes associated with frontotemporal lobar degeneration and 24 healthy controls. We measured synaptic density with positron emission tomography using the radioligand [11C]UCB-J, which binds to the presynaptic vesicle glycoprotein SV2A, neurite dispersion with diffusion magnetic resonance imaging, and network function with task-free magnetic resonance imaging functional connectivity. Synaptic density and neurite dispersion in patients was associated with reduced connectivity beyond atrophy. Functional connectivity moderated the relationship between synaptic density and clinical severity. Our findings confirm the importance of synaptic loss in frontotemporal lobar degeneration syndromes, and the resulting effect on behaviour as a function of abnormal connectivity.
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Affiliation(s)
- David J Whiteside
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.
| | - Negin Holland
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Kamen A Tsvetanov
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Elijah Mak
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Maura Malpetti
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - George Savulich
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - P Simon Jones
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Michelle Naessens
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Matthew A Rouse
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Tim D Fryer
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Young T Hong
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Franklin I Aigbirhio
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridge, UK
| | - Eoin Mulroy
- UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Kailash P Bhatia
- UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
| | - Timothy Rittman
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - John T O'Brien
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - James B Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
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3
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Mimura Y, Tobari Y, Nakahara K, Nakajima S, Yoshida K, Mimura M, Noda Y. Transcranial magnetic stimulation neurophysiology in patients with non-Alzheimer's neurodegenerative diseases: A systematic review and meta-analysis. Neurosci Biobehav Rev 2023; 155:105451. [PMID: 37926239 DOI: 10.1016/j.neubiorev.2023.105451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 10/26/2023] [Accepted: 10/27/2023] [Indexed: 11/07/2023]
Abstract
Non-Alzheimer's dementia (NAD) accounts for 30% of all neurodegenerative conditions and is characterized by cognitive decline beyond mere memory dysfunction. Diagnosing NAD remains challenging due to the lack of established biomarkers. Transcranial magnetic stimulation (TMS) is a non-invasive neurophysiological tool that enables the investigation of cortical excitability in the human brain. Paired-pulse TMS paradigms include short- and long-interval intracortical inhibition (SICI/LICI), intracortical facilitation (ICF), and short-latency afferent inhibition (SAI), which can assess neurophysiological functions of GABAergic, glutamatergic, and cholinergic neural circuits, respectively. We conducted the first systematic review and meta-analysis to compare these TMS indices among patients with NAD and healthy controls. Our meta-analyses indicated that TMS neurophysiological examinations revealed decreased glutamatergic function in patients with frontotemporal dementia (FTD) and decreased GABAergic function in patients with FTD, progressive supranuclear palsy, Huntington's disease, cortico-basal syndrome, and multiple system atrophy-parkinsonian type. In addition, decreased cholinergic function was found in dementia with Lewy body and vascular dementia. These results suggest the potential of TMS as an additional diagnostic tool to differentiate NAD.
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Affiliation(s)
- Yu Mimura
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Yui Tobari
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Kazuho Nakahara
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Shinichiro Nakajima
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan.
| | - Kazunari Yoshida
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan; Pharmacogenetics Research Clinic, Centre for Addiction and Mental Health, Toronto, ON, Canada; Azrieli Adult Neurodevelopmental Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Masaru Mimura
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan
| | - Yoshihiro Noda
- Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan.
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4
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Katsanevaki C, Bastos AM, Cagnan H, Bosman CA, Friston KJ, Fries P. Attentional effects on local V1 microcircuits explain selective V1-V4 communication. Neuroimage 2023; 281:120375. [PMID: 37714390 DOI: 10.1016/j.neuroimage.2023.120375] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 09/10/2023] [Accepted: 09/11/2023] [Indexed: 09/17/2023] Open
Abstract
Selective attention implements preferential routing of attended stimuli, likely through increasing the influence of the respective synaptic inputs on higher-area neurons. As the inputs of competing stimuli converge onto postsynaptic neurons, presynaptic circuits might offer the best target for attentional top-down influences. If those influences enabled presynaptic circuits to selectively entrain postsynaptic neurons, this might explain selective routing. Indeed, when two visual stimuli induce two gamma rhythms in V1, only the gamma induced by the attended stimulus entrains gamma in V4. Here, we modelled induced responses with a Dynamic Causal Model for Cross-Spectral Densities and found that selective entrainment can be explained by attentional modulation of intrinsic V1 connections. Specifically, local inhibition was decreased in the granular input layer and increased in the supragranular output layer of the V1 circuit that processed the attended stimulus. Thus, presynaptic attentional influences and ensuing entrainment were sufficient to mediate selective routing.
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Affiliation(s)
- Christini Katsanevaki
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt 60528, Germany; International Max Planck Research School for Neural Circuits, Frankfurt 60438, Germany.
| | - André M Bastos
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt 60528, Germany; Department of Psychology and Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN 37240, USA
| | - Hayriye Cagnan
- The Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3AR, UK; Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX1 3TH, UK
| | - Conrado A Bosman
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen 6525 EN, the Netherlands; Swammerdam Institute for Life Sciences, Center for Neuroscience, University of Amsterdam, Amsterdam 1098 XH, the Netherlands
| | - Karl J Friston
- The Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3AR, UK
| | - Pascal Fries
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt 60528, Germany; International Max Planck Research School for Neural Circuits, Frankfurt 60438, Germany; Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen 6525 EN, the Netherlands
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5
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Jafarian A, Hughes LE, Adams NE, Lanskey JH, Naessens M, Rouse MA, Murley AG, Friston KJ, Rowe JB. Neurochemistry-enriched dynamic causal models of magnetoencephalography, using magnetic resonance spectroscopy. Neuroimage 2023; 276:120193. [PMID: 37244323 DOI: 10.1016/j.neuroimage.2023.120193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 05/11/2023] [Accepted: 05/24/2023] [Indexed: 05/29/2023] Open
Abstract
We present a hierarchical empirical Bayesian framework for testing hypotheses about neurotransmitters' concertation as empirical prior for synaptic physiology using ultra-high field magnetic resonance spectroscopy (7T-MRS) and magnetoencephalography data (MEG). A first level dynamic causal modelling of cortical microcircuits is used to infer the connectivity parameters of a generative model of individuals' neurophysiological observations. At the second level, individuals' 7T-MRS estimates of regional neurotransmitter concentration supply empirical priors on synaptic connectivity. We compare the group-wise evidence for alternative empirical priors, defined by monotonic functions of spectroscopic estimates, on subsets of synaptic connections. For efficiency and reproducibility, we used Bayesian model reduction (BMR), parametric empirical Bayes and variational Bayesian inversion. In particular, we used Bayesian model reduction to compare alternative model evidence of how spectroscopic neurotransmitter measures inform estimates of synaptic connectivity. This identifies the subset of synaptic connections that are influenced by individual differences in neurotransmitter levels, as measured by 7T-MRS. We demonstrate the method using resting-state MEG (i.e., task-free recording) and 7T-MRS data from healthy adults. Our results confirm the hypotheses that GABA concentration influences local recurrent inhibitory intrinsic connectivity in deep and superficial cortical layers, while glutamate influences the excitatory connections between superficial and deep layers and connections from superficial to inhibitory interneurons. Using within-subject split-sampling of the MEG dataset (i.e., validation by means of a held-out dataset), we show that model comparison for hypothesis testing can be highly reliable. The method is suitable for applications with magnetoencephalography or electroencephalography, and is well-suited to reveal the mechanisms of neurological and psychiatric disorders, including responses to psychopharmacological interventions.
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Affiliation(s)
- Amirhossein Jafarian
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, United Kingdom; MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
| | - Laura E Hughes
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, United Kingdom; MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
| | - Natalie E Adams
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, United Kingdom.
| | - Juliette H Lanskey
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
| | - Michelle Naessens
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, United Kingdom; MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
| | - Matthew A Rouse
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, United Kingdom; MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
| | - Alexander G Murley
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, United Kingdom.
| | - Karl J Friston
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, United Kingdom.
| | - James B Rowe
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, United Kingdom; MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
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6
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Paparella I, Vanderwalle G, Stagg CJ, Maquet P. An integrated measure of GABA to characterize post-stroke plasticity. Neuroimage Clin 2023; 39:103463. [PMID: 37406594 PMCID: PMC10339061 DOI: 10.1016/j.nicl.2023.103463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 06/19/2023] [Accepted: 06/24/2023] [Indexed: 07/07/2023]
Abstract
Stroke is a major cause of death and chronic neurological disability. Despite the improvements in stroke care, the number of patients affected by stroke keeps increasing and many stroke survivors are left permanently disabled. Current therapies are limited in efficacy. Understanding the neurobiological mechanisms underlying post-stroke recovery is therefore crucial to find new therapeutic options to address this medical burden. Long-lasting and widespread alterations of γ-aminobutyric acid (GABA) neurotransmission seem to play a key role in stroke recovery. In this review we first discuss a possible model of GABAergic modulation of post-stroke plasticity. We then overview the techniques currently available to non-invasively assess GABA in patients and the conclusions drawn from this limited body of work. Finally, we address the remaining open questions to clarify GABAergic changes underlying post-stroke recovery, we briefly review possible ways to modulate GABA post stroke and propose a novel approach to thoroughly quantify GABA in stroke patients, by integrating its concentration, the activity of its receptors and its link with microstructural changes.
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Affiliation(s)
- Ilenia Paparella
- GIGA-Research, Cyclotron Research Center-In Vivo Imaging Unit, 8 allée du Six Août, Batiment B30, University of Liège, 4000 Liège, Belgium.
| | - Gilles Vanderwalle
- GIGA-Research, Cyclotron Research Center-In Vivo Imaging Unit, 8 allée du Six Août, Batiment B30, University of Liège, 4000 Liège, Belgium
| | - Charlotte J Stagg
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Medical Research Council Brain Network Dynamics Unit, Oxford, UK
| | - Pierre Maquet
- GIGA-Research, Cyclotron Research Center-In Vivo Imaging Unit, 8 allée du Six Août, Batiment B30, University of Liège, 4000 Liège, Belgium; Department of Neurology, Domaine Universitaire du Sart Tilman, Bâtiment B35, CHU de Liège, 4000 Liège, Belgium
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7
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Williams RS, Adams NE, Hughes LE, Rouse MA, Murley AG, Naessens M, Street D, Holland N, Rowe JB. Syndromes associated with frontotemporal lobar degeneration change response patterns on visual analogue scales. Sci Rep 2023; 13:8939. [PMID: 37268659 DOI: 10.1038/s41598-023-35758-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Accepted: 05/23/2023] [Indexed: 06/04/2023] Open
Abstract
Self-report scales are widely used in cognitive neuroscience and psychology. However, they rest on the central assumption that respondents engage meaningfully. We hypothesise that this assumption does not hold for many patients, especially those with syndromes associated with frontotemporal lobar degeneration. In this study we investigated differences in response patterns on a visual analogue scale between people with frontotemporal degeneration and controls. We found that people with syndromes associated with frontotemporal lobar degeneration respond with more invariance and less internal consistency than controls, with Bayes Factors = 15.2 and 14.5 respectively indicating strong evidence for a group difference. There was also evidence that patient responses feature lower entropy. These results have important implications for the interpretation of self-report data in clinical populations. Meta-response markers related to response patterns, rather than the values reported on individual items, may be an informative addition to future research and clinical practise.
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Affiliation(s)
- Rebecca S Williams
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.
| | - Natalie E Adams
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, UK
| | - Laura E Hughes
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, UK
| | - Matthew A Rouse
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, UK
| | - Alexander G Murley
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, UK
| | - Michelle Naessens
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, UK
| | - Duncan Street
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, UK
| | - Negin Holland
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, UK
| | - James B Rowe
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, UK
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8
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Chokesuwattanaskul A, Jiang H, Bond RL, Jimenez DA, Russell LL, Sivasathiaseelan H, Johnson JCS, Benhamou E, Agustus JL, van Leeuwen JEP, Chokesuwattanaskul P, Hardy CJD, Marshall CR, Rohrer JD, Warren JD. The architecture of abnormal reward behaviour in dementia: multimodal hedonic phenotypes and brain substrate. Brain Commun 2023; 5:fcad027. [PMID: 36942157 PMCID: PMC10023829 DOI: 10.1093/braincomms/fcad027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 10/11/2022] [Accepted: 02/07/2023] [Indexed: 02/11/2023] Open
Abstract
Abnormal reward processing is a hallmark of neurodegenerative diseases, most strikingly in frontotemporal dementia. However, the phenotypic repertoire and neuroanatomical substrates of abnormal reward behaviour in these diseases remain incompletely characterized and poorly understood. Here we addressed these issues in a large, intensively phenotyped patient cohort representing all major syndromes of sporadic frontotemporal dementia and Alzheimer's disease. We studied 27 patients with behavioural variant frontotemporal dementia, 58 with primary progressive aphasia (22 semantic variant, 24 non-fluent/agrammatic variant and 12 logopenic) and 34 with typical amnestic Alzheimer's disease, in relation to 42 healthy older individuals. Changes in behavioural responsiveness were assessed for canonical primary rewards (appetite, sweet tooth, sexual activity) and non-primary rewards (music, religion, art, colours), using a semi-structured survey completed by patients' primary caregivers. Changes in more general socio-emotional behaviours were also recorded. We applied multiple correspondence analysis and k-means clustering to map relationships between hedonic domains and extract core factors defining aberrant hedonic phenotypes. Neuroanatomical associations were assessed using voxel-based morphometry of brain MRI images across the combined patient cohort. Altered (increased and/or decreased) reward responsiveness was exhibited by most patients in the behavioural and semantic variants of frontotemporal dementia and around two-thirds of patients in other dementia groups, significantly (P < 0.05) more frequently than in healthy controls. While food-directed changes were most prevalent across the patient cohort, behavioural changes directed toward non-primary rewards occurred significantly more frequently (P < 0.05) in the behavioural and semantic variants of frontotemporal dementia than in other patient groups. Hedonic behavioural changes across the patient cohort were underpinned by two principal factors: a 'gating' factor determining the emergence of altered reward behaviour and a 'modulatory' factor determining how that behaviour is directed. These factors were expressed jointly in a set of four core, trans-diagnostic and multimodal hedonic phenotypes: 'reward-seeking', 'reward-restricted', 'eating-predominant' and 'control-like'-variably represented across the cohort and associated with more pervasive socio-emotional behavioural abnormalities. The principal gating factor was associated (P < 0.05 after correction for multiple voxel-wise comparisons over the whole brain) with a common profile of grey matter atrophy in anterior cingulate, bilateral temporal poles, right middle frontal and fusiform gyri: the cortical circuitry that mediates behavioural salience and semantic and affective appraisal of sensory stimuli. Our findings define a multi-domain phenotypic architecture for aberrant reward behaviours in major dementias, with novel implications for the neurobiological understanding and clinical management of these diseases.
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Affiliation(s)
- Anthipa Chokesuwattanaskul
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
- Division of Neurology, Department of Internal Medicine, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
- Cognitive Clinical and Computational Neuroscience Research Unit, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Harmony Jiang
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Rebecca L Bond
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Daniel A Jimenez
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
- Department of Neurological Sciences, Faculty of Medicine, University of Chile, Santiago, Chile
| | - Lucy L Russell
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Harri Sivasathiaseelan
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Jeremy C S Johnson
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Elia Benhamou
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Jennifer L Agustus
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Janneke E P van Leeuwen
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | | | - Chris J D Hardy
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Charles R Marshall
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
- Preventive Neurology Unit, Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | - Jonathan D Rohrer
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Jason D Warren
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
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9
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Giustiniani A, Danesin L, Bozzetto B, Macina A, Benavides-Varela S, Burgio F. Functional changes in brain oscillations in dementia: a review. Rev Neurosci 2023; 34:25-47. [PMID: 35724724 DOI: 10.1515/revneuro-2022-0010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 05/16/2022] [Indexed: 01/11/2023]
Abstract
A growing body of evidence indicates that several characteristics of electroencephalography (EEG) and magnetoencephalography (MEG) play a functional role in cognition and could be linked to the progression of cognitive decline in some neurological diseases such as dementia. The present paper reviews previous studies investigating changes in brain oscillations associated to the most common types of dementia, namely Alzheimer's disease (AD), frontotemporal degeneration (FTD), and vascular dementia (VaD), with the aim of identifying pathology-specific patterns of alterations and supporting differential diagnosis in clinical practice. The included studies analysed changes in frequency power, functional connectivity, and event-related potentials, as well as the relationship between electrophysiological changes and cognitive deficits. Current evidence suggests that an increase in slow wave activity (i.e., theta and delta) as well as a general reduction in the power of faster frequency bands (i.e., alpha and beta) characterizes AD, VaD, and FTD. Additionally, compared to healthy controls, AD exhibits alteration in latencies and amplitudes of the most common event related potentials. In the reviewed studies, these changes generally correlate with performances in many cognitive tests. In conclusion, particularly in AD, neurophysiological changes can be reliable early markers of dementia.
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Affiliation(s)
| | - Laura Danesin
- IRCCS San Camillo Hospital, via Alberoni 70, 30126 Venice, Italy
| | | | - AnnaRita Macina
- Department of Developmental Psychology and Socialization, University of Padua, via Venezia 8, 35131 Padova, Italy
| | - Silvia Benavides-Varela
- Department of Developmental Psychology and Socialization, University of Padua, via Venezia 8, 35131 Padova, Italy.,Department of Neuroscience, University of Padova, 35128 Padova, Italy.,Padova Neuroscience Center, University of Padova, 35131 Padova, Italy
| | - Francesca Burgio
- IRCCS San Camillo Hospital, via Alberoni 70, 30126 Venice, Italy
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10
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Davenport F, Gallacher J, Kourtzi Z, Koychev I, Matthews PM, Oxtoby NP, Parkes LM, Priesemann V, Rowe JB, Smye SW, Zetterberg H. Neurodegenerative disease of the brain: a survey of interdisciplinary approaches. J R Soc Interface 2023; 20:20220406. [PMID: 36651180 PMCID: PMC9846433 DOI: 10.1098/rsif.2022.0406] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Accepted: 12/16/2022] [Indexed: 01/19/2023] Open
Abstract
Neurodegenerative diseases of the brain pose a major and increasing global health challenge, with only limited progress made in developing effective therapies over the last decade. Interdisciplinary research is improving understanding of these diseases and this article reviews such approaches, with particular emphasis on tools and techniques drawn from physics, chemistry, artificial intelligence and psychology.
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Affiliation(s)
| | - John Gallacher
- Director of Dementias Platform, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Zoe Kourtzi
- Professor of Cognitive Computational Neuroscience, Department of Psychology, University of Cambridge, UK
| | - Ivan Koychev
- Senior Clinical Researcher, Department of Psychiatry, University of Oxford, Oxford, UK
- Consultant Neuropsychiatrist, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Paul M. Matthews
- Department of Brain Sciences and UK Dementia Research Institute Centre, Imperial College London, Oxford, UK
| | - Neil P. Oxtoby
- UCL Centre for Medical Image Computing and Department of Computer Science, University College London, Gower Street, London, UK
| | - Laura M. Parkes
- School of Health Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre, Manchester, UK
| | - Viola Priesemann
- Max Planck Group Leader and Fellow of the Schiemann Kolleg, Max Planck Institute for Dynamics and Self-Organization and Bernstein Center for Computational Neuroscience, Göttingen, Germany
| | - James B. Rowe
- Department of Clinical Neurosciences, MRC Cognition and Brain Sciences Unit and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, UK
| | | | - Henrik Zetterberg
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, People's Republic of China
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11
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Friston K. Computational psychiatry: from synapses to sentience. Mol Psychiatry 2023; 28:256-268. [PMID: 36056173 PMCID: PMC7614021 DOI: 10.1038/s41380-022-01743-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Revised: 08/08/2022] [Accepted: 08/11/2022] [Indexed: 01/09/2023]
Abstract
This review considers computational psychiatry from a particular viewpoint: namely, a commitment to explaining psychopathology in terms of pathophysiology. It rests on the notion of a generative model as underwriting (i) sentient processing in the brain, and (ii) the scientific process in psychiatry. The story starts with a view of the brain-from cognitive and computational neuroscience-as an organ of inference and prediction. This offers a formal description of neuronal message passing, distributed processing and belief propagation in neuronal networks; and how certain kinds of dysconnection lead to aberrant belief updating and false inference. The dysconnections in question can be read as a pernicious synaptopathy that fits comfortably with formal notions of how we-or our brains-encode uncertainty or its complement, precision. It then considers how the ensuing process theories are tested empirically, with an emphasis on the computational modelling of neuronal circuits and synaptic gain control that mediates attentional set, active inference, learning and planning. The opportunities afforded by this sort of modelling are considered in light of in silico experiments; namely, computational neuropsychology, computational phenotyping and the promises of a computational nosology for psychiatry. The resulting survey of computational approaches is not scholarly or exhaustive. Rather, its aim is to review a theoretical narrative that is emerging across subdisciplines within psychiatry and empirical scales of investigation. These range from epilepsy research to neurodegenerative disorders; from post-traumatic stress disorder to the management of chronic pain, from schizophrenia to functional medical symptoms.
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Affiliation(s)
- Karl Friston
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London, WC1N 3AR, UK.
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12
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Lanskey JH, Kocagoncu E, Quinn AJ, Cheng YJ, Karadag M, Pitt J, Lowe S, Perkinton M, Raymont V, Singh KD, Woolrich M, Nobre AC, Henson RN, Rowe JB. New Therapeutics in Alzheimer's Disease Longitudinal Cohort study (NTAD): study protocol. BMJ Open 2022; 12:e055135. [PMID: 36521898 PMCID: PMC9756184 DOI: 10.1136/bmjopen-2021-055135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 11/01/2022] [Indexed: 12/23/2022] Open
Abstract
INTRODUCTION With the pressing need to develop treatments that slow or stop the progression of Alzheimer's disease, new tools are needed to reduce clinical trial duration and validate new targets for human therapeutics. Such tools could be derived from neurophysiological measurements of disease. METHODS AND ANALYSIS The New Therapeutics in Alzheimer's Disease study (NTAD) aims to identify a biomarker set from magneto/electroencephalography that is sensitive to disease and progression over 1 year. The study will recruit 100 people with amyloid-positive mild cognitive impairment or early-stage Alzheimer's disease and 30 healthy controls aged between 50 and 85 years. Measurements of the clinical, cognitive and imaging data (magnetoencephalography, electroencephalography and MRI) of all participants will be taken at baseline. These measurements will be repeated after approximately 1 year on participants with Alzheimer's disease or mild cognitive impairment, and clinical and cognitive assessment of these participants will be repeated again after approximately 2 years. To assess reliability of magneto/electroencephalographic changes, a subset of 30 participants with mild cognitive impairment or early-stage Alzheimer's disease will also undergo repeat magneto/electroencephalography 2 weeks after baseline. Baseline and longitudinal changes in neurophysiology are the primary analyses of interest. Additional outputs will include atrophy and cognitive change and estimated numbers needed to treat each arm of simulated clinical trials of a future disease-modifying therapy. ETHICS AND DATA STATEMENT The study has received a favourable opinion from the East of England Cambridge Central Research Ethics Committee (REC reference 18/EE/0042). Results will be disseminated through internal reports, peer-reviewed scientific journals, conference presentations, website publication, submission to regulatory authorities and other publications. Data will be made available via the Dementias Platform UK Data Portal on completion of initial analyses by the NTAD study group.
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Affiliation(s)
| | - Ece Kocagoncu
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
| | - Andrew J Quinn
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Yun-Ju Cheng
- Lilly Corporate Center, Indianapolis, Indiana, USA
| | - Melek Karadag
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
| | - Jemma Pitt
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Stephen Lowe
- Lilly Centre for Clinical Pharmacology, Singapore
| | | | | | - Krish D Singh
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, UK
| | - Mark Woolrich
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Anna C Nobre
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK
| | - Richard N Henson
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - James B Rowe
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
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13
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Adams NE, Jafarian A, Perry A, Rouse MA, Shaw AD, Murley AG, Cope TE, Bevan-Jones WR, Passamonti L, Street D, Holland N, Nesbitt D, Hughes LE, Friston KJ, Rowe JB. Neurophysiological consequences of synapse loss in progressive supranuclear palsy. Brain 2022:6895791. [PMID: 36514918 DOI: 10.1093/brain/awac471] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 10/31/2022] [Accepted: 11/08/2022] [Indexed: 12/15/2022] Open
Abstract
Synaptic loss occurs early in many neurodegenerative diseases and contributes to cognitive impairment even in the absence of gross atrophy. Currently, for human disease there are few formal models to explain how cortical networks underlying cognition are affected by synaptic loss. We advocate that biophysical models of neurophysiology offer both a bridge from clinical to preclinical models of pathology, and quantitative assays for experimental medicine. Such biophysical models can also disclose hidden neuronal dynamics generating neurophysiological observations like electro- and magneto-encephalography. Here, we augment a biophysically informed mesoscale model of human cortical function by inclusion of synaptic density estimates as captured by [11C]UCB-J positron emission tomography, and provide insights into how regional synapse loss affects neurophysiology. We use the primary tauopathy of progressive supranuclear palsy (Richardson's syndrome) as an exemplar condition, with high clinicopathological correlations. Progressive supranuclear palsy causes a marked change in cortical neurophysiology in the presence of mild cortical atrophy and is associated with a decline in cognitive functions associated with the frontal lobe. Using parametric empirical Bayesian inversion of a conductance-based canonical microcircuit model of magnetoencephalography data, we show that the inclusion of regional synaptic density-as a subject-specific prior on laminar specific neuronal populations-markedly increases model evidence. Specifically, model comparison suggests that a reduction in synaptic density in inferior frontal cortex affects superficial and granular layer glutamatergic excitation. This predicted individual differences in behaviour, demonstrating the link between synaptic loss, neurophysiology, and cognitive deficits. The method we demonstrate is not restricted to progressive supranuclear palsy or the effects of synaptic loss: such pathology-enriched dynamic causal models can be used to assess the mechanisms of other neurological disorders, with diverse non-invasive measures of pathology, and is suitable to test the effects of experimental pharmacology.
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Affiliation(s)
- Natalie E Adams
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, UK.,MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Amirhossein Jafarian
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, UK
| | - Alistair Perry
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, UK.,MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Matthew A Rouse
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, UK.,MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Alexander D Shaw
- Washington Singer Laboratories, University of Exeter, Exeter, EX4 4QG, UK
| | - Alexander G Murley
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, UK
| | - Thomas E Cope
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, UK.,MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - W Richard Bevan-Jones
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, UK
| | - Luca Passamonti
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, UK.,MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Duncan Street
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, UK
| | - Negin Holland
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, UK
| | - David Nesbitt
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, UK
| | - Laura E Hughes
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, UK.,MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Karl J Friston
- Wellcome Centre for Human Neuroimaging, University College London, WC1N 3AR, UK
| | - James B Rowe
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, UK.,MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
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14
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Perry A, Hughes LE, Adams N, Naessens M, Murley AG, Rouse MA, Street D, Jones PS, Cope TE, Kocagoncu E, Rowe JB. The neurophysiological effect of NMDA-R antagonism of frontotemporal lobar degeneration is conditional on individual GABA concentration. Transl Psychiatry 2022; 12:348. [PMID: 36030249 PMCID: PMC9420128 DOI: 10.1038/s41398-022-02114-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 08/09/2022] [Accepted: 08/11/2022] [Indexed: 02/02/2023] Open
Abstract
There is a pressing need to accelerate therapeutic strategies against the syndromes caused by frontotemporal lobar degeneration, including symptomatic treatments. One approach is for experimental medicine, coupling neurophysiological studies of the mechanisms of disease with pharmacological interventions aimed at restoring neurochemical deficits. Here we consider the role of glutamatergic deficits and their potential as targets for treatment. We performed a double-blind placebo-controlled crossover pharmaco-magnetoencephalography study in 20 people with symptomatic frontotemporal lobar degeneration (10 behavioural variant frontotemporal dementia, 10 progressive supranuclear palsy) and 19 healthy age- and gender-matched controls. Both magnetoencephalography sessions recorded a roving auditory oddball paradigm: on placebo or following 10 mg memantine, an uncompetitive NMDA-receptor antagonist. Ultra-high-field magnetic resonance spectroscopy confirmed lower concentrations of GABA in the right inferior frontal gyrus of people with frontotemporal lobar degeneration. While memantine showed a subtle effect on early-auditory processing in patients, there was no significant main effect of memantine on the magnitude of the mismatch negativity (MMN) response in the right frontotemporal cortex in patients or controls. However, the change in the right auditory cortex MMN response to memantine (vs. placebo) in patients correlated with individuals' prefrontal GABA concentration. There was no moderating effect of glutamate concentration or cortical atrophy. This proof-of-concept study demonstrates the potential for baseline dependency in the pharmacological restoration of neurotransmitter deficits to influence cognitive neurophysiology in neurodegenerative disease. With changes to multiple neurotransmitters in frontotemporal lobar degeneration, we suggest that individuals' balance of excitation and inhibition may determine drug efficacy, with implications for drug selection and patient stratification in future clinical trials.
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Affiliation(s)
- Alistair Perry
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF, UK. .,Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ, UK.
| | - Laura E. Hughes
- grid.5335.00000000121885934MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF UK ,grid.5335.00000000121885934Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ UK
| | - Natalie Adams
- grid.5335.00000000121885934Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ UK
| | - Michelle Naessens
- grid.5335.00000000121885934Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ UK
| | - Alexander G. Murley
- grid.5335.00000000121885934Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ UK
| | - Matthew A. Rouse
- grid.5335.00000000121885934MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF UK
| | - Duncan Street
- grid.5335.00000000121885934Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ UK
| | - P. Simon Jones
- grid.5335.00000000121885934Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ UK
| | - Thomas E. Cope
- grid.5335.00000000121885934MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF UK ,grid.5335.00000000121885934Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ UK
| | - Ece Kocagoncu
- grid.5335.00000000121885934MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF UK ,grid.5335.00000000121885934Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ UK
| | - James B. Rowe
- grid.5335.00000000121885934MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF UK ,grid.5335.00000000121885934Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust, University of Cambridge, Cambridge, CB2 0QQ UK
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15
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Monteverdi A, Palesi F, Costa A, Vitali P, Pichiecchio A, Cotta Ramusino M, Bernini S, Jirsa V, Gandini Wheeler-Kingshott CAM, D’Angelo E. Subject-specific features of excitation/inhibition profiles in neurodegenerative diseases. Front Aging Neurosci 2022; 14:868342. [PMID: 35992607 PMCID: PMC9391060 DOI: 10.3389/fnagi.2022.868342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 07/05/2022] [Indexed: 11/26/2022] Open
Abstract
Brain pathologies are characterized by microscopic changes in neurons and synapses that reverberate into large scale networks altering brain dynamics and functional states. An important yet unresolved issue concerns the impact of patients' excitation/inhibition profiles on neurodegenerative diseases including Alzheimer's Disease, Frontotemporal Dementia, and Amyotrophic Lateral Sclerosis. In this work, we used The Virtual Brain (TVB) simulation platform to simulate brain dynamics in healthy and neurodegenerative conditions and to extract information about the excitatory/inhibitory balance in single subjects. The brain structural and functional connectomes were extracted from 3T-MRI (Magnetic Resonance Imaging) scans and TVB nodes were represented by a Wong-Wang neural mass model endowing an explicit representation of the excitatory/inhibitory balance. Simulations were performed including both cerebral and cerebellar nodes and their structural connections to explore cerebellar impact on brain dynamics generation. The potential for clinical translation of TVB derived biophysical parameters was assessed by exploring their association with patients' cognitive performance and testing their discriminative power between clinical conditions. Our results showed that TVB biophysical parameters differed between clinical phenotypes, predicting higher global coupling and inhibition in Alzheimer's Disease and stronger N-methyl-D-aspartate (NMDA) receptor-dependent excitation in Amyotrophic Lateral Sclerosis. These physio-pathological parameters allowed us to perform an advanced analysis of patients' conditions. In backward regressions, TVB-derived parameters significantly contributed to explain the variation of neuropsychological scores and, in discriminant analysis, the combination of TVB parameters and neuropsychological scores significantly improved the discriminative power between clinical conditions. Moreover, cluster analysis provided a unique description of the excitatory/inhibitory balance in individual patients. Importantly, the integration of cerebro-cerebellar loops in simulations improved TVB predictive power, i.e., the correlation between experimental and simulated functional connectivity in all pathological conditions supporting the cerebellar role in brain function disrupted by neurodegeneration. Overall, TVB simulations reveal differences in the excitatory/inhibitory balance of individual patients that, combined with cognitive assessment, can promote the personalized diagnosis and therapy of neurodegenerative diseases.
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Affiliation(s)
- Anita Monteverdi
- Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Fulvia Palesi
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Alfredo Costa
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Unit of Behavioral Neurology, IRCCS Mondino Foundation, Pavia, Italy
| | - Paolo Vitali
- Department of Radiology, IRCCS Policlinico San Donato, Milan, Italy
- Department of Biomedical Sciences for Health, University of Milan, Milan, Italy
| | - Anna Pichiecchio
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Advanced Imaging and Radiomic Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Matteo Cotta Ramusino
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- Unit of Behavioral Neurology, IRCCS Mondino Foundation, Pavia, Italy
| | - Sara Bernini
- Dementia Research Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Viktor Jirsa
- Institut de Neurosciences des Systèmes, INSERM, INS, Aix-Marseille University, Marseille, France
| | - Claudia A. M. Gandini Wheeler-Kingshott
- Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
- NMR Research Unit, Department of Neuroinflammation, Queen Square MS Centre, University College London (UCL) Queen Square Institute of Neurology, London, United Kingdom
| | - Egidio D’Angelo
- Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
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16
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Govaarts R, Beeldman E, Fraschini M, Griffa A, Engels MMA, van Es MA, Veldink JH, van den Berg LH, van der Kooi AJ, Pijnenburg YAL, de Visser M, Stam CJ, Raaphorst J, Hillebrand A. Cortical and subcortical changes in resting-state neuronal activity and connectivity in early symptomatic ALS and advanced frontotemporal dementia. Neuroimage Clin 2022; 34:102965. [PMID: 35217500 PMCID: PMC8867127 DOI: 10.1016/j.nicl.2022.102965] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 02/08/2022] [Accepted: 02/09/2022] [Indexed: 01/17/2023]
Abstract
The objective of this study was to examine if patterns of resting-state brain activity and functional connectivity in cortical and subcortical regions in patients with early symptomatic amyotrophic lateral sclerosis (ALS) resemble those of behavioural variant frontotemporal dementia (bvFTD). In a cross-sectional design, eyes-closed resting-state magnetoencephalography (MEG) data of 34 ALS patients, 18 bvFTD patients and 18 age- and gender-matched healthy controls (HCs) were projected to source-space using an atlas-based beamformer. Group differences in peak frequency, band-specific oscillatory activity and functional connectivity (corrected amplitude envelope correlation) in 78 cortical regions and 12 subcortical regions were determined. False discovery rate was used to correct for multiple comparisons. BvFTD patients, as compared to ALS and HCs, showed lower relative beta power in parietal, occipital, temporal and nearly all subcortical regions. Compared to HCs, patients with ALS and patients with bvFTD had a higher delta (0.5-4 Hz) and gamma (30-48 Hz) band resting-state functional connectivity in a high number of overlapping regions in the frontal lobe and in limbic and subcortical regions. Higher delta band connectivity was widespread in the bvFTD patients compared to HCs. ALS showed a more widespread higher gamma band functional connectivity compared to bvFTD. In conclusion, MEG in early symptomatic ALS patients shows resting-state functional connectivity changes in frontal, limbic and subcortical regions that overlap considerably with bvFTD. The findings show the potential of MEG to detect brain changes in early symptomatic phases of ALS and contribute to our understanding of the disease spectrum, with ALS and bvFTD at the two extreme ends.
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Affiliation(s)
- Rosanne Govaarts
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands.
| | - Emma Beeldman
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Matteo Fraschini
- University of Cagliari, Department of Electrical and Electronic Engineering, Cagliari, Italy
| | - Alessandra Griffa
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland; Institute of Bioengineering, Center of Neuroprosthetics, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland
| | - Marjolein M A Engels
- Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology, Magnetoencephalography Centre, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Michael A van Es
- University Medical Centre Utrecht, Department of Neurology, Brain Centre Rudolf Magnus, Utrecht, the Netherlands
| | - Jan H Veldink
- University Medical Centre Utrecht, Department of Neurology, Brain Centre Rudolf Magnus, Utrecht, the Netherlands
| | - Leonard H van den Berg
- University Medical Centre Utrecht, Department of Neurology, Brain Centre Rudolf Magnus, Utrecht, the Netherlands
| | - Anneke J van der Kooi
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Yolande A L Pijnenburg
- Amsterdam University Medical Centers, Vrije Universiteit, Alzheimer Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Marianne de Visser
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Cornelis J Stam
- Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology, Magnetoencephalography Centre, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Joost Raaphorst
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Arjan Hillebrand
- Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology, Magnetoencephalography Centre, Amsterdam Neuroscience, Amsterdam, the Netherlands
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17
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Molecular Imaging of the GABAergic System in Parkinson's Disease and Atypical Parkinsonisms. Curr Neurol Neurosci Rep 2022; 22:867-879. [PMID: 36400877 PMCID: PMC9750911 DOI: 10.1007/s11910-022-01245-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/21/2022] [Indexed: 11/20/2022]
Abstract
PURPOSE OF REVIEW During recent years, there has been a growing interest in GABAergic alterations in parkinsonian disorders. This paper aims to review the latest literature published, focusing on in vivo neuroimaging, and to suggest potential future avenues of research in the field. RECENT FINDINGS A growing number of neuroimaging studies have focused on the association with different symptoms of Parkinson's disease, thereby suggesting a GABAergic role in motor symptoms, gait disturbances, frontal cognition, somatic symptom disorder, and hallucinations. However, there are a number of conflicting results, and further investigations in larger, clinically well-defined cohorts are needed to elucidate possible correlations. In progressive supranuclear palsy, recent evidence suggests a decrease of GABA in the frontal lobe. In this narrative review, we discuss the possible GABAergic role in the symptoms of PD and atypical parkinsonisms and outline possible research strategies for future neuroimaging of GABAergic changes in parkinsonian disorders.
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18
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Kocagoncu E, Klimovich-Gray A, Hughes LE, Rowe JB. Evidence and implications of abnormal predictive coding in dementia. Brain 2021; 144:3311-3321. [PMID: 34240109 PMCID: PMC8677549 DOI: 10.1093/brain/awab254] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2020] [Revised: 03/15/2021] [Accepted: 06/17/2021] [Indexed: 11/14/2022] Open
Abstract
The diversity of cognitive deficits and neuropathological processes associated with dementias has encouraged divergence in pathophysiological explanations of disease. Here, we review an alternative framework that emphasizes convergent critical features of cognitive pathophysiology. Rather than the loss of ‘memory centres’ or ‘language centres’, or singular neurotransmitter systems, cognitive deficits are interpreted in terms of aberrant predictive coding in hierarchical neural networks. This builds on advances in normative accounts of brain function, specifically the Bayesian integration of beliefs and sensory evidence in which hierarchical predictions and prediction errors underlie memory, perception, speech and behaviour. We describe how analogous impairments in predictive coding in parallel neurocognitive systems can generate diverse clinical phenomena, including the characteristics of dementias. The review presents evidence from behavioural and neurophysiological studies of perception, language, memory and decision-making. The reformulation of cognitive deficits in terms of predictive coding has several advantages. It brings diverse clinical phenomena into a common framework; it aligns cognitive and movement disorders; and it makes specific predictions on cognitive physiology that support translational and experimental medicine studies. The insights into complex human cognitive disorders from the predictive coding framework may therefore also inform future therapeutic strategies.
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Affiliation(s)
- Ece Kocagoncu
- Cambridge Centre for Frontotemporal Dementia, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | | | - Laura E Hughes
- Cambridge Centre for Frontotemporal Dementia, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.,Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - James B Rowe
- Cambridge Centre for Frontotemporal Dementia, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.,Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
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