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Kucikova L, Kalabizadeh H, Motsi KG, Rashid S, O'Brien JT, Taylor JP, Su L. A systematic literature review of fMRI and EEG resting-state functional connectivity in Dementia with Lewy Bodies: Underlying mechanisms, clinical manifestation, and methodological considerations. Ageing Res Rev 2024; 93:102159. [PMID: 38056505 DOI: 10.1016/j.arr.2023.102159] [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: 05/25/2023] [Revised: 08/14/2023] [Accepted: 12/01/2023] [Indexed: 12/08/2023]
Abstract
Previous studies suggest that there may be important links between functional connectivity, disease mechanisms underpinning the Dementia with Lewy Body (DLB) and the key clinical symptoms, but the exact relationship remains unclear. We performed a systematic literature review to address this gap by summarising the research findings while critically considering the impact of methodological differences on findings. The main methodological choices of fMRI articles included data-driven, seed-based or regions of interest approaches, or their combinations. Most studies focused on examining large-scale resting-state networks, which revealed a consistent decrease in connectivity and some associations with non-cognitive symptoms. Although the inter-network connectivity showed mixed results, the main finding is consistent with theories positing disconnection between visual and attentional areas of the brain implicated in the aetiology of psychotic symptoms in the DLB. The primary methodological choice of EEG studies was implementing the phase lag index and using graph theory. The EEG studies revealed a consistent decrease in connectivity on alpha and beta frequency bands. While the overall trend of findings showed decreased connectivity, more subtle changes in the directionality of connectivity were observed when using a hypothesis-driven approach. Problems with cognition were also linked with greater functional connectivity disturbances. In summary, connectivity measures can capture brain disturbances in the DLB and remain crucial in uncovering the causal relationship between the networks' disorganisation and underlying mechanisms resulting in psychotic, motor, and cognitive symptoms of the DLB.
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Affiliation(s)
- Ludmila Kucikova
- Neuroscience Institute, University of Sheffield, Sheffield, United Kingdom; Insigneo Institute for in Silico Medicine, University of Sheffield, Sheffield, United Kingdom
| | - Hoda Kalabizadeh
- Oxford Machine Learning in NeuroImaging Lab, OMNI, Department of Computer Science, University of Oxford, Oxford, United Kingdom
| | | | - Sidrah Rashid
- Academic Unit of Medical Education, University of Sheffield, Sheffield, United Kingdom
| | - John T O'Brien
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
| | - John-Paul Taylor
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, United Kingdom
| | - Li Su
- Neuroscience Institute, University of Sheffield, Sheffield, United Kingdom; Insigneo Institute for in Silico Medicine, University of Sheffield, Sheffield, United Kingdom; Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom.
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2
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Khokhar SK, Kumar M, Kumar S, Manae T, Thanissery N, Ramakrishnan S, Arshad F, Nagaraj C, Mangalore S, Alladi S, Gandhi TK, Bharath RD. Alzheimer's Disease Is Associated with Increased Network Assortativity: Evidence from Metabolic Connectivity. Brain Connect 2023; 13:610-620. [PMID: 37930734 DOI: 10.1089/brain.2023.0024] [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] [Indexed: 11/07/2023] Open
Abstract
Introduction: Unraveling the network pathobiology in neurodegenerative disorders is a popular and promising field in research. We use a relatively newer network measure of assortativity in metabolic connectivity to understand network differences in patients with Alzheimer's Disease (AD), compared with those with mild cognitive impairment (MCI). Methods: Eighty-three demographically matched patients with dementia (56 AD and 27 MCI) who underwent positron emission tomography-magnetic resonance imaging (PET-MRI) study were recruited for this exploratory study. Global and nodal network measures obtained using the BRain Analysis using graPH theory toolbox were used to derive group-level differences (corrected p < 0.05). The methods were validated in age, and gender-matched 23 cognitively normal, 25 MCI, and 53 AD patients from the publicly available Alzheimer's Disease Neuroimaging Initiative (ADNI) data. Regions that revealed significant differences were correlated with the Addenbrooke's Cognitive Examination-III (ACE-III) scores. Results: Patients with AD revealed significantly increased global assortativity compared with the MCI group. In addition, they also revealed increased modularity and decreased participation coefficient. These findings were validated in the ADNI data. We also found that the regional standard uptake values of the right superior parietal and left superior temporal lobes were proportional to the ACE-III memory subdomain scores. Conclusion: Global errors associated with network assortativity are found in patients with AD, making the networks more regular and less resilient. Since the regional measures of these network errors were proportional to memory deficits, these measures could be useful in understanding the network pathobiology in AD.
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Affiliation(s)
- Sunil Kumar Khokhar
- Department of Neuroimaging and Interventional Radiology, and National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Manoj Kumar
- Department of Neuroimaging and Interventional Radiology, and National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Sandeep Kumar
- Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Tejaswini Manae
- Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Nithin Thanissery
- Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Subasree Ramakrishnan
- Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Faheem Arshad
- Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Chandana Nagaraj
- Department of Neuroimaging and Interventional Radiology, and National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Sandhya Mangalore
- Department of Neuroimaging and Interventional Radiology, and National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Suvarna Alladi
- Department of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
| | - Tapan K Gandhi
- Department of Electrical Engineering, Indian Institute of Technology (IIT) Delhi, New Delhi, Delhi, India
| | - Rose Dawn Bharath
- Department of Neuroimaging and Interventional Radiology, and National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, India
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Lizio R, Lopez S, Babiloni C, Del Percio C, Noce G, Losurdo A, Vernò L, De Tommaso M, Montemurno A, Dalfino G, Cirillo P, Soricelli A, Ferri R, Catania V, Nobili F, Giubilei F, Buttinelli C, Frisoni GB, Stocchi F, Scisci AM, Mastrofilippo N, Procaccini DA, Gesualdo L. Resting state EEG rhythms in different stages of chronic kidney disease with mild cognitive impairment. Neurobiol Aging 2023; 130:70-79. [PMID: 37473580 DOI: 10.1016/j.neurobiolaging.2023.05.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 05/30/2023] [Accepted: 05/31/2023] [Indexed: 07/22/2023]
Abstract
Here, we tested that standard eyes-closed resting-state electroencephalographic (rsEEG) rhythms may characterize patients with mild cognitive impairment due to chronic kidney disease at stages 3-4 (CKDMCI-3&4) in relation to CKDMCI patients under hemodialysis (CKDMCI-H) and mild cognitive impairment (MCI) patients with cerebrovascular disease (CVMCI). Clinical and rsEEG data in 22 CKDMCI-3&4, 15 CKDMCI-H, 18 CVMCI, and 30 matched healthy control (HC) participants were available in a national archive. Spectral rsEEG power density was calculated from delta to gamma frequency bands at scalp electrodes. Results showed that (1) all MCI groups over the HC group showed decreased occipital rsEEG alpha power density; (2) compared to the HC and CVMCI groups, the 2 CKDMCI groups had higher rsEEG delta-theta power density; and (3) the CKDMCI-3&4 group showed the lowest parietal rsEEG alpha power density. The present rsEEG measures may be useful to monitor the impact of circulating uremic toxins on brain regulation of cortical arousal for quiet vigilance in CKDMCI patients.
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Affiliation(s)
- Roberta Lizio
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy; Nephrology, Dialysis and Transplantation Unit, Department of Precision and Regenerative Medicine and Ionian Area (DiMePRe-J), University of Bari "Aldo Moro", Bari, Italy
| | - Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy; Hospital San Raffaele Cassino, Cassino (FR), Italy.
| | - Claudio Del Percio
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | | | - Antonia Losurdo
- Nephrology, Dialysis and Transplantation Unit, Department of Precision and Regenerative Medicine and Ionian Area (DiMePRe-J), University of Bari "Aldo Moro", Bari, Italy
| | - Lucia Vernò
- Nephrology, Dialysis and Transplantation Unit, Department of Precision and Regenerative Medicine and Ionian Area (DiMePRe-J), University of Bari "Aldo Moro", Bari, Italy
| | - Marina De Tommaso
- Neurophysiopathology Unit, DiBrain Department, Aldo Moro University of Bari, Bari, Italy
| | - Anna Montemurno
- Neurophysiopathology Unit, DiBrain Department, Aldo Moro University of Bari, Bari, Italy
| | - Giuseppe Dalfino
- National Institute of Gastroenterology "Saverio de Bellis" - IRCCS, via Turi n. 27 - 70013 Castellana Grotte (BA)
| | - Pietro Cirillo
- Nephrology, Dialysis and Transplantation Unit, Department of Precision and Regenerative Medicine and Ionian Area (DiMePRe-J), University of Bari "Aldo Moro", Bari, Italy
| | - Andrea Soricelli
- IRCCS Synlab SDN, Naples, Italy; Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | | | | | - Flavio Nobili
- Clinical Neurology, Department of Neuroscience (DiNOGMI), University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Franco Giubilei
- Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Carla Buttinelli
- Department of Neuroscience, Mental Health and Sensory Organs, Sapienza University of Rome, Rome, Italy
| | - Giovanni B Frisoni
- IRCCS San Giovanni di Dio Fatebenefratelli, Brescia, Italy; Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Fabrizio Stocchi
- IRCCS San Raffaele, Rome, Italy; Telematic University, San Raffaele, Rome, Italy
| | - Anna Maria Scisci
- Nephrology, Dialysis and Transplantation Unit, Department of Precision and Regenerative Medicine and Ionian Area (DiMePRe-J), University of Bari "Aldo Moro", Bari, Italy
| | - Nicola Mastrofilippo
- Nephrology, Dialysis and Transplantation Unit, Department of Precision and Regenerative Medicine and Ionian Area (DiMePRe-J), University of Bari "Aldo Moro", Bari, Italy
| | - Deni Aldo Procaccini
- Nephrology, Dialysis and Transplantation Unit, Department of Precision and Regenerative Medicine and Ionian Area (DiMePRe-J), University of Bari "Aldo Moro", Bari, Italy
| | - Loreto Gesualdo
- Nephrology, Dialysis and Transplantation Unit, Department of Precision and Regenerative Medicine and Ionian Area (DiMePRe-J), University of Bari "Aldo Moro", Bari, Italy
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Habich A, Oltra J, Schwarz CG, Przybelski SA, Oppedal K, Inguanzo A, Blanc F, Lemstra AW, Hort J, Westman E, Lowe VJ, Boeve BF, Dierks T, Aarsland D, Kantarci K, Ferreira D. Sex differences in grey matter networks in dementia with Lewy bodies. RESEARCH SQUARE 2023:rs.3.rs-2519935. [PMID: 36778448 PMCID: PMC9915801 DOI: 10.21203/rs.3.rs-2519935/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Objectives Sex differences permeate many aspects of dementia with Lewy bodies (DLB), including epidemiology, pathogenesis, disease progression, and symptom manifestation. However, less is known about potential sex differences in patterns of neurodegeneration in DLB. Here, we test whether grey matter networks also differ between female and male DLB patients. To assess the specificity of these sex differences to DLB, we additionally investigate sex differences in healthy controls (HCs). Methods A total of 119 (68.7 ± 8.4 years) male and 45 female (69.9 ± 9.1 years) DLB patients from three European centres and the Mayo Clinic were included in this study. Additionally, we included 119 male and 45 female age-matched HCs from the Mayo Clinic. Grey matter volumes of 58 cortical, subcortical, cerebellar, and pontine brain regions derived from structural magnetic resonance images were corrected for age, intracranial volume, and centre. Sex-specific grey matter networks for DLB patients and HCs were constructed by correlating each pair of brain regions. Network properties of the correlation matrices were compared between sexes and groups. Additional analyses were conducted on W-scored data to identify DLB-specific findings. Results Networks of male HCs and male DLB patients were characterised by a lower nodal strength compared to their respective female counterparts. In comparison to female HCs, the grey matter networks of male HCs showed a higher global efficiency, modularity, and a lower number of modules. None of the global and nodal network measures showed significant sex differences in DLB. Conclusions The disappearance of sex differences in the structural grey matter networks of DLB patients compared to HCs may indicate a sex-dependent network vulnerability to the alpha-synuclein pathology in DLB. Future studies might investigate whether the differences in structural network measures are associated with differences in cognitive scores and clinical symptoms between the sexes.
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Affiliation(s)
- Annegret Habich
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Javier Oltra
- Medical Psychology Unit, Department of Medicine, Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | | | | | - Ketil Oppedal
- Center for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Anna Inguanzo
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Frédéric Blanc
- Day Hospital of Geriatrics, Memory Resource and Research Centre (CM2R) of Strasbourg, Department of Geriatrics, Hopitaux Universitaires de Strasbourg, Strasbourg, France
| | - Afina W Lemstra
- Department of Neurology and Alzheimer Center, VU University Medical Center, Amsterdam, Netherlands
| | - Jakub Hort
- Motol University Hospital, Prague, Czech Republic
| | - Eric Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, USA
| | | | - Thomas Dierks
- University Hospital of Psychiatry and Psychotherapy Bern, University of Bern, Bern, Switzerland
| | - Dag Aarsland
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | | | - Daniel Ferreira
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
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5
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Habich A, Wahlund LO, Westman E, Dierks T, Ferreira D. (Dis-)Connected Dots in Dementia with Lewy Bodies-A Systematic Review of Connectivity Studies. Mov Disord 2023; 38:4-15. [PMID: 36253921 PMCID: PMC10092805 DOI: 10.1002/mds.29248] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 08/04/2022] [Accepted: 09/12/2022] [Indexed: 01/21/2023] Open
Abstract
Studies on dementia with Lewy bodies (DLB) have mainly focused on the degeneration of distinct cortical and subcortical regions related to the deposition of Lewy bodies. In view of the proposed trans-synaptic spread of the α-synuclein pathology, investigating the disease only in this segregated fashion would be detrimental to our understanding of its progression. In this systematic review, we summarize findings on structural and functional brain connectivity in DLB, as connectivity measures may offer better insights on how the brain is affected by the spread of the pathology. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched Web of Science, PubMed, and SCOPUS for relevant articles published up to November 1, 2021. Of 1215 identified records, we selected and systematically reviewed 53 articles that compared connectivity features between patients with DLB and healthy controls. Structural and functional magnetic resonance imaging, positron emission tomography, single-positron emission computer tomography, and electroencephalography assessments of patients revealed widespread abnormalities within and across brain networks in DLB. Frontoparietal, default mode, and visual networks and their connections to other brain regions featured the most consistent disruptions, which were also associated with core clinical features and cognitive impairments. Furthermore, graph theoretical measures revealed disease-related decreases in local and global network efficiency. This systematic review shows that structural and functional connectivity characteristics in DLB may be particularly valuable at early stages, before overt brain atrophy can be observed. This knowledge may help improve the diagnosis and prognosis in DLB as well as pinpoint targets for future disease-modifying treatments. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Annegret Habich
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Lars-Olof Wahlund
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Eric Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Department of Neuroimaging, Centre for Neuroimaging Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Thomas Dierks
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
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6
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Choi E, Han JW, Suh SW, Bae JB, Han JH, Lee S, Kim SE, Kim KW. Altered resting state brain metabolic connectivity in dementia with Lewy bodies. Front Neurol 2022; 13:847935. [PMID: 36003295 PMCID: PMC9393539 DOI: 10.3389/fneur.2022.847935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 06/27/2022] [Indexed: 11/24/2022] Open
Abstract
Although dementia with Lewy bodies (DLB) have Parkinsonism in common with Parkinson's disease (PD) or PD dementia (PDD), they have different neuropathologies that underlie Parkinsonism. Altered brain functional connectivity that may correspond to neuropathology has been reported in PD while never been studied in DLB. To identify the characteristic brain connectivity of Parkinsonism in DLB, we compared the resting state metabolic connectivity in striato-thalamo-cortical (STC) circuit, nigrostriatal pathway, and cerebello-thalamo-cortical motor (CTC) circuit in 27 patients with drug-naïve DLB and 27 age- and sex-matched normal controls using 18F-fluoro-2-deoxyglucose PET. We derived 118 regions of interest using the Automated Anatomical Labeling templates and the Wake Forest University Pick-Atlas. We applied the sparse inverse covariance estimation method to construct the metabolic connectivity matrix. Patients with DLB, with or without Parkinsonism, showed lower inter-regional connectivity between the areas included in the STC circuit (motor cortex–striatum, midbrain–striatum, striatum–globus pallidus, and globus pallidus–thalamus) than the controls. DLB patients with Parkinsonism showed less reduced inter-regional connectivity between the midbrain and the striatum than those without Parkinsonism, and higher inter-regional connectivity between the areas included in the CTC circuit (motor cortex–pons, pons–cerebellum, and cerebellum–thalamus) than those without Parkinsonism and the controls. The resting state metabolic connectivity in the STC circuit may be reduced in DLB. In DLB with Parkinsonism, the CTC circuit and the nigrostriatal pathway may be activated to mitigate Parkinsonism. This difference in the brain connectivity may be a candidate biomarker for differentiating DLB from PD or PDD.
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Affiliation(s)
- Euna Choi
- Department of Brain and Cognitive Science, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - Ji Won Han
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Seung Wan Suh
- Department of Psychiatry, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, South Korea
| | - Jong Bin Bae
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Ji Hyun Han
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Subin Lee
- Department of Brain and Cognitive Science, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - Sang Eun Kim
- Department of Nuclear Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, South Korea
- Center for Nanomolecular Imaging and Innovative Drug Development, Advanced Institutes of Convergence Technology, Suwon, South Korea
| | - Ki Woong Kim
- Department of Brain and Cognitive Science, Seoul National University College of Natural Sciences, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
- *Correspondence: Ki Woong Kim
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7
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Babiloni C, Noce G, Di Bonaventura C, Lizio R, Eldellaa A, Tucci F, Salamone EM, Ferri R, Soricelli A, Nobili F, Famà F, Arnaldi D, Palma E, Cifelli P, Marizzoni M, Stocchi F, Bruno G, Di Gennaro G, Frisoni GB, Del Percio C. Alzheimer's Disease with Epileptiform EEG Activity: Abnormal Cortical Sources of Resting State Delta Rhythms in Patients with Amnesic Mild Cognitive Impairment. J Alzheimers Dis 2022; 88:903-931. [PMID: 35694930 DOI: 10.3233/jad-220442] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Patients with amnesic mild cognitive impairment due to Alzheimer's disease (ADMCI) typically show a "slowing" of cortical resting-state eyes-closed electroencephalographic (rsEEG) rhythms. Some of them also show subclinical, non-convulsive, and epileptiform EEG activity (EEA) with an unclear relationship with that "slowing." OBJECTIVE Here we tested the hypothesis that the "slowing" of rsEEG rhythms is related to EEA in ADMCI patients. METHODS Clinical and instrumental datasets in 62 ADMCI patients and 38 normal elderly (Nold) subjects were available in a national archive. No participant had received a clinical diagnosis of epilepsy. The eLORETA freeware estimated rsEEG cortical sources. The area under the receiver operating characteristic curve (AUROCC) indexed the accuracy of eLORETA solutions in the classification between ADMCI-EEA and ADMCI-noEEA individuals. RESULTS EEA was observed in 15% (N = 8) of the ADMCI patients. The ADMCI-EEA group showed: 1) more abnormal Aβ 42 levels in the cerebrospinal fluid as compared to the ADMCI-noEEA group and 2) higher temporal and occipital delta (<4 Hz) rsEEG source activities as compared to the ADMCI-noEEA and Nold groups. Those source activities showed moderate accuracy (AUROCC = 0.70-0.75) in the discrimination between ADMCI-noEEA versus ADMCI-EEA individuals. CONCLUSION It can be speculated that in ADMCI-EEA patients, AD-related amyloid neuropathology may be related to an over-excitation in neurophysiological low-frequency (delta) oscillatory mechanisms underpinning cortical arousal and quiet vigilance.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy.,Hospital San Raffaele Cassino, Cassino (FR), Italy
| | | | - Carlo Di Bonaventura
- Epilepsy Unit, Department of Neurosciences/Mental Health, Sapienza University of Rome, Rome, Italy
| | | | - Ali Eldellaa
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Federico Tucci
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Enrico M Salamone
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy.,Epilepsy Unit, Department of Neurosciences/Mental Health, Sapienza University of Rome, Rome, Italy
| | | | - Andrea Soricelli
- IRCCS Synlab SDN, Naples, Italy.,Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | - Flavio Nobili
- Clinical Neurology, IRCCS Hospital Policlinico San Martino, Genoa, Italy.,Department of Neuroscience (DiNOGMI), University of Genoa, Genoa, Italy
| | - Francesco Famà
- Clinical Neurology, IRCCS Hospital Policlinico San Martino, Genoa, Italy
| | - Dario Arnaldi
- Clinical Neurology, IRCCS Hospital Policlinico San Martino, Genoa, Italy
| | - Eleonora Palma
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy.,Pasteur Institute-Cenci Bolognetti Foundation, Rome, Italy
| | - Pierangelo Cifelli
- IRCCS Neuromed, Pozzilli, (IS), Italy.,Department of Applied and Biotechnological Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Moira Marizzoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | | | - Giuseppe Bruno
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | | | - Giovanni B Frisoni
- Department of Applied and Biotechnological Clinical Sciences, University of L'Aquila, L'Aquila, Italy.,Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Claudio Del Percio
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
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8
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Zhou B, Wu X, Tang L, Li C. Dynamics of the Brain Functional Network Associated With Subjective Cognitive Decline and Its Relationship to Apolipoprotein E €4 Alleles. Front Aging Neurosci 2022; 14:806032. [PMID: 35356298 PMCID: PMC8959928 DOI: 10.3389/fnagi.2022.806032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Accepted: 02/08/2022] [Indexed: 11/13/2022] Open
Abstract
The aim of our study was to explore the dynamic functional alterations in the brain in patients with subjective cognitive decline (SCD) and their relationship to apolipoprotein E (APOE) €4 alleles. In total, 95 SCD patients and 49 healthy controls (HC) underwent resting-state functional magnetic resonance imaging (rs-fMRI). Then, the mean time series of 90 cortical or subcortical regions were extracted based on anatomical automatic labeling (AAL) atlas from the preprocessed rs-fMRI data. The static functional connectome (SFC) and dynamic functional connectome (DFC) were constructed and compared using graph theory methods and leading eigenvector dynamics analysis (LEiDA), respectively. The SCD group displayed a shorter lifetime (p = 0.003, false discovery rate corrected) and lower probability (p = 0.009, false discovery rate corrected) than the HC group in a characteristic dynamic functional network mainly involving the bilateral insular and temporal neocortex. No significant differences in the SFC were detected between the two groups. Moreover, the lower probability in the SCD group was found to be negatively correlated with the number of APOE ε4 alleles (r = −0.225, p = 0.041) in a partial correlation analysis with years of education as a covariate. Our results suggest that the DFC may be a more sensitive parameter than the SFC and can be used as a potential biomarker for the early detection of SCD.
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9
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Reorganization of rich clubs in functional brain networks of dementia with Lewy bodies and Alzheimer's disease. Neuroimage Clin 2021; 33:102930. [PMID: 34959050 PMCID: PMC8856913 DOI: 10.1016/j.nicl.2021.102930] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 11/18/2021] [Accepted: 12/23/2021] [Indexed: 12/12/2022]
Abstract
DLB and AD had the different functional reorganization patterns. Rich club nodes increased in frontal-parietal network in patients with DLB. The rich club nodes in temporal lobe decreased and those in cerebellum increased for AD. Compared with HC, rich club connectivity was enhanced in the DLB and AD groups.
The purpose of this study was to reveal the patterns of reorganization of rich club organization in brain functional networks in dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD). The study found that the rich club node shifts from sensory/somatomotor network to fronto-parietal network in DLB. For AD, the rich club nodes switch between the temporal lobe with obvious structural atrophy and the frontal lobe, parietal lobe and cerebellum with relatively preserved structure and function. In addition, compared with healthy controls, rich club connectivity was enhanced in the DLB and AD groups. The connection strength of DLB patients was related to cognitive assessment. In conclusion, we revealed the different functional reorganization patterns of DLB and AD. The conversion and redistribution of rich club members may play a causal role in disease-specific outcomes. It may be used as a potential biomarker to provide more accurate prevention and treatment strategies.
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10
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Lu J, Chen Q, Li D, Zhang W, Xing S, Wang J, Zhang X, Liu J, Qing Z, Dai Y, Zhang B. Reconfiguration of Dynamic Functional Connectivity States in Patients With Lifelong Premature Ejaculation. Front Neurosci 2021; 15:721236. [PMID: 34588948 PMCID: PMC8473781 DOI: 10.3389/fnins.2021.721236] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2021] [Accepted: 08/19/2021] [Indexed: 11/13/2022] Open
Abstract
Purpose: Neuroimaging has demonstrated altered static functional connectivity in patients with premature ejaculation (PE), while studies examining dynamic changes in spontaneous brain activity in PE patients are still lacking. We aimed to explore the reconfiguration of dynamic functional connectivity (DFC) states in lifelong PE (LPE) patients and to distinguish LPE patients from normal controls (NCs) using a machine learning method based on DFC state features. Methods: Thirty-six LPE patients and 23 NCs were recruited. Resting-state functional magnetic resonance imaging (fMRI) data, the clinical rating scores on the Chinese Index of PE (CIPE), and intravaginal ejaculatory latency time (IELT) were collected from each participant. DFC was calculated by the sliding window approach. Finally, the Lagrangian support vector machine (LSVM) classifier was applied to distinguish LPE patients from NCs using the DFC parameters. Two DFC state metrics (reoccurrence times and transition frequencies) were introduced and we assessed the correlations between DFC state metrics and clinical variables, and the accuracy, sensitivity, and specificity of the LSVM classifier. Results: By k-means clustering, four distinct DFC states were identified. The LPE patients showed an increase in the reoccurrence times for state 3 (p < 0.05, Bonferroni corrected) but a decrease for state 1 (p < 0.05, Bonferroni corrected) compared to the NCs. Moreover, the LPE patients had significantly less frequent transitions between state 1 and state 4 (p < 0.05, uncorrected) while more frequent transitions between state 3 and state 4 (p < 0.05, uncorrected) than the NCs. The reoccurrence times and transition frequencies showed significant associations with the CIPE scores and IELTs. The accuracy, sensitivity, and specificity of the LSVM classifier were 90.35, 87.59, and 85.59%, respectively. Conclusion: LPE patients were more inclined to be in DFC states reinforced intra-network and inter-network connection. These features correlated with clinical syndromes and can classify the LPE patients from NCs. Our results of reconfiguration of DFC states may provide novel insights for the understanding of central etiology underlying LPE, indicate neuroimaging biomarkers for the evaluation of clinical severity of LPE.
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Affiliation(s)
- Jiaming Lu
- Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Qian Chen
- Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Danyan Li
- Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China.,Department of Radiology, Nanjing Drum Tower Hospital, Clinical College of Nanjing Medical University, Nanjing, China
| | - Wen Zhang
- Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Siyan Xing
- Department of Andrology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Junxia Wang
- Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Xin Zhang
- Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Jiani Liu
- Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Zhao Qing
- Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Yutian Dai
- Department of Andrology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China
| | - Bing Zhang
- Department of Radiology, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Nanjing, China.,Department of Radiology, Nanjing Drum Tower Hospital, Clinical College of Nanjing Medical University, Nanjing, China.,Institute of Brain Science, Nanjing University, Nanjing, China
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11
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Chen X, Necus J, Peraza LR, Mehraram R, Wang Y, O'Brien JT, Blamire A, Kaiser M, Taylor JP. The functional brain favours segregated modular connectivity at old age unless affected by neurodegeneration. Commun Biol 2021; 4:973. [PMID: 34400752 PMCID: PMC8367990 DOI: 10.1038/s42003-021-02497-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2018] [Accepted: 07/22/2021] [Indexed: 11/29/2022] Open
Abstract
Brain's modular connectivity gives this organ resilience and adaptability. The ageing process alters the organised modularity of the brain and these changes are further accentuated by neurodegeneration, leading to disorganisation. To understand this further, we analysed modular variability-heterogeneity of modules-and modular dissociation-detachment from segregated connectivity-in two ageing cohorts and a mixed cohort of neurodegenerative diseases. Our results revealed that the brain follows a universal pattern of high modular variability in metacognitive brain regions: the association cortices. The brain in ageing moves towards a segregated modular structure despite presenting with increased modular heterogeneity-modules in older adults are not only segregated, but their shape and size are more variable than in young adults. In the presence of neurodegeneration, the brain maintains its segregated connectivity globally but not locally, and this is particularly visible in dementia with Lewy bodies and Parkinson's disease dementia; overall, the modular brain shows patterns of differentiated pathology.
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Affiliation(s)
- Xue Chen
- College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China.
- Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.
| | - Joe Necus
- Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.
- University of Nottingham, NIHR Nottingham Biomedical Research Centre, School of Medicine, Nottingham, UK.
| | - Luis R Peraza
- Translational and Clinical Research Institute, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, United Kingdom
- IXICO Plc, London, UK
| | - Ramtin Mehraram
- Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
- Translational and Clinical Research Institute, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, United Kingdom
- Experimental Oto-rhino-laryngology (ExpORL) Research Group, Department of Neurosciences, KU Leuven, Leuven, Belgium
- NIHR Newcastle Biomedical Research Centre, Campus for Ageing and Vitality, Newcastle upon Tyne, UK
| | - Yanjiang Wang
- College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China
| | - John T O'Brien
- Department of Psychiatry, University of Cambridge School of Medicine, Cambridge, United Kingdom
| | - Andrew Blamire
- Translational and Clinical Research Institute, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, United Kingdom
| | - Marcus Kaiser
- Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
- University of Nottingham, NIHR Nottingham Biomedical Research Centre, School of Medicine, Nottingham, UK
- Translational and Clinical Research Institute, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, United Kingdom
| | - John-Paul Taylor
- Translational and Clinical Research Institute, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, United Kingdom
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12
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O’Callaghan C, Firbank M, Tomassini A, Schumacher J, O’Brien JT, Taylor JP. Impaired sensory evidence accumulation and network function in Lewy body dementia. Brain Commun 2021; 3:fcab089. [PMID: 34396098 PMCID: PMC8361397 DOI: 10.1093/braincomms/fcab089] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 03/02/2021] [Accepted: 03/16/2021] [Indexed: 11/14/2022] Open
Abstract
Deficits in attention underpin many of the cognitive and neuropsychiatric features of Lewy body dementia. These attention-related symptoms remain difficult to treat and there are many gaps in our understanding of their neurobiology. An improved understanding of attention-related impairments can be achieved via mathematical modelling approaches, which identify cognitive parameters to provide an intermediate level between observed behavioural data and its underlying neural correlate. Here, we apply this approach to identify the role of impaired sensory evidence accumulation in the attention deficits that characterize Lewy body dementia. In 31 people with Lewy body dementia (including 13 Parkinson's disease dementia and 18 dementia with Lewy bodies cases), 16 people with Alzheimer's disease, and 23 healthy controls, we administered an attention task whilst they underwent functional 3 T MRI. Using hierarchical Bayesian estimation of a drift-diffusion model, we decomposed task performance into drift rate and decision boundary parameters. We tested the hypothesis that the drift rate-a measure of the quality of sensory evidence accumulation-is specifically impaired in Lewy body dementia, compared to Alzheimer's disease. We further explored whether trial-by-trial variations in the drift rate related to activity within the default and dorsal attention networks, to determine whether altered activity in these networks was associated with slowed drift rates in Lewy body dementia. Our results revealed slower drift rates in the Lewy body dementia compared to the Alzheimer's disease group, whereas the patient groups were equivalent for their decision boundaries. The patient groups were reduced relative to controls for both parameters. This highlights sensory evidence accumulation deficits as a key feature that distinguishes attention impairments in Lewy body dementia, consistent with impaired ability to efficiently process information from the environment to guide behaviour. We also found that the drift rate was strongly related to activity in the dorsal attention network across all three groups, whereas the Lewy body dementia group showed a divergent relationship relative to the Alzheimer's disease and control groups for the default network, consistent with altered default network modulation being associated with impaired evidence accumulation. Together, our findings reveal impaired sensory evidence accumulation as a specific marker of attention problems in Lewy body dementia, which may relate to large-scale network abnormalities. By identifying impairments in a specific sub-process of attention, these findings will inform future exploratory and intervention studies that aim to understand and treat attention-related symptoms that are a key feature of Lewy body dementia.
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Affiliation(s)
- Claire O’Callaghan
- Brain and Mind Centre and School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney 2050, Australia
- Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Michael Firbank
- Translational and Clinical Research Institute, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne NE4 5PL, UK
| | - Alessandro Tomassini
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, UK
| | - Julia Schumacher
- Translational and Clinical Research Institute, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne NE4 5PL, UK
| | - John T O’Brien
- Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK
| | - John-Paul Taylor
- Translational and Clinical Research Institute, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne NE4 5PL, UK
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13
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Babiloni C, Arakaki X, Azami H, Bennys K, Blinowska K, Bonanni L, Bujan A, Carrillo MC, Cichocki A, de Frutos-Lucas J, Del Percio C, Dubois B, Edelmayer R, Egan G, Epelbaum S, Escudero J, Evans A, Farina F, Fargo K, Fernández A, Ferri R, Frisoni G, Hampel H, Harrington MG, Jelic V, Jeong J, Jiang Y, Kaminski M, Kavcic V, Kilborn K, Kumar S, Lam A, Lim L, Lizio R, Lopez D, Lopez S, Lucey B, Maestú F, McGeown WJ, McKeith I, Moretti DV, Nobili F, Noce G, Olichney J, Onofrj M, Osorio R, Parra-Rodriguez M, Rajji T, Ritter P, Soricelli A, Stocchi F, Tarnanas I, Taylor JP, Teipel S, Tucci F, Valdes-Sosa M, Valdes-Sosa P, Weiergräber M, Yener G, Guntekin B. Measures of resting state EEG rhythms for clinical trials in Alzheimer's disease: Recommendations of an expert panel. Alzheimers Dement 2021; 17:1528-1553. [PMID: 33860614 DOI: 10.1002/alz.12311] [Citation(s) in RCA: 69] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Revised: 12/28/2020] [Accepted: 01/01/2021] [Indexed: 12/25/2022]
Abstract
The Electrophysiology Professional Interest Area (EPIA) and Global Brain Consortium endorsed recommendations on candidate electroencephalography (EEG) measures for Alzheimer's disease (AD) clinical trials. The Panel reviewed the field literature. As most consistent findings, AD patients with mild cognitive impairment and dementia showed abnormalities in peak frequency, power, and "interrelatedness" at posterior alpha (8-12 Hz) and widespread delta (< 4 Hz) and theta (4-8 Hz) rhythms in relation to disease progression and interventions. The following consensus statements were subscribed: (1) Standardization of instructions to patients, resting state EEG (rsEEG) recording methods, and selection of artifact-free rsEEG periods are needed; (2) power density and "interrelatedness" rsEEG measures (e.g., directed transfer function, phase lag index, linear lagged connectivity, etc.) at delta, theta, and alpha frequency bands may be use for stratification of AD patients and monitoring of disease progression and intervention; and (3) international multisectoral initiatives are mandatory for regulatory purposes.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy.,San Raffaele of Cassino, Cassino (FR), Italy
| | | | - Hamed Azami
- Department of Neurology and Massachusetts General Hospital, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Karim Bennys
- Centre Mémoire de Ressources et de Recherche (CMRR), Centre Hospitalier, Universitaire de Montpellier, Montpellier, France
| | - Katarzyna Blinowska
- Institute of Biocybernetics, Warsaw, Poland.,Faculty of Physics University of Warsaw and Nalecz, Warsaw, Poland
| | - Laura Bonanni
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University "G. D'Annunzio" of Chieti-Pescara, Chieti, Italy
| | - Ana Bujan
- Psychological Neuroscience Lab, School of Psychology, University of Minho, Minho, Portugal
| | - Maria C Carrillo
- Division of Medical & Scientific Relations, Alzheimer's Association, Chicago, Illinois, USA
| | - Andrzej Cichocki
- Skolkowo Institute of Science and Technology (SKOLTECH), Moscow, Russia.,Systems Research Institute PAS, Warsaw, Poland.,Nicolaus Copernicus University (UMK), Torun, Poland
| | - Jaisalmer de Frutos-Lucas
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | - Claudio Del Percio
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Bruno Dubois
- Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Institute of Memory and Alzheimer's Disease (IM2A), Paris, France.,ICM, INSERM U1127, CNRS UMR 7225, Sorbonne Université, Institut du Cerveau et de la Moelle épinière, Paris, France
| | - Rebecca Edelmayer
- Division of Medical & Scientific Relations, Alzheimer's Association, Chicago, Illinois, USA
| | - Gary Egan
- Foundation Director of the Monash Biomedical Imaging (MBI) Research Facilities, Monash University, Clayton, Australia
| | - Stephane Epelbaum
- Department of Neurology, Pitié-Salpêtrière Hospital, AP-HP, Boulevard de l'hôpital, Institute of Memory and Alzheimer's Disease (IM2A), Paris, France.,ICM, INSERM U1127, CNRS UMR 7225, Sorbonne Université, Institut du Cerveau et de la Moelle épinière, Paris, France
| | - Javier Escudero
- School of Engineering, Institute for Digital Communications, The University of Edinburgh, Edinburgh, UK
| | - Alan Evans
- Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
| | - Francesca Farina
- Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Keith Fargo
- Division of Medical & Scientific Relations, Alzheimer's Association, Chicago, Illinois, USA
| | - Alberto Fernández
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | | | - Giovanni Frisoni
- IRCCS San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Memory Clinic and LANVIE - Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Harald Hampel
- GRC n° 21, Alzheimer Precision Medicine (APM), AP-HP, Pitié-Salpêtrière Hospital, Boulevard de l'hôpital, Sorbonne University, Paris, France
| | | | - Vesna Jelic
- Division of Clinical Geriatrics, NVS Department, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Jaeseung Jeong
- Department of Bio and Brain Engineering/Program of Brain and Cognitive Engineering Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea
| | - Yang Jiang
- Department of Behavioral Science, College of Medicine, University of Kentucky, Lexington, Kentucky, USA
| | - Maciej Kaminski
- Faculty of Physics University of Warsaw and Nalecz, Warsaw, Poland
| | - Voyko Kavcic
- Institute of Gerontology, Wayne State University, Detroit, Michigan, USA
| | - Kerry Kilborn
- School of Psychology, University of Glasgow, Glasgow, UK
| | - Sanjeev Kumar
- Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Alice Lam
- MGH Epilepsy Service, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Lew Lim
- Vielight Inc., Toronto, Ontario, Canada
| | | | - David Lopez
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | - Brendan Lucey
- Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Universidad Complutense and Universidad Politécnica de Madrid, Madrid, Spain
| | - William J McGeown
- School of Psychological Sciences and Health, University of Strathclyde, Glasgow, UK
| | - Ian McKeith
- Newcastle upon Tyne, Translational and Clinical Research Institute, Newcastle University, UK
| | | | - Flavio Nobili
- Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy.,Clinica Neurologica, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | | | - John Olichney
- UC Davis Department of Neurology and Center for Mind and Brain, Davis, California, USA
| | - Marco Onofrj
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University "G. D'Annunzio" of Chieti-Pescara, Chieti, Italy
| | - Ricardo Osorio
- Center for Brain Health, Department of Psychiatry, NYU Langone Medical Center, New York, New York, USA
| | | | - Tarek Rajji
- Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Petra Ritter
- Brain Simulation Section, Department of Neurology, Charité Universitätsmedizin and Berlin Institute of Health, Berlin, Germany.,Bernstein Center for Computational Neuroscience, Berlin, Germany
| | - Andrea Soricelli
- IRCCS SDN, Napoli, Italy.,Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | | | - Ioannis Tarnanas
- Global Brain Health Institute, University of California San Francisco, San Francisco, USA.,Global Brain Health Institute, Trinity College Dublin, Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - John Paul Taylor
- Newcastle upon Tyne, Translational and Clinical Research Institute, Newcastle University, UK
| | - Stefan Teipel
- Department of Psychosomatic Medicine, University of Rostock, Rostock, Germany.,German Center for Neurodegenerative Diseases (DZNE) - Rostock/Greifswald, Rostock, Germany
| | - Federico Tucci
- Department of Physiology and Pharmacology "Vittorio Erspamer", Sapienza University of Rome, Rome, Italy
| | | | - Pedro Valdes-Sosa
- Cuban Neuroscience Center, Havana, Cuba.,Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Marco Weiergräber
- Experimental Neuropsychopharmacology, BfArM), Federal Institute for Drugs and Medical Devices (Bundesinstitut für Arzneimittel und Medizinprodukte, Bonn, Germany
| | - Gorsev Yener
- Departments of Neurosciences and Department of Neurology, Dokuz Eylül University Medical School, Izmir, Turkey
| | - Bahar Guntekin
- Department of Biophysics, School of Medicine, Istanbul Medipol University, Istanbul, Turkey.,REMER, Clinical Electrophysiology, Neuroimaging and Neuromodulation Lab, Istanbul Medipol University, Istanbul, Turkey
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14
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Chen Q, Lu J, Zhang X, Sun Y, Chen W, Li X, Zhang W, Qing Z, Zhang B. Alterations in Dynamic Functional Connectivity in Individuals With Subjective Cognitive Decline. Front Aging Neurosci 2021; 13:646017. [PMID: 33613274 PMCID: PMC7886811 DOI: 10.3389/fnagi.2021.646017] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Accepted: 01/06/2021] [Indexed: 11/13/2022] Open
Abstract
Purpose: To investigate the dynamic functional connectivity (DFC) and static parameters of graph theory in individuals with subjective cognitive decline (SCD) and the associations of DFC and topological properties with cognitive performance. Methods: Thirty-three control subjects and 32 SCD individuals were enrolled in this study, and neuropsychological evaluations and resting-state functional magnetic resonance imaging scanning were performed. Thirty-three components were selected by group independent component analysis to construct 7 functional networks. Based on the sliding window approach and k-means clustering, distinct DFC states were identified. We calculated the temporal properties of fractional windows in each state, the mean dwell time in each state, and the number of transitions between each pair of DFC states. The global and local static parameters were assessed by graph theory analysis. The differences in DFC and topological metrics, and the associations of the altered neuroimaging measures with cognitive performance were assessed. Results: The whole cohort demonstrated 4 distinct connectivity states. Compared to the control group, the SCD group showed increased fractional windows and an increased mean dwell time in state 4, characterized by hypoconnectivity both within and between networks. The SCD group also showed decreased fractional windows and a decreased mean dwell time in state 2, dominated by hyperconnectivity within and between the auditory, visual and somatomotor networks. The number of transitions between state 1 and state 2, between state 2 and state 3, and between state 2 and state 4 was significantly reduced in the SCD group compared to the control group. No significant differences in global or local topological metrics were observed. The altered DFC properties showed significant correlations with cognitive performance. Conclusion: Our findings indicated DFC network reconfiguration in the SCD stage, which may underlie the early cognitive decline in SCD subjects and serve as sensitive neuroimaging biomarkers for the preclinical detection of individuals with incipient Alzheimer's disease.
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Affiliation(s)
- Qian Chen
- Department of Radiology, Drum Tower Hospital, Clinical College of Nanjing Medical University, Nanjing, China
| | - Jiaming Lu
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
| | - Xin Zhang
- Department of Radiology, Drum Tower Hospital, Clinical College of Nanjing Medical University, Nanjing, China.,Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
| | - Yi Sun
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
| | - Wenqian Chen
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
| | - Xin Li
- Department of Radiology, Drum Tower Hospital, Clinical College of Nanjing Medical University, Nanjing, China
| | - Wen Zhang
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
| | - Zhao Qing
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.,Institute of Brain Science, Nanjing University, Nanjing, China
| | - Bing Zhang
- Department of Radiology, Drum Tower Hospital, Clinical College of Nanjing Medical University, Nanjing, China.,Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.,Institute of Brain Science, Nanjing University, Nanjing, China
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15
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Orad RI, Shiner T. Differentiating dementia with Lewy bodies from Alzheimer's disease and Parkinson's disease dementia: an update on imaging modalities. J Neurol 2021; 269:639-653. [PMID: 33511432 DOI: 10.1007/s00415-021-10402-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 01/07/2021] [Accepted: 01/08/2021] [Indexed: 12/16/2022]
Abstract
Dementia with Lewy bodies is the second most common cause of neurodegenerative dementia after Alzheimer's disease. Dementia with Lewy bodies can provide a diagnostic challenge due to the frequent overlap of clinical signs with other neurodegenerative conditions, namely Parkinson's disease dementia, and Alzheimer's disease. Part of this clinical overlap is due to the neuropathological overlap. Dementia with Lewy bodies is characterized by the accumulation of aggregated α-synuclein protein in Lewy bodies, similar to Parkinson's disease and Parkinson's disease dementia. However, it is also frequently accompanied by aggregation of amyloid-beta and tau, the pathological hallmarks of Alzheimer's disease. Neuroimaging is central to the diagnostic process. This review is an overview of both established and evolving imaging methods that can improve diagnostic accuracy and improve management of this disorder.
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Affiliation(s)
- Rotem Iris Orad
- Cognitive Neurology Unit, Neurological Institute, Tel Aviv Sourasky Medical Center, 6, Weismann St, Tel Aviv, Israel. .,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.
| | - Tamara Shiner
- Cognitive Neurology Unit, Neurological Institute, Tel Aviv Sourasky Medical Center, 6, Weismann St, Tel Aviv, Israel.,Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel.,Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.,Movement Disorders Unit, Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
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16
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Dudchenko NG, Vasenina EE. [Fluctuation of cognitive functions in dementia with Lewy bodies]. Zh Nevrol Psikhiatr Im S S Korsakova 2020; 120:89-95. [PMID: 33205936 DOI: 10.17116/jnevro202012010289] [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: 11/18/2022]
Abstract
Fluctuations of cognitive function (FCF) is one of the core diagnostic features of dementia with Lewy bodies (DLB). However, identification, pathophysiology, management of this unusual phenomena remain poor understood. The review presents modern ideas about phenomenology, causes, systematization, clinical significance and current methods of diagnosis and treatment of FCF in patients with DLB.
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Affiliation(s)
- N G Dudchenko
- Russian Medical Academy of Continuous Professional Education, Moscow, Russia
| | - E E Vasenina
- Russian Medical Academy of Continuous Professional Education, Moscow, Russia
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17
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Chang YT, Hsu JL, Huang SH, Hsu SW, Lee CC, Chang CC. Functional connectome and neuropsychiatric symptom clusters of Alzheimer's disease. J Affect Disord 2020; 273:48-54. [PMID: 32421622 DOI: 10.1016/j.jad.2020.04.054] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Revised: 03/14/2020] [Accepted: 04/27/2020] [Indexed: 12/22/2022]
Abstract
BACKGROUND Neuropsychiatric symptoms (NPSs) are important aspects of Alzheimer's disease (AD). Investigation of the effect of functional network abnormalities on clustered NPSs may uncover loci of altered connectivity for more targeted pharmacological and behavioral interventions in AD. The study aimed to investigate functional connectivity in AD and the clustered NPSs, as assessed by the Neuropsychiatric Inventory (NPI). METHODS In one hundred and fifty-nine patients with mild dementia stage of AD, graph metrics measuring functional connectivity at global network- and local network-level were assessed by closeness-centrality, betweenness-centrality, average-path-length, local-efficiency, and clustering-coefficient, respectively. The relationship between the NPI composite score and functional connectivity was assessed. RESULTS In AD, an increase in behavioral composite score was associated with changes in functional connectivity at local network-level, and regions displayed the changes was left lingual gyrus, left sub-genual ACC nodes, and left supra-genual ACC nodes (P < 0.05). An increase in affective composite score was associated with changes in functional connectivity at global network-level, and regions displayed the change was right caudate (P = 0.014). An increase in psychotic composite score was associated with changes in functional connectivity at global network-level, and regions displayed the change was left precuneus and right dorsolateral superior frontal gyrus (P < 0.05). LIMITATIONS Cognitively normal elderly subjects and longitudinal follow-up will be needed to see the evolution of NPS clusters and pathological changes in the functional connectivity at global or local network-level. CONCLUSIONS Different NPS clusters corresponded to distinct changes in functional connectivity at global and local network-level.
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Affiliation(s)
- Ya-Ting Chang
- Department of Neurology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan; Department of Psychiatry, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan.
| | - Jung-Lung Hsu
- Department of Neurology, New Taipei Municipal TuCheng Hospital, New Taipei City, Taiwan; Department of Neurology, Chang Gung Memorial Hospital Linkou Medical Center and College of Medicine, Neuroscience Research Center, Chang-Gung University, Linkou, Taoyuan, Taiwan; Taipei Medical University, Graduate Institute of Humanities in Medicine and Research Center for Brain and Consciousness, Shuang Ho Hospital, Taipei, Taiwan
| | - Shu-Hua Huang
- Department of Nuclear Medicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan
| | - Shih-Wei Hsu
- Department of Radiology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan
| | - Chen-Chang Lee
- Department of Nuclear Medicine, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan
| | - Chiung-Chih Chang
- Department of Neurology, Kaohsiung Chang Gung Memorial Hospital, Chang Gung University College of Medicine, Kaohsiung 83301, Taiwan.
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18
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Mheich A, Wendling F, Hassan M. Brain network similarity: methods and applications. Netw Neurosci 2020; 4:507-527. [PMID: 32885113 PMCID: PMC7462433 DOI: 10.1162/netn_a_00133] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2019] [Accepted: 02/26/2020] [Indexed: 12/11/2022] Open
Abstract
Graph theoretical approach has proved an effective tool to understand, characterize, and quantify the complex brain network. However, much less attention has been paid to methods that quantitatively compare two graphs, a crucial issue in the context of brain networks. Comparing brain networks is indeed mandatory in several network neuroscience applications. Here, we discuss the current state of the art, challenges, and a collection of analysis tools that have been developed in recent years to compare brain networks. We first introduce the graph similarity problem in brain network application. We then describe the methodological background of the available metrics and algorithms of comparing graphs, their strengths, and limitations. We also report results obtained in concrete applications from normal brain networks. More precisely, we show the potential use of brain network similarity to build a "network of networks" that may give new insights into the object categorization in the human brain. Additionally, we discuss future directions in terms of network similarity methods and applications.
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Affiliation(s)
- Ahmad Mheich
- Laboratoire Traitement du Signal et de l’Image, Institut National de la Santé et de la Recherche Médicale, Rennes, France
| | - Fabrice Wendling
- Laboratoire Traitement du Signal et de l’Image, Institut National de la Santé et de la Recherche Médicale, Rennes, France
| | - Mahmoud Hassan
- Laboratoire Traitement du Signal et de l’Image, Institut National de la Santé et de la Recherche Médicale, Rennes, France
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19
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Chen H, Sheng X, Luo C, Qin R, Ye Q, Zhao H, Xu Y, Bai F. The compensatory phenomenon of the functional connectome related to pathological biomarkers in individuals with subjective cognitive decline. Transl Neurodegener 2020; 9:21. [PMID: 32460888 PMCID: PMC7254770 DOI: 10.1186/s40035-020-00201-6] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Accepted: 05/20/2020] [Indexed: 01/01/2023] Open
Abstract
Background Subjective cognitive decline (SCD) is a preclinical stage along the Alzheimer’s disease (AD) continuum. However, little is known about the aberrant patterns of connectivity and topological alterations of the brain functional connectome and their diagnostic value in SCD. Methods Resting-state functional magnetic resonance imaging and graph theory analyses were used to investigate the alterations of the functional connectome in 66 SCD individuals and 64 healthy controls (HC). Pearson correlation analysis was computed to assess the relationships among network metrics, neuropsychological performance and pathological biomarkers. Finally, we used the multiple kernel learning-support vector machine (MKL-SVM) to differentiate the SCD and HC individuals. Results SCD individuals showed higher nodal topological properties (including nodal strength, nodal global efficiency and nodal local efficiency) associated with amyloid-β levels and memory function than the HC, and these regions were mainly located in the default mode network (DMN). Moreover, increased local and medium-range connectivity mainly between the bilateral parahippocampal gyrus (PHG) and other DMN-related regions was found in SCD individuals compared with HC individuals. These aberrant functional network measures exhibited good classification performance in the differentiation of SCD individuals from HC individuals at an accuracy up to 79.23%. Conclusion The findings of this study provide insight into the compensatory mechanism of the functional connectome underlying SCD. The proposed classification method highlights the potential of connectome-based metrics for the identification of the preclinical stage of AD.
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Affiliation(s)
- Haifeng Chen
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, 321 Zhongshan Road, Nanjing, Jiangsu, 210008, P. R. China.,Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Xiaoning Sheng
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, 321 Zhongshan Road, Nanjing, Jiangsu, 210008, P. R. China.,Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Caimei Luo
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, 321 Zhongshan Road, Nanjing, Jiangsu, 210008, P. R. China.,Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Ruomeng Qin
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, 321 Zhongshan Road, Nanjing, Jiangsu, 210008, P. R. China.,Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Qing Ye
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, 321 Zhongshan Road, Nanjing, Jiangsu, 210008, P. R. China.,Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Hui Zhao
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, 321 Zhongshan Road, Nanjing, Jiangsu, 210008, P. R. China.,Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Yun Xu
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, 321 Zhongshan Road, Nanjing, Jiangsu, 210008, P. R. China.,Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Feng Bai
- Department of Neurology, Drum Tower Hospital, Medical School and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, 321 Zhongshan Road, Nanjing, Jiangsu, 210008, P. R. China. .,Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, China. .,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China. .,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China.
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20
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O'Dowd S, Schumacher J, Burn DJ, Bonanni L, Onofrj M, Thomas A, Taylor JP. Fluctuating cognition in the Lewy body dementias. Brain 2020; 142:3338-3350. [PMID: 31411317 DOI: 10.1093/brain/awz235] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Revised: 05/28/2019] [Accepted: 06/09/2019] [Indexed: 01/17/2023] Open
Abstract
Fluctuating cognition is a core diagnostic feature of dementia with Lewy bodies and is also a key clinical feature of Parkinson's disease dementia. These dementias share common pathological features and are referred to as Lewy body dementias. Whilst highly prevalent in Lewy body dementia, with up to 90% of patients experiencing the symptom at some point in the disease trajectory, clinical identification of fluctuating cognition is often challenging. Furthermore, its underlying pathophysiological processes remain unclear. However, neuroimaging and neurophysiological techniques have recently provided insight into potential drivers of the phenomenon. In this update, we review data pertaining to clinical features and underlying mechanisms of fluctuating cognition in Lewy body dementia. We collate evidence for different proposed aetiologies: fluctuating cognition as an attentional disorder, as a consequence of loss of cholinergic drive, as a manifestation of failure in neuronal efficiency and synchrony, and as a disorder of sleep/arousal. We also review data relating to putative mechanisms that have received less attention to date. Increased understanding of fluctuating cognition may help to illuminate pathophysiological mechanisms in cognitive processing in Lewy body dementia, guide future research, and facilitate the design of targeted therapeutic approaches.
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Affiliation(s)
- Seán O'Dowd
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK.,Department of Neurology, Tallaght University Hospital, Dublin 24, Ireland; Academic Unit of Neurology, Trinity College Dublin, Ireland
| | - Julia Schumacher
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK
| | - David J Burn
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK
| | - Laura Bonanni
- Department of Neuroscience, Imaging and Clinical Science and Aging Research Centre, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy
| | - Marco Onofrj
- Department of Neuroscience, Imaging and Clinical Science and Aging Research Centre, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy
| | - Alan Thomas
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK
| | - John-Paul Taylor
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK
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21
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Chabran E, Noblet V, Loureiro de Sousa P, Demuynck C, Philippi N, Mutter C, Anthony P, Martin-Hunyadi C, Cretin B, Blanc F. Changes in gray matter volume and functional connectivity in dementia with Lewy bodies compared to Alzheimer's disease and normal aging: implications for fluctuations. Alzheimers Res Ther 2020; 12:9. [PMID: 31907068 PMCID: PMC6945518 DOI: 10.1186/s13195-019-0575-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Accepted: 12/23/2019] [Indexed: 12/02/2022]
Abstract
BACKGROUND Fluctuations are one of the core clinical features characterizing dementia with Lewy bodies (DLB). They represent a determining factor for its diagnosis and strongly impact the quality of life of patients and their caregivers. However, the neural correlates of this complex symptom remain poorly understood. This study aimed to investigate the structural and functional changes in DLB patients, compared to Alzheimer's disease (AD) patients and healthy elderly subjects, and their potential links with fluctuations. METHODS Structural and resting-state functional MRI data were collected from 92 DLB patients, 70 AD patients, and 22 control subjects, who also underwent a detailed clinical examination including the Mayo Clinic Fluctuation Scale. Gray matter volume changes were analyzed using whole-brain voxel-based morphometry, and resting-state functional connectivity was investigated using a seed-based analysis, with regions of interest corresponding to the main nodes of the salience network (SN), frontoparietal network (FPN), dorsal attention network (DAN), and default mode network (DMN). RESULTS At the structural level, fluctuation scores in DLB patients did not relate to the atrophy of insular, temporal, and frontal regions typically found in this pathology, but instead showed a weak correlation with more subtle volume reductions in different regions of the cholinergic system. At the functional level, the DLB group was characterized by a decreased connectivity within the SN and attentional networks, while the AD group showed decreases within the SN and DMN. In addition, higher fluctuation scores in DLB patients were correlated to a greater connectivity of the SN with the DAN and left thalamus, along with a decreased connectivity between the SN and DMN, and between the right thalamus and both the FPN and DMN. CONCLUSIONS Functional connectivity changes, rather than significant gray matter loss, could play an important role in the emergence of fluctuations in DLB. Notably, fluctuations in DLB patients appeared to be related to a disturbed external functional connectivity of the SN, which may lead to less relevant transitions between different cognitive states in response to internal and environmental stimuli. Our results also suggest that the thalamus could be a key region for the occurrence of this symptom.
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Affiliation(s)
- Eléna Chabran
- ICube Laboratory UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), Team IMIS, University of Strasbourg and CNRS, Strasbourg, France
| | - Vincent Noblet
- ICube Laboratory UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), Team IMIS, University of Strasbourg and CNRS, Strasbourg, France
| | - Paulo Loureiro de Sousa
- ICube Laboratory UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), Team IMIS, University of Strasbourg and CNRS, Strasbourg, France
| | - Catherine Demuynck
- CM2R (Research and Resources Memory Centre), Geriatrics Department, University Hospitals of Strasbourg, Geriatric Day Hospital and Neuropsychology Unit, Strasbourg, France
| | - Nathalie Philippi
- ICube Laboratory UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), Team IMIS, University of Strasbourg and CNRS, Strasbourg, France
- CM2R (Research and Resources Memory Centre), Geriatrics Department, University Hospitals of Strasbourg, Geriatric Day Hospital and Neuropsychology Unit, Strasbourg, France
| | - Catherine Mutter
- INSERM Centre d’Investigation Clinique 1434, University Hospitals of Strasbourg, Strasbourg, France
| | - Pierre Anthony
- General Hospital Centre, Geriatrics Department, CM2R, Geriatric Day Hospital, Colmar, France
| | - Catherine Martin-Hunyadi
- CM2R (Research and Resources Memory Centre), Geriatrics Department, University Hospitals of Strasbourg, Geriatric Day Hospital and Neuropsychology Unit, Strasbourg, France
| | - Benjamin Cretin
- ICube Laboratory UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), Team IMIS, University of Strasbourg and CNRS, Strasbourg, France
- CM2R (Research and Resources Memory Centre), Geriatrics Department, University Hospitals of Strasbourg, Geriatric Day Hospital and Neuropsychology Unit, Strasbourg, France
| | - Frédéric Blanc
- ICube Laboratory UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), Team IMIS, University of Strasbourg and CNRS, Strasbourg, France
- CM2R (Research and Resources Memory Centre), Geriatrics Department, University Hospitals of Strasbourg, Geriatric Day Hospital and Neuropsychology Unit, Strasbourg, France
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22
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Campabadal A, Abos A, Segura B, Serradell M, Uribe C, Baggio HC, Gaig C, Santamaria J, Compta Y, Bargallo N, Junque C, Iranzo A. Disruption of posterior brain functional connectivity and its relation to cognitive impairment in idiopathic REM sleep behavior disorder. NEUROIMAGE-CLINICAL 2019; 25:102138. [PMID: 31911344 PMCID: PMC6948254 DOI: 10.1016/j.nicl.2019.102138] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Revised: 12/16/2019] [Accepted: 12/21/2019] [Indexed: 12/12/2022]
Abstract
There is a reduced brain posterior functional connectivity in IRBD patients. Reduced temporo-parietal connectivity correlates with mental processing slowness. Left superior parietal lobule has reduced centrality in IRBD patients.
Background Resting-state functional MRI has been proposed as a new biomarker of prodromal neurodegenerative disorders, but it has been poorly investigated in the idiopathic form of rapid-eye-movement sleep behavior disorder (IRBD), a clinical harbinger of subsequent synucleinopathy. Particularly, a complex-network approach has not been tested to study brain functional connectivity in IRBD patients. Objectives The aim of the current work is to characterize resting-state functional connectivity in IRBD patients using a complex-network approach and to determine its possible relation to cognitive impairment. Method Twenty patients with IRBD and 27 matched healthy controls (HC) underwent resting-state functional MRI with a 3T scanner and a comprehensive neuropsychological battery. The functional connectome was studied using threshold-free network-based statistics. Global and local network parameters were calculated based on graph theory and compared between groups. Head motion, age and sex were introduced as covariates in all analyses. Results IRBD patients showed reduced cortico-cortical functional connectivity strength in comparison with HC in edges located in posterior regions (p <0.05, FWE corrected). This regional pattern was also shown in an independent analysis comprising posterior areas where a decreased connectivity in 51 edges was found, whereas no significant results were detected when an anterior network was considered (p <0.05, FWE corrected). In the posterior network, the left superior parietal lobule had reduced centrality in IRBD. Functional connectivity strength between left inferior temporal lobe and right superior parietal lobule positively correlated with mental processing speed in IRBD (r = .633; p = .003). No significant correlations were found in the HC group. Conclusion : Our findings support the presence of disrupted posterior functional brain connectivity of IRBD patients similar to that found in synucleinopathies. Moreover, connectivity reductions in IRBD were associated with lower performance in mental processing speed domain.
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Affiliation(s)
- A Campabadal
- Medical Psychology Unit, Department of Medicine. Institute of Neuroscience, University of Barcelona. Barcelona, Catalonia, Spain
| | - A Abos
- Medical Psychology Unit, Department of Medicine. Institute of Neuroscience, University of Barcelona. Barcelona, Catalonia, Spain
| | - B Segura
- Medical Psychology Unit, Department of Medicine. Institute of Neuroscience, University of Barcelona. Barcelona, Catalonia, Spain; Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED:CB06/05/0018-ISCIII) Barcelona, Spain; Institute of Biomedical Research August Pi i Sunyer (IDIBAPS). Barcelona, Catalonia, Spain
| | - M Serradell
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED:CB06/05/0018-ISCIII) Barcelona, Spain; Institute of Biomedical Research August Pi i Sunyer (IDIBAPS). Barcelona, Catalonia, Spain.; Multidisciplinary Sleep Unit, Neurology Service, Hospital Clínic, Barcelona, Catalonia, Spain
| | - C Uribe
- Medical Psychology Unit, Department of Medicine. Institute of Neuroscience, University of Barcelona. Barcelona, Catalonia, Spain
| | - H C Baggio
- Medical Psychology Unit, Department of Medicine. Institute of Neuroscience, University of Barcelona. Barcelona, Catalonia, Spain
| | - C Gaig
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED:CB06/05/0018-ISCIII) Barcelona, Spain; Institute of Biomedical Research August Pi i Sunyer (IDIBAPS). Barcelona, Catalonia, Spain.; Multidisciplinary Sleep Unit, Neurology Service, Hospital Clínic, Barcelona, Catalonia, Spain
| | - J Santamaria
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED:CB06/05/0018-ISCIII) Barcelona, Spain; Institute of Biomedical Research August Pi i Sunyer (IDIBAPS). Barcelona, Catalonia, Spain.; Multidisciplinary Sleep Unit, Neurology Service, Hospital Clínic, Barcelona, Catalonia, Spain
| | - Y Compta
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED:CB06/05/0018-ISCIII) Barcelona, Spain; Institute of Biomedical Research August Pi i Sunyer (IDIBAPS). Barcelona, Catalonia, Spain.; Parkinson's disease & Movement Disorders Unit, Neurology Service, Hospital Clínic de Barcelona. Institute of Neuroscience, University of Barcelona, Barcelona, Catalonia, Spain
| | - N Bargallo
- Centre de Diagnòstic per la Imatge, Hospital Clínic, Barcelona, Catalonia, Spain
| | - C Junque
- Medical Psychology Unit, Department of Medicine. Institute of Neuroscience, University of Barcelona. Barcelona, Catalonia, Spain; Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED:CB06/05/0018-ISCIII) Barcelona, Spain; Institute of Biomedical Research August Pi i Sunyer (IDIBAPS). Barcelona, Catalonia, Spain..
| | - A Iranzo
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED:CB06/05/0018-ISCIII) Barcelona, Spain; Institute of Biomedical Research August Pi i Sunyer (IDIBAPS). Barcelona, Catalonia, Spain.; Multidisciplinary Sleep Unit, Neurology Service, Hospital Clínic, Barcelona, Catalonia, Spain
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23
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Mehraram R, Kaiser M, Cromarty R, Graziadio S, O'Brien JT, Killen A, Taylor JP, Peraza LR. Weighted network measures reveal differences between dementia types: An EEG study. Hum Brain Mapp 2019; 41:1573-1590. [PMID: 31816147 PMCID: PMC7267959 DOI: 10.1002/hbm.24896] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Revised: 09/03/2019] [Accepted: 11/29/2019] [Indexed: 11/18/2022] Open
Abstract
The diagnosis of dementia with Lewy bodies (DLB) versus Alzheimer's disease (AD) can be difficult especially early in the disease process. However, one inexpensive and non‐invasive biomarker which could help is electroencephalography (EEG). Previous studies have shown that the brain network architecture assessed by EEG is altered in AD patients compared with age‐matched healthy control people (HC). However, similar studies in Lewy body diseases, that is, DLB and Parkinson's disease dementia (PDD) are still lacking. In this work, we (a) compared brain network connectivity patterns across conditions, AD, DLB and PDD, in order to infer EEG network biomarkers that differentiate between these conditions, and (b) tested whether opting for weighted matrices led to more reliable results by better preserving the topology of the network. Our results indicate that dementia groups present with reduced connectivity in the EEG α band, whereas DLB shows weaker posterior–anterior patterns within the β‐band and greater network segregation within the θ‐band compared with AD. Weighted network measures were more consistent across global thresholding levels, and the network properties reflected reduction in connectivity strength in the dementia groups. In conclusion, β‐ and θ‐band network measures may be suitable as biomarkers for discriminating DLB from AD, whereas the α‐band network is similarly affected in DLB and PDD compared with HC. These variations may reflect the impairment of attentional networks in Parkinsonian diseases such as DLB and PDD.
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Affiliation(s)
- Ramtin Mehraram
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK.,NIHR Newcastle Biomedical Research Centre, Campus for Ageing and Vitality, Newcastle upon Tyne, UK.,Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing, Newcastle University, Newcastle upon Tyne, UK
| | - Marcus Kaiser
- Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing, Newcastle University, Newcastle upon Tyne, UK.,Department of Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ruth Cromarty
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK
| | - Sara Graziadio
- NIHR Newcastle in vitro Diagnostics Co-operative, Newcastle-Upon-Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - John T O'Brien
- Department of Psychiatry, University of Cambridge School of Medicine, Cambridge, UK
| | - Alison Killen
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK
| | - John-Paul Taylor
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK
| | - Luis R Peraza
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, UK.,IXICO Plc, London, UK
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24
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Ma WY, Yao Q, Hu GJ, Xiao CY, Shi JP, Chen J. Dysfunctional Dynamics of Intra- and Inter-network Connectivity in Dementia With Lewy Bodies. Front Neurol 2019; 10:1265. [PMID: 31849824 PMCID: PMC6902076 DOI: 10.3389/fneur.2019.01265] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Accepted: 11/15/2019] [Indexed: 12/28/2022] Open
Abstract
Dementia with Lewy bodies (DLB) is characterized by the transient fluctuating cognition and recurrent visual hallucinations, which may be caused by disorders of the intrinsic brain network dynamics. However, little is known regarding the dynamic features of the brain network behind these symptoms in DLB. In the present study, the intra- and inter-brain network dynamics were explored on a time scale in 17 DLB and 20 healthy controls (HC) applying a sliding-window method followed by k-means clustering analysis. To further evaluate the impact of network dynamics on brain performance, the local and global efficiency of the brain network was calculated. Compared with HC, the dynamic functional connectivity variation matrix in DLB patients was represented by a mixed change of intra-network increase and inter-network decrease. DLB patients devoted more time to a negative connectivity pattern, which represents a state of functional separation. Furthermore, the local efficiency of DLB patients was significantly lower compared with HC. These observations indicate an altered dynamic variability and disorders to the time allocation of state sequences in DLB, which might result in a disturbance of the intricate brain network dynamic properties, thereby leading to a lack of integration and flexibility and an ineffective brain function. In conclusion, dynamic functional connectivity analysis could identify differences between DLB and HC, providing evidences for DLB diagnosis and contributing to the understanding of the widespread clinical features and complex treatment strategies in DLB patients.
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Affiliation(s)
- Wen-Ying Ma
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Qun Yao
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Guan-Jie Hu
- Department of Neurosurgery, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Chao-Yong Xiao
- Department of Radiology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Jing-Ping Shi
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.,Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, China
| | - Jiu Chen
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, China.,Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
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Zhou H, Jiang J, Wu P, Guo Q, Zuo C. Disrupted network topology in patients with Lewy bodies dementia compared to Alzheimer's disease, Parkinson disease dementia and Health Control .. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2019; 2018:1899-1902. [PMID: 30440768 DOI: 10.1109/embc.2018.8512637] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
The clinical manifestation of Lewy body dementia (DLB) is distinct from Alzheimer's disease (AD), but overlap with Parkinson's disease dementia (PDD). However, little is known about different topology properties of abnormal brain networks associated with these neurodegenerative diseases. In order to study the difference of brain networks in various dementia subtypes, we used $^{\mathbf {18}}\text{F}$-Fluorodeoxyglucose positron emission tomography ($^{\mathbf {18}}\text{F}$-FDG PET) images and graph theory methods to investigate altered whole-brain intrinsic glucose metabolic functional networks in three Chinese dementia groups compared to healthy control (HC) group, including 22 AD patients, 18 PDD patients, 22 DLB patients and 22 HC subjects from Huashan Hospital, Shanghai, China. The experimental results disclosed that in the three dementia groups, compared to HC group, the small-world characteristics were lost. Additionally, compared with HC group, the clustering coefficients of three dementia groups were higher; the characteristic path lengths were longer. In terms of local efficiency and global efficiency, it was at the lowest level in DLB group. We also found differences about distributions of hub regions amongst the four groups. This finding could further help physicians to understand pathological mechanisms of different dementia.
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26
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Wang B, Miao L, Niu Y, Cao R, Li D, Yan P, Guo H, Yan T, Wu J, Xiang J. Abnormal Functional Brain Networks in Mild Cognitive Impairment and Alzheimer's Disease: A Minimum Spanning Tree Analysis. J Alzheimers Dis 2019; 65:1093-1107. [PMID: 30149457 DOI: 10.3233/jad-180603] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Alzheimer's disease (AD) disrupts the topological architecture of whole-brain connectivity. Minimum spanning tree (MST), which captures the most important connections in a network, has been considered an unbiased method for brain network analysis. However, the alterations in the MST of functional brain networks during the progression of AD remain unclear. Here, we performed an MST analysis to examine the alterations in functional networks among normal controls (NCs), mild cognitive impairment (MCI) patients, and AD patients. We identified substantial differences in the connections among the three groups. The maximum betweenness centrality, leaf number, and tree hierarchy of the MSTs showed significant group differences, indicating a more star-like topology in the MCI patients and a more line-like topology in the NCs and AD patients. These findings may correspond to changes in the core of the functional brain networks. For nodal properties (degree and betweenness centrality), we determined that brain regions around the cingulate gyrus, occipital lobes, subcortex, and inferior temporal gyrus showed significant differences among the three groups and contributed to the global topological alterations. The leaf number and tree hierarchy, as well as the nodal properties, were significantly correlated with clinical features in the MCI and AD patients, which demonstrated that more star-to-line topology changes were associated with worse cognitive performance in these patients. These findings indicated that MST properties could capture slight alterations in network topology, particularly for the differences between NCs and MCI patients, and may be applicable as neuroimaging markers of the early stage of AD.
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27
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Sala A, Caminiti SP, Iaccarino L, Beretta L, Iannaccone S, Magnani G, Padovani A, Ferini-Strambi L, Perani D. Vulnerability of multiple large-scale brain networks in dementia with Lewy bodies. Hum Brain Mapp 2019; 40:4537-4550. [PMID: 31322307 DOI: 10.1002/hbm.24719] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2019] [Revised: 06/01/2019] [Accepted: 06/19/2019] [Indexed: 01/08/2023] Open
Abstract
Aberrations of large-scale brain networks are found in the majority of neurodegenerative disorders. The brain connectivity alterations underlying dementia with Lewy bodies (DLB) remain, however, still elusive, with contrasting results possibly due to the pathological and clinical heterogeneity characterizing this disorder. Here, we provide a molecular assessment of brain network alterations, based on cerebral metabolic measurements as proxies of synaptic activity and density, in a large cohort of DLB patients (N = 72). We applied a seed-based interregional correlation analysis approach (p < .01, false discovery rate corrected) to evaluate large-scale resting-state networks' integrity and their interactions. We found both local and long-distance metabolic connectivity alterations, affecting the posterior cortical networks, that is, primary visual and the posterior default mode network, as well as the limbic and attention networks, suggesting a widespread derangement of the brain connectome. Notably, patients with the lowest visual and attention cognitive scores showed the most severe connectivity derangement in regions of the primary visual network. In addition, network-level alterations were differentially associated with the core clinical manifestations, namely, hallucinations with more severe metabolic dysfunction of the attention and visual networks, and rapid eye movement sleep behavior disorder with alterations of connectivity of attention and subcortical networks. These multiple network-level vulnerabilities may modulate the core clinical and cognitive features of DLB and suggest that DLB should be considered as a complex multinetwork disorder.
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Affiliation(s)
- Arianna Sala
- Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Silvia Paola Caminiti
- Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Leonardo Iaccarino
- Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Luca Beretta
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Sandro Iannaccone
- Clinical Neuroscience Department, San Raffaele Turro Hospital, Milan, Italy
| | - Giuseppe Magnani
- Department of Neurology, IRCCS San Raffaele Hospital, Milan, Italy
| | - Alessandro Padovani
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Luigi Ferini-Strambi
- Vita-Salute San Raffaele University, Milan, Italy.,Department of Clinical Neurosciences, San Raffaele Scientific Institute, Neurology, Sleep Disorders Center, Milan, Italy
| | - Daniela Perani
- Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Nuclear Medicine Unit, IRCCS San Raffaele Hospital, Milan, Italy
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28
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Chen D, Jiang J, Lu J, Wu P, Zhang H, Zuo C, Shi K. Brain Network and Abnormal Hemispheric Asymmetry Analyses to Explore the Marginal Differences in Glucose Metabolic Distributions Among Alzheimer's Disease, Parkinson's Disease Dementia, and Lewy Body Dementia. Front Neurol 2019; 10:369. [PMID: 31031697 PMCID: PMC6473028 DOI: 10.3389/fneur.2019.00369] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2018] [Accepted: 03/25/2019] [Indexed: 12/17/2022] Open
Abstract
Facilitating accurate diagnosis and ensuring appropriate treatment of dementia subtypes, including Alzheimer's disease (AD), Parkinson's disease dementia (PDD), and Lewy body dementia (DLB), is clinically important. However, the differences in glucose metabolic distribution among these three dementia subtypes are minor, which can result in difficulties in diagnosis by visual assessment or traditional quantification methods. Here, we explored this issue using novel approaches, including brain network and abnormal hemispheric asymmetry analyses. We generated 18F-labeled fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) images from patients with AD, PDD, and DLB, and healthy control (HC) subjects (n = 22, 18, 22, and 22, respectively) from Huashan hospital, Shanghai, China. Brain network properties were measured and between-group differences evaluated using graph theory. We also calculated and explored asymmetry indices for the cerebral hemispheres in the four groups, to explore whether differences between the two hemispheres were characteristic of each group. Our study revealed significant differences in the network properties of the HC and AD groups (small-world coefficient, 1.36 vs. 1.28; clustering coefficient, 1.48 vs. 1.59; characteristic path length, 1.57 vs. 1.64). In addition, differing hub regions were identified in the different dementias. We also identified rightward asymmetry in the hemispheric brain networks of patients with AD and DLB, and leftward asymmetry in the hemispheric brain networks of patients with PDD, which were attributable to aberrant topological properties in the corresponding hemispheres.
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Affiliation(s)
- Danyan Chen
- Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China
| | - Jiehui Jiang
- Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China.,Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication, Shanghai University, Shanghai, China
| | - Jiaying Lu
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Ping Wu
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Huiwei Zhang
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Chuantao Zuo
- PET Center, Huashan Hospital, Fudan University, Shanghai, China.,Institute of Functional and Molecular Medical Imaging, Fudan University, Shanghai, China
| | - Kuangyu Shi
- Department Nuclear Medicine, University of Bern, Bern, Switzerland.,Department of Informatics, Technical University of Munich, Munich, Germany
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29
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van Montfort SJT, van Dellen E, Stam CJ, Ahmad AH, Mentink LJ, Kraan CW, Zalesky A, Slooter AJC. Brain network disintegration as a final common pathway for delirium: a systematic review and qualitative meta-analysis. NEUROIMAGE-CLINICAL 2019; 23:101809. [PMID: 30981940 PMCID: PMC6461601 DOI: 10.1016/j.nicl.2019.101809] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 03/25/2019] [Accepted: 03/31/2019] [Indexed: 01/05/2023]
Abstract
Delirium is an acute neuropsychiatric syndrome characterized by altered levels of attention and awareness with cognitive deficits. It is most prevalent in elderly hospitalized patients and related to poor outcomes. Predisposing risk factors, such as older age, determine the baseline vulnerability for delirium, while precipitating factors, such as use of sedatives, trigger the syndrome. Risk factors are heterogeneous and the underlying biological mechanisms leading to vulnerability for delirium are poorly understood. We tested the hypothesis that delirium and its risk factors are associated with consistent brain network changes. We performed a systematic review and qualitative meta-analysis and included 126 brain network publications on delirium and its risk factors. Findings were evaluated after an assessment of methodological quality, providing N=99 studies of good or excellent quality on predisposing risk factors, N=10 on precipitation risk factors and N=7 on delirium. Delirium was consistently associated with functional network disruptions, including lower EEG connectivity strength and decreased fMRI network integration. Risk factors for delirium were associated with lower structural connectivity strength and less efficient structural network organization. Decreased connectivity strength and efficiency appear to characterize structural brain networks of patients at risk for delirium, possibly impairing the functional network, while functional network disintegration seems to be a final common pathway for the syndrome. Delirium is consistently associated with functional network impairments. Risk factors are associated with lower structural connectivity strength. Risk factors are associated with a less efficient structural network organization. Structural impairments make the functional network more vulnerable to deterioration. Functional network disintegration seems to be a final common pathway for delirium.
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Affiliation(s)
- S J T van Montfort
- Department of Intensive Care Medicine and Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands.
| | - E van Dellen
- Department of Psychiatry and Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands; Melbourne Neuropsychiatry Center, Department of Psychiatry, Level 3, Alan Gilbert Building, 161 Barry Street, Carlton South, 3053 Victoria, University of Melbourne and Melbourne Health, Australia
| | - C J Stam
- Department of Clinical Neurophysiology and MEG Center, Neuroscience Campus Amsterdam, VU University Medical Center, De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands
| | - A H Ahmad
- Department of Intensive Care Medicine and Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands; Faculty of Psychology, Utrecht University, Heidelberglaan 1, 3584 CS Utrecht, The Netherlands
| | - L J Mentink
- Department of Intensive Care Medicine and Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands; Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
| | - C W Kraan
- Department of Intensive Care Medicine and Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands; Faculty of Science and Technology, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands
| | - A Zalesky
- Melbourne Neuropsychiatry Center, Department of Psychiatry, Level 3, Alan Gilbert Building, 161 Barry Street, Carlton South, 3053 Victoria, University of Melbourne and Melbourne Health, Australia
| | - A J C Slooter
- Department of Intensive Care Medicine and Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht University, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
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30
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Network imaging biomarkers: insights and clinical applications in Parkinson's disease. Lancet Neurol 2019; 17:629-640. [PMID: 29914708 DOI: 10.1016/s1474-4422(18)30169-8] [Citation(s) in RCA: 114] [Impact Index Per Article: 22.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Revised: 04/13/2018] [Accepted: 04/25/2018] [Indexed: 12/14/2022]
Abstract
Parkinson's disease presents several practical challenges: it can be difficult to distinguish from atypical parkinsonian syndromes, clinical ratings can be insensitive as markers of disease progression, and its non-motor manifestations are not readily assessed in animal models. These challenges, along with others, are beginning to be addressed by innovative imaging methods to characterise Parkinson's disease-specific functional networks across the whole brain and measure their expression in each patient. These signatures can help improve differential diagnosis, guide selection of patients for clinical trials, and quantify treatment responses and placebo effects in individual patients. The primary Parkinson's disease-related metabolic pattern has been replicated in multiple patient populations and used as an outcome measure in clinical trials. It can also be used as a predictor of near-term phenoconversion in prodromal syndromes, such as rapid eye movement sleep behaviour disorder. Functional network imaging holds great promise for future clinical use in the management of neurodegenerative disorders.
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31
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Schumacher J, Peraza LR, Firbank M, Thomas AJ, Kaiser M, Gallagher P, O'Brien JT, Blamire AM, Taylor JP. Dynamic functional connectivity changes in dementia with Lewy bodies and Alzheimer's disease. Neuroimage Clin 2019; 22:101812. [PMID: 30991620 PMCID: PMC6462776 DOI: 10.1016/j.nicl.2019.101812] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Revised: 03/12/2019] [Accepted: 04/02/2019] [Indexed: 01/22/2023]
Abstract
We studied the dynamic functional connectivity profile of dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) compared to controls, how it differs between the two dementia subtypes, and a possible relation between dynamic connectivity alterations and temporally transient clinical symptoms in DLB. Resting state fMRI data from 31 DLB, 29 AD, and 31 healthy control participants were analyzed using dual regression to determine between-network functional connectivity. Subsequently, we used a sliding window approach followed by k-means clustering and dynamic network analyses to study dynamic functional connectivity. Dynamic connectivity measures that showed significant group differences were tested for correlations with clinical symptom severity. Our results show that AD and DLB patients spent more time than controls in sparse connectivity configurations with absence of strong positive and negative connections and a relative isolation of motor networks from other networks. Additionally, DLB patients spent less time in a more strongly connected state and the variability of global brain network efficiency was reduced in DLB compared to controls. There were no significant correlations between dynamic connectivity measures and clinical symptom severity. An inability to switch out of states of low inter-network connectivity into more highly and specifically connected network configurations might be related to the presence of dementia in general as it was observed in both AD and DLB. In contrast, the loss of global efficiency variability in DLB might indicate the presence of an abnormally rigid brain network and the lack of economical dynamics, factors which could contribute to cognitive slowing and an inability to respond appropriately to situational demands.
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Affiliation(s)
- Julia Schumacher
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne NE4 5PL, United Kingdom.
| | - Luis R Peraza
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne NE4 5PL, United Kingdom; Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, United Kingdom
| | - Michael Firbank
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne NE4 5PL, United Kingdom
| | - Alan J Thomas
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne NE4 5PL, United Kingdom
| | - Marcus Kaiser
- Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing, Newcastle University, Newcastle upon Tyne NE4 5TG, United Kingdom; Institute of Neuroscience, Newcastle University, The Henry Wellcome Building, Newcastle upon Tyne NE2 4HH, United Kingdom
| | - Peter Gallagher
- Institute of Neuroscience, Newcastle University, The Henry Wellcome Building, Newcastle upon Tyne NE2 4HH, United Kingdom
| | - John T O'Brien
- Department of Psychiatry, University of Cambridge School of Medicine, Cambridge CB2 0SP, United Kingdom
| | - Andrew M Blamire
- Institute of Cellular Medicine & Newcastle Magnetic Resonance Centre, Campus for Ageing and Vitality, Newcastle upon Tyne NE4 5PL, United Kingdom
| | - John-Paul Taylor
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne NE4 5PL, United Kingdom
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Babiloni C, Del Percio C, Lizio R, Noce G, Lopez S, Soricelli A, Ferri R, Pascarelli MT, Catania V, Nobili F, Arnaldi D, Famà F, Aarsland D, Orzi F, Buttinelli C, Giubilei F, Onofrj M, Stocchi F, Vacca L, Stirpe P, Fuhr P, Gschwandtner U, Ransmayr G, Garn H, Fraioli L, Pievani M, Frisoni GB, D'Antonio F, De Lena C, Güntekin B, Hanoğlu L, Başar E, Yener G, Emek-Savaş DD, Triggiani AI, Franciotti R, Taylor JP, De Pandis MF, Bonanni L. Abnormalities of Resting State Cortical EEG Rhythms in Subjects with Mild Cognitive Impairment Due to Alzheimer's and Lewy Body Diseases. J Alzheimers Dis 2019; 62:247-268. [PMID: 29439335 DOI: 10.3233/jad-170703] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The present study tested the hypothesis that cortical sources of resting state eyes-closed electroencephalographic (rsEEG) rhythms reveal different abnormalities in cortical neural synchronization in groups of patients with mild cognitive impairment due to Alzheimer's disease (ADMCI) and dementia with Lewy bodies (DLBMCI) as compared to cognitively normal elderly (Nold) subjects. Clinical and rsEEG data in 30 ADMCI, 23 DLBMCI, and 30 Nold subjects were available in an international archive. Age, gender, and education were carefully matched in the three groups. The Mini-Mental State Evaluation (MMSE) score was matched between the ADMCI and DLBMCI groups. Individual alpha frequency peak (IAF) was used to determine the delta, theta, alpha1, alpha2, and alpha3 frequency band ranges. Fixed beta1, beta2, and gamma bands were also considered. eLORETA estimated the rsEEG cortical sources. Receiver operating characteristic curve (ROCC) classified these sources across individuals. Compared to Nold, IAF showed marked slowing in DLBMCI and moderate in ADMCI. Furthermore, the posterior alpha 2 and alpha 3 source activities were more abnormal in the ADMCI than the DLBMCI group, while widespread delta source activities were more abnormal in the DLBMCI than the ADMCI group. The posterior delta and alpha sources correlated with the MMSE score and correctly classified the Nold and MCI individuals (area under the ROCC >0.85). In conclusion, the ADMCI and DLBMCI patients showed different features of cortical neural synchronization at delta and alpha frequencies underpinning brain arousal and vigilance in the quiet wakefulness. Future prospective cross-validation studies will have to test the clinical validity of these rsEEG markers.
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Affiliation(s)
- Claudio Babiloni
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy.,Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | | | - Roberta Lizio
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy.,Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Giuseppe Noce
- Department of Integrated Imaging, IRCCS SDN, Naples, Italy
| | - Susanna Lopez
- Department of Physiology and Pharmacology "Vittorio Erspamer", University of Rome "La Sapienza", Rome, Italy
| | - Andrea Soricelli
- Department of Integrated Imaging, IRCCS SDN, Naples, Italy.,Department of Motor Sciences and Healthiness, University of Naples Parthenope, Naples, Italy
| | - Raffaele Ferri
- Department of Neurology, IRCCS Oasi Institute for Research on Mental Retardation and Brain Aging, Troina, Enna, Italy
| | - Maria Teresa Pascarelli
- Department of Neurology, IRCCS Oasi Institute for Research on Mental Retardation and Brain Aging, Troina, Enna, Italy
| | - Valentina Catania
- Department of Neurology, IRCCS Oasi Institute for Research on Mental Retardation and Brain Aging, Troina, Enna, Italy
| | - Flavio Nobili
- Department of Neuroscience (DiNOGMI), Clinical Neurology, University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Dario Arnaldi
- Department of Neuroscience (DiNOGMI), Clinical Neurology, University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Francesco Famà
- Department of Neuroscience (DiNOGMI), Clinical Neurology, University of Genoa and IRCCS AOU S Martino-IST, Genoa, Italy
| | - Dag Aarsland
- Department of Old Age Psychiatry, King's College University, London, UK
| | - Francesco Orzi
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Carla Buttinelli
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Franco Giubilei
- Department of Neuroscience, Mental Health and Sensory Organs, University of Rome "La Sapienza", Rome, Italy
| | - Marco Onofrj
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
| | - Fabrizio Stocchi
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Laura Vacca
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Paola Stirpe
- Institute for Research and Medical Care, IRCCS San Raffaele Pisana, Rome, Italy
| | - Peter Fuhr
- Universitätsspital Basel, Abteilung Neurophysiologie, Basel, Switzerland
| | - Ute Gschwandtner
- Universitätsspital Basel, Abteilung Neurophysiologie, Basel, Switzerland
| | - Gerhard Ransmayr
- Department of Neurology 2, Med Campus III, Kepler University Hospital, Medical Faculty of the Johannes Kepler University, Linz, Austria
| | - Heinrich Garn
- AIT Austrian Institute of Technology GmbH, Vienna, Austria
| | | | - Michela Pievani
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Giovanni B Frisoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Fabrizia D'Antonio
- Department of Neurology and Psychiatry, Sapienza, University of Rome, Italy
| | - Carlo De Lena
- Department of Neurology and Psychiatry, Sapienza, University of Rome, Italy
| | - Bahar Güntekin
- Department of Biophysics, Istanbul Medipol University, Istanbul, Turkey
| | - Lutfu Hanoğlu
- Department of Neurology, University of Istanbul-Medipol, Istanbul, Turkey
| | - Erol Başar
- IBG, Departments of Neurology and Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | - Görsev Yener
- IBG, Departments of Neurology and Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | - Derya Durusu Emek-Savaş
- Department of Psychology and Department of Neurosciences, Dokuz Eylül University, Izmir, Turkey
| | | | - Raffaella Franciotti
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
| | | | | | - Laura Bonanni
- Department of Neuroscience Imaging and Clinical Sciences and CESI, University G d'Annunzio of Chieti-Pescara, Chieti, Italy
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33
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Wada A, Tsuruta K, Irie R, Kamagata K, Maekawa T, Fujita S, Koshino S, Kumamaru K, Suzuki M, Nakanishi A, Hori M, Aoki S. Differentiating Alzheimer's Disease from Dementia with Lewy Bodies Using a Deep Learning Technique Based on Structural Brain Connectivity. Magn Reson Med Sci 2018; 18:219-224. [PMID: 30504639 PMCID: PMC6630050 DOI: 10.2463/mrms.mp.2018-0091] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
PURPOSE Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) are representative disorders of dementia of the elderly and the neuroimaging has contributed to early diagnosis by estimation of alterations of brain volume, blood flow and metabolism. A brain network analysis by MR imaging (MR connectome) is a recently developed technique and can estimate the dysfunction of the brain network in AD and DLB. A graph theory which is a major technique of network analysis is useful for a group study to extract the feature of disorders, but is not necessarily suitable for the disorder differentiation at the individual level. In this investigation, we propose a deep learning technique as an alternative method of the graph analysis for recognition and classification of AD and DLB at the individual subject level. MATERIALS AND METHODS Forty-eight brain structural connectivity data of 18 AD, 8 DLB and 22 healthy controls were applied to the machine learning consisting of a six-layer convolution neural network (CNN) model. Estimation of the deep learning model to classify AD, DLB and non-AD/DLB was performed using the 4-fold cross-validation method. RESULTS The accuracy, average precision and recall of our CNN model were 0.73, 0.78 and 0.73, and the specificity precision and recall were 0.68 and 0.79 in AD, 0.94 and 0.65 in DLB and 0.73 and 0.75 in non-AD/DLB. The triangular probability map of the MR connectome revealed the probability of AD, DLB and non-AD/DLB in each subject. CONCLUSION Our preliminary investigation revealed the adaptation of deep learning to the MR connectome and proposed its utility in the differentiation of dementia disorders at the individual subject level.
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34
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Balážová Z, Nováková M, Minsterová A, Rektorová I. Structural and Functional Magnetic Resonance Imaging of Dementia With Lewy Bodies. INTERNATIONAL REVIEW OF NEUROBIOLOGY 2018; 144:95-141. [PMID: 30638458 DOI: 10.1016/bs.irn.2018.10.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Dementia with Lewy bodies (DLB) is the second most common cause of neurodegenerative dementia after Alzheimer's disease (AD). Although diagnosis may be challenging, there is increasing evidence that the use of biomarkers according to 2017 revised criteria for diagnosis and management of dementia with Lewy bodies can increase diagnostic accuracy. Apart from nuclear medicine techniques, various magnetic resonance imaging (MRI) techniques have been utilized in attempt to enhance diagnostic accuracy. This chapter reviews structural, functional and diffusion MRI studies in DLB cohorts being compared to healthy controls, AD or dementia in Parkinson's disease (PDD). We also included relatively new MRI methods that may have potential to identify early DLB subjects and aim at examining brain iron and neuromelanin.
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Affiliation(s)
- Zuzana Balážová
- Applied Neuroscience Research Group, Central European Institute of Technology, CEITEC MU, Masaryk University, Brno, Czech Republic; Department of Radiology and Nuclear Medicine, University Hospital Brno, Faculty of Medicine, Brno, Czech Republic
| | - Marie Nováková
- Applied Neuroscience Research Group, Central European Institute of Technology, CEITEC MU, Masaryk University, Brno, Czech Republic
| | - Alžběta Minsterová
- Applied Neuroscience Research Group, Central European Institute of Technology, CEITEC MU, Masaryk University, Brno, Czech Republic
| | - Irena Rektorová
- Applied Neuroscience Research Group, Central European Institute of Technology, CEITEC MU, Masaryk University, Brno, Czech Republic; St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic.
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Chen D, Jiang J, Wu P, Guo Q, Zuo C. Module differences of glucose metabolic brain network among Alzheimer's disease, Parkinson's disease dementia, Lewy body dementia and health control. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2018; 2018:2036-2039. [PMID: 30440801 DOI: 10.1109/embc.2018.8512655] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Dementia has become a serious disease in elderly population. Graph theory based brain network analysis method is considered as a popular and universal technique in the field of the neurosciences. It can help neuroscientists to investigate the neuropathology of dementia, especially to understand dementia subtypes. However, brain network analysis for various dementia subtypes at the same time is still limited. The aim at this study is to investigate the similarities and differences in brain network modular parameters of three dementia subtypes: Alzheimer's disease (AD), Parkinson's disease dementia (PDD), Lewy body dementia (DLB). Health control has also been compared. All subjects of health control(HC), AD, PDD and DLB groups were from Huashan Hospital. Using topological analysis algorithms, we found that HC brain was divided into 4 modules; AD brain was divided into 4 modules; PDD brain was divided into 6 modules; and DLB brain was divided into 10 modules, which demonstrated differences in these dementia subtypes. We also found that right thalamus area was scattered in all dementia subtypes. After using the seed point correlation analysis, it can be seen that the connections between right thalamus and subcortical, frontal gyrus were enhanced and the connections with the occipital gyrus was attenuated in dementia subtypes. As a result, findings in this paper are expected to be useful for neuroscientists to further understand the pathology of AD, PDD and DLB.
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Glucose Metabolic Brain Network Differences between Chinese Patients with Lewy Body Dementia and Healthy Control. Behav Neurol 2018; 2018:8420658. [PMID: 29854020 PMCID: PMC5964431 DOI: 10.1155/2018/8420658] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Accepted: 03/25/2018] [Indexed: 11/21/2022] Open
Abstract
Dementia with Lewy bodies (DLB) is the second most common degenerative dementia of the central nervous system. The technique 18F-fluorodeoxyglucose positron emission tomography (18F FDG PET) was used to investigate brain metabolism patterns in DLB patients. Conventional statistical methods did not consider intern metabolism transforming connections between various brain regions; therefore, most physicians do not understand the underlying neuropathology of DLB patients. In this study, 18F FDG-PET images and graph-theoretical methods were used to investigate alterations in whole-brain intrinsic functional connectivity in a Chinese DLB group and healthy control (HC) group. This experimental study was performed on 22 DLB patients and 22 HC subjects in Huashan Hospital, Shanghai, China. Experimental results indicate that compared with the HC group, the DLB group has severely impaired small-world network. Compared to those of the HC group, the clustering coefficients of the DLB group were higher and characteristic path lengths were longer, and in terms of global efficiencies, those of the DLB group was also lower. Moreover, four significantly altered regions were observed in the DLB group: Inferior frontal gyrus, opercular part (IFG.R), olfactory cortex (OLF.R), hippocampus (HIP.R), and fusiform gyrus (FFG.L). Amongst them, in the DLB group, betweenness centrality became strong in OLF.R, HIP.R, and FFG.L, whereas betweenness centrality became weaker in IFG.R. Finally, IFGoperc.R was selected as a seed and a voxel-wise correlation analysis was performed. Compared to the HC group, the DLB group showed several regions of strengthened connection with IFGoperc.R; these regions were located in the prefrontal cortex and regions of weakened connection were located in the occipital cortex. The results of this paper may help physicians to better understand and characterize DLB patients.
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Erskine D, Ding J, Thomas AJ, Kaganovich A, Khundakar AA, Hanson PS, Taylor JP, McKeith IG, Attems J, Cookson MR, Morris CM. Molecular changes in the absence of severe pathology in the pulvinar in dementia with Lewy bodies. Mov Disord 2018; 33:982-991. [PMID: 29570843 DOI: 10.1002/mds.27333] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Revised: 01/20/2018] [Accepted: 01/22/2018] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Dementia with Lewy bodies is characterized by transient clinical features, including fluctuating cognition and visual hallucinations, implicating dysfunction of cerebral hub regions, such as the pulvinar nuclei of the thalamus. However, the pulvinar is typically only mildly affected by Lewy body pathology in dementia with Lewy bodies, suggesting additional factors may account for its proposed dysfunction. METHODS We conducted a comprehensive analysis of postmortem pulvinar tissue using whole-transcriptome RNA sequencing, protein expression analysis, and histological evaluation. RESULTS We identified 321 transcripts as significantly different between dementia with Lewy bodies cases and neurologically normal controls, with gene ontology pathway analysis suggesting the enrichment of transcripts related to synapses and positive regulation of immune functioning. At the protein level, proteins related to synaptic efficiency were decreased, and general synaptic markers remained intact. Analysis of glial subpopulations revealed astrogliosis without activated microglia, which was associated with synaptic changes but not neurodegenerative pathology. DISCUSSION These results indicate that the pulvinar, a region with relatively low Lewy body pathological burden, manifests changes at the molecular level that differ from previous reports in a more severely affected region. We speculate that these alterations result from neurodegenerative changes in regions connected to the pulvinar and likely contribute to a variety of cognitive changes resulting from decreased cortical synchrony in dementia with Lewy bodies. © 2018 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Daniel Erskine
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK
| | - Jinhui Ding
- Laboratory of Neurogenetics, National Institutes of Health, Bethesda, Maryland, USA
| | - Alan J Thomas
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK
| | - Alice Kaganovich
- Laboratory of Neurogenetics, National Institutes of Health, Bethesda, Maryland, USA
| | - Ahmad A Khundakar
- School of Science, Engineering and Design, Teesside University, Middlesbrough, UK
| | - Peter S Hanson
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK
| | - John-Paul Taylor
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK
| | - Ian G McKeith
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK
| | - Johannes Attems
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK
| | - Mark R Cookson
- Laboratory of Neurogenetics, National Institutes of Health, Bethesda, Maryland, USA
| | - Christopher M Morris
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK.,Laboratory of Neurogenetics, National Institutes of Health, Bethesda, Maryland, USA
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Hohenfeld C, Werner CJ, Reetz K. Resting-state connectivity in neurodegenerative disorders: Is there potential for an imaging biomarker? Neuroimage Clin 2018; 18:849-870. [PMID: 29876270 PMCID: PMC5988031 DOI: 10.1016/j.nicl.2018.03.013] [Citation(s) in RCA: 145] [Impact Index Per Article: 24.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 02/06/2018] [Accepted: 03/14/2018] [Indexed: 12/14/2022]
Abstract
Biomarkers in whichever modality are tremendously important in diagnosing of disease, tracking disease progression and clinical trials. This applies in particular for disorders with a long disease course including pre-symptomatic stages, in which only subtle signs of clinical progression can be observed. Magnetic resonance imaging (MRI) biomarkers hold particular promise due to their relative ease of use, cost-effectiveness and non-invasivity. Studies measuring resting-state functional MR connectivity have become increasingly common during recent years and are well established in neuroscience and related fields. Its increasing application does of course also include clinical settings and therein neurodegenerative diseases. In the present review, we critically summarise the state of the literature on resting-state functional connectivity as measured with functional MRI in neurodegenerative disorders. In addition to an overview of the results, we briefly outline the methods applied to the concept of resting-state functional connectivity. While there are many different neurodegenerative disorders cumulatively affecting a substantial number of patients, for most of them studies on resting-state fMRI are lacking. Plentiful amounts of papers are available for Alzheimer's disease (AD) and Parkinson's disease (PD), but only few works being available for the less common neurodegenerative diseases. This allows some conclusions on the potential of resting-state fMRI acting as a biomarker for the aforementioned two diseases, but only tentative statements for the others. For AD, the literature contains a relatively strong consensus regarding an impairment of the connectivity of the default mode network compared to healthy individuals. However, for AD there is no considerable documentation on how that alteration develops longitudinally with the progression of the disease. For PD, the available research points towards alterations of connectivity mainly in limbic and motor related regions and networks, but drawing conclusions for PD has to be done with caution due to a relative heterogeneity of the disease. For rare neurodegenerative diseases, no clear conclusions can be drawn due to the few published results. Nevertheless, summarising available data points towards characteristic connectivity alterations in Huntington's disease, frontotemporal dementia, dementia with Lewy bodies, multiple systems atrophy and the spinocerebellar ataxias. Overall at this point in time, the data on AD are most promising towards the eventual use of resting-state fMRI as an imaging biomarker, although there remain issues such as reproducibility of results and a lack of data demonstrating longitudinal changes. Improved methods providing more precise classifications as well as resting-state network changes that are sensitive to disease progression or therapeutic intervention are highly desirable, before routine clinical use could eventually become a reality.
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Affiliation(s)
- Christian Hohenfeld
- RWTH Aachen University, Department of Neurology, Aachen, Germany; JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich GmbH and RWTH Aachen University, Aachen, Germany
| | - Cornelius J Werner
- RWTH Aachen University, Department of Neurology, Aachen, Germany; RWTH Aachen University, Section Interdisciplinary Geriatrics, Aachen, Germany
| | - Kathrin Reetz
- RWTH Aachen University, Department of Neurology, Aachen, Germany; JARA-BRAIN Institute Molecular Neuroscience and Neuroimaging, Forschungszentrum Jülich GmbH and RWTH Aachen University, Aachen, Germany.
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Schumacher J, Peraza LR, Firbank M, Thomas AJ, Kaiser M, Gallagher P, O'Brien JT, Blamire AM, Taylor J. Functional connectivity in dementia with Lewy bodies: A within- and between-network analysis. Hum Brain Mapp 2018; 39:1118-1129. [PMID: 29193464 PMCID: PMC5900719 DOI: 10.1002/hbm.23901] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2017] [Revised: 10/28/2017] [Accepted: 11/20/2017] [Indexed: 01/07/2023] Open
Abstract
Dementia with Lewy bodies (DLB) is a common form of dementia and is characterized by cognitive fluctuations, visual hallucinations, and Parkinsonism. The phenotypic expression of the disease may, in part, relate to alterations in functional connectivity within and between brain networks. This resting-state study sought to clarify this in DLB, how networks differed from Alzheimer's disease (AD), and whether they were related to clinical symptoms in DLB. Resting-state networks were estimated using independent component analysis. We investigated functional connectivity changes in 31 DLB patients compared to 31 healthy controls and a disease comparator group of 29 AD patients using dual regression and FSLNets. Within-network connectivity was generally decreased in DLB compared to controls, mainly in motor, temporal, and frontal networks. Between-network connectivity was mainly intact; only the connection between a frontal and a temporal network showed increased connectivity in DLB. Differences between AD and DLB were subtle and we did not find any significant correlations with the severity of clinical symptoms in DLB. This study emphasizes the importance of reduced connectivity within motor, frontal, and temporal networks in DLB with relative sparing of the default mode network. The lack of significant correlations between connectivity measures and clinical scores indicates that the observed reduced connectivity within these networks might be related to the presence, but not to the severity of motor and cognitive impairment in DLB patients. Furthermore, our results suggest that AD and DLB may show more similarities than differences in patients with mild disease.
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Affiliation(s)
- Julia Schumacher
- Institute of Neuroscience, Newcastle University, Campus for Ageing and VitalityNewcastle upon TyneNE4 5PLUnited Kingdom
| | - Luis R. Peraza
- Institute of Neuroscience, Newcastle University, Campus for Ageing and VitalityNewcastle upon TyneNE4 5PLUnited Kingdom
- Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing, Newcastle UniversityNewcastle upon TyneNE4 5TGUnited Kingdom
| | - Michael Firbank
- Institute of Neuroscience, Newcastle University, Campus for Ageing and VitalityNewcastle upon TyneNE4 5PLUnited Kingdom
| | - Alan J. Thomas
- Institute of Neuroscience, Newcastle University, Campus for Ageing and VitalityNewcastle upon TyneNE4 5PLUnited Kingdom
| | - Marcus Kaiser
- Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing, Newcastle UniversityNewcastle upon TyneNE4 5TGUnited Kingdom
- Institute of Neuroscience, Newcastle University, The Henry Wellcome BuildingNewcastle upon TyneNE2 4HHUnited Kingdom
| | - Peter Gallagher
- Institute of Neuroscience, Newcastle University, The Henry Wellcome BuildingNewcastle upon TyneNE2 4HHUnited Kingdom
| | - John T. O'Brien
- Department of PsychiatryUniversity of Cambridge School of MedicineCambridgeCB2 0SPUnited Kingdom
| | - Andrew M. Blamire
- Institute of Cellular Medicine & Newcastle Magnetic Resonance Centre, Campus for Ageing and VitalityNewcastle upon TyneNE4 5PLUnited Kingdom
| | - John‐Paul Taylor
- Institute of Neuroscience, Newcastle University, Campus for Ageing and VitalityNewcastle upon TyneNE4 5PLUnited Kingdom
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Jiang J, Zhou H, Duan H, Liu X, Zuo C, Huang Z, Yu Z, Yan Z. A novel individual-level morphological brain networks constructing method and its evaluation in PET and MR images. Heliyon 2017; 3:e00475. [PMID: 29322101 PMCID: PMC5753611 DOI: 10.1016/j.heliyon.2017.e00475] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2017] [Revised: 11/14/2017] [Accepted: 11/27/2017] [Indexed: 12/17/2022] Open
Abstract
Mapping the human brain is one of the great scientific challenges of the 21st century. Brain network analysis is an effective technique based on graph theory that is widely used to investigate network patterns in the human brain. Currently, mapping an individual brain network using a single image has been a hotspot in the field of brain science; techniques, such as the Kullback-Leibler (KL) method, have applications in structural Magnetic Resonance (MR) imaging. However, maintaining an image's intensity, shape, texture and gradient information during feature extraction is very challenging. In this study, we propose a novel method for individual-level network construction based on the high-resolution Brainnetome Atlas, which shows 246 brain regions. Principal components (PCs) were obtained for each brain region using principal component analysis (PCA) for feature extraction. Individual brain networks were followed and used to construct the PC similarity measurement based on the mutual information (MI) method. To evaluate the robustness of the proposed method, three independent experiments were carried out. In the first, 34 healthy subjects underwent two Carbon 11-labeled Pittsburgh compound B Positron emission tomography (11C-PiB PET) scans; in the second, 32 healthy subjects underwent two structural MRI scans; and in the last, 10 Alzheimer's disease (AD) subjects and 10Healthy Control (HC) subjects underwent 11C-PiB PET scans. For each subject, network metrics including clustering coefficient, path length, small-world coefficient, efficiency and node betweenness centrality were calculated. The results suggested that both the individual PET and structural MRI networks exhibited a good small-word property, and the variances within subjects was also quite small in all metrics, The average value of Coefficient of variation (CV) map was 0.33 and 0.32 for PiB PET and MR images respectively, and intra-class correlation coefficients (ICC) range from approximately 0.4 to 0.7, indicating that the new method was well adapted to the subjects. The results of intra-class correlation coefficients from the test-retest experiment were consistent with previous research employing KL divergence, but with low computational complexity. Further, differences between AD subjects and HC subjects can be observed in network metrics. The method proposed herein provides a new perspective for investigating individual brain connectivity; it would enable neuroscientists to further understand the functions of the human brain.
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Affiliation(s)
- Jiehui Jiang
- Shanghai Institute for Advanced Communication and Data Science, Shanghai University, Shanghai, China
- Institute of Biomedical Engineering, School of Communication and Information Technology, Shanghai University, Shanghai, China
| | - Hucheng Zhou
- Institute of Biomedical Engineering, School of Communication and Information Technology, Shanghai University, Shanghai, China
| | - Huoqiang Duan
- Institute of Biomedical Engineering, School of Communication and Information Technology, Shanghai University, Shanghai, China
| | - Xin Liu
- Institute of Biomedical Engineering, School of Communication and Information Technology, Shanghai University, Shanghai, China
| | - Chuantao Zuo
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Zhemin Huang
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Zhihua Yu
- Shanghai Geriatric Institute of Chinese Medicine, Shanghai, China
| | - Zhuangzhi Yan
- Institute of Biomedical Engineering, School of Communication and Information Technology, Shanghai University, Shanghai, China
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Firbank MJ, O'Brien JT, Taylor JP. Long reaction times are associated with delayed brain activity in lewy body dementia. Hum Brain Mapp 2017; 39:633-643. [PMID: 29094778 PMCID: PMC5813138 DOI: 10.1002/hbm.23866] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2017] [Revised: 10/13/2017] [Accepted: 10/18/2017] [Indexed: 12/22/2022] Open
Abstract
A significant symptom of Lewy body dementia (LBD) is slow cognitive processing or bradyphrenia. In a previous fMRI task‐based study, we found slower responses in LBD, accompanied by greater deactivation in the default mode network. In this study, we investigated the timing and magnitude of the activations and deactivations with respect to reaction time to determine whether the slower responses in LBD were associated with delayed neuronal activity. Using fMRI, we examined the magnitude and latency of activations and deactivations during an event‐related attention task in 32 patients with LBD and 23 healthy controls using predefined regions of interest. Default mode network deactivations did not significantly differ in their timing between groups or task conditions, while the task‐related activations in the parietal, occipital, frontal, and motor cortex were all significantly later in the LBD group. Repeating the analysis with reaction time as a parametric modulator of activation magnitude produced similar findings, with the reaction time modulator being significant in a number of regions including the default mode network, suggesting that the increased deactivation in LBD is partly explained by slower task completion. Our data suggest that the default mode network deactivation is initiated at the start of the task, and remains deactivated until its end, with the increased magnitude of deactivation in LBD reflecting the more prolonged cognitive processing in these patients. These data add substantially to our understanding of the neural origins of bradyphrenia, which will be essential for determining optimum therapeutic strategies for cognitive impairment in LBD. Hum Brain Mapp 39:633–643, 2018. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
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Affiliation(s)
- Michael J Firbank
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, NE4 5PL, United Kingdom
| | - John T O'Brien
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - John Paul Taylor
- Institute of Neuroscience, Newcastle University, Campus for Ageing and Vitality, Newcastle upon Tyne, NE4 5PL, United Kingdom
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Pezzoli S, Cagnin A, Bandmann O, Venneri A. Structural and Functional Neuroimaging of Visual Hallucinations in Lewy Body Disease: A Systematic Literature Review. Brain Sci 2017; 7:E84. [PMID: 28714891 PMCID: PMC5532597 DOI: 10.3390/brainsci7070084] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2017] [Revised: 06/27/2017] [Accepted: 07/09/2017] [Indexed: 01/01/2023] Open
Abstract
Patients with Lewy body disease (LBD) frequently experience visual hallucinations (VH), well-formed images perceived without the presence of real stimuli. The structural and functional brain mechanisms underlying VH in LBD are still unclear. The present review summarises the current literature on the neural correlates of VH in LBD, namely Parkinson's disease (PD), and dementia with Lewy bodies (DLB). Following a systematic literature search, 56 neuroimaging studies of VH in PD and DLB were critically reviewed and evaluated for quality assessment. The main structural neuroimaging results on VH in LBD revealed grey matter loss in frontal areas in patients with dementia, and parietal and occipito-temporal regions in PD without dementia. Parietal and temporal hypometabolism was also reported in hallucinating PD patients. Disrupted functional connectivity was detected especially in the default mode network and fronto-parietal regions. However, evidence on structural and functional connectivity is still limited and requires further investigation. The current literature is in line with integrative models of VH suggesting a role of attention and perception deficits in the development of VH. However, despite the close relationship between VH and cognitive impairment, its associations with brain structure and function have been explored only by a limited number of studies.
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Affiliation(s)
- Stefania Pezzoli
- Department of Neuroscience, University of Sheffield, Sheffield, S10 2RX, UK.
| | - Annachiara Cagnin
- Department of Neurosciences, University of Padua, 35128 Padua, Italy.
- Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Fondazione Ospedale San Camillo, 30126 Venice, Italy.
| | - Oliver Bandmann
- Department of Neuroscience, University of Sheffield, Sheffield, S10 2RX, UK.
| | - Annalena Venneri
- Department of Neuroscience, University of Sheffield, Sheffield, S10 2RX, UK.
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Mak E, Su L, Williams GB, Firbank MJ, Lawson RA, Yarnall AJ, Duncan GW, Mollenhauer B, Owen AM, Khoo TK, Brooks DJ, Rowe JB, Barker RA, Burn DJ, O'Brien JT. Longitudinal whole-brain atrophy and ventricular enlargement in nondemented Parkinson's disease. Neurobiol Aging 2017; 55:78-90. [PMID: 28431288 PMCID: PMC5454799 DOI: 10.1016/j.neurobiolaging.2017.03.012] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2016] [Revised: 03/05/2017] [Accepted: 03/08/2017] [Indexed: 11/28/2022]
Abstract
We investigated whole-brain atrophy and ventricular enlargement over 18 months in nondemented Parkinson's disease (PD) and examined their associations with clinical measures and baseline CSF markers. PD subjects (n = 100) were classified at baseline into those with mild cognitive impairment (MCI; PD-MCI, n = 36) and no cognitive impairment (PD-NC, n = 64). Percentage of whole-brain volume change (PBVC) and ventricular expansion over 18 months were assessed with FSL-SIENA and ventricular enlargement (VIENA) respectively. PD-MCI showed increased global atrophy (-1.1% ± 0.8%) and ventricular enlargement (6.9 % ± 5.2%) compared with both PD-NC (PBVC: -0.4 ± 0.5, p < 0.01; VIENA: 2.1% ± 4.3%, p < 0.01) and healthy controls. In a subset of 35 PD subjects, CSF levels of tau, and Aβ42/Aβ40 ratio were correlated with PBVC and ventricular enlargement respectively. The sample size required to demonstrate a 20% reduction in PBVC and VIENA was approximately 1/15th of that required to detect equivalent changes in cognitive decline. These findings suggest that longitudinal MRI measurements have potential to serve as surrogate markers to complement clinical assessments for future disease-modifying trials in PD.
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Affiliation(s)
- Elijah Mak
- Department of Psychiatry, University of Cambridge, Cambridgeshire, UK
| | - Li Su
- Department of Psychiatry, University of Cambridge, Cambridgeshire, UK
| | - Guy B Williams
- Wolfson Brain Imaging Centre, University of Cambridge, Cambridgeshire, UK
| | - Michael J Firbank
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK
| | - Rachael A Lawson
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK
| | - Alison J Yarnall
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK
| | - Gordon W Duncan
- Medicine of the Elderly, Western General Hospital, Edinburgh, UK
| | - Brit Mollenhauer
- Paracelsus-Elena-Klinik, Kassel, Germany; University Medical Center Goettingen, Institute of Neuropathology, Goettingen, Germany
| | - Adrian M Owen
- Brain and Mind Institute, University of Western Ontario, London, Canada; Department of Psychology, University of Western Ontario, London, Canada
| | - Tien K Khoo
- Menzies Health Institute, Queensland and School of Medicine, Griffith University, Gold Coast, Australia
| | - David J Brooks
- Division of Neuroscience, Imperial College London, London, UK; Institute of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - James B Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK; Medical Research Council, Cognition and Brain Sciences Unit, Cambridge, UK; Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK
| | - Roger A Barker
- John van Geest Centre for Brain Repair, University of Cambridge, Cambridge, UK
| | - David J Burn
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK
| | - John T O'Brien
- Department of Psychiatry, University of Cambridge, Cambridgeshire, UK.
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Dipasquale O, Cercignani M. Network functional connectivity and whole-brain functional connectomics to investigate cognitive decline in neurodegenerative conditions. FUNCTIONAL NEUROLOGY 2017; 31:191-203. [PMID: 28072380 DOI: 10.11138/fneur/2016.31.4.191] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Non-invasive mapping of brain functional connectivity (FC) has played a fundamental role in neuroscience, and numerous scientists have been fascinated by its ability to reveal the brain's intricate morphology and functional properties. In recent years, two different techniques have been developed that are able to explore FC in pathophysiological conditions and to provide simple and non-invasive biomarkers for the detection of disease onset, severity and progression. These techniques are independent component analysis, which allows a network-based functional exploration of the brain, and graph theory, which provides a quantitative characterization of the whole-brain FC. In this paper we provide an overview of these two techniques and some examples of their clinical applications in the most common neurodegenerative disorders associated with cognitive decline, including mild cognitive impairment, Alzheimer's disease, Parkinson's disease, dementia with Lewy Bodies and behavioral variant frontotemporal dementia.
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Peraza LR, Nesbitt D, Lawson RA, Duncan GW, Yarnall AJ, Khoo TK, Kaiser M, Firbank MJ, O'Brien JT, Barker RA, Brooks DJ, Burn DJ, Taylor JP. Intra- and inter-network functional alterations in Parkinson's disease with mild cognitive impairment. Hum Brain Mapp 2017; 38:1702-1715. [PMID: 28084651 DOI: 10.1002/hbm.23499] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2016] [Revised: 10/16/2016] [Accepted: 12/07/2016] [Indexed: 01/13/2023] Open
Abstract
Mild cognitive impairment (MCI) is prevalent in 15%-40% of Parkinson's disease (PD) patients at diagnosis. In this investigation, we study brain intra- and inter-network alterations in resting state functional magnetic resonance imaging (rs-fMRI) in recently diagnosed PD patients and characterise them as either cognitive normal (PD-NC) or with MCI (PD-MCI). Patients were divided into two groups, PD-NC (N = 62) and PD-MCI (N = 37) and for comparison, healthy controls (HC, N = 30) were also included. Intra- and inter-network connectivity were investigated from participants' rs-fMRIs in 26 resting state networks (RSNs). Intra-network differences were found between both patient groups and HCs for networks associated with motor control (motor cortex), spatial attention and visual perception. When comparing both PD-NC and PD-MCI, intra-network alterations were found in RSNs related to attention, executive function and motor control (cerebellum). The inter-network analysis revealed a hyper-synchronisation between the basal ganglia network and the motor cortex in PD-NC compared with HCs. When both patient groups were compared, intra-network alterations in RSNs related to attention, motor control, visual perception and executive function were found. We also detected disease-driven negative synchronisations and synchronisation shifts from positive to negative and vice versa in both patient groups compared with HCs. The hyper-synchronisation between basal ganglia and motor cortical RSNs in PD and its synchronisation shift from negative to positive compared with HCs, suggest a compensatory response to basal dysfunction and altered basal-cortical motor control in the resting state brain of PD patients. Hum Brain Mapp 38:1702-1715, 2017. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Luis R Peraza
- Institute of Neuroscience, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, NE4 5PL, United Kingdom.,Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing Science, Newcastle University, Newcastle upon Tyne, NE1 7RU, United Kingdom
| | - David Nesbitt
- Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF, United Kingdom.,Department of Clinical Neurosciences, University of Cambridge, Cambridge, CB2 0SZ, United Kingdom
| | - Rachael A Lawson
- Institute of Neuroscience, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, NE4 5PL, United Kingdom
| | - Gordon W Duncan
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Alison J Yarnall
- Institute of Neuroscience, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, NE4 5PL, United Kingdom
| | - Tien K Khoo
- School of Medicine and Menzies Health Institute Queensland, Griffith University, QLD, 4222, Australia
| | - Marcus Kaiser
- Institute of Neuroscience, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, NE4 5PL, United Kingdom.,Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing Science, Newcastle University, Newcastle upon Tyne, NE1 7RU, United Kingdom
| | - Michael J Firbank
- Institute of Neuroscience, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, NE4 5PL, United Kingdom
| | - John T O'Brien
- Institute of Neuroscience, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, NE4 5PL, United Kingdom.,Department of Psychiatry, University of Cambridge, Cambridge, CB2 0QC, United Kingdom
| | - Roger A Barker
- John van Geest Centre for Brain Repair, University of Cambridge, Cambridge, CB2 0PY, United Kingdom
| | - David J Brooks
- Institute of Neuroscience, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, NE4 5PL, United Kingdom.,Department of Nuclear Medicine, Institute of Clinical Medicine, Aarhus University, Aarhus C, Denmark
| | - David J Burn
- Institute of Neuroscience, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, NE4 5PL, United Kingdom
| | - John-Paul Taylor
- Institute of Neuroscience, Campus for Ageing and Vitality, Newcastle University, Newcastle upon Tyne, NE4 5PL, United Kingdom
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Cabral-Calderin Y, Williams KA, Opitz A, Dechent P, Wilke M. Transcranial alternating current stimulation modulates spontaneous low frequency fluctuations as measured with fMRI. Neuroimage 2016; 141:88-107. [DOI: 10.1016/j.neuroimage.2016.07.005] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2016] [Accepted: 07/02/2016] [Indexed: 01/05/2023] Open
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Abstract
BACKGROUND Dementia with Lewy bodies (DLB) is a common cause of dementia in the elderly population after Alzheimer's disease (AD), and at early stages differential diagnosis between DLB and AD might be difficult due to their symptomatic overlap, e.g. cognitive and memory impairments. We aimed to investigate functional brain differences between both diseases in patients recently diagnosed. METHODS We investigated regional functional synchronizations using regional homogeneity (ReHo) in patients clinically diagnosed with DLB (n = 19) and AD (n = 18), and for comparisons we also included healthy controls (HC, n = 16). Patient groups were matched by age, education, and by the level of cognitive impairment (MMSE p-value = 0.36). Additionally, correlations between ReHo values and clinical scores were investigated. RESULTS The DLB group showed lower ReHo in sensory-motor cortices and higher ReHo in left middle temporal gyrus when compared with HCs (p-value < 0.001 uncorrected). The AD group demonstrated lower ReHo in the cerebellum and higher ReHo in the left/right lingual gyri, precuneus cortex, and other occipital and parietal regions (p-value < 0.001 uncorrected). CONCLUSIONS Our results agree with previous ReHo investigations in Parkinson's disease (PD), suggesting that functional alterations in motor-related regions might be a characteristic of the Lewy body disease spectrum. However, our results in AD contradict previously reported findings for this disease and ReHo, which we speculate are a reflection of compensatory brain responses at early disease stages. ReHo differences between patient groups were at regions related to the default mode and sensory-motor resting state networks which might reflect the aetiological divergences in the underlying disease processes between AD and DLB.
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50
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Gaiteri C, Mostafavi S, Honey CJ, De Jager PL, Bennett DA. Genetic variants in Alzheimer disease - molecular and brain network approaches. Nat Rev Neurol 2016; 12:413-27. [PMID: 27282653 PMCID: PMC5017598 DOI: 10.1038/nrneurol.2016.84] [Citation(s) in RCA: 69] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Genetic studies in late-onset Alzheimer disease (LOAD) are aimed at identifying core disease mechanisms and providing potential biomarkers and drug candidates to improve clinical care of AD. However, owing to the complexity of LOAD, including pathological heterogeneity and disease polygenicity, extraction of actionable guidance from LOAD genetics has been challenging. Past attempts to summarize the effects of LOAD-associated genetic variants have used pathway analysis and collections of small-scale experiments to hypothesize functional convergence across several variants. In this Review, we discuss how the study of molecular, cellular and brain networks provides additional information on the effects of LOAD-associated genetic variants. We then discuss emerging combinations of these omic data sets into multiscale models, which provide a more comprehensive representation of the effects of LOAD-associated genetic variants at multiple biophysical scales. Furthermore, we highlight the clinical potential of mechanistically coupling genetic variants and disease phenotypes with multiscale brain models.
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Affiliation(s)
- Chris Gaiteri
- Rush Alzheimer's Disease Center, Rush University Medical Center, 600 S Paulina Street, Chicago, Illinois 60612, USA
| | - Sara Mostafavi
- Department of Statistics, and Medical Genetics; Centre for Molecular and Medicine and Therapeutics, University of British Columbia, 950 West 28th Avenue, Vancouver, British Columbia V5Z 4H4, Canada
| | - Christopher J Honey
- Department of Psychology, University of Toronto, 100 St. George Street, 4th Floor Sidney Smith Hall, Toronto, Ontario M5S 3G3, Canada
| | - Philip L De Jager
- Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Departments of Neurology and Psychiatry, Brigham and Women's Hospital, 75 Francis Street, Boston MA 02115, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, 600 S Paulina Street, Chicago, Illinois 60612, USA
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