1
|
Kudo K, Ranasinghe KG, Morise H, Syed F, Sekihara K, Rankin KP, Miller BL, Kramer JH, Rabinovici GD, Vossel K, Kirsch HE, Nagarajan SS. Neurophysiological trajectories in Alzheimer's disease progression. eLife 2024; 12:RP91044. [PMID: 38546337 PMCID: PMC10977971 DOI: 10.7554/elife.91044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/01/2024] Open
Abstract
Alzheimer's disease (AD) is characterized by the accumulation of amyloid-β and misfolded tau proteins causing synaptic dysfunction, and progressive neurodegeneration and cognitive decline. Altered neural oscillations have been consistently demonstrated in AD. However, the trajectories of abnormal neural oscillations in AD progression and their relationship to neurodegeneration and cognitive decline are unknown. Here, we deployed robust event-based sequencing models (EBMs) to investigate the trajectories of long-range and local neural synchrony across AD stages, estimated from resting-state magnetoencephalography. The increases in neural synchrony in the delta-theta band and the decreases in the alpha and beta bands showed progressive changes throughout the stages of the EBM. Decreases in alpha and beta band synchrony preceded both neurodegeneration and cognitive decline, indicating that frequency-specific neuronal synchrony abnormalities are early manifestations of AD pathophysiology. The long-range synchrony effects were greater than the local synchrony, indicating a greater sensitivity of connectivity metrics involving multiple regions of the brain. These results demonstrate the evolution of functional neuronal deficits along the sequence of AD progression.
Collapse
Affiliation(s)
- Kiwamu Kudo
- Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan FranciscoUnited States
- Medical Imaging Business Center, Ricoh Company LtdKanazawaJapan
| | - Kamalini G Ranasinghe
- Memory and Aging Center,UCSF Weill Institute for Neurosciences, University of California, San FranciscoSan FranciscoUnited States
| | - Hirofumi Morise
- Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan FranciscoUnited States
- Medical Imaging Business Center, Ricoh Company LtdKanazawaJapan
| | - Faatimah Syed
- Memory and Aging Center,UCSF Weill Institute for Neurosciences, University of California, San FranciscoSan FranciscoUnited States
| | | | - Katherine P Rankin
- Memory and Aging Center,UCSF Weill Institute for Neurosciences, University of California, San FranciscoSan FranciscoUnited States
| | - Bruce L Miller
- Memory and Aging Center,UCSF Weill Institute for Neurosciences, University of California, San FranciscoSan FranciscoUnited States
| | - Joel H Kramer
- Memory and Aging Center,UCSF Weill Institute for Neurosciences, University of California, San FranciscoSan FranciscoUnited States
| | - Gil D Rabinovici
- Memory and Aging Center,UCSF Weill Institute for Neurosciences, University of California, San FranciscoSan FranciscoUnited States
- Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan FranciscoUnited States
| | - Keith Vossel
- Memory and Aging Center,UCSF Weill Institute for Neurosciences, University of California, San FranciscoSan FranciscoUnited States
- Mary S. Easton Center for Alzheimer’s Research and Care, Department of Neurology, David Geffen School of Medicine, University of California, Los AngelesLos AngelesUnited States
| | - Heidi E Kirsch
- Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan FranciscoUnited States
| | - Srikantan S Nagarajan
- Biomagnetic Imaging Laboratory, Department of Radiology and Biomedical Imaging, University of California, San FranciscoSan FranciscoUnited States
| |
Collapse
|
2
|
van Heusden FC, van Nifterick AM, Souza BC, França ASC, Nauta IM, Stam CJ, Scheltens P, Smit AB, Gouw AA, van Kesteren RE. Neurophysiological alterations in mice and humans carrying mutations in APP and PSEN1 genes. Alzheimers Res Ther 2023; 15:142. [PMID: 37608393 PMCID: PMC10464047 DOI: 10.1186/s13195-023-01287-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 08/11/2023] [Indexed: 08/24/2023]
Abstract
BACKGROUND Studies in animal models of Alzheimer's disease (AD) have provided valuable insights into the molecular and cellular processes underlying neuronal network dysfunction. Whether and how AD-related neurophysiological alterations translate between mice and humans remains however uncertain. METHODS We characterized neurophysiological alterations in mice and humans carrying AD mutations in the APP and/or PSEN1 genes, focusing on early pre-symptomatic changes. Longitudinal local field potential recordings were performed in APP/PS1 mice and cross-sectional magnetoencephalography recordings in human APP and/or PSEN1 mutation carriers. All recordings were acquired in the left frontal cortex, parietal cortex, and hippocampus. Spectral power and functional connectivity were analyzed and compared with wildtype control mice and healthy age-matched human subjects. RESULTS APP/PS1 mice showed increased absolute power, especially at higher frequencies (beta and gamma) and predominantly between 3 and 6 moa. Relative power showed an overall shift from lower to higher frequencies over almost the entire recording period and across all three brain regions. Human mutation carriers, on the other hand, did not show changes in power except for an increase in relative theta power in the hippocampus. Mouse parietal cortex and hippocampal power spectra showed a characteristic peak at around 8 Hz which was not significantly altered in transgenic mice. Human power spectra showed a characteristic peak at around 9 Hz, the frequency of which was significantly reduced in mutation carriers. Significant alterations in functional connectivity were detected in theta, alpha, beta, and gamma frequency bands, but the exact frequency range and direction of change differed for APP/PS1 mice and human mutation carriers. CONCLUSIONS Both mice and humans carrying APP and/or PSEN1 mutations show abnormal neurophysiological activity, but several measures do not translate one-to-one between species. Alterations in absolute and relative power in mice should be interpreted with care and may be due to overexpression of amyloid in combination with the absence of tau pathology and cholinergic degeneration. Future studies should explore whether changes in brain activity in other AD mouse models, for instance, those also including tau pathology, provide better translation to the human AD continuum.
Collapse
Affiliation(s)
- Fran C van Heusden
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, 1081HV, The Netherlands
| | - Anne M van Nifterick
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, 1081HV, The Netherlands
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, 1081HV, The Netherlands
| | - Bryan C Souza
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, 6525AJ, The Netherlands
| | - Arthur S C França
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, 6525AJ, The Netherlands
- Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, 1105 BA, The Netherlands
| | - Ilse M Nauta
- MS Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, 1081HV, The Netherlands
| | - Cornelis J Stam
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, 1081HV, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, 1081HV, The Netherlands
| | - August B Smit
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, 1081HV, The Netherlands
| | - Alida A Gouw
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, 1081HV, The Netherlands
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, 1081HV, The Netherlands
| | - Ronald E van Kesteren
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam, 1081HV, The Netherlands.
| |
Collapse
|
3
|
Soula M, Maslarova A, Harvey RE, Valero M, Brandner S, Hamer H, Fernández‐Ruiz A, Buzsáki G. Interictal epileptiform discharges affect memory in an Alzheimer's disease mouse model. Proc Natl Acad Sci U S A 2023; 120:e2302676120. [PMID: 37590406 PMCID: PMC10450667 DOI: 10.1073/pnas.2302676120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Accepted: 07/06/2023] [Indexed: 08/19/2023] Open
Abstract
Interictal epileptiform discharges (IEDs) are transient abnormal electrophysiological events commonly observed in epilepsy patients but are also present in other neurological diseases, such as Alzheimer's disease (AD). Understanding the role IEDs have on the hippocampal circuit is important for our understanding of the cognitive deficits seen in epilepsy and AD. We characterize and compare the IEDs of human epilepsy patients from microwire hippocampal recording with those of AD transgenic mice with implanted multilayer hippocampal silicon probes. Both the local field potential features and firing patterns of pyramidal cells and interneurons were similar in the mouse and human. We found that as IEDs emerged from the CA3-1 circuits, they recruited pyramidal cells and silenced interneurons, followed by post-IED suppression. IEDs suppressed the incidence and altered the properties of physiological sharp-wave ripples, altered their physiological properties, and interfered with the replay of place field sequences in a maze. In addition, IEDs in AD mice inversely correlated with daily memory performance. Together, our work implies that IEDs may present a common and epilepsy-independent phenomenon in neurodegenerative diseases that perturbs hippocampal-cortical communication and interferes with memory.
Collapse
Affiliation(s)
- Marisol Soula
- Neuroscience Institute, Langone Medical Center, New York University, New York, NY10016
| | - Anna Maslarova
- Neuroscience Institute, Langone Medical Center, New York University, New York, NY10016
- Department of Neurosurgery, Erlangen University Hospital, Friedrich Alexander University Erlangen-Nuremberg, 91054Erlangen, Germany
| | - Ryan E. Harvey
- Department of Neurobiology and Behavior, Cornell University, Ithaca, NY14853
| | - Manuel Valero
- Hospital del Mar Medical Research Institute, Barcelona Biomedical Research Park, Barcelona08003, Spain
| | - Sebastian Brandner
- Department of Neurosurgery, Erlangen University Hospital, Friedrich Alexander University Erlangen-Nuremberg, 91054Erlangen, Germany
| | - Hajo Hamer
- Department of Neurology, Epilepsy Center, Erlangen University Hospital, Friedrich Alexander University Erlangen-Nuremberg, 91054Erlangen, Germany
| | | | - György Buzsáki
- Neuroscience Institute, Langone Medical Center, New York University, New York, NY10016
- Department of Physiology and Neuroscience, Langone Medical Center, New York University, New York, NY10016
- Department of Neurology, Langone Medical Center, New York University, New York, NY10016
| |
Collapse
|
4
|
van Nifterick AM, Mulder D, Duineveld DJ, Diachenko M, Scheltens P, Stam CJ, van Kesteren RE, Linkenkaer-Hansen K, Hillebrand A, Gouw AA. Resting-state oscillations reveal disturbed excitation-inhibition ratio in Alzheimer's disease patients. Sci Rep 2023; 13:7419. [PMID: 37150756 PMCID: PMC10164744 DOI: 10.1038/s41598-023-33973-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 04/21/2023] [Indexed: 05/09/2023] Open
Abstract
An early disruption of neuronal excitation-inhibition (E-I) balance in preclinical animal models of Alzheimer's disease (AD) has been frequently reported, but is difficult to measure directly and non-invasively in humans. Here, we examined known and novel neurophysiological measures sensitive to E-I in patients across the AD continuum. Resting-state magnetoencephalography (MEG) data of 86 amyloid-biomarker-confirmed subjects across the AD continuum (17 patients diagnosed with subjective cognitive decline, 18 with mild cognitive impairment (MCI) and 51 with dementia due to probable AD (AD dementia)), 46 healthy elderly and 20 young control subjects were reconstructed to source-space. E-I balance was investigated by detrended fluctuation analysis (DFA), a functional E/I (fE/I) algorithm, and the aperiodic exponent of the power spectrum. We found a disrupted E-I ratio in AD dementia patients specifically, by a lower DFA, and a shift towards higher excitation, by a higher fE/I and a lower aperiodic exponent. Healthy subjects showed lower fE/I ratios (< 1.0) than reported in previous literature, not explained by age or choice of an arbitrary threshold parameter, which warrants caution in interpretation of fE/I results. Correlation analyses showed that a lower DFA (E-I imbalance) and a lower aperiodic exponent (more excitation) was associated with a worse cognitive score in AD dementia patients. In contrast, a higher DFA in the hippocampi of MCI patients was associated with a worse cognitive score. This MEG-study showed E-I imbalance, likely due to increased excitation, in AD dementia, but not in early stage AD patients. To accurately determine the direction of shift in E-I balance, validations of the currently used markers and additional in vivo markers of E-I are required.
Collapse
Affiliation(s)
- Anne M van Nifterick
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands.
| | - Danique Mulder
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Denise J Duineveld
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Marina Diachenko
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Cornelis J Stam
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Ronald E van Kesteren
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
| | - Klaus Linkenkaer-Hansen
- Department of Integrative Neurophysiology, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Systems and Network Neurosciences, Amsterdam, The Netherlands
| | - Alida A Gouw
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| |
Collapse
|
5
|
Brown J, Camporesi E, Lantero-Rodriguez J, Olsson M, Wang A, Medem B, Zetterberg H, Blennow K, Karikari TK, Wall M, Hill E. Tau in cerebrospinal fluid induces neuronal hyperexcitability and alters hippocampal theta oscillations. Acta Neuropathol Commun 2023; 11:67. [PMID: 37095572 PMCID: PMC10127378 DOI: 10.1186/s40478-023-01562-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 04/03/2023] [Indexed: 04/26/2023] Open
Abstract
Alzheimer's disease (AD) and other tauopathies are characterized by the aggregation of tau into soluble and insoluble forms (including tangles and neuropil threads). In humans, a fraction of both phosphorylated and non-phosphorylated N-terminal to mid-domain tau species, are secreted into cerebrospinal fluid (CSF). Some of these CSF tau species can be measured as diagnostic and prognostic biomarkers, starting from early stages of disease. While in animal models of AD pathology, soluble tau aggregates have been shown to disrupt neuronal function, it is unclear whether the tau species present in CSF will modulate neural activity. Here, we have developed and applied a novel approach to examine the electrophysiological effects of CSF from patients with a tau-positive biomarker profile. The method involves incubation of acutely-isolated wild-type mouse hippocampal brain slices with small volumes of diluted human CSF, followed by a suite of electrophysiological recording methods to evaluate their effects on neuronal function, from single cells through to the network level. Comparison of the toxicity profiles of the same CSF samples, with and without immuno-depletion for tau, has enabled a pioneering demonstration that CSF-tau potently modulates neuronal function. We demonstrate that CSF-tau mediates an increase in neuronal excitability in single cells. We then observed, at the network level, increased input-output responses and enhanced paired-pulse facilitation as well as an increase in long-term potentiation. Finally, we show that CSF-tau modifies the generation and maintenance of hippocampal theta oscillations, which have important roles in learning and memory and are known to be altered in AD patients. Together, we describe a novel method for screening human CSF-tau to understand functional effects on neuron and network activity, which could have far-reaching benefits in understanding tau pathology, thus allowing for the development of better targeted treatments for tauopathies in the future.
Collapse
Affiliation(s)
- Jessica Brown
- School of Life Sciences, University of Warwick, Coventry, CV4 7AL, UK
- Division of Pharmacy and Optometry, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PL, UK
| | - Elena Camporesi
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, 43180, Mölndal, Sweden
| | - Juan Lantero-Rodriguez
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, 43180, Mölndal, Sweden
| | - Maria Olsson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, 43180, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 43180, Mölndal, Sweden
| | - Alice Wang
- School of Life Sciences, University of Warwick, Coventry, CV4 7AL, UK
| | - Blanca Medem
- School of Life Sciences, University of Warwick, Coventry, CV4 7AL, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, 43180, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 43180, Mölndal, Sweden
- UK Dementia Research Institute at UCL, London, WC1E 6BT, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, WC1E 6BT, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin, Madison, WI, 53792, USA
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, 43180, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 43180, Mölndal, Sweden
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, 43180, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 43180, Mölndal, Sweden
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Mark Wall
- School of Life Sciences, University of Warwick, Coventry, CV4 7AL, UK
| | - Emily Hill
- School of Life Sciences, University of Warwick, Coventry, CV4 7AL, UK.
| |
Collapse
|
6
|
Plaza-Rosales I, Brunetti E, Montefusco-Siegmund R, Madariaga S, Hafelin R, Ponce DP, Behrens MI, Maldonado PE, Paula-Lima A. Visual-spatial processing impairment in the occipital-frontal connectivity network at early stages of Alzheimer's disease. Front Aging Neurosci 2023; 15:1097577. [PMID: 36845655 PMCID: PMC9947357 DOI: 10.3389/fnagi.2023.1097577] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 01/20/2023] [Indexed: 02/11/2023] Open
Abstract
Introduction Alzheimer's disease (AD) is the leading cause of dementia worldwide, but its pathophysiological phenomena are not fully elucidated. Many neurophysiological markers have been suggested to identify early cognitive impairments of AD. However, the diagnosis of this disease remains a challenge for specialists. In the present cross-sectional study, our objective was to evaluate the manifestations and mechanisms underlying visual-spatial deficits at the early stages of AD. Methods We combined behavioral, electroencephalography (EEG), and eye movement recordings during the performance of a spatial navigation task (a virtual version of the Morris Water Maze adapted to humans). Participants (69-88 years old) with amnesic mild cognitive impairment-Clinical Dementia Rating scale (aMCI-CDR 0.5) were selected as probable early AD (eAD) by a neurologist specialized in dementia. All patients included in this study were evaluated at the CDR 0.5 stage but progressed to probable AD during clinical follow-up. An equal number of matching healthy controls (HCs) were evaluated while performing the navigation task. Data were collected at the Department of Neurology of the Clinical Hospital of the Universidad de Chile and the Department of Neuroscience of the Faculty of Universidad de Chile. Results Participants with aMCI preceding AD (eAD) showed impaired spatial learning and their visual exploration differed from the control group. eAD group did not clearly prefer regions of interest that could guide solving the task, while controls did. The eAD group showed decreased visual occipital evoked potentials associated with eye fixations, recorded at occipital electrodes. They also showed an alteration of the spatial spread of activity to parietal and frontal regions at the end of the task. The control group presented marked occipital activity in the beta band (15-20 Hz) at early visual processing time. The eAD group showed a reduction in beta band functional connectivity in the prefrontal cortices reflecting poor planning of navigation strategies. Discussion We found that EEG signals combined with visual-spatial navigation analysis, yielded early and specific features that may underlie the basis for understanding the loss of functional connectivity in AD. Still, our results are clinically promising for early diagnosis required to improve quality of life and decrease healthcare costs.
Collapse
Affiliation(s)
- Iván Plaza-Rosales
- Department of Medical Technology, Faculty of Medicine, Universidad de Chile, Santiago, Chile,Biomedical Neuroscience Institute, Faculty of Medicine, Universidad de Chile, Santiago, Chile
| | - Enzo Brunetti
- Biomedical Neuroscience Institute, Faculty of Medicine, Universidad de Chile, Santiago, Chile,Institute of Neurosurgery and Brain Research Dr. Alfonso Asenjo, Santiago, Chile,Department of Neuroscience, Faculty of Medicine, Universidad de Chile, Santiago, Chile
| | - Rodrigo Montefusco-Siegmund
- Faculty of Medicine, Institute of Locomotor System and Rehabilitation, Universidad Austral de Chile, Valdivia, Chile
| | - Samuel Madariaga
- Biomedical Neuroscience Institute, Faculty of Medicine, Universidad de Chile, Santiago, Chile
| | - Rodrigo Hafelin
- Biomedical Neuroscience Institute, Faculty of Medicine, Universidad de Chile, Santiago, Chile
| | - Daniela P. Ponce
- Department of Neurology and Neurosurgery, Hospital Clínico Universidad de Chile, Santiago, Chile,Faculty of Medicine, Center for Advanced Clinical Research, Universidad de Chile, Santiago, Chile
| | - María Isabel Behrens
- Department of Neuroscience, Faculty of Medicine, Universidad de Chile, Santiago, Chile,Department of Neurology and Neurosurgery, Hospital Clínico Universidad de Chile, Santiago, Chile,Faculty of Medicine, Center for Advanced Clinical Research, Universidad de Chile, Santiago, Chile,Department of Neurology and Psychiatry, Clínica Alemana-Universidad del Desarrollo, Santiago, Chile
| | - Pedro E. Maldonado
- Biomedical Neuroscience Institute, Faculty of Medicine, Universidad de Chile, Santiago, Chile,Department of Neuroscience, Faculty of Medicine, Universidad de Chile, Santiago, Chile,Pedro E. Maldonado,
| | - Andrea Paula-Lima
- Biomedical Neuroscience Institute, Faculty of Medicine, Universidad de Chile, Santiago, Chile,Department of Neuroscience, Faculty of Medicine, Universidad de Chile, Santiago, Chile,Institute for Research in Dental Sciences, Faculty of Dentistry, Universidad de Chile, Santiago, Chile,*Correspondence: Andrea Paula-Lima,
| |
Collapse
|
7
|
Giustiniani A, Danesin L, Bozzetto B, Macina A, Benavides-Varela S, Burgio F. Functional changes in brain oscillations in dementia: a review. Rev Neurosci 2023; 34:25-47. [PMID: 35724724 DOI: 10.1515/revneuro-2022-0010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 05/16/2022] [Indexed: 01/11/2023]
Abstract
A growing body of evidence indicates that several characteristics of electroencephalography (EEG) and magnetoencephalography (MEG) play a functional role in cognition and could be linked to the progression of cognitive decline in some neurological diseases such as dementia. The present paper reviews previous studies investigating changes in brain oscillations associated to the most common types of dementia, namely Alzheimer's disease (AD), frontotemporal degeneration (FTD), and vascular dementia (VaD), with the aim of identifying pathology-specific patterns of alterations and supporting differential diagnosis in clinical practice. The included studies analysed changes in frequency power, functional connectivity, and event-related potentials, as well as the relationship between electrophysiological changes and cognitive deficits. Current evidence suggests that an increase in slow wave activity (i.e., theta and delta) as well as a general reduction in the power of faster frequency bands (i.e., alpha and beta) characterizes AD, VaD, and FTD. Additionally, compared to healthy controls, AD exhibits alteration in latencies and amplitudes of the most common event related potentials. In the reviewed studies, these changes generally correlate with performances in many cognitive tests. In conclusion, particularly in AD, neurophysiological changes can be reliable early markers of dementia.
Collapse
Affiliation(s)
| | - Laura Danesin
- IRCCS San Camillo Hospital, via Alberoni 70, 30126 Venice, Italy
| | | | - AnnaRita Macina
- Department of Developmental Psychology and Socialization, University of Padua, via Venezia 8, 35131 Padova, Italy
| | - Silvia Benavides-Varela
- Department of Developmental Psychology and Socialization, University of Padua, via Venezia 8, 35131 Padova, Italy.,Department of Neuroscience, University of Padova, 35128 Padova, Italy.,Padova Neuroscience Center, University of Padova, 35131 Padova, Italy
| | - Francesca Burgio
- IRCCS San Camillo Hospital, via Alberoni 70, 30126 Venice, Italy
| |
Collapse
|
8
|
Fide E, Polat H, Yener G, Özerdem MS. Effects of Pharmacological Treatments in Alzheimer's Disease: Permutation Entropy-Based EEG Complexity Study. Brain Topogr 2023; 36:106-118. [PMID: 36399219 DOI: 10.1007/s10548-022-00927-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Accepted: 11/03/2022] [Indexed: 11/19/2022]
Abstract
Alzheimer's disease (AD) is a neurodegenerative brain disease affecting cognitive and physical functioning. The currently available pharmacological treatments for AD mainly contain cholinesterase inhibitors (AChE-I) and N-methyl-D-aspartic acid (NMDA) receptor antagonists (i.e., memantine). Because brain signals have complex nonlinear dynamics, there has been an increase in interest in researching complexity changes in the time series of brain signals in individuals with AD. In this study, we explore the electroencephalographic (EEG) complexity for making better observation of pharmacological therapy-based treatment effects on AD patients using the permutation entropy (PE) method. We examined EEG sub-band (delta, theta, alpha, beta, and gamma) complexity in de-novo, monotherapy (AChE-I), dual therapy (AChE-I and memantine) receiving AD participants compared with healthy elderly controls. We showed that each frequency band depicts its own complexity profile, which is regionally altered between groups. These alterations were also found to be associated with global cognitive scores. Overall, our findings indicate that entropy measures could be useful to show medication effects in AD.
Collapse
Affiliation(s)
- Ezgi Fide
- Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
| | - Hasan Polat
- Department of Electrical and Energy, Bingöl University, Selahaddin-i Eyyübi Mah. Aydınlık Cad No: 1, 12000, Bingöl, Turkey.
| | - Görsev Yener
- Brain Dynamics Multidisciplinary Research Center, Izmir, Turkey.,Faculty of Medicine, Izmir University of Economics, Izmir, Turkey.,International Biomedicine and Genome Institute, Izmir, Turkey
| | - Mehmet Siraç Özerdem
- Department of Electrical and Electronics Engineering, Dicle University, Diyarbakır, Turkey
| |
Collapse
|
9
|
Tarasova I, Trubnikova O, Kupriyanova DS, Maleva O, Syrova I, Kukhareva I, Sosnina A, Tarasov R, Barbarash O. Cognitive functions and patterns of brain activity in patients after simultaneous coronary and carotid artery revascularization. Front Hum Neurosci 2023; 17:996359. [PMID: 37125348 PMCID: PMC10130512 DOI: 10.3389/fnhum.2023.996359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 03/13/2023] [Indexed: 05/02/2023] Open
Abstract
Background On-pump coronary artery bypass grafting (CABG) is associated with a high risk of neurological complications in patients with severe carotid stenosis. Moreover, early postoperative cognitive dysfunction (POCD) incidence remains high in patients undergoing simultaneous coronary and carotid surgery. Recent studies have shown that even moderate carotid stenosis (≥50%) is associated with postoperative cognitive decline after CABG. Data on brain health in the postoperative period of simultaneous coronary and carotid surgery are limited. Objectives This study aimed to analyze early postoperative changes in the cognitive function and patterns of brain electrical activity in patients after simultaneous coronary and carotid artery revascularization. Materials and methods Between January 2017 and December 2020, consecutive patients were assigned to on-pump CABG with or without carotid endarterectomy (CEA) according to clinical indications. An extended neuropsychological and electroencephalographic (EEG) assessment was performed before surgery and at 7-10 days after CABG or CABG + CEA. Results A total of 100 patients were included [median age 59 (55; 65), 95% men, MMSE 27 (26; 28)], and among these, 46 underwent CEA. POCD was diagnosed in 29 (63.0%) patients with CABG + CEA and in 32 (59.0%) patients with isolated CABG. All patients presented with a postoperative theta power increase. However, patients with CABG + right-sided CEA demonstrated the most pronounced theta power increase compared to patients with isolated CABG. Conclusion The findings of our study show that patients with CABG + CEA and isolated CABG have comparable POCD incidence; however, patients with CABG + right-sided CEA presented with lower brain activity.
Collapse
Affiliation(s)
- Irina Tarasova
- Department of Clinical Cardiology, State Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
- *Correspondence: Irina Tarasova
| | - Olga Trubnikova
- Department of Clinical Cardiology, State Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| | - Darya S. Kupriyanova
- Department of Clinical Cardiology, State Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| | - Olga Maleva
- Department of Clinical Cardiology, State Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| | - Irina Syrova
- Department of Clinical Cardiology, State Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| | - Irina Kukhareva
- Department of Clinical Cardiology, State Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| | - Anastasia Sosnina
- Department of Clinical Cardiology, State Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| | - Roman Tarasov
- Department of Cardiac and Vascular Surgery, State Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| | - Olga Barbarash
- Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| |
Collapse
|
10
|
Caravaglios G, Muscoso EG, Blandino V, Di Maria G, Gangitano M, Graziano F, Guajana F, Piccoli T. EEG Resting-State Functional Networks in Amnestic Mild Cognitive Impairment. Clin EEG Neurosci 2023; 54:36-50. [PMID: 35758261 DOI: 10.1177/15500594221110036] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Background. Alzheimer's cognitive-behavioral syndrome is the result of impaired connectivity between nerve cells, due to misfolded proteins, which accumulate and disrupt specific brain networks. Electroencephalography, because of its excellent temporal resolution, is an optimal approach for assessing the communication between functionally related brain regions. Objective. To detect and compare EEG resting-state networks (RSNs) in patients with amnesic mild cognitive impairment (aMCI), and healthy elderly (HE). Methods. We recruited 125 aMCI patients and 70 healthy elderly subjects. One hundred and twenty seconds of artifact-free EEG data were selected and compared between patients with aMCI and HE. We applied standard low-resolution brain electromagnetic tomography (sLORETA)-independent component analysis (ICA) to assess resting-state networks. Each network consisted of a set of images, one for each frequency (delta, theta, alpha1/2, beta1/2). Results. The functional ICA analysis revealed 17 networks common to groups. The statistical procedure demonstrated that aMCI used some networks differently than HE. The most relevant findings were as follows. Amnesic-MCI had: i) increased delta/beta activity in the superior frontal gyrus and decreased alpha1 activity in the paracentral lobule (ie, default mode network); ii) greater delta/theta/alpha/beta in the superior frontal gyrus (i.e, attention network); iii) lower alpha in the left superior parietal lobe, as well as a lower delta/theta and beta, respectively in post-central, and in superior frontal gyrus(ie, attention network). Conclusions. Our study confirms sLORETA-ICA method is effective in detecting functional resting-state networks, as well as between-groups connectivity differences. The findings provide support to the Alzheimer's network disconnection hypothesis.
Collapse
Affiliation(s)
- G Caravaglios
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - E G Muscoso
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - V Blandino
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), 18998University of Palermo, Palermo, Italy
| | - G Di Maria
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - M Gangitano
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), 18998University of Palermo, Palermo, Italy
| | - F Graziano
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - F Guajana
- U.O.C. Neurologia, A.O. Cannizzaro per l'emergenza, Catania, Italy
| | - T Piccoli
- Department of Biomedicine, Neuroscience and Advanced Diagnostics (Bi.N.D.), 18998University of Palermo, Palermo, Italy
| |
Collapse
|
11
|
van Nifterick AM, Gouw AA, van Kesteren RE, Scheltens P, Stam CJ, de Haan W. A multiscale brain network model links Alzheimer’s disease-mediated neuronal hyperactivity to large-scale oscillatory slowing. Alzheimers Res Ther 2022; 14:101. [PMID: 35879779 PMCID: PMC9310500 DOI: 10.1186/s13195-022-01041-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Accepted: 07/02/2022] [Indexed: 01/30/2023]
Abstract
Background Neuronal hyperexcitability and inhibitory interneuron dysfunction are frequently observed in preclinical animal models of Alzheimer’s disease (AD). This study investigates whether these microscale abnormalities explain characteristic large-scale magnetoencephalography (MEG) activity in human early-stage AD patients. Methods To simulate spontaneous electrophysiological activity, we used a whole-brain computational network model comprised of 78 neural masses coupled according to human structural brain topology. We modified relevant model parameters to simulate six literature-based cellular scenarios of AD and compare them to one healthy and six contrast (non-AD-like) scenarios. The parameters include excitability, postsynaptic potentials, and coupling strength of excitatory and inhibitory neuronal populations. Whole-brain spike density and spectral power analyses of the simulated data reveal mechanisms of neuronal hyperactivity that lead to oscillatory changes similar to those observed in MEG data of 18 human prodromal AD patients compared to 18 age-matched subjects with subjective cognitive decline. Results All but one of the AD-like scenarios showed higher spike density levels, and all but one of these scenarios had a lower peak frequency, higher spectral power in slower (theta, 4–8Hz) frequencies, and greater total power. Non-AD-like scenarios showed opposite patterns mainly, including reduced spike density and faster oscillatory activity. Human AD patients showed oscillatory slowing (i.e., higher relative power in the theta band mainly), a trend for lower peak frequency and higher total power compared to controls. Combining model and human data, the findings indicate that neuronal hyperactivity can lead to oscillatory slowing, likely due to hyperexcitation (by hyperexcitability of pyramidal neurons or greater long-range excitatory coupling) and/or disinhibition (by reduced excitability of inhibitory interneurons or weaker local inhibitory coupling strength) in early AD. Conclusions Using a computational brain network model, we link findings from different scales and models and support the hypothesis of early-stage neuronal hyperactivity underlying E/I imbalance and whole-brain network dysfunction in prodromal AD. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-022-01041-4.
Collapse
|
12
|
Hyperconnectivity matters in early-onset Alzheimer's disease: a resting-state EEG connectivity study. Neurophysiol Clin 2022; 52:459-471. [DOI: 10.1016/j.neucli.2022.10.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Revised: 10/17/2022] [Accepted: 10/21/2022] [Indexed: 11/11/2022] Open
|
13
|
Miotto EC, Brucki SMD, Cerqueira CT, Bazán PR, Silva GADA, Martin MDGM, da Silveira PS, Faria DDP, Coutinho AM, Buchpiguel CA, Busatto Filho G, Nitrini R. Episodic Memory, Hippocampal Volume, and Function for Classification of Mild Cognitive Impairment Patients Regarding Amyloid Pathology. J Alzheimers Dis 2022; 89:181-192. [PMID: 35871330 PMCID: PMC9484090 DOI: 10.3233/jad-220100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: Previous studies of hippocampal function and volume related to episodic memory deficits in patients with amnestic mild cognitive impairment (aMCI) have produced mixed results including increased or decreased activity and volume. However, most of them have not included biomarkers, such as amyloid-β (Aβ) deposition which is the hallmark for early identification of the Alzheimer’s disease continuum. Objective: We investigated the role of Aβ deposition, functional hippocampal activity and structural volume in aMCI patients and healthy elderly controls (HC) using a new functional MRI (fMRI) ecological episodic memory task. Methods: Forty-six older adults were included, among them Aβ PET PIB positive (PIB+) aMCI (N = 17), Aβ PET PIB negative (PIB–) aMCI (N = 15), and HC (N = 14). Hippocampal volume and function were analyzed using Freesurfer v6.0 and FSL for news headlines episodic memory fMRI task, and logistic regression for group classification in conjunction with episodic memory task and traditional neuropsychological tests. Results: The aMCI PIB+ and PIB–patients showed significantly worse performance in relation to HC in most traditional neuropsychological tests and within group difference only on story recall and the ecological episodic memory fMRI task delayed recall. The classification model reached a significant accuracy (78%) and the classification pattern characterizing the PIB+ included decreased left hippocampal function and volume, increased right hippocampal function and volume, and worse episodic memory performance differing from PIB–which showed increased left hippocampus volume. Conclusion: The main findings showed differential neural correlates, hippocampal volume and function during episodic memory in aMCI patients with the presence of Aβ deposition.
Collapse
Affiliation(s)
- Eliane Correa Miotto
- Department of Neurology, University of São Paulo, São Paulo, Brazil.,Institute of Radiology, LIM-44, Hospital das Clinicas, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil
| | | | | | - Paulo R Bazán
- Institute of Radiology, LIM-44, Hospital das Clinicas, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil.,Hospital Israelita Albert Einstein, São Paulo, Brazil
| | | | - Maria da Graça M Martin
- Institute of Radiology, LIM-44, Hospital das Clinicas, Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brazil
| | | | - Daniele de Paula Faria
- Laboratory of Nuclear Medicine, LIM 43, Department of Radiology and Oncology, University of Sao Paulo, Brazil
| | - Artur Martins Coutinho
- Laboratory of Nuclear Medicine, LIM 43, Department of Radiology and Oncology, University of Sao Paulo, Brazil
| | - Carlos Alberto Buchpiguel
- Laboratory of Nuclear Medicine, LIM 43, Department of Radiology and Oncology, University of Sao Paulo, Brazil
| | | | - Ricardo Nitrini
- Department of Neurology, University of São Paulo, São Paulo, Brazil
| |
Collapse
|
14
|
Exploring sex differences in alpha brain activity as a potential neuromarker associated with neuropathic pain. Pain 2022; 163:1291-1302. [PMID: 34711764 DOI: 10.1097/j.pain.0000000000002491] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 09/09/2021] [Indexed: 12/31/2022]
Abstract
ABSTRACT Alpha oscillatory activity (8-13 Hz) is the dominant rhythm in the awake brain and is known to play an important role in pain states. Previous studies have identified alpha band slowing and increased power in the dynamic pain connectome (DPC) of people with chronic neuropathic pain. However, a link between alpha-band abnormalities and sex differences in brain organization in healthy individuals and those with chronic pain is not known. Here, we used resting-state magnetoencephalography to test the hypothesis that peak alpha frequency (PAF) abnormalities are general features across chronic central and peripheral conditions causing neuropathic pain but exhibit sex-specific differences in networks of the DPC (ascending nociceptive pathway [ANP], default mode network, salience network [SN], and subgenual anterior cingulate cortex). We found that neuropathic pain (N = 25 men and 25 women) was associated with increased PAF power in the DPC compared with 50 age- and sex-matched healthy controls, whereas slower PAF in nodes of the SN (temporoparietal junction) and the ANP (posterior insula) was associated with higher trait pain intensity. In the neuropathic pain group, women exhibited lower PAF power in the subgenual anterior cingulate cortex and faster PAF in the ANP and SN than men. The within-sex analyses indicated that women had neuropathic pain-related increased PAF power in the ANP, SN, and default mode network, whereas men with neuropathic pain had increased PAF power restricted to the ANP. These findings highlight neuropathic pain-related and sex-specific abnormalities in alpha oscillations across the DPC that could underlie aberrant neuronal communication in nociceptive processing and modulation.
Collapse
|
15
|
Tok S, Maurin H, Delay C, Crauwels D, Manyakov NV, Van Der Elst W, Moechars D, Drinkenburg WHIM. Pathological and neurophysiological outcomes of seeding human-derived tau pathology in the APP-KI NL-G-F and NL-NL mouse models of Alzheimer's Disease. Acta Neuropathol Commun 2022; 10:92. [PMID: 35739575 PMCID: PMC9219251 DOI: 10.1186/s40478-022-01393-w] [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: 04/27/2022] [Accepted: 06/07/2022] [Indexed: 12/02/2022] Open
Abstract
The two main histopathological hallmarks that characterize Alzheimer’s Disease are the presence of amyloid plaques and neurofibrillary tangles. One of the current approaches to studying the consequences of amyloid pathology relies on the usage of transgenic animal models that incorporate the mutant humanized form of the amyloid precursor protein (hAPP), with animal models progressively developing amyloid pathology as they age. However, these mice models generally overexpress the hAPP protein to facilitate the development of amyloid pathology, which has been suggested to elicit pathological and neuropathological changes unrelated to amyloid pathology. In this current study, we characterized APP knock-in (APP-KI) animals, that do not overexpress hAPP but still develop amyloid pathology to understand the influence of protein overexpression. We also induced tau pathology via human-derived tau seeding material to understand the neurophysiological effects of amyloid and tau pathology. We report that tau-seeded APP-KI animals progressively develop tau pathology, exacerbated by the presence of amyloid pathology. Interestingly, older amyloid-bearing, tau-seeded animals exhibited more amyloid pathology in the entorhinal area, isocortex and hippocampus, but not thalamus, which appeared to correlate with impairments in gamma oscillations before seeding. Tau-seeded animals also featured immediate deficits in power spectra values and phase-amplitude indices in the hippocampus after seeding, with gamma power spectra deficits persisting in younger animals. Both deficits in hippocampal phase-amplitude coupling and gamma power differentiate tau-seeded, amyloid-positive animals from buffer controls. Based on our results, impairments in gamma oscillations appear to be strongly associated with the presence and development of amyloid and tau pathology, and may also be an indicator of neuropathology, network dysfunction, and even potential disposition to the future development of amyloid pathology.
Collapse
Affiliation(s)
- S Tok
- Department of Neuroscience, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium.,Groningen Institute for Evolutionary Life Sciences, Faculty of Science and Engineering, University of Groningen, Groningen, The Netherlands
| | - H Maurin
- Department of Neuroscience, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - C Delay
- Department of Neuroscience, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - D Crauwels
- Department of Neuroscience, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - N V Manyakov
- Data Sciences, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - W Van Der Elst
- Quantitative Sciences Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - D Moechars
- Department of Neuroscience, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - W H I M Drinkenburg
- Department of Neuroscience, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium. .,Groningen Institute for Evolutionary Life Sciences, Faculty of Science and Engineering, University of Groningen, Groningen, The Netherlands.
| |
Collapse
|
16
|
Wang J, Sun T, Zhang Y, Yu X, Wang H. Distinct Effects of the Apolipoprotein E ε4 Genotype on Associations Between Delayed Recall Performance and Resting-State Electroencephalography Theta Power in Elderly People Without Dementia. Front Aging Neurosci 2022; 14:830149. [PMID: 35693343 PMCID: PMC9178171 DOI: 10.3389/fnagi.2022.830149] [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: 12/06/2021] [Accepted: 05/06/2022] [Indexed: 11/21/2022] Open
Abstract
Background Abnormal electroencephalography (EEG) activity has been demonstrated in mild cognitive impairment (MCI), and theta rhythm might be inversely related to memory. The apolipoprotein E (ApoE) epsilon 4 (ε4) allele, as a genetic vulnerability factor for pathologic and normal age-related cognitive decline, may influence different patterns of cognitive dysfunction. Therefore, the present study primarily aimed to verify the role of resting theta rhythm in delayed recall deficits, and further explore the effects of the ApoE genotype on the associations between the resting theta power and delayed recall performance in the elderly individuals without dementia. Methods A total of 47 individuals without dementia, including 23 MCI and 24 healthy subjects (HCs), participated in the study. All subjects were administered the Hopkins Verbal Learning Test–Revised (HVLT-R) to measure delayed recall performance. Power spectra based on resting-state EEG data were used to examine brain oscillations. Linear regression was used to examine the relationships between EEG power and delayed recall performance in each subgroup. Results The increased theta power in the bilateral central and temporal areas (Ps = 0.02–0.044, uncorrected) was found in the patients with MCI, and were negatively correlated with delayed recall performance (rs = −0.358 to −0.306, Ps = 0.014–0.036, FDR corrected) in the elderly individuals without dementia. The worse delayed recall performance was associated with higher theta power in the left central and temporal areas, especially in ApoE ε4 non-carriers and not in carriers (rs = −0.404 to −0.369, Ps = 0.02–0.035, uncorrected). Conclusion Our study suggests that theta disturbances might contribute to delayed recall memory decline. The ApoE genotype may have distinct effects on EEG-based neural correlates of episodic memory performance.
Collapse
Affiliation(s)
- Jing Wang
- Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health, Peking University, Beijing, China
- Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
| | - Tingting Sun
- Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health, Peking University, Beijing, China
- Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
- Department of Psychiatry, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Ying Zhang
- Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health, Peking University, Beijing, China
- Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
| | - Xin Yu
- Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health, Peking University, Beijing, China
- Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
| | - Huali Wang
- Peking University Institute of Mental Health (Sixth Hospital), Beijing, China
- National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health, Peking University, Beijing, China
- Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China
- *Correspondence: Huali Wang,
| |
Collapse
|
17
|
Govaarts R, Beeldman E, Fraschini M, Griffa A, Engels MMA, van Es MA, Veldink JH, van den Berg LH, van der Kooi AJ, Pijnenburg YAL, de Visser M, Stam CJ, Raaphorst J, Hillebrand A. Cortical and subcortical changes in resting-state neuronal activity and connectivity in early symptomatic ALS and advanced frontotemporal dementia. Neuroimage Clin 2022; 34:102965. [PMID: 35217500 PMCID: PMC8867127 DOI: 10.1016/j.nicl.2022.102965] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 02/08/2022] [Accepted: 02/09/2022] [Indexed: 01/17/2023]
Abstract
The objective of this study was to examine if patterns of resting-state brain activity and functional connectivity in cortical and subcortical regions in patients with early symptomatic amyotrophic lateral sclerosis (ALS) resemble those of behavioural variant frontotemporal dementia (bvFTD). In a cross-sectional design, eyes-closed resting-state magnetoencephalography (MEG) data of 34 ALS patients, 18 bvFTD patients and 18 age- and gender-matched healthy controls (HCs) were projected to source-space using an atlas-based beamformer. Group differences in peak frequency, band-specific oscillatory activity and functional connectivity (corrected amplitude envelope correlation) in 78 cortical regions and 12 subcortical regions were determined. False discovery rate was used to correct for multiple comparisons. BvFTD patients, as compared to ALS and HCs, showed lower relative beta power in parietal, occipital, temporal and nearly all subcortical regions. Compared to HCs, patients with ALS and patients with bvFTD had a higher delta (0.5-4 Hz) and gamma (30-48 Hz) band resting-state functional connectivity in a high number of overlapping regions in the frontal lobe and in limbic and subcortical regions. Higher delta band connectivity was widespread in the bvFTD patients compared to HCs. ALS showed a more widespread higher gamma band functional connectivity compared to bvFTD. In conclusion, MEG in early symptomatic ALS patients shows resting-state functional connectivity changes in frontal, limbic and subcortical regions that overlap considerably with bvFTD. The findings show the potential of MEG to detect brain changes in early symptomatic phases of ALS and contribute to our understanding of the disease spectrum, with ALS and bvFTD at the two extreme ends.
Collapse
Affiliation(s)
- Rosanne Govaarts
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands.
| | - Emma Beeldman
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Matteo Fraschini
- University of Cagliari, Department of Electrical and Electronic Engineering, Cagliari, Italy
| | - Alessandra Griffa
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland; Institute of Bioengineering, Center of Neuroprosthetics, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland
| | - Marjolein M A Engels
- Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology, Magnetoencephalography Centre, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Michael A van Es
- University Medical Centre Utrecht, Department of Neurology, Brain Centre Rudolf Magnus, Utrecht, the Netherlands
| | - Jan H Veldink
- University Medical Centre Utrecht, Department of Neurology, Brain Centre Rudolf Magnus, Utrecht, the Netherlands
| | - Leonard H van den Berg
- University Medical Centre Utrecht, Department of Neurology, Brain Centre Rudolf Magnus, Utrecht, the Netherlands
| | - Anneke J van der Kooi
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Yolande A L Pijnenburg
- Amsterdam University Medical Centers, Vrije Universiteit, Alzheimer Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Marianne de Visser
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Cornelis J Stam
- Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology, Magnetoencephalography Centre, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Joost Raaphorst
- Amsterdam University Medical Centers, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Arjan Hillebrand
- Amsterdam University Medical Centers, Vrije Universiteit Amsterdam, Department of Clinical Neurophysiology, Magnetoencephalography Centre, Amsterdam Neuroscience, Amsterdam, the Netherlands
| |
Collapse
|
18
|
Tok S, Maurin H, Delay C, Crauwels D, Manyakov NV, Van Der Elst W, Moechars D, Drinkenburg WHIM. Neurophysiological effects of human-derived pathological tau conformers in the APPKM670/671NL.PS1/L166P amyloid mouse model of Alzheimer's disease. Sci Rep 2022; 12:7784. [PMID: 35546164 PMCID: PMC9094605 DOI: 10.1038/s41598-022-11582-1] [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: 12/30/2021] [Accepted: 04/19/2022] [Indexed: 11/09/2022] Open
Abstract
Alzheimer’s Disease (AD) is a neurodegenerative disease characterized by two main pathological hallmarks: amyloid plaques and intracellular tau neurofibrillary tangles. However, a majority of studies focus on the individual pathologies and seldom on the interaction between the two pathologies. Herein, we present the longitudinal neuropathological and neurophysiological effects of a combined amyloid-tau model by hippocampal seeding of human-derived tau pathology in the APP.PS1/L166P amyloid animal model. We statistically assessed both neurophysiological and pathological changes using linear mixed modelling to determine if factors such as the age at which animals were seeded, genotype, seeding or buffer, brain region where pathology was quantified, and time-post injection differentially affect these outcomes. We report that AT8-positive tau pathology progressively develops and is facilitated by the amount of amyloid pathology present at the time of injection. The amount of AT8-positive tau pathology was influenced by the interaction of age at which the animal was injected, genotype, and time after injection. Baseline pathology-related power spectra and Higuchi Fractal Dimension (HFD) score alterations were noted in APP.PS1/L166P before any manipulations were performed, indicating a baseline difference associated with genotype. We also report immediate localized hippocampal dysfunction in the electroencephalography (EEG) power spectra associated with tau seeding which returned to comparable levels at 1 month-post-injection. Longitudinal effects of seeding indicated that tau-seeded wild-type mice showed an increase in gamma power earlier than buffer control comparisons which was influenced by the age at which the animal was injected. A reduction of hippocampal broadband power spectra was noted in tau-seeded wild-type mice, but absent in APP.PS1 animals. HFD scores appeared to detect subtle effects associated with tau seeding in APP.PS1 animals, which was differentially influenced by genotype. Notably, while tau histopathological changes were present, a lack of overt longitudinal electrophysiological alterations was noted, particularly in APP.PS1 animals that feature both pathologies after seeding, reiterating and underscoring the difficulty and complexity associated with elucidating physiologically relevant and translatable biomarkers of Alzheimer’s Disease at the early stages of the disease.
Collapse
Affiliation(s)
- S Tok
- Department of Neuroscience, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium. .,Faculty of Science and Engineering, Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, The Netherlands.
| | - H Maurin
- Department of Neuroscience, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - C Delay
- Department of Neuroscience, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - D Crauwels
- Department of Neuroscience, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - N V Manyakov
- Data Sciences, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - W Van Der Elst
- Quantitative Sciences Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - D Moechars
- Department of Neuroscience, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium
| | - W H I M Drinkenburg
- Department of Neuroscience, Janssen Research and Development, Janssen Pharmaceutica NV, Turnhoutseweg 30, 2340, Beerse, Belgium.,Faculty of Science and Engineering, Groningen Institute for Evolutionary Life Sciences, University of Groningen, Groningen, The Netherlands
| |
Collapse
|
19
|
Schoonhoven DN, Briels CT, Hillebrand A, Scheltens P, Stam CJ, Gouw AA. Sensitive and reproducible MEG resting-state metrics of functional connectivity in Alzheimer's disease. Alzheimers Res Ther 2022; 14:38. [PMID: 35219327 PMCID: PMC8881826 DOI: 10.1186/s13195-022-00970-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 01/30/2022] [Indexed: 01/08/2023]
Abstract
Background Analysis of functional brain networks in Alzheimer’s disease (AD) has been hampered by a lack of reproducible, yet valid metrics of functional connectivity (FC). This study aimed to assess both the sensitivity and reproducibility of the corrected amplitude envelope correlation (AEC-c) and phase lag index (PLI), two metrics of FC that are insensitive to the effects of volume conduction and field spread, in two separate cohorts of patients with dementia due to AD versus healthy elderly controls. Methods Subjects with a clinical diagnosis of AD dementia with biomarker proof, and a control group of subjective cognitive decline (SCD), underwent two 5-min resting-state MEG recordings. Data consisted of a test (AD = 28; SCD = 29) and validation (AD = 29; SCD = 27) cohort. Time-series were estimated for 90 regions of interest (ROIs) in the automated anatomical labelling (AAL) atlas. For each of five canonical frequency bands, the AEC-c and PLI were calculated between all 90 ROIs, and connections were averaged per ROI. General linear models were constructed to compare the global FC differences between the groups, assess the reproducibility, and evaluate the effects of age and relative power. Reproducibility of the regional FC differences was assessed using the Mann-Whitney U tests, with correction for multiple testing using the false discovery rate (FDR). Results The AEC-c showed significantly and reproducibly lower global FC for the AD group compared to SCD, in the alpha (8–13 Hz) and beta (13–30 Hz) bands, while the PLI revealed reproducibly lower FC for the AD group in the delta (0.5–4 Hz) band and higher FC for the theta (4–8 Hz) band. Regionally, the beta band AEC-c showed reproducibility for almost all ROIs (except for 13 ROIs in the frontal and temporal lobes). For the other bands, the AEC-c and PLI did not show regional reproducibility after FDR correction. The theta band PLI was susceptible to the effect of relative power. Conclusion For MEG, the AEC-c is a sensitive and reproducible metric, able to distinguish FC differences between patients with AD dementia and cognitively healthy controls. These two measures likely reflect different aspects of neural activity and show differential sensitivity to changes in neural dynamics. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-022-00970-4.
Collapse
Affiliation(s)
- Deborah N Schoonhoven
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands. .,Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
| | - Casper T Briels
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Alida A Gouw
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| |
Collapse
|
20
|
Wiesman AI, Murman DL, Losh RA, Schantell M, Christopher-Hayes NJ, Johnson HJ, Willett MP, Wolfson SL, Losh KL, Johnson CM, May PE, Wilson TW. Spatially resolved neural slowing predicts impairment and amyloid burden in Alzheimer's disease. Brain 2022; 145:2177-2189. [PMID: 35088842 PMCID: PMC9246709 DOI: 10.1093/brain/awab430] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 10/05/2021] [Accepted: 10/24/2021] [Indexed: 11/28/2022] Open
Abstract
An extensive electrophysiological literature has proposed a pathological ‘slowing’ of neuronal activity in patients on the Alzheimer’s disease spectrum. Supported by numerous studies reporting increases in low-frequency and decreases in high-frequency neural oscillations, this pattern has been suggested as a stable biomarker with potential clinical utility. However, no spatially resolved metric of such slowing exists, stymieing efforts to understand its relation to proteinopathy and clinical outcomes. Further, the assumption that this slowing is occurring in spatially overlapping populations of neurons has not been empirically validated. In the current study, we collected cross-sectional resting state measures of neuronal activity using magnetoencephalography from 38 biomarker-confirmed patients on the Alzheimer’s disease spectrum and 20 cognitively normal biomarker-negative older adults. From these data, we compute and validate a new metric of spatially resolved oscillatory deviations from healthy ageing for each patient on the Alzheimer’s disease spectrum. Using this Pathological Oscillatory Slowing Index, we show that patients on the Alzheimer’s disease spectrum exhibit robust neuronal slowing across a network of temporal, parietal, cerebellar and prefrontal cortices. This slowing effect is shown to be directly relevant to clinical outcomes, as oscillatory slowing in temporal and parietal cortices significantly predicted both general (i.e. Montreal Cognitive Assessment scores) and domain-specific (i.e. attention, language and processing speed) cognitive function. Further, regional amyloid-β accumulation, as measured by quantitative 18F florbetapir PET, robustly predicted the magnitude of this pathological neural slowing effect, and the strength of this relationship between amyloid-β burden and neural slowing also predicted attentional impairments across patients. These findings provide empirical support for a spatially overlapping effect of oscillatory neural slowing in biomarker-confirmed patients on the Alzheimer’s disease spectrum, and link this effect to both regional proteinopathy and cognitive outcomes in a spatially resolved manner. The Pathological Oscillatory Slowing Index also represents a novel metric that is of potentially high utility across a number of clinical neuroimaging applications, as oscillatory slowing has also been extensively documented in other patient populations, most notably Parkinson’s disease, with divergent spectral and spatial features.
Collapse
Affiliation(s)
- Alex I Wiesman
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada.,Department of Neurological Sciences, University of Nebraska Medical Center (UNMC), Omaha, NE, USA
| | - Daniel L Murman
- Department of Neurological Sciences, University of Nebraska Medical Center (UNMC), Omaha, NE, USA.,Memory Disorders & Behavioral Neurology Program, UNMC, Omaha, NE, USA
| | - Rebecca A Losh
- Institute for Human Neuroscience,Boys Town National Research Hospital, Omaha, NE, USA
| | - Mikki Schantell
- Institute for Human Neuroscience,Boys Town National Research Hospital, Omaha, NE, USA
| | | | - Hallie J Johnson
- Institute for Human Neuroscience,Boys Town National Research Hospital, Omaha, NE, USA
| | - Madelyn P Willett
- Institute for Human Neuroscience,Boys Town National Research Hospital, Omaha, NE, USA
| | | | - Kathryn L Losh
- Institute for Human Neuroscience,Boys Town National Research Hospital, Omaha, NE, USA
| | | | - Pamela E May
- Department of Neurological Sciences, University of Nebraska Medical Center (UNMC), Omaha, NE, USA
| | - Tony W Wilson
- Institute for Human Neuroscience,Boys Town National Research Hospital, Omaha, NE, USA
| |
Collapse
|
21
|
Griffa A, Legdeur N, Badissi M, van den Heuvel MP, Stam CJ, Visser PJ, Hillebrand A. Magnetoencephalography Brain Signatures Relate to Cognition and Cognitive Reserve in the Oldest-Old: The EMIF-AD 90 + Study. Front Aging Neurosci 2021; 13:746373. [PMID: 34899269 PMCID: PMC8656941 DOI: 10.3389/fnagi.2021.746373] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 11/01/2021] [Indexed: 11/25/2022] Open
Abstract
The oldest-old subjects represent the fastest growing segment of society and are at high risk for dementia with a prevalence of up to 40%. Lifestyle factors, such as lifelong participation in cognitive and leisure activities, may contribute to individual cognitive reserve and reduce the risk for cognitive impairments. However, the neural bases underlying cognitive functioning and cognitive reserve in this age range are still poorly understood. Here, we investigate spectral and functional connectivity features obtained from resting-state MEG recordings in a cohort of 35 cognitively normal (92.2 ± 1.8 years old, 19 women) and 11 cognitively impaired (90.9 ± 1.9 years old, 1 woman) oldest-old participants, in relation to cognitive traits and cognitive reserve. The latter was approximated with a self-reported scale on lifelong engagement in cognitively demanding activities. Cognitively impaired oldest-old participants had slower cortical rhythms in frontal, parietal and default mode network regions compared to the cognitively normal subjects. These alterations mainly concerned the theta and beta band and partially explained inter-subject variability of episodic memory scores. Moreover, a distinct spectral pattern characterized by higher relative power in the alpha band was specifically associated with higher cognitive reserve while taking into account the effect of age and education level. Finally, stronger functional connectivity in the alpha and beta band were weakly associated with better cognitive performances in the whole group of subjects, although functional connectivity effects were less prominent than the spectral ones. Our results shed new light on the neural underpinnings of cognitive functioning in the oldest-old population and indicate that cognitive performance and cognitive reserve may have distinct spectral electrophysiological substrates.
Collapse
Affiliation(s)
- Alessandra Griffa
- Division of Neurology, Department of Clinical Neurosciences, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Center of Neuroprosthetics, Institute of Bioengineering, École Polytechnique Fédérale De Lausanne (EPFL), Geneva, Switzerland.,Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Nienke Legdeur
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Maryam Badissi
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Martijn P van den Heuvel
- Dutch Connectome Lab, Department of Complex Trait Genetics, Center for Neuroscience and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Pieter Jelle Visser
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands.,Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| |
Collapse
|
22
|
Ranasinghe KG, Petersen C, Kudo K, Mizuiri D, Rankin KP, Rabinovici GD, Gorno-Tempini ML, Seeley WW, Spina S, Miller BL, Vossel K, Grinberg LT, Nagarajan SS. Reduced synchrony in alpha oscillations during life predicts post mortem neurofibrillary tangle density in early-onset and atypical Alzheimer's disease. Alzheimers Dement 2021; 17:2009-2019. [PMID: 33884753 PMCID: PMC8528895 DOI: 10.1002/alz.12349] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 03/04/2021] [Accepted: 03/19/2021] [Indexed: 12/13/2022]
Abstract
INTRODUCTION Neurophysiological manifestations selectively associated with amyloid beta and tau depositions in Alzheimer's disease (AD) are useful network biomarkers to identify peptide specific pathological processes. The objective of this study was to validate the associations between reduced neuronal synchrony within alpha oscillations and neurofibrillary tangle (NFT) density in autopsy examination, in patients with AD. METHODS In a well-characterized clinicopathological cohort of AD patients (n = 13), we quantified neuronal synchrony within alpha (8-12 Hz) and delta-theta (2-8 Hz) oscillations, using magnetoencephalography during the disease course, within six selected neocortical and hippocampal regions, including angular gyrus, superior temporal gurus, middle frontal gyrus, primary motor cortex, CA1, and subiculum, and correlated these with regional NFT density quantified at histopathological examination. RESULTS Abnormal synchrony in alpha, but not in delta-theta, significantly predicted the NFT density at post mortem neuropathological examination. DISCUSSION Reduced alpha synchrony is a sensitive neurophysiological index associated with pathological tau, and a potential network biomarker for clinical trials, to gauge the extent of network dysfunction and the degree of rescue in treatments targeting tau pathways in AD.
Collapse
Affiliation(s)
- Kamalini G. Ranasinghe
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA
| | - Cathrine Petersen
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA
| | - Kiwamu Kudo
- Department Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA,Medical Imaging Business Center, Ricoh Company, Ltd., Kanazawa, Japan
| | - Danielle Mizuiri
- Department Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Katherine P. Rankin
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA
| | - Gil D. Rabinovici
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA,Department Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA
| | - William W. Seeley
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA,Department of Pathology, University of California, San Francisco, San Francisco, California, USA
| | - Salvatore Spina
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA
| | - Bruce L. Miller
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA
| | - Keith Vossel
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA,Mary S. Easton Center for Alzheimer’s Disease Research, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Lea T. Grinberg
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, California, USA,Department of Pathology, University of California, San Francisco, San Francisco, California, USA,Department of Pathology, LIM22, University of Sao Paulo, Sao Paulo, Brazil
| | - Srikantan S. Nagarajan
- Department Radiology & Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| |
Collapse
|
23
|
Scheijbeler EP, Schoonhoven DN, Engels MMA, Scheltens P, Stam CJ, Gouw AA, Hillebrand A. Generating diagnostic profiles of cognitive decline and dementia using magnetoencephalography. Neurobiol Aging 2021; 111:82-94. [PMID: 34906377 DOI: 10.1016/j.neurobiolaging.2021.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 10/11/2021] [Accepted: 11/04/2021] [Indexed: 10/19/2022]
Abstract
Accurate identification of the underlying cause(s) of cognitive decline and dementia is challenging due to significant symptomatic overlap between subtypes. This study presents a multi-class classification framework for subjects with subjective cognitive decline, mild cognitive impairment, Alzheimer's disease, dementia with Lewy bodies, fronto-temporal dementia and cognitive decline due to psychiatric illness, trained on source-localized resting-state magnetoencephalography data. Diagnostic profiles, describing probability estimates for each of the 6 diagnoses, were assigned to individual subjects. A balanced accuracy rate of 41% and multi-class area under the curve value of 0.75 were obtained for 6-class classification. Classification primarily depended on posterior relative delta, theta and beta power and amplitude-based functional connectivity in the beta and gamma frequency band. Dementia with Lewy bodies (sensitivity: 100%, precision: 20%) and Alzheimer's disease subjects (sensitivity: 51%, precision: 90%) could be classified most accurately. Fronto-temporal dementia subjects (sensitivity: 11%, precision: 3%) were most frequently misclassified. Magnetoencephalography biomarkers hold promise to increase diagnostic accuracy in a noninvasive manner. Diagnostic profiles could provide an intuitive tool to clinicians and may facilitate implementation of the classifier in the memory clinic.
Collapse
Affiliation(s)
- Elliz P Scheijbeler
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands; Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrij Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
| | - Deborah N Schoonhoven
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands; Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrij Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Marjolein M A Engels
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands; Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrij Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrij Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Alida A Gouw
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands; Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrij Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrij Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| |
Collapse
|
24
|
Tait L, Özkan A, Szul MJ, Zhang J. A systematic evaluation of source reconstruction of resting MEG of the human brain with a new high-resolution atlas: Performance, precision, and parcellation. Hum Brain Mapp 2021; 42:4685-4707. [PMID: 34219311 PMCID: PMC8410546 DOI: 10.1002/hbm.25578] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 06/09/2021] [Accepted: 06/12/2021] [Indexed: 12/21/2022] Open
Abstract
Noninvasive functional neuroimaging of the human brain can give crucial insight into the mechanisms that underpin healthy cognition and neurological disorders. Magnetoencephalography (MEG) measures extracranial magnetic fields originating from neuronal activity with high temporal resolution, but requires source reconstruction to make neuroanatomical inferences from these signals. Many source reconstruction algorithms are available, and have been widely evaluated in the context of localizing task-evoked activities. However, no consensus yet exists on the optimum algorithm for resting-state data. Here, we evaluated the performance of six commonly-used source reconstruction algorithms based on minimum-norm and beamforming estimates. Using human resting-state MEG, we compared the algorithms using quantitative metrics, including resolution properties of inverse solutions and explained variance in sensor-level data. Next, we proposed a data-driven approach to reduce the atlas from the Human Connectome Project's multi-modal parcellation of the human cortex based on metrics such as MEG signal-to-noise-ratio and resting-state functional connectivity gradients. This procedure produced a reduced cortical atlas with 230 regions, optimized to match the spatial resolution and the rank of MEG data from the current generation of MEG scanners. Our results show that there is no "one size fits all" algorithm, and make recommendations on the appropriate algorithms depending on the data and aimed analyses. Our comprehensive comparisons and recommendations can serve as a guide for choosing appropriate methodologies in future studies of resting-state MEG.
Collapse
Affiliation(s)
- Luke Tait
- Cardiff University Brain Research Imaging CentreCardiff UniversityCardiff
| | - Ayşegül Özkan
- Cardiff University Brain Research Imaging CentreCardiff UniversityCardiff
| | - Maciej J. Szul
- Cardiff University Brain Research Imaging CentreCardiff UniversityCardiff
| | - Jiaxiang Zhang
- Cardiff University Brain Research Imaging CentreCardiff UniversityCardiff
| |
Collapse
|
25
|
Gouw AA, Hillebrand A, Schoonhoven DN, Demuru M, Ris P, Scheltens P, Stam CJ. Routine magnetoencephalography in memory clinic patients: A machine learning approach. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2021; 13:e12227. [PMID: 34568539 PMCID: PMC8449227 DOI: 10.1002/dad2.12227] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Revised: 05/12/2021] [Accepted: 06/04/2021] [Indexed: 11/06/2022]
Abstract
INTRODUCTION We report the routine application of magnetoencephalography (MEG) in a memory clinic, and its value in the discrimination of patients with Alzheimer's disease (AD) dementia from controls. METHODS Three hundred sixty-six patients visiting our memory clinic underwent MEG recording. Source-reconstructed MEG data were visually assessed and evaluated in the context of clinical findings and other diagnostic markers. We analyzed the diagnostic accuracy of MEG spectral measures in the discrimination of individual AD dementia patients (n = 40) from subjective cognitive decline (SCD) patients (n = 40) using random forest models. RESULTS Best discrimination was obtained using a combination of relative theta and delta power (accuracy 0.846, sensitivity 0.855, specificity 0.837). The results were validated in an independent cohort. Hippocampal and thalamic regions, besides temporal-occipital lobes, contributed considerably to the model. DISCUSSION MEG has been implemented successfully in the workup of memory clinic patients and has value in diagnostic decision-making.
Collapse
Affiliation(s)
- Alida A. Gouw
- Alzheimer Center and Department of Neurology, VU University medical center, Amsterdam UMCAmsterdamThe Netherlands
- Department of Clinical Neurophysiology and MEG CenterNeuroscience Campus AmsterdamVU University Medical CenterAmsterdam UMCAmsterdamThe Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG CenterNeuroscience Campus AmsterdamVU University Medical CenterAmsterdam UMCAmsterdamThe Netherlands
| | - Deborah N. Schoonhoven
- Alzheimer Center and Department of Neurology, VU University medical center, Amsterdam UMCAmsterdamThe Netherlands
- Department of Clinical Neurophysiology and MEG CenterNeuroscience Campus AmsterdamVU University Medical CenterAmsterdam UMCAmsterdamThe Netherlands
| | - Matteo Demuru
- Alzheimer Center and Department of Neurology, VU University medical center, Amsterdam UMCAmsterdamThe Netherlands
- Department of Clinical Neurophysiology and MEG CenterNeuroscience Campus AmsterdamVU University Medical CenterAmsterdam UMCAmsterdamThe Netherlands
| | - Peterjan Ris
- Department of Clinical Neurophysiology and MEG CenterNeuroscience Campus AmsterdamVU University Medical CenterAmsterdam UMCAmsterdamThe Netherlands
| | - Philip Scheltens
- Alzheimer Center and Department of Neurology, VU University medical center, Amsterdam UMCAmsterdamThe Netherlands
| | - Cornelis J. Stam
- Department of Clinical Neurophysiology and MEG CenterNeuroscience Campus AmsterdamVU University Medical CenterAmsterdam UMCAmsterdamThe Netherlands
| |
Collapse
|
26
|
Goel A, Roy S, Punjabi K, Mishra R, Tripathi M, Shukla D, Mandal PK. PRATEEK: Integration of Multimodal Neuroimaging Data to Facilitate Advanced Brain Research. J Alzheimers Dis 2021; 83:305-317. [PMID: 34308905 DOI: 10.3233/jad-210440] [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: 11/15/2022]
Abstract
BACKGROUND In vivo neuroimaging modalities such as magnetic resonance imaging (MRI), functional MRI (fMRI), magnetoencephalography (MEG), magnetic resonance spectroscopy (MRS), and quantitative susceptibility mapping (QSM) are useful techniques to understand brain anatomical structure, functional activity, source localization, neurochemical profiles, and tissue susceptibility respectively. Integrating unique and distinct information from these neuroimaging modalities will further help to enhance the understanding of complex neurological diseases. OBJECTIVE To develop a processing scheme for multimodal data integration in a seamless manner on healthy young population, thus establishing a generalized framework for various clinical conditions (e.g., Alzheimer's disease). METHODS A multimodal data integration scheme has been developed to integrate the outcomes from multiple neuroimaging data (fMRI, MEG, MRS, and QSM) spatially. Furthermore, the entire scheme has been incorporated into a user-friendly toolbox- "PRATEEK". RESULTS The proposed methodology and toolbox has been tested for viability among fourteen healthy young participants. The data-integration scheme was tested for bilateral occipital cortices as the regions of interest and can also be extended to other anatomical regions. Overlap percentage from each combination of two modalities (fMRI-MRS, MEG-MRS, fMRI-QSM, and fMRI-MEG) has been computed and also been qualitatively assessed for combinations of the three (MEG-MRS-QSM) and four (fMRI-MEG-MRS-QSM) modalities. CONCLUSION This user-friendly toolbox minimizes the need of an expertise in handling different neuroimaging tools for processing and analyzing multimodal data. The proposed scheme will be beneficial for clinical studies where geometric information plays a crucial role for advance brain research.
Collapse
Affiliation(s)
- Anshika Goel
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, India
| | - Saurav Roy
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, India
| | - Khushboo Punjabi
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, India
| | - Ritwick Mishra
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, India
| | - Manjari Tripathi
- Department of Neurology, All Indian Institute of Medical Sciences, New Delhi, India
| | - Deepika Shukla
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, India
| | - Pravat K Mandal
- NeuroImaging and NeuroSpectroscopy (NINS) Laboratory, National Brain Research Centre, Gurgaon, India.,Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
| |
Collapse
|
27
|
Random walks on B distributed resting-state functional connectivity to identify Alzheimer's disease and Mild Cognitive Impairment. Clin Neurophysiol 2021; 132:2540-2550. [PMID: 34455312 DOI: 10.1016/j.clinph.2021.06.036] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 05/29/2021] [Accepted: 06/29/2021] [Indexed: 11/20/2022]
Abstract
OBJECTIVE Resting-state functional connectivity reveals a promising way for the early detection of dementia. This study proposes a novel method to accurately classify Healthy Controls, Early Mild Cognitive Impairment, Late Mild Cognitive Impairment, and Alzheimer's Disease individuals. METHODS A novel mapping function based on the B distribution has been developed to map correlation matrices to robust functional connectivity. The node2vec algorithm is applied to the functional connectivity to produce node embeddings. The concatenation of these embedding has been used to derive the patients' feature vectors for further feeding into the Support Vector Machine and Logistic Regression classifiers. RESULTS The experimental results indicate promising results in the complex four-class classification problem with an accuracy rate of 97.73% and a quadratic kappa score of 96.86% for the Support Vector Machine. These values are 97.32% and 96.74% for Logistic Regression. CONCLUSION This study presents an accurate automated method for dementia classification. Default Mode Network and Dorsal Attention Network have been found to demonstrate a significant role in the classification method. SIGNIFICANCE A new mapping function is proposed in this study, the mapping function improves accuracy by 10-11% in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database.
Collapse
|
28
|
Tok S, Ahnaou A, Drinkenburg W. Functional Neurophysiological Biomarkers of Early-Stage Alzheimer's Disease: A Perspective of Network Hyperexcitability in Disease Progression. J Alzheimers Dis 2021; 88:809-836. [PMID: 34420957 PMCID: PMC9484128 DOI: 10.3233/jad-210397] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Network hyperexcitability (NH) has recently been suggested as a potential neurophysiological indicator of Alzheimer’s disease (AD), as new, more accurate biomarkers of AD are sought. NH has generated interest as a potential indicator of certain stages in the disease trajectory and even as a disease mechanism by which network dysfunction could be modulated. NH has been demonstrated in several animal models of AD pathology and multiple lines of evidence point to the existence of NH in patients with AD, strongly supporting the physiological and clinical relevance of this readout. Several hypotheses have been put forward to explain the prevalence of NH in animal models through neurophysiological, biochemical, and imaging techniques. However, some of these hypotheses have been built on animal models with limitations and caveats that may have derived NH through other mechanisms or mechanisms without translational validity to sporadic AD patients, potentially leading to an erroneous conclusion of the underlying cause of NH occurring in patients with AD. In this review, we discuss the substantiation for NH in animal models of AD pathology and in human patients, as well as some of the hypotheses considering recently developed animal models that challenge existing hypotheses and mechanisms of NH. In addition, we provide a preclinical perspective on how the development of animal models incorporating AD-specific NH could provide physiologically relevant translational experimental data that may potentially aid the discovery and development of novel therapies for AD.
Collapse
Affiliation(s)
- Sean Tok
- Department of Neuroscience, Janssen Research & Development, Janssen Pharmaceutica NV, Beerse, Belgium.,Groningen Institute for Evolutionary Life Sciences, Faculty of Science and Engineering, University of Groningen, The Netherlands
| | - Abdallah Ahnaou
- Department of Neuroscience, Janssen Research & Development, Janssen Pharmaceutica NV, Beerse, Belgium
| | - Wilhelmus Drinkenburg
- Department of Neuroscience, Janssen Research & Development, Janssen Pharmaceutica NV, Beerse, Belgium.,Groningen Institute for Evolutionary Life Sciences, Faculty of Science and Engineering, University of Groningen, The Netherlands
| |
Collapse
|
29
|
Puttaert D, Wens V, Fery P, Rovai A, Trotta N, Coquelet N, De Breucker S, Sadeghi N, Coolen T, Goldman S, Peigneux P, Bier JC, De Tiège X. Decreased Alpha Peak Frequency Is Linked to Episodic Memory Impairment in Pathological Aging. Front Aging Neurosci 2021; 13:711375. [PMID: 34475819 PMCID: PMC8406997 DOI: 10.3389/fnagi.2021.711375] [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: 05/18/2021] [Accepted: 07/21/2021] [Indexed: 12/04/2022] Open
Abstract
The Free and Cued Selective Reminding Test (FCSRT) is a largely validated neuropsychological test for the identification of amnestic syndrome from the early stage of Alzheimer's disease (AD). Previous electrophysiological data suggested a slowing down of the alpha rhythm in the AD-continuum as well as a key role of this rhythmic brain activity for episodic memory processes. This study therefore investigates the link between alpha brain activity and alterations in episodic memory as assessed by the FCSRT. For that purpose, 37 patients with altered FCSRT performance underwent a comprehensive neuropsychological assessment, supplemented by 18F-fluorodeoxyglucose positron emission tomography/structural magnetic resonance imaging (18FDG-PET/MR), and 10 min of resting-state magnetoencephalography (MEG). The individual alpha peak frequency (APF) in MEG resting-state data was positively correlated with patients' encoding efficiency as well as with the efficacy of semantic cues in facilitating patients' retrieval of previous stored word. The APF also correlated positively with patients' hippocampal volume and their regional glucose consumption in the posterior cingulate cortex. Overall, this study demonstrates that alterations in the ability to learn and store new information for a relatively short-term period are related to a slowing down of alpha rhythmic activity, possibly due to altered interactions in the extended mnemonic system. As such, a decreased APF may be considered as an electrophysiological correlate of short-term episodic memory dysfunction accompanying pathological aging.
Collapse
Affiliation(s)
- Delphine Puttaert
- Laboratoire de Cartographie Fonctionnelle du Cerveau, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
- Neuropsychology and Functional Neuroimaging Research Unit (UR2NF), Center for Research in Cognition and Neurosciences, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
| | - Vincent Wens
- Laboratoire de Cartographie Fonctionnelle du Cerveau, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
- Clinic of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Patrick Fery
- Neuropsychology and Functional Neuroimaging Research Unit (UR2NF), Center for Research in Cognition and Neurosciences, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
- Service of Neuropsychology and Speech Therapy, CUB Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Antonin Rovai
- Laboratoire de Cartographie Fonctionnelle du Cerveau, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
- Clinic of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Nicola Trotta
- Laboratoire de Cartographie Fonctionnelle du Cerveau, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
- Clinic of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Nicolas Coquelet
- Laboratoire de Cartographie Fonctionnelle du Cerveau, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
| | - Sandra De Breucker
- Department of Geriatrics, CUB Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Niloufar Sadeghi
- Department of Radiology, CUB Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Tim Coolen
- Department of Radiology, CUB Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Serge Goldman
- Laboratoire de Cartographie Fonctionnelle du Cerveau, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
- Clinic of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Philippe Peigneux
- Neuropsychology and Functional Neuroimaging Research Unit (UR2NF), Center for Research in Cognition and Neurosciences, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
| | - Jean-Christophe Bier
- Department of Neurology, CUB Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| | - Xavier De Tiège
- Laboratoire de Cartographie Fonctionnelle du Cerveau, ULB Neuroscience Institute, Université Libre de Bruxelles, Brussels, Belgium
- Clinic of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium
| |
Collapse
|
30
|
Quinn AJ, Green GGR, Hymers M. Delineating between-subject heterogeneity in alpha networks with Spatio-Spectral Eigenmodes. Neuroimage 2021; 240:118330. [PMID: 34237443 PMCID: PMC8456753 DOI: 10.1016/j.neuroimage.2021.118330] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 05/30/2021] [Accepted: 07/01/2021] [Indexed: 12/12/2022] Open
Abstract
A data-driven modal decomposition describes oscillations by their resonant frequency, damping time and network structure. We show that the full multivariate transfer function can be rewritten as a linear superposition of these modes. These modal coordinates factorise oscillatory systems without pre-specification of frequency bands or regions of interest. Using these modes, we find a spatial gradient in alpha peak frequency between Occipital and Parietal cortex . This gradient is highly variable between participants, showing shifts in spatial structure and peak frequency.
Between subject variability in the spatial and spectral structure of oscillatory networks can be highly informative but poses a considerable analytic challenge. Here, we describe a data-driven modal decomposition of a multivariate autoregressive model that simultaneously identifies oscillations by their peak frequency, damping time and network structure. We use this decomposition to define a set of Spatio-Spectral Eigenmodes (SSEs) providing a parsimonious description of oscillatory networks. We show that the multivariate system transfer function can be rewritten in these modal coordinates, and that the full transfer function is a linear superposition of all modes in the decomposition. The modal transfer function is a linear summation and therefore allows for single oscillatory signals to be isolated and analysed in terms of their spectral content, spatial distribution and network structure. We validate the method on simulated data and explore the structure of whole brain oscillatory networks in eyes-open resting state MEG data from the Human Connectome Project. We are able to show a wide between participant variability in peak frequency and network structure of alpha oscillations and show a distinction between occipital ’high-frequency alpha’ and parietal ’low-frequency alpha’. The frequency difference between occipital and parietal alpha components is present within individual participants but is partially masked by larger between subject variability; a 10Hz oscillation may represent the high-frequency occipital component in one participant and the low-frequency parietal component in another. This rich characterisation of individual neural phenotypes has the potential to enhance analyses into the relationship between neural dynamics and a person’s behavioural, cognitive or clinical state.
Collapse
Affiliation(s)
- Andrew J Quinn
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University Department of Psychiatry, Warneford Hospital, Oxford OX3 7JX, UK.
| | - Gary G R Green
- York Neuroimaging Centre, The Biocentre York Science Park, Heslington, York YO10 5NY, UK; Department of Psychology, University of York, Heslington, York YO10 5DD, UK
| | - Mark Hymers
- York Neuroimaging Centre, The Biocentre York Science Park, Heslington, York YO10 5NY, UK; Department of Psychology, University of York, Heslington, York YO10 5DD, UK
| |
Collapse
|
31
|
Neuronal Network Excitability in Alzheimer's Disease: The Puzzle of Similar versus Divergent Roles of Amyloid β and Tau. eNeuro 2021; 8:ENEURO.0418-20.2020. [PMID: 33741601 PMCID: PMC8174042 DOI: 10.1523/eneuro.0418-20.2020] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 12/02/2020] [Accepted: 12/18/2020] [Indexed: 12/12/2022] Open
Abstract
Alzheimer’s disease (AD) is the most frequent neurodegenerative disorder that commonly causes dementia in the elderly. Recent evidence indicates that network abnormalities, including hypersynchrony, altered oscillatory rhythmic activity, interneuron dysfunction, and synaptic depression, may be key mediators of cognitive decline in AD. In this review, we discuss characteristics of neuronal network excitability in AD, and the role of Aβ and tau in the induction of network hyperexcitability. Many patients harboring genetic mutations that lead to increased Aβ production suffer from seizures and epilepsy before the development of plaques. Similarly, pathologic accumulation of hyperphosphorylated tau has been associated with hyperexcitability in the hippocampus. We present common and divergent roles of tau and Aβ on neuronal hyperexcitability in AD, and hypotheses that could serve as a template for future experiments.
Collapse
|
32
|
Maestú F, Fernández A. Role of Magnetoencephalography in the Early Stages of Alzheimer Disease. Neuroimaging Clin N Am 2021; 30:217-227. [PMID: 32336408 DOI: 10.1016/j.nic.2020.01.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
As synaptic dysfunction is an early manifestation of Alzheimer disease (AD) pathology, magnetoencephalography (MEG) is capable of detecting disruptions by assessing the synchronized oscillatory activity of thousands of neurons that rely on the integrity of neural connections. MEG findings include slowness of the oscillatory activity, accompanied by a reduction of the alpha band power, and dysfunction of the functional networks. These findings are associated with the neuropathology of the disease and cognitive impairment. These neurophysiological biomarkers predict which patients with mild cognitive impairment will develop dementia. MEG has demonstrated its utility as a noninvasive biomarker for early detection of AD.
Collapse
Affiliation(s)
- Fernando Maestú
- Department of Experimental Psychology, Complutense University of Madrid, Madrid, Spain; Centro de Tecnología Biomédica, Campus de Montegancedo de la UPM, Pozuelo de Alarcón, Madrid 28223, Spain.
| | - Alberto Fernández
- Centro de Tecnología Biomédica, Campus de Montegancedo de la UPM, Pozuelo de Alarcón, Madrid 28223, Spain; Department of Legal Medicine, Psychiatry and Pathology, Complutense University of Madrid, Madrid, Spain
| |
Collapse
|
33
|
Kim JA, Davis KD. Magnetoencephalography: physics, techniques, and applications in the basic and clinical neurosciences. J Neurophysiol 2021; 125:938-956. [PMID: 33567968 DOI: 10.1152/jn.00530.2020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Magnetoencephalography (MEG) is a technique used to measure the magnetic fields generated from neuronal activity in the brain. MEG has a high temporal resolution on the order of milliseconds and provides a more direct measure of brain activity when compared with hemodynamic-based neuroimaging methods such as magnetic resonance imaging and positron emission tomography. The current review focuses on basic features of MEG such as the instrumentation and the physics that are integral to the signals that can be measured, and the principles of source localization techniques, particularly the physics of beamforming and the techniques that are used to localize the signal of interest. In addition, we review several metrics that can be used to assess functional coupling in MEG and describe the advantages and disadvantages of each approach. Lastly, we discuss the current and future applications of MEG.
Collapse
Affiliation(s)
- Junseok A Kim
- Division of Brain, Imaging and Behaviour, Krembil Brain Institute, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Karen D Davis
- Division of Brain, Imaging and Behaviour, Krembil Brain Institute, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,Department of Surgery, University of Toronto, Toronto, Ontario, Canada
| |
Collapse
|
34
|
Coomans EM, Schoonhoven DN, Tuncel H, Verfaillie SCJ, Wolters EE, Boellaard R, Ossenkoppele R, den Braber A, Scheper W, Schober P, Sweeney SP, Ryan JM, Schuit RC, Windhorst AD, Barkhof F, Scheltens P, Golla SSV, Hillebrand A, Gouw AA, van Berckel BNM. In vivo tau pathology is associated with synaptic loss and altered synaptic function. Alzheimers Res Ther 2021; 13:35. [PMID: 33546722 PMCID: PMC7866464 DOI: 10.1186/s13195-021-00772-0] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Accepted: 01/11/2021] [Indexed: 01/08/2023]
Abstract
BACKGROUND The mechanism of synaptic loss in Alzheimer's disease is poorly understood and may be associated with tau pathology. In this combined positron emission tomography (PET) and magnetoencephalography (MEG) study, we aimed to investigate spatial associations between regional tau pathology ([18F]flortaucipir PET), synaptic density (synaptic vesicle 2A [11C]UCB-J PET) and synaptic function (MEG) in Alzheimer's disease. METHODS Seven amyloid-positive Alzheimer's disease subjects from the Amsterdam Dementia Cohort underwent dynamic 130-min [18F]flortaucipir PET, dynamic 60-min [11C]UCB-J PET with arterial sampling and 2 × 5-min resting-state MEG measurement. [18F]flortaucipir- and [11C]UCB-J-specific binding (binding potential, BPND) and MEG spectral measures (relative delta, theta and alpha power; broadband power; and peak frequency) were assessed in cortical brain regions of interest. Associations between regional [18F]flortaucipir BPND, [11C]UCB-J BPND and MEG spectral measures were assessed using Spearman correlations and generalized estimating equation models. RESULTS Across subjects, higher regional [18F]flortaucipir uptake was associated with lower [11C]UCB-J uptake. Within subjects, the association between [11C]UCB-J and [18F]flortaucipir depended on within-subject neocortical tau load; negative associations were observed when neocortical tau load was high, gradually changing into opposite patterns with decreasing neocortical tau burden. Both higher [18F]flortaucipir and lower [11C]UCB-J uptake were associated with altered synaptic function, indicative of slowing of oscillatory activity, most pronounced in the occipital lobe. CONCLUSIONS These results indicate that in Alzheimer's disease, tau pathology is closely associated with reduced synaptic density and synaptic dysfunction.
Collapse
Affiliation(s)
- Emma M Coomans
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
| | - Deborah N Schoonhoven
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Hayel Tuncel
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Sander C J Verfaillie
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Emma E Wolters
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Ronald Boellaard
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Anouk den Braber
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Wiep Scheper
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Clinical Genetics, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, The Netherlands
- Center for Neurogenomics and Cognitive Research, Department of Functional Genomics, Faculty of Science, Vrije Universiteit, Amsterdam, The Netherlands
| | - Patrick Schober
- Department of Anaesthesiology, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | | | | | - Robert C Schuit
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Albert D Windhorst
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- UCL Institutes of Neurology and Healthcare Engineering, London, UK
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Sandeep S V Golla
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Alida A Gouw
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Clinical Neurophysiology and MEG Center, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| |
Collapse
|
35
|
Xing H, Xu S, Xie X, Wang Y, Lu C, Han X. Levetiracetam induction of theta frequency oscillations in rodent hippocampus in vitro. Can J Physiol Pharmacol 2020; 98:725-732. [PMID: 32516556 DOI: 10.1139/cjpp-2019-0727] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Levetiracetam (LEV) has been demonstrated to improve cognitive function. Hippocampal theta rhythm (4-12 Hz) is associated with a variety of cognitively related behaviors, such as exploration in both humans and animal models. We investigated the effects of LEV on the theta rhythm in the rat hippocampal CA3 in hippocampal slices in vitro. We found that LEV increased the theta power in a dose-dependent manner. The increase in theta power can be blocked by GABAA receptor (GABAAR) or NMDA receptor (NMDAR) antagonists but not by AMPA receptor antagonist, indicating the involvement of GABAAR and NMDAR in the induction of theta activity. Interestingly, LEV enhancement of theta power can be also blocked by taurine or GABA-A agonist THIP, indicating that LEV induction of theta may be related to the indirect boosting of GABA action via reduction of extrasynaptic GABAAR activation. Furthermore, the increased theta power can be partially reduced by the mACh receptor (mAChR) antagonist atropine but not by nACh receptor antagonists, suggesting that mAChR activation provides excitatory input into local network responsible for LEV-induced theta. Our study demonstrated that LEV induced a novel theta oscillation in vitro, which may have implications in the treatment of the neuronal disorders with impaired theta oscillation and cognitive function.
Collapse
Affiliation(s)
- Hang Xing
- Key Lab of Brain Research of Henan Province, Department of Physiology and Neurobiology, Xinxiang Medical University, Henan, 453000, P.R. China.,Department of Neurology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, Henan, 450000, P.R. China
| | - Sihan Xu
- Key Lab of Brain Research of Henan Province, Department of Physiology and Neurobiology, Xinxiang Medical University, Henan, 453000, P.R. China
| | - Xin'e Xie
- Key Lab of Brain Research of Henan Province, Department of Physiology and Neurobiology, Xinxiang Medical University, Henan, 453000, P.R. China
| | - Yuan Wang
- Key Lab of Brain Research of Henan Province, Department of Physiology and Neurobiology, Xinxiang Medical University, Henan, 453000, P.R. China
| | - Chengbiao Lu
- Key Lab of Brain Research of Henan Province, Department of Physiology and Neurobiology, Xinxiang Medical University, Henan, 453000, P.R. China
| | - Xiong Han
- Department of Neurology, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, Henan, 450000, P.R. China
| |
Collapse
|
36
|
Soltani Zangbar H, Ghadiri T, Seyedi Vafaee M, Ebrahimi Kalan A, Fallahi S, Ghorbani M, Shahabi P. Theta Oscillations Through Hippocampal/Prefrontal Pathway: Importance in Cognitive Performances. Brain Connect 2020; 10:157-169. [PMID: 32264690 DOI: 10.1089/brain.2019.0733] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Among various hippocampal rhythms, including sharp-wave ripples, gamma, and theta, theta rhythm is crucial for cognitive processing, particularly learning and memory. Theta oscillations are observable in both humans and rodents during spatial navigations. However, the hippocampus (Hip) is well known as the generator of current rhythm, and other brain areas, such as prefrontal cortex (PFC), can be affected by theta rhythm, too. The PFC is a core structure for the execution of diverse higher cortical functions defined as cognition. This region is connected to the hippocampus through the hippocampal/prefrontal pathway; hereby, theta oscillations convey hippocampal inputs to the PFC and simultaneously synchronize the activity of these two regions during memory, learning and other cognitive tasks. Importantly, thalamic nucleus reunions (nRE) and basolateral amygdala are salient relay structures modulating the synchronization, firing rate, and phase-locking of the hippocampal/prefrontal oscillations. Herein, we summarized experimental studies, chiefly animal researches in which the theta rhythm of the Hip-PFC axis was investigated using either electrophysiological assessments in rodent or integrated diffusion-weighted imaging and electroencephalography in human cases under memory-based tasks. Moreover, we briefly reviewed alterations of theta rhythm in some CNS diseases with the main feature of cognitive disturbance. Interestingly, animal studies implied the interruption of theta synchronization in psychiatric disorders such as schizophrenia and depression. To disclose the precise role of theta rhythm fluctuations through the Hip-PFC axis in cognitive performances, further studies are needed.
Collapse
Affiliation(s)
- Hamid Soltani Zangbar
- Department of Neuroscience and Cognition, Faculty of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran.,Aging Research Institute, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Tahereh Ghadiri
- Department of Neuroscience and Cognition, Faculty of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
| | | | - Abbas Ebrahimi Kalan
- Department of Neuroscience and Cognition, Faculty of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Solmaz Fallahi
- Department of Physiology, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Meysam Ghorbani
- Department of Physiology, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Parviz Shahabi
- Aging Research Institute, Tabriz University of Medical Sciences, Tabriz, Iran
| |
Collapse
|
37
|
Abnormal alpha band power in the dynamic pain connectome is a marker of chronic pain with a neuropathic component. NEUROIMAGE-CLINICAL 2020; 26:102241. [PMID: 32203904 PMCID: PMC7090370 DOI: 10.1016/j.nicl.2020.102241] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/29/2019] [Revised: 02/25/2020] [Accepted: 03/10/2020] [Indexed: 01/08/2023]
Abstract
High theta and low gamma activity in the dynamic pain connectome is linked to chronic pain. High alpha-band activity is present when neuropathic pain is likely. Spectral frequency band strength distinguish neuropathic from non-neuropathic pain.
We previously identified alpha frequency slowing and beta attenuation in the dynamic pain connectome related to pain severity and interference in patients with multiple sclerosis-related neuropathic pain (NP). Here, we determined whether these abnormalities, are markers of aberrant temporal dynamics in non-neuropathic inflammatory pain (non-NP) or when NP is also suspected. We measured resting-state magnetoencephalography (MEG) spectral density in 45 people (17 females, 28 males) with chronic back pain due to ankylosing spondylitis (AS) and 38 age/sex matched healthy controls. We used painDETECT scores to divide the chronic pain group into those with only non-NP (NNP) and those who likely also had a component of NP in addition to their inflammatory pain. We also assessed pain severity, pain interference, and disease activity with the Brief Pain Inventory and Bath AS Disease Activity Index (BASDAI). We examined spectral power in the dynamic pain connectome, including nodes of the ascending nociceptive pathway (ANP), default mode (DMN), and salience networks (SN). Compared to the healthy controls, the AS patients exhibited increased theta power in the DMN and decreased low-gamma power in the DMN and ANP, but did not exhibit beta-band attenuation or peak-alpha slowing. The NNP patients were not different from HCs. Compared to both healthy controls and NNP, NP patients had increased alpha power in the ANP. Increased alpha power within the ANP was associated with reduced BASDAI in the NNP group, and increased pain in the mixed-NP group within the DMN, SN, and ANP. Thus, high theta and low gamma activity may be markers of chronic pain but high alpha-band activity may relate to particular features of neuropathic chronic pain.
Collapse
|
38
|
Tait L, Stothart G, Coulthard E, Brown JT, Kazanina N, Goodfellow M. Network substrates of cognitive impairment in Alzheimer’s Disease. Clin Neurophysiol 2019; 130:1581-1595. [DOI: 10.1016/j.clinph.2019.05.027] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Revised: 03/26/2019] [Accepted: 05/17/2019] [Indexed: 12/28/2022]
|
39
|
Douw L, van Dellen E, Gouw AA, Griffa A, de Haan W, van den Heuvel M, Hillebrand A, Van Mieghem P, Nissen IA, Otte WM, Reijmer YD, Schoonheim MM, Senden M, van Straaten ECW, Tijms BM, Tewarie P, Stam CJ. The road ahead in clinical network neuroscience. Netw Neurosci 2019; 3:969-993. [PMID: 31637334 PMCID: PMC6777944 DOI: 10.1162/netn_a_00103] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 07/23/2019] [Indexed: 12/15/2022] Open
Abstract
Clinical network neuroscience, the study of brain network topology in neurological and psychiatric diseases, has become a mainstay field within clinical neuroscience. Being a multidisciplinary group of clinical network neuroscience experts based in The Netherlands, we often discuss the current state of the art and possible avenues for future investigations. These discussions revolve around questions like "How do dynamic processes alter the underlying structural network?" and "Can we use network neuroscience for disease classification?" This opinion paper is an incomplete overview of these discussions and expands on ten questions that may potentially advance the field. By no means intended as a review of the current state of the field, it is instead meant as a conversation starter and source of inspiration to others.
Collapse
Affiliation(s)
- Linda Douw
- Department of Anatomy and Neuroscience, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Edwin van Dellen
- Department of Psychiatry, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
- Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Alida A. Gouw
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Alessandra Griffa
- Connectome Lab, Department of Neuroscience, section Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Willem de Haan
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Martijn van den Heuvel
- Connectome Lab, Department of Neuroscience, section Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Clinical Genetics, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Piet Van Mieghem
- Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands
| | - Ida A. Nissen
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Willem M. Otte
- Biomedical MR Imaging and Spectroscopy Group, Center for Image Sciences, University Medical Center Utrecht and Utrecht University, Utrecht, The Netherlands
- Department of Pediatric Neurology, Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Yael D. Reijmer
- Department of Neurology, Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Menno M. Schoonheim
- Department of Anatomy and Neuroscience, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Mario Senden
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Maastricht Brain Imaging Centre, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Elisabeth C. W. van Straaten
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Betty M. Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Prejaas Tewarie
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Cornelis J. Stam
- Department of Neurology, Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| |
Collapse
|
40
|
Tarasova IV, Akbirov RM, Tarasov RS, Trubnikova OA, Barbarash OL. [Electric brain activity in patients with simultaneous coronary artery bypass grafting and carotid endarterectomy]. Zh Nevrol Psikhiatr Im S S Korsakova 2019; 119:41-47. [PMID: 31464288 DOI: 10.17116/jnevro201911907141] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
AIM To analyze the postoperative electroencephalography (EEG) power changes in patients after simultaneous coronary artery bypass grafting (CABG) and a left- or right-sided carotid endarterectomy (CEE). MATERIAL AND METHODS Forty-four patients with indications for surgical myocardial revascularization, including 24 patients with indications for CEE, were studied. Patients after simultaneous coronary and carotid surgery were divided into groups depending on the side of CEE: the left+CEE CABG group included 14 patients, the right CEE+CABG group included 10 patients. The group of isolated CABG consisted of 20 patients. The resting-state EEG with closed eyes was recorded before and at the 7-10th day after surgery. The changes of the spectral power (μV2/Hz), theta1 (4-6 Hz), theta2 (6-8 Hz), alpha1 (8-10 Hz), alpha2 (10-13 Hz) rhythms were analyzed, the hemispheric asymmetry (HA) coefficient of the rhythms was calculated. RESULTS AND CONCLUSION In the early postoperative period, the power of theta1 and theta2 rhythms increased compared to the preoperative level regardless of the type of cardiosurgical intervention. A local character of postoperative theta activity changes was revealed in the left+CEE CABG group, whereas the most pronounced decrease of the alpha-rhythm HA coefficient was observed in the right CEE+CABG group at the 7-10th day after surgery in comparison to the preoperative level. The results of the study suggest that the simultaneous coronary and carotid surgery does not significantly exacerbate the severity of brain damage compared to isolated CABG.
Collapse
Affiliation(s)
- I V Tarasova
- Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| | - R M Akbirov
- Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| | - R S Tarasov
- Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| | - O A Trubnikova
- Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| | - O L Barbarash
- Research Institute for Complex Issues of Cardiovascular Diseases, Kemerovo, Russia
| |
Collapse
|
41
|
Nakamura A, Cuesta P, Fernández A, Arahata Y, Iwata K, Kuratsubo I, Bundo M, Hattori H, Sakurai T, Fukuda K, Washimi Y, Endo H, Takeda A, Diers K, Bajo R, Maestú F, Ito K, Kato T. Electromagnetic signatures of the preclinical and prodromal stages of Alzheimer's disease. Brain 2019. [PMID: 29522156 PMCID: PMC5920328 DOI: 10.1093/brain/awy044] [Citation(s) in RCA: 87] [Impact Index Per Article: 17.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Biomarkers useful for the predementia stages of Alzheimer’s disease are needed. Electroencephalography and magnetoencephalography (MEG) are expected to provide potential biomarker candidates for evaluating the predementia stages of Alzheimer’s disease. However, the physiological relevance of EEG/MEG signal changes and their role in pathophysiological processes such as amyloid-β deposition and neurodegeneration need to be elucidated. We evaluated 28 individuals with mild cognitive impairment and 38 cognitively normal individuals, all of whom were further classified into amyloid-β-positive mild cognitive impairment (n = 17, mean age 74.7 ± 5.4 years, nine males), amyloid-β-negative mild cognitive impairment (n = 11, mean age 73.8 ± 8.8 years, eight males), amyloid-β-positive cognitively normal (n = 13, mean age 71.8 ± 4.4 years, seven males), and amyloid-β-negative cognitively normal (n = 25, mean age 72.5 ± 3.4 years, 11 males) individuals using Pittsburgh compound B-PET. We measured resting state MEG for 5 min with the eyes closed, and investigated regional spectral patterns of MEG signals using atlas-based region of interest analysis. Then, the relevance of the regional spectral patterns and their associations with pathophysiological backgrounds were analysed by integrating information from Pittsburgh compound B-PET, fluorodeoxyglucose-PET, structural MRI, and cognitive tests. The results demonstrated that regional spectral patterns of resting state activity could be separated into several types of MEG signatures as follows: (i) the effects of amyloid-β deposition were expressed as the alpha band power augmentation in medial frontal areas; (ii) the delta band power increase in the same region was associated with disease progression within the Alzheimer’s disease continuum and was correlated with entorhinal atrophy and an Alzheimer’s disease-like regional decrease in glucose metabolism; and (iii) the global theta power augmentation, which was previously considered to be an Alzheimer’s disease-related EEG/MEG signature, was associated with general cognitive decline and hippocampal atrophy, but was not specific to Alzheimer’s disease because these changes could be observed in the absence of amyloid-β deposition. The results suggest that these MEG signatures may be useful as unique biomarkers for the predementia stages of Alzheimer’s disease.
Collapse
Affiliation(s)
- Akinori Nakamura
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Pablo Cuesta
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan.,Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, 28223, Spain.,Electrical Engineering and Bioengineering Lab, Department of Industrial Engineering, University of La Laguna, Tenerife, 38200, Spain
| | - Alberto Fernández
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, 28223, Spain.,Department of Psychiatry, Faculty of Medicine, Complutense University of Madrid, Madrid, 28040, Spain
| | - Yutaka Arahata
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan.,Innovation Center for Clinical Research, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Kaori Iwata
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Izumi Kuratsubo
- Innovation Center for Clinical Research, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Masahiko Bundo
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan.,National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Hideyuki Hattori
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Takashi Sakurai
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Koji Fukuda
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Yukihiko Washimi
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Hidetoshi Endo
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Akinori Takeda
- National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Kersten Diers
- Department of Psychology, Technische Universität Dresden, Dresden, 01069, Germany
| | - Ricardo Bajo
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, 28223, Spain
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Madrid, 28223, Spain.,Department of Basic Psychology II, Complutense University of Madrid, Madrid, 28223, Spain
| | - Kengo Ito
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan.,National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan.,Innovation Center for Clinical Research, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| | - Takashi Kato
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan.,National Hospital for Geriatric Medicine, National Center for Geriatrics and Gerontology, Obu, 474-8511, Japan
| |
Collapse
|
42
|
Hughes LE, Henson RN, Pereda E, Bruña R, López-Sanz D, Quinn AJ, Woolrich MW, Nobre AC, Rowe JB, Maestú F. Biomagnetic biomarkers for dementia: A pilot multicentre study with a recommended methodological framework for magnetoencephalography. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2019; 11:450-462. [PMID: 31431918 PMCID: PMC6579903 DOI: 10.1016/j.dadm.2019.04.009] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Introduction An increasing number of studies are using magnetoencephalography (MEG) to study dementia. Here we define a common methodological framework for MEG resting-state acquisition and analysis to facilitate the pooling of data from different sites. Methods Two groups of patients with mild cognitive impairment (MCI, n = 84) and healthy controls (n = 84) were combined from three sites, and site and group differences inspected in terms of power spectra and functional connectivity. Classification accuracy for MCI versus controls was compared across three different types of MEG analyses, and compared with classification based on structural MRI. Results The spectral analyses confirmed frequency-specific differences in patients with MCI, both in power and connectivity patterns, with highest classification accuracy from connectivity. Critically, site acquisition differences did not dominate the results. Discussion This work provides detailed protocols and analyses that are sensitive to cognitive impairment, and that will enable standardized data sharing to facilitate large-scale collaborative projects.
Collapse
Affiliation(s)
- Laura E Hughes
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.,MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Richard N Henson
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK.,Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Ernesto Pereda
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology, Madrid, Spain.,Department of Industrial Engineering, Instituto Universitario de Neurociencia, Universidad de La Laguna, Tenerife, Spain
| | - Ricardo Bruña
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology, Madrid, Spain.,Biomedical Research Networking Center in Bioengineering Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain.,Department of Experimental Psychology, Faculty of Psychology, Universidad Complutense de Madrid, Madrid, Spain
| | - David López-Sanz
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology, Madrid, Spain.,Department of Experimental Psychology, Faculty of Psychology, Universidad Complutense de Madrid, Madrid, Spain
| | - Andrew J Quinn
- Oxford Centre for Human Brain Activity, University of Oxford, Oxford, UK.,Wellcome Centre for Integrative Neuroscience, University of Oxford, Oxford, UK
| | - Mark W Woolrich
- Oxford Centre for Human Brain Activity, University of Oxford, Oxford, UK.,Wellcome Centre for Integrative Neuroscience, University of Oxford, Oxford, UK
| | - Anna C Nobre
- Oxford Centre for Human Brain Activity, University of Oxford, Oxford, UK.,Wellcome Centre for Integrative Neuroscience, University of Oxford, Oxford, UK.,Department of Experimental Psychology, University of Oxford, Oxford, UK
| | - James B Rowe
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.,MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology, Madrid, Spain.,Biomedical Research Networking Center in Bioengineering Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain.,Department of Experimental Psychology, Faculty of Psychology, Universidad Complutense de Madrid, Madrid, Spain
| | | |
Collapse
|
43
|
López-Sanz D, Bruña R, de Frutos-Lucas J, Maestú F. Magnetoencephalography applied to the study of Alzheimer's disease. PROGRESS IN MOLECULAR BIOLOGY AND TRANSLATIONAL SCIENCE 2019; 165:25-61. [PMID: 31481165 DOI: 10.1016/bs.pmbts.2019.04.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Magnetoencephalography (MEG) is a relatively modern neuroimaging technique able to study normal and pathological brain functioning with temporal resolution in the order of milliseconds and adequate spatial resolution. Although its clinical applications are still relatively limited, great advances have been made in recent years in the field of dementia and Alzheimer's disease (AD) in particular. In this chapter, we briefly describe the physiological phenomena underlying MEG brain signals and the different metrics that can be computed from these data in order to study the alterations disrupting brain activity not only in demented patients, but also in the preclinical and prodromal stages of the disease. Changes in non-linear brain dynamics, power spectral properties, functional connectivity and network topological changes observed in AD are narratively summarized in the context of the pathophysiology of the disease. Furthermore, the potential of MEG as a potential biomarker to identify AD pathology before dementia onset is discussed in the light of current knowledge and the relationship between potential MEG biomarkers and current established hallmarks of the disease is also reviewed. To this aim, findings from different approaches such as resting state or during the performance of different cognitive paradigms are discussed.Lastly, there is an increasing interest in current scientific literature in promoting interventions aimed at modifying certain lifestyles, such as nutrition or physical activity among others, thought to reduce or delay AD risk. We discuss the utility of MEG as a potential marker of the success of such interventions from the available literature.
Collapse
Affiliation(s)
- David López-Sanz
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology (CTB), Technical University of Madrid (UPM), Madrid, Spain; Department of Experimental Psychology, Complutense University of Madrid (UCM), Madrid, Spain
| | - Ricardo Bruña
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology (CTB), Technical University of Madrid (UPM), Madrid, Spain; Department of Experimental Psychology, Complutense University of Madrid (UCM), Madrid, Spain; Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Zaragoza, Spain
| | - Jaisalmer de Frutos-Lucas
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology (CTB), Technical University of Madrid (UPM), Madrid, Spain; Biological and Health Psychology Department, Universidad Autonoma de Madrid, Madrid, Spain; School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Fernando Maestú
- Laboratory of Cognitive and Computational Neuroscience (UCM-UPM), Centre for Biomedical Technology (CTB), Technical University of Madrid (UPM), Madrid, Spain; Department of Experimental Psychology, Complutense University of Madrid (UCM), Madrid, Spain; Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Zaragoza, Spain.
| |
Collapse
|
44
|
Tarasova IV, Trubnikova OA, Barbarash OL. EEG and Clinical Factors Associated with Mild Cognitive Impairment in Coronary Artery Disease Patients. Dement Geriatr Cogn Disord 2019; 46:275-284. [PMID: 30404079 DOI: 10.1159/000493787] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2018] [Accepted: 09/15/2018] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Although an impaired cognitive status in patients with coronary artery disease (CAD) is not rare, the neurophysiological and clinical indicators of mild cognitive impairment (MCI) have been insufficiently investigated so far. METHODS EEG and neuropsychological testing as well as clinical examination were performed on 122 patients with CAD, who were divided into two groups, those with MCI (n = 60; mean age 57.4 ± 5.81 years) and those without MCI (n = 62; mean age 57.0 ± 5.04 years). Binary logistic regression was used to identify the relationship between EEG and clinical variables and the probability of MCI. RESULTS Higher theta/alpha ratios, theta1 rhythm power with closed eyes in the frontal and occipital areas of the left hemisphere, and alpha2 rhythm power with eyes open in the frontal areas of the right hemisphere were associated with an increased risk for MCI in CAD patients. A low educational level, type 2 diabetes mellitus, and severe coronary lesions according to the SYNTAX Score (≥23 points) increased the risk for MCI as well. CONCLUSIONS The findings of our study show that a theta activity increase in frontal and occipital sites, as well as high theta/alpha ratios, may be considered as the earliest EEG markers of vascular cognitive disorders.
Collapse
Affiliation(s)
- Irina V Tarasova
- Department of Cardiovascular Diagnostics, Federal State Budgetary Institution "Research Institute for Complex Issues of Cardiovascular Diseases", Kemerovo, Russian Federation,
| | - Olga A Trubnikova
- Department of Multifocal Atherosclerosis, Federal State Budgetary Institution "Research Institute for Complex Issues of Cardiovascular Diseases", Kemerovo, Russian Federation
| | - Olga L Barbarash
- Department of Multifocal Atherosclerosis, Federal State Budgetary Institution "Research Institute for Complex Issues of Cardiovascular Diseases", Kemerovo, Russian Federation
| |
Collapse
|
45
|
Labyt E, Corsi MC, Fourcault W, Palacios Laloy A, Bertrand F, Lenouvel F, Cauffet G, Le Prado M, Berger F, Morales S. Magnetoencephalography With Optically Pumped 4He Magnetometers at Ambient Temperature. IEEE TRANSACTIONS ON MEDICAL IMAGING 2019; 38:90-98. [PMID: 30010553 DOI: 10.1109/tmi.2018.2856367] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
In this paper, we present the first proof of concept confirming the possibility to record magnetoencephalographic (MEG) signals with optically pumped magnetometers (OPMs) based on the parametric resonance of 4He atoms. The main advantage of this kind of OPM is the possibility to provide a tri-axis vector measurement of the magnetic field at room-temperature (the 4He vapor is neither cooled nor heated). The sensor achieves a sensitivity of 210 fT/ √ Hz in the bandwidth [2-300 Hz]. MEG simulation studies with a brain phantom were cross-validated with real MEG measurements on a healthy subject. For both studies, MEG signal was recorded consecutively with OPMs and superconducting quantum interference devices (SQUIDs) used as reference sensors. For healthy subject MEG recordings, three MEG proofs of concept were carried out: auditory evoked fields, visual evoked fields, and spontaneous activity. M100 peaks have been detected on evoked responses recorded by both OPMs and SQUIDs with no significant difference in latency. Concerning spontaneous activity, an attenuation of the signal power between 8-12 Hz (alpha band) related to eyes opening has been observed with OPM similarly to SQUID. All these results confirm that the room temperature vector 4He OPMs can record MEG signals and provide reliable information on brain activity.
Collapse
|
46
|
Jacini F, Sorrentino P, Lardone A, Rucco R, Baselice F, Cavaliere C, Aiello M, Orsini M, Iavarone A, Manzo V, Carotenuto A, Granata C, Hillebrand A, Sorrentino G. Amnestic Mild Cognitive Impairment Is Associated With Frequency-Specific Brain Network Alterations in Temporal Poles. Front Aging Neurosci 2018; 10:400. [PMID: 30574086 PMCID: PMC6291511 DOI: 10.3389/fnagi.2018.00400] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Accepted: 11/20/2018] [Indexed: 12/13/2022] Open
Abstract
There is general agreement that the neuropathological processes leading to Alzheimer’s disease (AD) begin decades before the clinical onset. In order to detect early topological changes, we applied functional connectivity and network analysis to magnetoencephalographic (MEG) data obtained from 16 patients with amnestic Mild Cognitive Impairment (aMCI), a prodromal stage of AD, and 16 matched healthy control (HCs). Significant differences between the two groups were found in the theta band, which is associated with memory processes, in both temporal poles (TPs). In aMCI, the degree and betweenness centrality (BC) were lower in the left superior TP, whereas in the right middle TP the BC was higher. A statistically significant negative linear correlation was found between the BC of the left superior TP and a delayed recall score, a sensitive marker of the “hippocampal memory” deficit in early AD. Our results suggest that the TPs, which are involved early in AD pathology and belong to the memory circuitry, have an altered role in the functional network in aMCI.
Collapse
Affiliation(s)
- Francesca Jacini
- Department of Motor Sciences and Wellness, Parthenope University of Naples, Naples, Italy.,Institute for Diagnosis and Cure Hermitage Capodimonte, Naples, Italy
| | - Pierpaolo Sorrentino
- Department of Engineering, Parthenope University of Naples, Naples, Italy.,Department of Clinical Neurophysiology and MEG Center, VU University Medical Center Amsterdam, Amsterdam, Netherlands
| | - Anna Lardone
- Department of Motor Sciences and Wellness, Parthenope University of Naples, Naples, Italy.,Institute for Diagnosis and Cure Hermitage Capodimonte, Naples, Italy
| | - Rosaria Rucco
- Department of Motor Sciences and Wellness, Parthenope University of Naples, Naples, Italy.,Institute for Diagnosis and Cure Hermitage Capodimonte, Naples, Italy
| | - Fabio Baselice
- Department of Engineering, Parthenope University of Naples, Naples, Italy
| | - Carlo Cavaliere
- Diagnostic and Nuclear Research Institute, IRCCS SDN, Naples, Italy
| | - Marco Aiello
- Diagnostic and Nuclear Research Institute, IRCCS SDN, Naples, Italy
| | - Mario Orsini
- Diagnostic and Nuclear Research Institute, IRCCS SDN, Naples, Italy
| | - Alessandro Iavarone
- Neurological and Stroke Unit, CTO Hospital-AORN Ospedale dei Colli, Naples, Italy
| | | | | | - Carmine Granata
- Institute of Applied Sciences and Intelligent Systems, CNR, Pozzuoli, Italy
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, VU University Medical Center Amsterdam, Amsterdam, Netherlands
| | - Giuseppe Sorrentino
- Department of Motor Sciences and Wellness, Parthenope University of Naples, Naples, Italy.,Institute for Diagnosis and Cure Hermitage Capodimonte, Naples, Italy
| |
Collapse
|
47
|
Schoonhoven DN, Fraschini M, Tewarie P, Uitdehaag BM, Eijlers AJ, Geurts JJ, Hillebrand A, Schoonheim MM, Stam CJ, Strijbis EM. Resting-state MEG measurement of functional activation as a biomarker for cognitive decline in MS. Mult Scler 2018; 25:1896-1906. [PMID: 30465461 PMCID: PMC6875827 DOI: 10.1177/1352458518810260] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Neurophysiological measures of brain function, such as magnetoencephalography (MEG), are widely used in clinical neurology and have strong relations with cognitive impairment and dementia but are still underdeveloped in multiple sclerosis (MS). OBJECTIVES To demonstrate the value of clinically applicable MEG-measures in evaluating cognitive impairment in MS. METHODS In eyes-closed resting-state, MEG data of 83 MS patients and 34 healthy controls (HCs) peak frequencies and relative power of six canonical frequency bands for 78 cortical and 10 deep gray matter (DGM) areas were calculated. Linear regression models, correcting for age, gender, and education, assessed the relation between cognitive performance and MEG biomarkers. RESULTS Increased alpha1 and theta power was strongly associated with impaired cognition in patients, which differed between cognitively impaired (CI) patients and HCs in bilateral parietotemporal cortices. CI patients had a lower peak frequency than HCs. Oscillatory slowing was also widespread in the DGM, most pronounced in the thalamus. CONCLUSION There is a clinically relevant slowing of neuronal activity in MS patients in parietotemporal cortical areas and the thalamus, strongly related to cognitive impairment. These measures hold promise for the application of resting-state MEG as a biomarker for cognitive disturbances in MS in a clinical setting.
Collapse
Affiliation(s)
- Deborah N Schoonhoven
- Departments of Neurology and Clinical Neurophysiology, Magnetoencephalography Center Amsterdam UMC, location VUmc, Amsterdam, The Netherlands
| | - Matteo Fraschini
- Departments of Neurology and Clinical Neurophysiology, Magnetoencephalography Center Amsterdam UMC, location VUmc, Amsterdam, The Netherlands/Department of Electrical and Electronic Engineering, University of Cagliari, Cagliari, Italy
| | - Prejaas Tewarie
- Departments of Neurology and Clinical Neurophysiology, Magnetoencephalography Center Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
| | - Bernard Mj Uitdehaag
- Department of Neurology, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
| | - Anand Jc Eijlers
- Department of Anatomy and Neurosciences, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
| | - Jeroen Jg Geurts
- Department of Anatomy and Neurosciences, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Department of Clini cal Neurophysiology, Magnetoencephalography Center Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology, Magnetoencephalography Center Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
| | - Eva Mm Strijbis
- Departments of Neurology and Clinical Neurophysiology, Magnetoencephalography Center Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
| |
Collapse
|
48
|
Bi XA, Jiang Q, Sun Q, Shu Q, Liu Y. Analysis of Alzheimer's Disease Based on the Random Neural Network Cluster in fMRI. Front Neuroinform 2018; 12:60. [PMID: 30245623 PMCID: PMC6137384 DOI: 10.3389/fninf.2018.00060] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2018] [Accepted: 08/22/2018] [Indexed: 01/16/2023] Open
Abstract
As Alzheimer’s disease (AD) is featured with degeneration and irreversibility, the diagnosis of AD at early stage is important. In recent years, some researchers have tried to apply neural network (NN) to classify AD patients from healthy controls (HC) based on functional MRI (fMRI) data. But most study focus on a single NN and the classification accuracy was not high. Therefore, this paper used the random neural network cluster which was composed of multiple NNs to improve classification performance. Sixty one subjects (25 AD and 36 HC) were acquired from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. This method not only could be used in the classification, but also could be used for feature selection. Firstly, we chose Elman NN from five types of NNs as the optimal base classifier of random neural network cluster based on the results of feature selection, and the accuracies of the random Elman neural network cluster could reach to 92.31% which was the highest and stable. Then we used the random Elman neural network cluster to select significant features and these features could be used to find out the abnormal regions. Finally, we found out 23 abnormal regions such as the precentral gyrus, the frontal gyrus and supplementary motor area. These results fully show that the random neural network cluster is worthwhile and meaningful for the diagnosis of AD.
Collapse
Affiliation(s)
- Xia-An Bi
- College of Information Science and Engineering, Hunan Normal University, Changsha, China
| | - Qin Jiang
- College of Information Science and Engineering, Hunan Normal University, Changsha, China
| | - Qi Sun
- College of Information Science and Engineering, Hunan Normal University, Changsha, China
| | - Qing Shu
- College of Information Science and Engineering, Hunan Normal University, Changsha, China
| | - Yingchao Liu
- College of Information Science and Engineering, Hunan Normal University, Changsha, China
| |
Collapse
|
49
|
Neuropathic pain and pain interference are linked to alpha-band slowing and reduced beta-band magnetoencephalography activity within the dynamic pain connectome in patients with multiple sclerosis. Pain 2018; 160:187-197. [DOI: 10.1097/j.pain.0000000000001391] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
|
50
|
Mandal PK, Banerjee A, Tripathi M, Sharma A. A Comprehensive Review of Magnetoencephalography (MEG) Studies for Brain Functionality in Healthy Aging and Alzheimer's Disease (AD). Front Comput Neurosci 2018; 12:60. [PMID: 30190674 PMCID: PMC6115612 DOI: 10.3389/fncom.2018.00060] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2018] [Accepted: 07/09/2018] [Indexed: 12/16/2022] Open
Abstract
Neural oscillations were established with their association with neurophysiological activities and the altered rhythmic patterns are believed to be linked directly to the progression of cognitive decline. Magnetoencephalography (MEG) is a non-invasive technique to record such neuronal activity due to excellent temporal and fair amount of spatial resolution. Single channel, connectivity as well as brain network analysis using MEG data in resting state and task-based experiments were analyzed from existing literature. Single channel analysis studies reported a less complex, more regular and predictable oscillations in Alzheimer's disease (AD) primarily in the left parietal, temporal and occipital regions. Investigations on both functional connectivity (FC) and effective (EC) connectivity analysis demonstrated a loss of connectivity in AD compared to healthy control (HC) subjects found in higher frequency bands. It has been reported from multiplex network of MEG study in AD in the affected regions of hippocampus, posterior default mode network (DMN) and occipital areas, however, conclusions cannot be drawn due to limited availability of clinical literature. Potential utilization of high spatial resolution in MEG likely to provide information related to in-depth brain functioning and underlying factors responsible for changes in neuronal waves in AD. This review is a comprehensive report to investigate diagnostic biomarkers for AD may be identified by from MEG data. It is also important to note that MEG data can also be utilized for the same pursuit in combination with other imaging modalities.
Collapse
Affiliation(s)
- Pravat K. Mandal
- Neuroimaging and Neurospectroscopy Lab, National Brain Research Centre, Gurgaon, India
- Department of Neurodegeneration, Florey Institute of Neuroscience and Mental Health, Melbourne, VIC, Australia
| | - Anwesha Banerjee
- Neuroimaging and Neurospectroscopy Lab, National Brain Research Centre, Gurgaon, India
| | - Manjari Tripathi
- Department of Neurology, All Indian Institute of Medical Sciences, New Delhi, India
| | - Ankita Sharma
- Neuroimaging and Neurospectroscopy Lab, National Brain Research Centre, Gurgaon, India
| |
Collapse
|