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Trubshaw M, Gohil C, Yoganathan K, Kohl O, Edmond E, Proudfoot M, Thompson AG, Talbot K, Stagg CJ, Nobre AC, Woolrich M, Turner MR. The cortical neurophysiological signature of amyotrophic lateral sclerosis. Brain Commun 2024; 6:fcae164. [PMID: 38779353 PMCID: PMC11109820 DOI: 10.1093/braincomms/fcae164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 03/11/2024] [Accepted: 03/09/2024] [Indexed: 05/25/2024] Open
Abstract
The progressive loss of motor function characteristic of amyotrophic lateral sclerosis is associated with widespread cortical pathology extending beyond primary motor regions. Increasing muscle weakness reflects a dynamic, variably compensated brain network disorder. In the quest for biomarkers to accelerate therapeutic assessment, the high temporal resolution of magnetoencephalography is uniquely able to non-invasively capture micro-magnetic fields generated by neuronal activity across the entire cortex simultaneously. This study examined task-free magnetoencephalography to characterize the cortical oscillatory signature of amyotrophic lateral sclerosis for having potential as a pharmacodynamic biomarker. Eight to ten minutes of magnetoencephalography in the task-free, eyes-open state was recorded in amyotrophic lateral sclerosis (n = 36) and healthy age-matched controls (n = 51), followed by a structural MRI scan for co-registration. Extracted magnetoencephalography metrics from the delta, theta, alpha, beta, low-gamma, high-gamma frequency bands included oscillatory power (regional activity), 1/f exponent (complexity) and amplitude envelope correlation (connectivity). Groups were compared using a permutation-based general linear model with correction for multiple comparisons and confounders. To test whether the extracted metrics could predict disease severity, a random forest regression model was trained and evaluated using nested leave-one-out cross-validation. Amyotrophic lateral sclerosis was characterized by reduced sensorimotor beta band and increased high-gamma band power. Within the premotor cortex, increased disability was associated with a reduced 1/f exponent. Increased disability was more widely associated with increased global connectivity in the delta, theta and high-gamma bands. Intra-hemispherically, increased disability scores were particularly associated with increases in temporal connectivity and inter-hemispherically with increases in frontal and occipital connectivity. The random forest model achieved a coefficient of determination (R2) of 0.24. The combined reduction in cortical sensorimotor beta and rise in gamma power is compatible with the established hypothesis of loss of inhibitory, GABAergic interneuronal circuits in pathogenesis. A lower 1/f exponent potentially reflects a more excitable cortex and a pathology unique to amyotrophic lateral sclerosis when considered with the findings published in other neurodegenerative disorders. Power and complexity changes corroborate with the results from paired-pulse transcranial magnetic stimulation. Increased magnetoencephalography connectivity in worsening disability is thought to represent compensatory responses to a failing motor system. Restoration of cortical beta and gamma band power has significant potential to be tested in an experimental medicine setting. Magnetoencephalography-based measures have potential as sensitive outcome measures of therapeutic benefit in drug trials and may have a wider diagnostic value with further study, including as predictive markers in asymptomatic carriers of disease-causing genetic variants.
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Affiliation(s)
- Michael Trubshaw
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Chetan Gohil
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
| | - Katie Yoganathan
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Oliver Kohl
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
| | - Evan Edmond
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Malcolm Proudfoot
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Alexander G Thompson
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Kevin Talbot
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Charlotte J Stagg
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Anna C Nobre
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
| | - Mark Woolrich
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
| | - Martin R Turner
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 7JX, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
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Penhale SH, Arif Y, Schantell M, Johnson HJ, Willett MP, Okelberry HJ, Meehan CE, Heinrichs‐Graham E, Wilson TW. Healthy aging alters the oscillatory dynamics and fronto-parietal connectivity serving fluid intelligence. Hum Brain Mapp 2024; 45:e26591. [PMID: 38401133 PMCID: PMC10893975 DOI: 10.1002/hbm.26591] [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: 07/26/2023] [Revised: 12/13/2023] [Accepted: 12/31/2023] [Indexed: 02/26/2024] Open
Abstract
Fluid intelligence (Gf) involves logical reasoning and novel problem-solving abilities. Often, abstract reasoning tasks like Raven's progressive matrices are used to assess Gf. Prior work has shown an age-related decline in fluid intelligence capabilities, and although many studies have sought to identify the underlying mechanisms, our understanding of the critical brain regions and dynamics remains largely incomplete. In this study, we utilized magnetoencephalography (MEG) to investigate 78 individuals, ages 20-65 years, as they completed an abstract reasoning task. MEG data was co-registered with structural MRI data, transformed into the time-frequency domain, and the resulting neural oscillations were imaged using a beamformer. We found worsening behavioral performance with age, including prolonged reaction times and reduced accuracy. MEG analyses indicated robust oscillations in the theta, alpha/beta, and gamma range during the task. Whole brain correlation analyses with age revealed relationships in the theta and alpha/beta frequency bands, such that theta oscillations became stronger with increasing age in a right prefrontal region and alpha/beta oscillations became stronger with increasing age in parietal and right motor cortices. Follow-up connectivity analyses revealed increasing parieto-frontal connectivity with increasing age in the alpha/beta frequency range. Importantly, our findings are consistent with the parieto-frontal integration theory of intelligence (P-FIT). These results further suggest that as people age, there may be alterations in neural responses that are spectrally specific, such that older people exhibit stronger alpha/beta oscillations across the parieto-frontal network during abstract reasoning tasks.
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Affiliation(s)
- Samantha H. Penhale
- Institute for Human Neuroscience, Boys Town National Research HospitalNebraskaUSA
| | - Yasra Arif
- Institute for Human Neuroscience, Boys Town National Research HospitalNebraskaUSA
| | - Mikki Schantell
- Institute for Human Neuroscience, Boys Town National Research HospitalNebraskaUSA
- University of Nebraska Medical CenterOmahaNebraskaUSA
| | - Hallie J. Johnson
- Institute for Human Neuroscience, Boys Town National Research HospitalNebraskaUSA
| | - Madelyn P. Willett
- Institute for Human Neuroscience, Boys Town National Research HospitalNebraskaUSA
| | - Hannah J. Okelberry
- Institute for Human Neuroscience, Boys Town National Research HospitalNebraskaUSA
| | - Chloe E. Meehan
- Institute for Human Neuroscience, Boys Town National Research HospitalNebraskaUSA
- Department of PsychologyUniversity of NebraskaOmahaNebraskaUSA
| | - Elizabeth Heinrichs‐Graham
- Institute for Human Neuroscience, Boys Town National Research HospitalNebraskaUSA
- Department of Pharmacology and NeuroscienceCreighton UniversityOmahaNebraskaUSA
| | - Tony W. Wilson
- Institute for Human Neuroscience, Boys Town National Research HospitalNebraskaUSA
- Department of Pharmacology and NeuroscienceCreighton UniversityOmahaNebraskaUSA
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Petro NM, Picci G, Embury CM, Ott LR, Penhale SH, Rempe MP, Johnson HJ, Willett MP, Wang YP, Stephen JM, Calhoun VD, Doucet GE, Wilson TW. Developmental differences in functional organization of multispectral networks. Cereb Cortex 2023; 33:9175-9185. [PMID: 37279931 PMCID: PMC10505424 DOI: 10.1093/cercor/bhad193] [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: 02/24/2023] [Revised: 05/11/2023] [Accepted: 05/17/2023] [Indexed: 06/08/2023] Open
Abstract
Assessing brain connectivity during rest has become a widely used approach to identify changes in functional brain organization during development. Generally, previous works have demonstrated that brain activity shifts from more local to more distributed processing from childhood into adolescence. However, the majority of those works have been based on functional magnetic resonance imaging measures, whereas multispectral functional connectivity, as measured using magnetoencephalography (MEG), has been far less characterized. In our study, we examined spontaneous cortical activity during eyes-closed rest using MEG in 101 typically developing youth (9-15 years old; 51 females, 50 males). Multispectral MEG images were computed, and connectivity was estimated in the canonical delta, theta, alpha, beta, and gamma bands using the imaginary part of the phase coherence, which was computed between 200 brain regions defined by the Schaefer cortical atlas. Delta and alpha connectivity matrices formed more communities as a function of increasing age. Connectivity weights predominantly decreased with age in both frequency bands; delta-band differences largely implicated limbic cortical regions and alpha band differences in attention and cognitive networks. These results are consistent with previous work, indicating the functional organization of the brain becomes more segregated across development, and highlight spectral specificity across different canonical networks.
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Affiliation(s)
- Nathan M Petro
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, United States
| | - Giorgia Picci
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, United States
- Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, United States
| | - Christine M Embury
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, United States
| | - Lauren R Ott
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, United States
| | - Samantha H Penhale
- Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Maggie P Rempe
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
- College of Medicine, University of Nebraska Medical Center, Omaha, NE, United States
| | - Hallie J Johnson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
| | - Madelyn P Willett
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
| | - Yu-Ping Wang
- Department of Biomedical Engineering, Tulane University, New Orleans, LA, United States
| | | | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, United States
| | - Gaelle E Doucet
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, United States
- Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, United States
| | - Tony W Wilson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, United States
- Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, United States
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Cohen SL, Woo Choi J, Toga AW, Pouratian N, Duncan D. Exaggerated High-Beta Oscillations are Associated with Cortical Thinning at the Motor Cortex in Parkinson's Disease. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38083533 DOI: 10.1109/embc40787.2023.10341040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Elevated β oscillations (13-35 Hz) are characteristic pathophysiology in Parkinson's Disease (PD). Cortical thinning has also been reported in the disease, however the relationship between these biomarkers of PD has not been established. By comparing electrophysiological measurements with cortical thickness, this study aims to reveal the pathoetiology of disease and symptoms in PD. Preoperative magnetic resonance imaging (MRI) and intraoperative local field potentials (LFPs) were collected from 34 subjects diagnosed with PD. Cortical surfaces were reconstructed from the images, and cortical thickness was extracted from the subregions where the recording electrode was placed in M1. LFPs were preprocessed and cleaned using a semiautomatic artifact detection algorithm, then power spectral densities (PSD) were computed and periodic and aperiodic frequency components were calculated. Nonparametric Spearman rank correlations assessed the relationship between electrophysiological components (i.e. center frequency (CF), power, bandwidth, 1/f exponent, knee), with cortical thickness. According to the CF of each subject's PSD, the cohort was split into two sub-groups: low-β peak (13-20 Hz) and high-β peak (20-35 Hz) groups. There was a significant negative correlation between power and cortical thickness only in the high-β subgroup (r=-0.48, p(corrected)=0.049). This relationship remained significant when correcting for age (r=-0.52,p=0.015), indicating that the effect of age on cortical thinning was not the determining factor. We did not find significant differences between UPDRS-III motor symptom scores for the low-and high-β subgroups. Of note is the dominance of high-β oscillatory power and its relationship with cortical thickness. As suggested by the literature, increased high-β activity during movement may be exaggerated in PD. These findings suggest that the characteristic cortical thinning in PD causes variation in electrical activity, leading to elevated high-β activity.Clinical relevance- This multimodal study provides additional insights on the pathophysiology and its relevance with morphology of Parkinson's Disease.
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Xia Y, Sun H, Hua L, Dai Z, Wang X, Tang H, Han Y, Du Y, Zhou H, Zou H, Yao Z, Lu Q. Spontaneous beta power, motor-related beta power and cortical thickness in major depressive disorder with psychomotor disturbance. Neuroimage Clin 2023; 38:103433. [PMID: 37216848 PMCID: PMC10209543 DOI: 10.1016/j.nicl.2023.103433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 05/05/2023] [Accepted: 05/11/2023] [Indexed: 05/24/2023]
Abstract
INTRODUCTION The psychomotor disturbance is a common symptom in patients with major depressive disorder (MDD). The neurological mechanisms of psychomotor disturbance are intricate, involving alterations in the structure and function of motor-related regions. However, the relationship among changes in the spontaneous activity, motor-related activity, local cortical thickness, and psychomotor function remains unclear. METHOD A total of 140 patients with MDD and 68 healthy controls performed a simple right-hand visuomotor task during magnetoencephalography (MEG) scanning. All patients were divided into two groups according to the presence of psychomotor slowing. Spontaneous beta power, movement-related beta desynchronization (MRBD), absolute beta power during movement and cortical characteristics in the bilateral primary motor cortex were compared using general linear models with the group as a fixed effect and age as a covariate. Finally, the moderated mediation model was tested to examine the relationship between brain metrics with group differences and psychomotor performance. RESULTS The patients with psychomotor slowing showed higher spontaneous beta power, movement-related beta desynchronization and absolute beta power during movement than patients without psychomotor slowing. Compared with the other two groups, significant decreases were found in cortical thickness of the left primary motor cortex in patients with psychomotor slowing. Our moderated mediation model showed that the increased spontaneous beta power indirectly affected impaired psychomotor performance by abnormal MRBD, and the indirect effects were moderated by cortical thickness. CONCLUSION These results suggest that patients with MDD have aberrant cortical beta activity at rest and during movement, combined with abnormal cortical thickness, contributing to the psychomotor disturbance observed in this patient population.
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Affiliation(s)
- Yi Xia
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Hao Sun
- Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing 210093, China
| | - Lingling Hua
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Zhongpeng Dai
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing 210096, China
| | - Xiaoqin Wang
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Hao Tang
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Yinglin Han
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Yishan Du
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Hongliang Zhou
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Haowen Zou
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China; Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing 210093, China
| | - Zhijian Yao
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China; School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Nanjing Brain Hospital, Medical School of Nanjing University, Nanjing 210093, China.
| | - Qing Lu
- School of Biological Sciences & Medical Engineering, Southeast University, Nanjing 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Southeast University, Nanjing 210096, China.
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