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Coleman SC, Seedat ZA, Pakenham DO, Quinn AJ, Brookes MJ, Woolrich MW, Mullinger KJ. Post-task responses following working memory and movement are driven by transient spectral bursts with similar characteristics. Hum Brain Mapp 2024; 45:e26700. [PMID: 38726799 PMCID: PMC11082833 DOI: 10.1002/hbm.26700] [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] [Received: 09/19/2023] [Revised: 03/09/2024] [Accepted: 04/14/2024] [Indexed: 05/13/2024] Open
Abstract
The post-movement beta rebound has been studied extensively using magnetoencephalography (MEG) and is reliably modulated by various task parameters as well as illness. Our recent study showed that rebounds, which we generalise as "post-task responses" (PTRs), are a ubiquitous phenomenon in the brain, occurring across the cortex in theta, alpha, and beta bands. Currently, it is unknown whether PTRs following working memory are driven by transient bursts, which are moments of short-lived high amplitude activity, similar to those that drive the post-movement beta rebound. Here, we use three-state univariate hidden Markov models (HMMs), which can identify bursts without a priori knowledge of frequency content or response timings, to compare bursts that drive PTRs in working memory and visuomotor MEG datasets. Our results show that PTRs across working memory and visuomotor tasks are driven by pan-spectral transient bursts. These bursts have very similar spectral content variation over the cortex, correlating strongly between the two tasks in the alpha (R2 = .89) and beta (R2 = .53) bands. Bursts also have similar variation in duration over the cortex (e.g., long duration bursts occur in the motor cortex for both tasks), strongly correlating over cortical regions between tasks (R2 = .56), with a mean over all regions of around 300 ms in both datasets. Finally, we demonstrate the ability of HMMs to isolate signals of interest in MEG data, such that the HMM probability timecourse correlates more strongly with reaction times than frequency filtered power envelopes from the same brain regions. Overall, we show that induced PTRs across different tasks are driven by bursts with similar characteristics, which can be identified using HMMs. Given the similarity between bursts across tasks, we suggest that PTRs across the cortex may be driven by a common underlying neural phenomenon.
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Affiliation(s)
- Sebastian C. Coleman
- Sir Peter Mansfield Imaging Centre, School of Physics and AstronomyUniversity of NottinghamNottinghamUK
| | - Zelekha A. Seedat
- Sir Peter Mansfield Imaging Centre, School of Physics and AstronomyUniversity of NottinghamNottinghamUK
- Young EpilepsyLingfieldUK
| | - Daisie O. Pakenham
- Sir Peter Mansfield Imaging Centre, School of Physics and AstronomyUniversity of NottinghamNottinghamUK
- Clinical NeurophysiologyQueen's Medical Centre, Nottingham University Hospitals NHS TrustNottinghamUK
| | - Andrew J. Quinn
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of PsychiatryUniversity of OxfordOxfordUK
- Centre for Human Brain Health, School of PsychologyUniversity of BirminghamBirminghamUK
| | - Matthew J. Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and AstronomyUniversity of NottinghamNottinghamUK
| | - Mark W. Woolrich
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of PsychiatryUniversity of OxfordOxfordUK
| | - Karen J. Mullinger
- Sir Peter Mansfield Imaging Centre, School of Physics and AstronomyUniversity of NottinghamNottinghamUK
- Centre for Human Brain Health, School of PsychologyUniversity of BirminghamBirminghamUK
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Xia Y, Hua L, Dai Z, Han Y, Du Y, Zhao S, Zhou H, Wang X, Yan R, Wang X, Zou H, Sun H, Huang Y, Yao Z, Lu Q. Attenuated post-movement beta rebound reflects psychomotor alterations in major depressive disorder during a simple visuomotor task: a MEG study. BMC Psychiatry 2023; 23:395. [PMID: 37270511 DOI: 10.1186/s12888-023-04844-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Accepted: 05/04/2023] [Indexed: 06/05/2023] Open
Abstract
BACKGROUND Psychomotor alterations are a common symptom in patients with major depressive disorder (MDD). The primary motor cortex (M1) plays a vital role in the mechanism of psychomotor alterations. Post-movement beta rebound (PMBR) in the sensorimotor cortex is abnormal in patients with motor abnormalities. However, the changes in M1 beta rebound in patients with MDD remain unclear. This study aimed to primarily explore the relationship between psychomotor alterations and PMBR in MDD. METHODS One hundred thirty-two subjects were enrolled in the study, comprising 65 healthy controls (HCs) and 67 MDD patients. All participants performed a simple right-hand visuomotor task during MEG scanning. PMBR was measured in the left M1 at the source reconstruction level with the time-frequency analysis method. Retardation factor scores and neurocognitive test performance, including the Digit Symbol Substitution Test (DSST), the Making Test Part A (TMT-A), and the Verbal Fluency Test (VFT), were used to measure psychomotor functions. Pearson correlation analyses were used to assess relationships between PMBR and psychomotor alterations in MDD. RESULTS The MDD group showed worse neurocognitive performance than the HC group in all three neurocognitive tests. The PMBR was diminished in patients with MDD compared to HCs. In a group of MDD patients, the reduced PMBR was negatively correlated with retardation factor scores. Further, there was a positive correlation between the PMBR and DSST scores. PMBR is negatively associated with the TMT-A scores. CONCLUSION Our findings suggested that the attenuated PMBR in M1 could illustrate the psychomotor disturbance in MDD, possibly contributing to clinical psychomotor symptoms and deficits of cognitive functions.
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Affiliation(s)
- Yi Xia
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, 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
| | - 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
| | - Shuai Zhao
- 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
| | - Xiaoqin Wang
- Department of Psychiatry, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing, 210029, China
| | - Rui Yan
- 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
| | - Xumiao Wang
- 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
| | - Hao Sun
- 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
| | - YingHong Huang
- 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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Coleman SC, Seedat ZA, Whittaker AC, Lenartowicz A, Mullinger KJ. Beyond the Beta Rebound: Post-Task Responses in Oscillatory Activity follow Cessation of Working Memory Processes. Neuroimage 2023; 265:119801. [PMID: 36496181 DOI: 10.1016/j.neuroimage.2022.119801] [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: 09/23/2022] [Revised: 11/23/2022] [Accepted: 12/05/2022] [Indexed: 12/13/2022] Open
Abstract
Post-task responses (PTRs) are transitionary responses occurring for several seconds between the end of a stimulus/task and a period of rest. The most well-studied of these are beta band (13 - 30 Hz) PTRs in motor networks following movement, often called post-movement beta rebounds, which have been shown to differ in patients with schizophrenia and autism. Previous studies have proposed that beta PTRs reflect inhibition of task-positive networks to enable a return to resting brain activity, scaling with cognitive demand and reflecting cortical self-regulation. It is unknown whether PTRs are a phenomenon of the motor system, or whether they are a more general self-modulatory property of cortex that occur following cessation of higher cognitive processes as well as movement. To test this, we recorded magnetoencephalography (MEG) responses in 20 healthy participants to a working-memory task, known to recruit cortical networks associated with higher cognition. Our results revealed PTRs in the theta, alpha and beta bands across many regions of the brain, including the dorsal attention network (DAN) and lateral visual regions. These PTRs increased significantly (p < 0.05) in magnitude with working-memory load, an effect which is independent of oscillatory modulations occurring over the task period as well as those following individual stimuli. Furthermore, we showed that PTRs are functionally related to reaction times in left lateral visual (p < 0.05) and left parietal (p < 0.1) regions, while the oscillatory responses measured during the task period are not. Importantly, motor PTRs following button presses did not modulate with task condition, suggesting that PTRs in different networks are driven by different aspects of cognition. Our findings show that PTRs are not limited to motor networks but are widespread in regions which are recruited during the task. We provide evidence that PTRs have unique properties, scaling with cognitive load and correlating significantly with behaviour. Based on the evidence, we suggest that PTRs inhibit task-positive network activity to enable a transition to rest, however, further investigation is required to uncover their role in neuroscience and pathology.
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Affiliation(s)
- Sebastian C Coleman
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, NG7 2RD, UK
| | - Zelekha A Seedat
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, NG7 2RD, UK; Young Epilepsy, St Pier's Lane, Dormansland, Lingfield, RH7 6PW, UK
| | - Anna C Whittaker
- Faculty of Health Sciences and Sport, University of Stirling, Stirling, UK
| | - Agatha Lenartowicz
- Department of Psychiatry & Biobehavioral Sciences, University of California Los Angeles
| | - Karen J Mullinger
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, NG7 2RD, UK; Centre for Human Brain Health, School of Psychology, University of Birmingham, UK.
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Peter J, Ferraioli F, Mathew D, George S, Chan C, Alalade T, Salcedo SA, Saed S, Tatti E, Quartarone A, Ghilardi MF. Movement-related beta ERD and ERS abnormalities in neuropsychiatric disorders. Front Neurosci 2022; 16:1045715. [PMID: 36507340 PMCID: PMC9726921 DOI: 10.3389/fnins.2022.1045715] [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: 09/15/2022] [Accepted: 10/31/2022] [Indexed: 11/24/2022] Open
Abstract
Movement-related oscillations in the beta range (from 13 to 30 Hz) have been observed over sensorimotor areas with power decrease (i.e., event-related desynchronization, ERD) during motor planning and execution followed by an increase (i.e., event-related synchronization, ERS) after the movement's end. These phenomena occur during active, passive, imaged, and observed movements. Several electrophysiology studies have used beta ERD and ERS as functional indices of sensorimotor integrity, primarily in diseases affecting the motor system. Recent literature also highlights other characteristics of beta ERD and ERS, implying their role in processes not strictly related to motor function. Here we review studies about movement-related ERD and ERS in diseases characterized by motor dysfunction, including Parkinson's disease, dystonia, stroke, amyotrophic lateral sclerosis, cerebral palsy, and multiple sclerosis. We also review changes of beta ERD and ERS reported in physiological aging, Alzheimer's disease, and schizophrenia, three conditions without overt motor symptoms. The review of these works shows that ERD and ERS abnormalities are present across the spectrum of the examined pathologies as well as development and aging. They further suggest that cognition and movement are tightly related processes that may share common mechanisms regulated by beta modulation. Future studies with a multimodal approach are warranted to understand not only the specific topographical dynamics of movement-related beta modulation but also the general meaning of beta frequency changes occurring in relation to movement and cognitive processes at large. Such an approach will provide the foundation to devise and implement novel therapeutic approaches to neuropsychiatric disorders.
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Affiliation(s)
- Jaime Peter
- Department of Molecular, Cellular and Biomedical Sciences, CUNY School of Medicine, New York, NY, United States
| | - Francesca Ferraioli
- Department of Molecular, Cellular and Biomedical Sciences, CUNY School of Medicine, New York, NY, United States
| | - Dave Mathew
- Department of Molecular, Cellular and Biomedical Sciences, CUNY School of Medicine, New York, NY, United States
| | - Shaina George
- Department of Molecular, Cellular and Biomedical Sciences, CUNY School of Medicine, New York, NY, United States
| | - Cameron Chan
- Department of Molecular, Cellular and Biomedical Sciences, CUNY School of Medicine, New York, NY, United States
| | - Tomisin Alalade
- Department of Molecular, Cellular and Biomedical Sciences, CUNY School of Medicine, New York, NY, United States
| | - Sheilla A. Salcedo
- Department of Molecular, Cellular and Biomedical Sciences, CUNY School of Medicine, New York, NY, United States
| | - Shannon Saed
- Department of Molecular, Cellular and Biomedical Sciences, CUNY School of Medicine, New York, NY, United States
| | - Elisa Tatti
- Department of Molecular, Cellular and Biomedical Sciences, CUNY School of Medicine, New York, NY, United States,*Correspondence: Elisa Tatti,
| | - Angelo Quartarone
- IRCCS Centro Neurolesi Bonino Pulejo-Piemonte, Messina, Italy,Angelo Quartarone,
| | - M. Felice Ghilardi
- Department of Molecular, Cellular and Biomedical Sciences, CUNY School of Medicine, New York, NY, United States,M. Felice Ghilardi,
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Zhang J, Yang H, Li W, Li Y, Qin J, He L. Automatic Schizophrenia Detection Using Multimodality Media via a Text Reading Task. Front Neurosci 2022; 16:933049. [PMID: 35911987 PMCID: PMC9331283 DOI: 10.3389/fnins.2022.933049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Accepted: 06/13/2022] [Indexed: 11/13/2022] Open
Abstract
Schizophrenia is a crippling chronic mental disease that affects people worldwide. In this work, an automatic schizophrenia detection algorithm is proposed based on the reading deficit of schizophrenic patients. From speech and video modalities, the automatic schizophrenia detection algorithm illustrates abnormal speech, head movement, and reading fluency during the reading task. In the speech modality, an acoustic model of speech emotional flatness in schizophrenia is established to reflect the emotional expression flatness of schizophrenic speech from the perspective of speech production and perception. In the video modality, the head-movement-related features are proposed to illustrate the spontaneous head movement caused by repeated reading and unconscious movement, and the reading-fluency-related features are proposed to convey the damaged degree of schizophrenic patients' reading fluency. The experimental data of this work are 160 segments of speech and video data recorded by 40 participants (20 schizophrenic patients and 20 normal controls). Combined with support vector machines and random forest, the accuracy of the proposed acoustic model, the head-movement-related features, and the reading-fluency-related features range from 94.38 to 96.50%, 73.38 to 83.38%, and 79.50 to 83.63%, respectively. The average accuracy of the proposed automatic schizophrenia detection algorithm reaches 97.50%. The experimental results indicate the effectiveness of the proposed automatic detection algorithm as an auxiliary diagnostic method for schizophrenia.
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Affiliation(s)
- Jing Zhang
- College of Biomedical Engineering, Sichuan University, Chengdu, China
| | - Hui Yang
- College of Biomedical Engineering, Sichuan University, Chengdu, China
| | - Wen Li
- College of Biomedical Engineering, Sichuan University, Chengdu, China
| | - Yuanyuan Li
- Mental Health Center, West China Hospital of Sichuan University, Chengdu, China
| | - Jing Qin
- Centre for Smart Health, School of Nursing, The Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR, China
| | - Ling He
- College of Biomedical Engineering, Sichuan University, Chengdu, China
- *Correspondence: Ling He
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Liddle PF, Liddle EB. Imprecise Predictive Coding Is at the Core of Classical Schizophrenia. Front Hum Neurosci 2022; 16:818711. [PMID: 35308615 PMCID: PMC8928728 DOI: 10.3389/fnhum.2022.818711] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 02/14/2022] [Indexed: 12/23/2022] Open
Abstract
Current diagnostic criteria for schizophrenia place emphasis on delusions and hallucinations, whereas the classical descriptions of schizophrenia by Kraepelin and Bleuler emphasized disorganization and impoverishment of mental activity. Despite the availability of antipsychotic medication for treating delusions and hallucinations, many patients continue to experience persisting disability. Improving treatment requires a better understanding of the processes leading to persisting disability. We recently introduced the term classical schizophrenia to describe cases with disorganized and impoverished mental activity, cognitive impairment and predisposition to persisting disability. Recent evidence reveals that a polygenic score indicating risk for schizophrenia predicts severity of the features of classical schizophrenia: disorganization, and to a lesser extent, impoverishment of mental activity and cognitive impairment. Current understanding of brain function attributes a cardinal role to predictive coding: the process of generating models of the world that are successively updated in light of confirmation or contradiction by subsequent sensory information. It has been proposed that abnormalities of these predictive processes account for delusions and hallucinations. Here we examine the evidence provided by electrophysiology and fMRI indicating that imprecise predictive coding is the core pathological process in classical schizophrenia, accounting for disorganization, psychomotor poverty and cognitive impairment. Functional imaging reveals aberrant brain activity at network hubs engaged during encoding of predictions. We discuss the possibility that frequent prediction errors might promote excess release of the neurotransmitter, dopamine, thereby accounting for the occurrence of episodes of florid psychotic symptoms including delusions and hallucinations in classical schizophrenia. While the predictive coding hypotheses partially accounts for the time-course of classical schizophrenia, the overall body of evidence indicates that environmental factors also contribute. We discuss the evidence that chronic inflammation is a mechanism that might link diverse genetic and environmental etiological factors, and contribute to the proposed imprecision of predictive coding.
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Affiliation(s)
- Peter F. Liddle
- Centre for Translational Neuroimaging for Mental Health, School of Medicine, Institute of Mental Health, University of Nottingham, Nottingham, United Kingdom
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7
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Laaksonen K, Ward NS. Biomarkers of plasticity for stroke recovery. HANDBOOK OF CLINICAL NEUROLOGY 2022; 184:287-298. [PMID: 35034742 DOI: 10.1016/b978-0-12-819410-2.00033-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
Stroke is the commonest cause of physical disability in the world. Our understanding of the biologic mechanisms involved in recovery and repair has advanced to the point that therapeutic opportunities to promote recovery through manipulation of post-stroke plasticity have never been greater. This work has almost exclusively been carried out in rodent models of stroke with little translation into human studies. The challenge ahead is to develop a mechanistic understanding of recovery from stroke in humans. Advances in neuroimaging techniques can now provide the appropriate intermediate level of description to bridge the gap between a molecular and cellular account of recovery and a behavioral one. Clinical trials can then be designed in a stratified manner taking into account when an intervention should be delivered and who is most likely to benefit. This approach is most likely to lead to the step-change in how restorative therapeutic strategies are delivered in human stroke patients.
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Affiliation(s)
- Kristina Laaksonen
- Department of Neurology, Helsinki University Hospital, and Clinical Neurosciences, Neurology, University of Helsinki, Helsinki, Finland
| | - Nick S Ward
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, United Kingdom; Department of Neurology, National Hospital for Neurology and Neurosurgery, Queen Square, London, United Kingdom.
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Briley PM, Liddle EB, Simmonite M, Jansen M, White TP, Balain V, Palaniyappan L, Bowtell R, Mullinger KJ, Liddle PF. Regional Brain Correlates of Beta Bursts in Health and Psychosis: A Concurrent Electroencephalography and Functional Magnetic Resonance Imaging Study. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2021; 6:1145-1156. [PMID: 33495122 PMCID: PMC8648891 DOI: 10.1016/j.bpsc.2020.10.018] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 10/12/2020] [Accepted: 10/22/2020] [Indexed: 12/27/2022]
Abstract
BACKGROUND There is emerging evidence for abnormal beta oscillations in psychosis. Beta oscillations are likely to play a key role in the coordination of sensorimotor information that is crucial to healthy mental function. Growing evidence suggests that beta oscillations typically manifest as transient beta bursts that increase in probability following a motor response, observable as post-movement beta rebound. Evidence indicates that post-movement beta rebound is attenuated in psychosis, with greater attenuation associated with greater symptom severity and impairment. Delineating the functional role of beta bursts therefore may be key to understanding the mechanisms underlying persistent psychotic illness. METHODS We used concurrent electroencephalography and functional magnetic resonance imaging to identify blood oxygen level-dependent correlates of beta bursts during the n-back working memory task and intervening rest periods in healthy control participants (n = 30) and patients with psychosis (n = 48). RESULTS During both task blocks and intervening rest periods, beta bursts phasically activated regions implicated in task-relevant content while suppressing currently tonically active regions. Patients showed attenuated post-movement beta rebound that was associated with persisting disorganization symptoms as well as impairments in cognition and role function. Patients also showed greater task-related reductions in overall beta burst rate and showed greater, more extensive, beta burst-related blood oxygen level-dependent activation. CONCLUSIONS Our evidence supports a model in which beta bursts reactivate latently maintained sensorimotor information and are dysregulated and inefficient in psychosis. We propose that abnormalities in the mechanisms by which beta bursts coordinate reactivation of contextually appropriate content can manifest as disorganization, working memory deficits, and inaccurate forward models and may underlie a core deficit associated with persisting symptoms and impairment.
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Affiliation(s)
- Paul M Briley
- Institute of Mental Health, Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, University Park, Nottingham, United Kingdom; Nottinghamshire Healthcare NHS Foundation Trust, Mapperley, Nottingham, United Kingdom
| | - Elizabeth B Liddle
- Institute of Mental Health, Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Molly Simmonite
- Institute of Mental Health, Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Marije Jansen
- Institute of Mental Health, Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Thomas P White
- Institute of Mental Health, Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Vijender Balain
- Institute of Mental Health, Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, University Park, Nottingham, United Kingdom; Burnaby Centre for Mental Health and Addictions, Burnaby, British Columbia, Canada
| | - Lena Palaniyappan
- Institute of Mental Health, Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, University Park, Nottingham, United Kingdom; Department of Psychiatry, University of Western Ontario, London, Ontario, Canada; Robarts Research Institute, University of Western Ontario, London, Ontario, Canada; Lawson Health Research Institute, London, Ontario, Canada
| | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Karen J Mullinger
- Sir Peter Mansfield Imaging Centre, University of Nottingham, University Park, Nottingham, United Kingdom; School of Psychology, University of Birmingham, Edgbaston, Birmingham, United Kingdom
| | - Peter F Liddle
- Institute of Mental Health, Division of Psychiatry and Applied Psychology, School of Medicine, University of Nottingham, University Park, Nottingham, United Kingdom.
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Khan H, Sami MB, Litvak V. The utility of Magnetoencephalography in multiple sclerosis - A systematic review. NEUROIMAGE-CLINICAL 2021; 32:102814. [PMID: 34537682 PMCID: PMC8455859 DOI: 10.1016/j.nicl.2021.102814] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 08/28/2021] [Accepted: 08/30/2021] [Indexed: 01/29/2023]
Abstract
We conducted a Systematic Review of studies, looking at 30 studies from 13 centres. MS patients had reduced power in some induced responses (motor beta, visual gamma). Increased latency and reduced connectivity were seen for somatosensory evoked fields. There was an association between upper alpha connectivity and cognitive function. MEG shows promise, although work is too preliminary to recommend current clinical use.
Introduction Magnetoencephalography (MEG), allows for a high degree temporal and spatial accuracy in recording cortical oscillatory activity and evoked fields. To date, no review has been undertaken to synthesise all MEG studies in Multiple Sclerosis (MS). We undertook a Systematic Review of the utility of MEG in MS. Methods We identified MEG studies carried out in MS using EMBASE, Medline, Cochrane, TRIP and Psychinfo databases. We included original research articles with a cohort of minimum of five multiple sclerosis patients and quantifying of at least one MEG parameter. We used a modified version of the JBI (mJBI) for case-control studies to assess for risk of bias. Results We identified 30 studies from 13 centres involving at least 433 MS patients and 347 controls. We found evidence that MEG shows perturbed activity (most commonly reduced power modulations), reduced connectivity and association with altered clinical function in Multiple Sclerosis. Specific replicated findings were decreased motor induced responses in the beta band, diminished increase of gamma power after visual stimulation, increased latency and reduced connectivity for somatosensory evoked fields. There was an association between upper alpha connectivity and cognitive measures in people with MS. Overall studies were of moderate quality (mean mJBI score 6.7). Discussion We find evidence for the utility of MEG in Multiple Sclerosis. Event-related designs are of particular value and show replicability between centres. At this stage, it is not clear whether these changes are specific to Multiple Sclerosis or are also observable in other diseases. Further studies should look to explore cognitive control in more depth using in-task designs and undertake longitudinal studies to determine whether these changes have prognostic value.
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Affiliation(s)
- H Khan
- UCL Queen's Square Institute of Neurology, Queen Square, London WC1N 3BG, United Kingdom; Queen's Medical Centre Nottingham, Clifton Boulevard, Derby Rd, Nottingham NG7 2UH, United Kingdom.
| | - M B Sami
- Institute of Mental Health, Jubilee Campus, University of Nottingham Innovation Park, Triumph Road, Nottingham NG7 2TU, United Kingdom
| | - V Litvak
- UCL Queen's Square Institute of Neurology, Queen Square, London WC1N 3BG, United Kingdom
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Palaniyappan L. Dissecting the neurobiology of linguistic disorganisation and impoverishment in schizophrenia. Semin Cell Dev Biol 2021; 129:47-60. [PMID: 34507903 DOI: 10.1016/j.semcdb.2021.08.015] [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: 03/25/2021] [Revised: 08/13/2021] [Accepted: 05/06/2021] [Indexed: 12/16/2022]
Abstract
Schizophrenia provides a quintessential disease model of how disturbances in the molecular mechanisms of neurodevelopment lead to disruptions in the emergence of cognition. The central and often persistent feature of this illness is the disorganisation and impoverishment of language and related expressive behaviours. Though clinically more prominent, the periodic perceptual distortions characterised as psychosis are non-specific and often episodic. While several insights into psychosis have been gained based on study of the dopaminergic system, the mechanistic basis of linguistic disorganisation and impoverishment is still elusive. Key findings from cellular to systems-level studies highlight the role of ubiquitous, inhibitory processes in language production. Dysregulation of these processes at critical time periods, in key brain areas, provides a surprisingly parsimonious account of linguistic disorganisation and impoverishment in schizophrenia. This review links the notion of excitatory/inhibitory (E/I) imbalance at cortical microcircuits to the expression of language behaviour characteristic of schizophrenia, through the building blocks of neurochemistry, neurophysiology, and neurocognition.
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Affiliation(s)
- Lena Palaniyappan
- Department of Psychiatry,University of Western Ontario, London, Ontario, Canada; Robarts Research Institute,University of Western Ontario, London, Ontario, Canada; Lawson Health Research Institute, London, Ontario, Canada.
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Nasiriavanaki Z, Barbour T, Farabaugh AH, Fava M, Holmes AJ, Tootell RBH, Holt DJ. Anxious attachment is associated with heightened responsivity of a parietofrontal cortical network that monitors peri-personal space. NEUROIMAGE-CLINICAL 2021; 30:102585. [PMID: 33773165 PMCID: PMC8024770 DOI: 10.1016/j.nicl.2021.102585] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 12/17/2020] [Accepted: 01/29/2021] [Indexed: 12/13/2022]
Abstract
A parietofrontal cortical network is more active when stimuli are near the body. Responses of this network were positively correlated with “attachment anxiety”. No other types of attachment or symptoms accounted for this association. Connectivity strength within this network was not linked with attachment anxiety.
Background Attachment, or affiliative bonding among conspecifics, is thought to involve neural mechanisms underlying behavioral responses to threat and reward-related social signals. However, attachment-oriented responses may also rely on basic sensorimotor processes. One sensorimotor system that may play a role in attachment is the parietofrontal cortical network that responds to stimuli that are near or approaching the body, the peripersonal space (PPS) monitoring system. We hypothesized that this network may vary in responsivity to such potentially harmful stimuli, particularly those with social salience, based on individual differences in attachment styles. Methods Young adults viewed images of human faces or cars that appeared to move towards or away from them, while functional magnetic resonance imaging data were collected. Correlations between each of four adult attachment styles, measured using the Relationship Questionnaire, and responses of the PPS network to approaching (versus withdrawing) stimuli were measured. Results A region-of-interest (ROI) analysis, focused on six cortical regions of the PPS network that showed significant responses to approaching versus withdrawing face stimuli in an independent sample (n = 80), revealed that anxious attachment style (but not the other 3 attachment styles) was significantly positively correlated with responses to faces (but not to cars) in all six ROIs (r = 0.33–0.49, p = 0.01–0.0001, n = 50). Conclusions These findings suggest that anxious attachment is associated with over-responsivity of a sensorimotor network involved in attending to social stimuli near the body.
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Affiliation(s)
- Zahra Nasiriavanaki
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States
| | - Tracy Barbour
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States
| | - Amy H Farabaugh
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States
| | - Maurizio Fava
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States
| | - Avram J Holmes
- Department of Psychology, Yale University, New Haven, CT, United States
| | - Roger B H Tootell
- Harvard Medical School, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States; Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States
| | - Daphne J Holt
- Department of Psychiatry, Massachusetts General Hospital, Charlestown, MA, United States; Harvard Medical School, Boston, MA, United States; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, United States.
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12
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A New Recognition Method for the Auditory Evoked Magnetic Fields. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2021; 2021:6645270. [PMID: 33628215 PMCID: PMC7892250 DOI: 10.1155/2021/6645270] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 01/15/2021] [Accepted: 01/21/2021] [Indexed: 11/17/2022]
Abstract
Magnetoencephalography (MEG) is a persuasive tool to study the human brain in physiology and psychology. It can be employed to obtain the inference of change between the external environment and the internal psychology, which requires us to recognize different single trial event-related magnetic fields (ERFs) originated from different functional areas of the brain. Current recognition methods for the single trial data are mainly used for event-related potentials (ERPs) in the electroencephalography (EEG). Although the MEG shares the same signal sources with the EEG, much less interference from the other brain tissues may give the MEG an edge in recognition of the ERFs. In this work, we propose a new recognition method for the single trial auditory evoked magnetic fields (AEFs) through enhancing the signal. We find that the signal strength of the single trial AEFs is concentrated in the primary auditory cortex of the temporal lobe, which can be clearly displayed in the 2D images. These 2D images are then recognized by an artificial neural network (ANN) with 100% accuracy, which realizes the automatic recognition for the single trial AEFs. The method not only may be combined with the source estimation algorithm to improve its accuracy but also paves the way for the implementation of the brain-computer interface (BCI) with the MEG.
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13
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Gascoyne LE, Brookes MJ, Rathnaiah M, Katshu MZUH, Koelewijn L, Williams G, Kumar J, Walters JTR, Seedat ZA, Palaniyappan L, Deakin JFW, Singh KD, Liddle PF, Morris PG. Motor-related oscillatory activity in schizophrenia according to phase of illness and clinical symptom severity. Neuroimage Clin 2020; 29:102524. [PMID: 33340975 PMCID: PMC7750164 DOI: 10.1016/j.nicl.2020.102524] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 11/12/2020] [Accepted: 12/01/2020] [Indexed: 11/19/2022]
Abstract
Magnetoencephalography (MEG) measures magnetic fields generated by synchronised neural current flow and provides direct inference on brain electrophysiology and connectivity, with high spatial and temporal resolution. The movement-related beta decrease (MRBD) and the post-movement beta rebound (PMBR) are well-characterised effects in magnetoencephalography (MEG), with the latter having been shown to relate to long-range network integrity. Our previous work has shown that the PMBR is diminished (relative to controls) in a group of schizophrenia patients. However, little is known about how this effect might differ in patients at different stages of illness and degrees of clinical severity. Here, we extend our previous findings showing that the MEG derived PMBR abnormality in schizophrenia exists in 29 recent-onset and 35 established cases (i.e., chronic patients), compared to 42 control cases. In established cases, PMBR is negatively correlated with severity of disorganization symptoms. Further, using a hidden Markov model analysis, we show that transient pan-spectral oscillatory "bursts", which underlie the PMBR, differ between healthy controls and patients. Results corroborate that PMBR is associated with disorganization of mental activity in schizophrenia.
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Affiliation(s)
- Lauren E Gascoyne
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom.
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - Mohanbabu Rathnaiah
- Institute of Mental Health, University of Nottingham, Jubilee Campus, Nottingham NG7 2TU, United Kingdom; Nottinghamshire Healthcare NHS Foundation Trust, Nottingham NG3 6AA, United Kingdom
| | - Mohammad Zia Ul Haq Katshu
- Institute of Mental Health, University of Nottingham, Jubilee Campus, Nottingham NG7 2TU, United Kingdom; Nottinghamshire Healthcare NHS Foundation Trust, Nottingham NG3 6AA, United Kingdom
| | - Loes Koelewijn
- CUBRIC, School of Psychology, College of Biomedical and Life Sciences, Cardiff, Cardiff University CF24 4HQ, United Kingdom
| | - Gemma Williams
- CUBRIC, School of Psychology, College of Biomedical and Life Sciences, Cardiff, Cardiff University CF24 4HQ, United Kingdom
| | - Jyothika Kumar
- Institute of Mental Health, University of Nottingham, Jubilee Campus, Nottingham NG7 2TU, United Kingdom
| | - James T R Walters
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, CF24 4HQ, United Kingdom
| | - Zelekha A Seedat
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - Lena Palaniyappan
- Department of Psychiatry & Robarts Research Institute, University of Western Ontario & Lawson Health Research Institute, London ON, Canada
| | - J F William Deakin
- Division of Neuroscience and Experimental Psychology, University of Manchester, Oxford Rd, Manchester M13 9PL, United Kingdom
| | - Krish D Singh
- CUBRIC, School of Psychology, College of Biomedical and Life Sciences, Cardiff, Cardiff University CF24 4HQ, United Kingdom
| | - Peter F Liddle
- Institute of Mental Health, University of Nottingham, Jubilee Campus, Nottingham NG7 2TU, United Kingdom
| | - Peter G Morris
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
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14
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Haar S, Faisal AA. Brain Activity Reveals Multiple Motor-Learning Mechanisms in a Real-World Task. Front Hum Neurosci 2020; 14:354. [PMID: 32982707 PMCID: PMC7492608 DOI: 10.3389/fnhum.2020.00354] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 08/05/2020] [Indexed: 11/22/2022] Open
Abstract
Many recent studies found signatures of motor learning in neural beta oscillations (13-30 Hz), and specifically in the post-movement beta rebound (PMBR). All these studies were in controlled laboratory-tasks in which the task designed to induce the studied learning mechanism. Interestingly, these studies reported opposing dynamics of the PMBR magnitude over learning for the error-based and reward-based tasks (increase vs. decrease, respectively). Here, we explored the PMBR dynamics during real-world motor-skill-learning in a billiards task using mobile-brain-imaging. Our EEG recordings highlight the opposing dynamics of PMBR magnitudes (increase vs. decrease) between different subjects performing the same task. The groups of subjects, defined by their neural dynamics, also showed behavioral differences expected for different learning mechanisms. Our results suggest that when faced with the complexity of the real-world different subjects might use different learning mechanisms for the same complex task. We speculate that all subjects combine multi-modal mechanisms of learning, but different subjects have different predominant learning mechanisms.
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Affiliation(s)
- Shlomi Haar
- Brain and Behaviour Laboratory, Department of Bioengineering, Imperial College London, London, United Kingdom
- Behaviour Analytics Lab, Data Science Institute, Imperial College London, London, United Kingdom
| | - A. Aldo Faisal
- Brain and Behaviour Laboratory, Department of Bioengineering, Imperial College London, London, United Kingdom
- Behaviour Analytics Lab, Data Science Institute, Imperial College London, London, United Kingdom
- Department of Computing, Imperial College London, London, United Kingdom
- MRC London Institute of Medical Sciences, London, United Kingdom
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15
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Koola MM, Looney SW, Hong H, Pillai A, Hou W. Meta-analysis of randomized controlled trials of galantamine in schizophrenia: significant cognitive enhancement. Psychiatry Res 2020; 291:113285. [PMID: 32763546 DOI: 10.1016/j.psychres.2020.113285] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2020] [Revised: 07/08/2020] [Accepted: 07/09/2020] [Indexed: 12/11/2022]
Abstract
Cognitive impairments are core features of schizophrenia and the best predictor of functional outcome. Cholinergic system and alpha-7 nicotinic acetylcholine (α7nACh) receptors are strongly implicated in the pathophysiologic mechanisms associated with cognitive impairments in schizophrenia. Galantamine is not only a reversible, competitive inhibitor of acetylcholinesterase but also a type I positive allosteric modulator of α7nACh receptors. The objective of this meta-analysis was to examine the efficacy of galantamine for cognitive symptoms of schizophrenia. In the meta-analysis that included six randomized controlled trials (RCTs, N=226), cognitive impairments significantly improved with galantamine compared to placebo, with a small Hedges' g effect size of 0.233. This finding is consistent with other RCTs in schizophrenia with medications with a similar mechanism of action. On the basis of the results from all the failed (although some efficacy has been shown) RCTs to date in schizophrenia, targeting only one pathophysiologic mechanism may be insufficient to detect a clinically meaningful signal. Nicotinergic medications, like any other add-on medications, are unlikely to be effective as stand-alone medications. Hence, these medications may have to be combined with other medications with complementary mechanisms such as glutamatergic/N-methyl-D-aspartate systems to detect a meaningful effect size for the three domains of psychopathology.
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Affiliation(s)
- Maju Mathew Koola
- Department of Psychiatry and Behavioral Health, Stony Brook University Renaissance School of Medicine, Stony Brook, NY, 11794, USA.
| | - Stephen W Looney
- Department of Population Health Sciences, Division of Biostatistics and Data Science, Augusta University, Augusta, GA, USA
| | - Houlin Hong
- Department of Family, Population and Preventive Medicine, School of Medicine, Stony Brook University, Stony Brook, NY, USA
| | - Anilkumar Pillai
- Department of Psychiatry and Health Behavior, Medical College of Georgia, Augusta University, Augusta, GA, USA
| | - Wei Hou
- Department of Family, Population and Preventive Medicine, School of Medicine, Stony Brook University, Stony Brook, NY, USA
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16
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Rathnaiah M, Liddle EB, Gascoyne L, Kumar J, Zia Ul Haq Katshu M, Faruqi C, Kelly C, Gill M, Robson S, Brookes M, Palaniyappan L, Morris P, Liddle PF. Quantifying the Core Deficit in Classical Schizophrenia. ACTA ACUST UNITED AC 2020; 1:sgaa031. [PMID: 32803162 PMCID: PMC7418866 DOI: 10.1093/schizbullopen/sgaa031] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
In the classical descriptions of schizophrenia, Kraepelin and Bleuler recognized disorganization and impoverishment of mental activity as fundamental symptoms. Their classical descriptions also included a tendency to persisting disability. The psychopathological processes underlying persisting disability in schizophrenia remain poorly understood. The delineation of a core deficit underlying persisting disability would be of value in predicting outcome and enhancing treatment. We tested the hypothesis that mental disorganization and impoverishment are associated with persisting impairments of cognition and role function, and together reflect a latent core deficit that is discernible in cases diagnosed by modern criteria. We used Confirmatory Factor Analysis to determine whether measures of disorganization, mental impoverishment, impaired cognition, and role functioning in 40 patients with schizophrenia represent a single latent variable. Disorganization scores were computed from the variance shared between disorganization measures from 3 commonly used symptom scales. Mental impoverishment scores were computed similarly. A single factor model exhibited a good fit, supporting the hypothesis that these measures reflect a core deficit. Persisting brain disorders are associated with a reduction in post-movement beta rebound (PMBR), the characteristic increase in electrophysiological beta amplitude that follows a motor response. Patients had significantly reduced PMBR compared with healthy controls. PMBR was negatively correlated with core deficit score. While the symptoms constituting impoverished and disorganized mental activity are dissociable in schizophrenia, nonetheless, the variance that these 2 symptom domains share with impaired cognition and role function, appears to reflect a pathophysiological process that might be described as the core deficit of classical schizophrenia.
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Affiliation(s)
- Mohanbabu Rathnaiah
- Institute of Mental Health, University of Nottingham, Nottingham, UK.,Nottinghamshire Healthcare NHS Foundation Trust, Duncan McMillan House, Nottingham, UK
| | | | - Lauren Gascoyne
- Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, UK
| | - Jyothika Kumar
- Institute of Mental Health, University of Nottingham, Nottingham, UK
| | - Mohammad Zia Ul Haq Katshu
- Institute of Mental Health, University of Nottingham, Nottingham, UK.,Nottinghamshire Healthcare NHS Foundation Trust, Duncan McMillan House, Nottingham, UK
| | - Catherine Faruqi
- Nottinghamshire Healthcare NHS Foundation Trust, Duncan McMillan House, Nottingham, UK
| | - Christina Kelly
- Nottinghamshire Healthcare NHS Foundation Trust, Duncan McMillan House, Nottingham, UK
| | - Malkeet Gill
- Nottinghamshire Healthcare NHS Foundation Trust, Duncan McMillan House, Nottingham, UK
| | - Sian Robson
- Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, UK
| | - Matt Brookes
- Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, UK
| | - Lena Palaniyappan
- Department of Psychiatry and Robarts Research Institute, Western University, London, ON, Canada.,Lawson Imaging, Lawson Health Research Institute, London, ON, Canada
| | - Peter Morris
- Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, UK
| | - Peter F Liddle
- Institute of Mental Health, University of Nottingham, Nottingham, UK
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17
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Hill RM, Boto E, Rea M, Holmes N, Leggett J, Coles LA, Papastavrou M, Everton SK, Hunt BAE, Sims D, Osborne J, Shah V, Bowtell R, Brookes MJ. Multi-channel whole-head OPM-MEG: Helmet design and a comparison with a conventional system. Neuroimage 2020; 219:116995. [PMID: 32480036 PMCID: PMC8274815 DOI: 10.1016/j.neuroimage.2020.116995] [Citation(s) in RCA: 88] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 05/20/2020] [Accepted: 05/23/2020] [Indexed: 12/18/2022] Open
Abstract
Magnetoencephalography (MEG) is a powerful technique for functional
neuroimaging, offering a non-invasive window on brain electrophysiology. MEG
systems have traditionally been based on cryogenic sensors which detect the
small extracranial magnetic fields generated by synchronised current in neuronal
assemblies, however, such systems have fundamental limitations. In recent years,
non-cryogenic quantum-enabled sensors, called optically-pumped magnetometers
(OPMs), in combination with novel techniques for accurate background magnetic
field control, have promised to lift those restrictions offering an adaptable,
motion-robust MEG system, with improved data quality, at reduced cost. However,
OPM-MEG remains a nascent technology, and whilst viable systems exist, most
employ small numbers of sensors sited above targeted brain regions. Here,
building on previous work, we construct a wearable OPM-MEG system with
‘whole-head’ coverage based upon commercially available OPMs, and
test its capabilities to measure alpha, beta and gamma oscillations. We design
two methods for OPM mounting; a flexible (EEG-like) cap and rigid
(additively-manufactured) helmet. Whilst both designs allow for high quality
data to be collected, we argue that the rigid helmet offers a more robust option
with significant advantages for reconstruction of field data into 3D images of
changes in neuronal current. Using repeat measurements in two participants, we
show signal detection for our device to be highly robust. Moreover, via
application of source-space modelling, we show that, despite having 5 times
fewer sensors, our system exhibits comparable performance to an established
cryogenic MEG device. While significant challenges still remain, these
developments provide further evidence that OPM-MEG is likely to facilitate a
step change for functional neuroimaging.
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Affiliation(s)
- Ryan M Hill
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK.
| | - Elena Boto
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Molly Rea
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Niall Holmes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - James Leggett
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Laurence A Coles
- Added Scientific Limited, No 4, The Isaac Newton Centre, Nottingham Science Park, Nottingham, NG72RH, UK
| | - Manolis Papastavrou
- Added Scientific Limited, No 4, The Isaac Newton Centre, Nottingham Science Park, Nottingham, NG72RH, UK
| | - Sarah K Everton
- Added Scientific Limited, No 4, The Isaac Newton Centre, Nottingham Science Park, Nottingham, NG72RH, UK
| | - Benjamin A E Hunt
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Dominic Sims
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - James Osborne
- QuSpin Inc. 331 South 104th Street, Suite 130, Louisville, CO, 80027, USA
| | - Vishal Shah
- QuSpin Inc. 331 South 104th Street, Suite 130, Louisville, CO, 80027, USA
| | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
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18
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Comparing MEG and EEG in detecting the ~20-Hz rhythm modulation to tactile and proprioceptive stimulation. Neuroimage 2020; 215:116804. [PMID: 32276061 DOI: 10.1016/j.neuroimage.2020.116804] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Revised: 03/06/2020] [Accepted: 03/31/2020] [Indexed: 12/13/2022] Open
Abstract
Modulation of the ~20-Hz brain rhythm has been used to evaluate the functional state of the sensorimotor cortex both in healthy subjects and patients, such as stroke patients. The ~20-Hz brain rhythm can be detected by both magnetoencephalography (MEG) and electroencephalography (EEG), but the comparability of these methods has not been evaluated. Here, we compare these two methods in the evaluating of ~20-Hz activity modulation to somatosensory stimuli. Rhythmic ~20-Hz activity during separate tactile and proprioceptive stimulation of the right and left index finger was recorded simultaneously with MEG and EEG in twenty-four healthy participants. Both tactile and proprioceptive stimulus produced a clear suppression at 300-350 ms followed by a subsequent rebound at 700-900 ms after stimulus onset, detected at similar latencies both with MEG and EEG. The relative amplitudes of suppression and rebound correlated strongly between MEG and EEG recordings. However, the relative strength of suppression and rebound in the contralateral hemisphere (with respect to the stimulated hand) was significantly stronger in MEG than in EEG recordings. Our results indicate that MEG recordings produced signals with higher signal-to-noise ratio than EEG, favoring MEG as an optimal tool for studies evaluating sensorimotor cortical functions. However, the strong correlation between MEG and EEG results encourages the use of EEG when translating studies to clinical practice. The clear advantage of EEG is the availability of the method in hospitals and bed-side measurements at the acute phase.
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19
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Seedat ZA, Quinn AJ, Vidaurre D, Liuzzi L, Gascoyne LE, Hunt BAE, O'Neill GC, Pakenham DO, Mullinger KJ, Morris PG, Woolrich MW, Brookes MJ. The role of transient spectral 'bursts' in functional connectivity: A magnetoencephalography study. Neuroimage 2020; 209:116537. [PMID: 31935517 DOI: 10.1016/j.neuroimage.2020.116537] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Revised: 12/02/2019] [Accepted: 01/10/2020] [Indexed: 12/29/2022] Open
Abstract
Neural oscillations dominate electrophysiological measures of macroscopic brain activity and fluctuations in these rhythms offer an insightful window on cortical excitation, inhibition, and connectivity. However, in recent years the 'classical' picture of smoothly varying oscillations has been challenged by the idea that many 'oscillations' may actually be formed from the recurrence of punctate high-amplitude bursts in activity, whose spectral composition intersects the traditionally defined frequency ranges (e.g. alpha/beta band). This finding offers a new interpretation of measurable brain activity, however neither the methodological means to detect bursts, nor their link to other findings (e.g. connectivity) have been settled. Here, we use a new approach to detect bursts in magnetoencephalography (MEG) data. We show that a time-delay embedded Hidden Markov Model (HMM) can be used to delineate single-region bursts which are in agreement with existing techniques. However, unlike existing techniques, the HMM looks for specific spectral patterns in timecourse data. We characterise the distribution of burst duration, frequency of occurrence and amplitude across the cortex in resting state MEG data. During a motor task we show how the movement related beta decrease and post movement beta rebound are driven by changes in burst occurrence. Finally, we show that the beta band functional connectome can be derived using a simple measure of burst overlap, and that coincident bursts in separate regions correspond to a period of heightened coherence. In summary, this paper offers a new methodology for burst identification and connectivity analysis which will be important for future investigations of neural oscillations.
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Affiliation(s)
- Zelekha A Seedat
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Andrew J Quinn
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, UK
| | - Diego Vidaurre
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, UK; Department of Clinical Medicine, Palle Juul-Jensens Boulevard 82, Building 2, Incuba/Skejby, 8200 Aarhus N, Denmark
| | - Lucrezia Liuzzi
- Mood Brain and Development Unit, Emotion and Development Branch, NIH/NIMH, Bethesda, MD 20892, USA
| | - Lauren E Gascoyne
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Benjamin A E Hunt
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK; Diagnostic Imaging, Hospital for Sick Children, 555 University Avenue, Toronto, Ontario, M5G 1X8, Canada
| | - George C O'Neill
- Wellcome Centre for Human Neuroimaging, University College London, 12 Queen Square, London, WC1N 3AR, UK
| | - Daisie O Pakenham
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Karen J Mullinger
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK; Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, B15 2TT, UK
| | - Peter G Morris
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Mark W Woolrich
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, UK
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK.
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20
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Li XB, Wang LB, Xiong YB, Bo QJ, He F, Li F, Hou WP, Wen YJ, Wang XQ, Yang NB, Mao Z, Dong QH, Zhang FF, Yang R, Wang D, Xiang YT, Zhu YY, Tang YL, Yang Z, Wang CY. Altered resting-state functional connectivity of the insula in individuals with clinical high-risk and patients with first-episode schizophrenia. Psychiatry Res 2019; 282:112608. [PMID: 31655405 DOI: 10.1016/j.psychres.2019.112608] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Revised: 10/09/2019] [Accepted: 10/10/2019] [Indexed: 12/18/2022]
Abstract
OBJECTIVES Abnormalities in insular functional connectivity have been implicated in many clinical features of schizophrenia. The aim of this study was to determine to what degree such abnormalities occur in individuals with clinical high risk for psychosis (CHR), and whether which is associated with symptom severity. METHODS Resting-state fMRI data were collected from 47 healthy controls, 24 CHR individuals and 19 patients with first-episode schizophrenia. Using the posterior, dorsal and ventral insular subregions as separate seeds, we examined resting-state functional connectivity differences between different groups and the association between concurrent symptom severity and dysconnectivity. RESULTS Compared with healthy controls, both CHR individuals and schizophrenia patients showed hypoconnectivity between posterior insula (PI) and somatosensory areas, and between dorsal anterior insula (dAI) and putamen. Schizophrenia patients also showed dAI and ventral anterior insula(vAI) hyperconnectivity with visual areas relative to controls and CHR individuals. Correlation analysis revealed that dAI functional connectivity with superior temporal gyrus was positively correlated with positive symptoms of CHR, and vAI connectivity with dorsolateral prefrontal cortex was negatively correlated with the severity of the symptoms of first-episode schizophrenia. CONCLUSIONS Our findings suggest that insular functional dysconnectivity with the sensory cortex may be a system-level neural substrate preceding the onset of psychosis.
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Affiliation(s)
- Xian-Bin Li
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Lu-Bin Wang
- Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing 100850, China
| | - Yan-Bing Xiong
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Qi-Jing Bo
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Fan He
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Feng Li
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Wen-Peng Hou
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Yu-Jie Wen
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Xue-Qi Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Ning-Bo Yang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Zhen Mao
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Qian-Hong Dong
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Fei-Fei Zhang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Rui Yang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Di Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Yu-Tao Xiang
- Unit of Psychiatry, Institute of Translational Medicine, Faculty of Health Sciences, University of Macau, Macao SAR, China; Center for Cognition and Brain Sciences, University of Macau, Macao SAR, China
| | - Yu-Yang Zhu
- Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing 100850, China
| | - Yi-Lang Tang
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Zheng Yang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China; Institute of Military Cognition and Brain Sciences, Academy of Military Medical Sciences, Beijing 100850, China
| | - Chuan-Yue Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China; Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.
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21
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Byrne Á, O'Dea RD, Forrester M, Ross J, Coombes S. Next-generation neural mass and field modeling. J Neurophysiol 2019; 123:726-742. [PMID: 31774370 DOI: 10.1152/jn.00406.2019] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
The Wilson-Cowan population model of neural activity has greatly influenced our understanding of the mechanisms for the generation of brain rhythms and the emergence of structured brain activity. As well as the many insights that have been obtained from its mathematical analysis, it is now widely used in the computational neuroscience community for building large-scale in silico brain networks that can incorporate the increasing amount of knowledge from the Human Connectome Project. Here, we consider a neural population model in the spirit of that originally developed by Wilson and Cowan, albeit with the added advantage that it can account for the phenomena of event-related synchronization and desynchronization. This derived mean-field model provides a dynamic description for the evolution of synchrony, as measured by the Kuramoto order parameter, in a large population of quadratic integrate-and-fire model neurons. As in the original Wilson-Cowan framework, the population firing rate is at the heart of our new model; however, in a significant departure from the sigmoidal firing rate function approach, the population firing rate is now obtained as a real-valued function of the complex-valued population synchrony measure. To highlight the usefulness of this next-generation Wilson-Cowan style model, we deploy it in a number of neurobiological contexts, providing understanding of the changes in power spectra observed in electro- and magnetoencephalography neuroimaging studies of motor cortex during movement, insights into patterns of functional connectivity observed during rest and their disruption by transcranial magnetic stimulation, and to describe wave propagation across cortex.
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Affiliation(s)
- Áine Byrne
- Center for Neural Science, New York University, New York, New York.,School of Mathematics and Statistics, University College Dublin, Dublin, Ireland
| | - Reuben D O'Dea
- Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, Nottingham, United Kingdom
| | - Michael Forrester
- Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, Nottingham, United Kingdom
| | - James Ross
- Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, Nottingham, United Kingdom
| | - Stephen Coombes
- Centre for Mathematical Medicine and Biology, School of Mathematical Sciences, University of Nottingham, Nottingham, United Kingdom
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22
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Gaetz W, Rhodes E, Bloy L, Blaskey L, Jackel CR, Brodkin ES, Waldman A, Embick D, Hall S, Roberts TPL. Evaluating motor cortical oscillations and age-related change in autism spectrum disorder. Neuroimage 2019; 207:116349. [PMID: 31726253 DOI: 10.1016/j.neuroimage.2019.116349] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2019] [Revised: 11/07/2019] [Accepted: 11/09/2019] [Indexed: 12/11/2022] Open
Abstract
Autism spectrum disorder (ASD) is primarily characterized by impairments in social communication and the appearance of repetitive behaviors with restricted interests. Increasingly, evidence also points to a general deficit of motor tone and coordination in children and adults with ASD; yet the neural basis of motor functional impairment in ASD remains poorly characterized. In this study, we used magnetoencephalography (MEG) to (1) assess potential group differences between typically developing (TD) and ASD participants in motor cortical oscillatory activity observed on a simple button-press task and (2) to do so over a sufficiently broad age-range so as to capture age-dependent changes associated with development. Event-related desynchronization was evaluated in Mu (8-13 Hz) and Beta (15-30 Hz) frequency bands (Mu-ERD, Beta-ERD). In addition, post-movement Beta rebound (PMBR), and movement-related gamma (60-90 Hz) synchrony (MRGS) were also assessed in a cohort of 123 participants (63 typically developing (TD) and 59 with ASD) ranging in age from 8 to 24.9 years. We observed significant age-dependent linear trends in Beta-ERD and MRGS power with age for both TD and ASD groups; which did not differ significantly between groups. However, for PMBR, in addition to a significant effect of age, we also observed a significant reduction in PMBR power in the ASD group (p < 0.05). Post-hoc tests showed that this omnibus group difference was driven by the older cohort of children >13.2 years (p < 0.001) and this group difference was not observed when assessing PMBR activity for the younger PMBR groups (ages 8-13.2 years; p = 0.48). Moreover, for the older ASD cohort, hierarchical regression showed a significant relationship between PMBR activity and clinical scores of ASD severity (Social Responsiveness Scale (SRS T scores)), after regressing out the effect of age (p < 0.05). Our results show substantial age-dependent changes in motor cortical oscillations (Beta-ERD and MRGS) occur for both TD and ASD children and diverge only for PMBR, and most significantly for older adolescents and adults with ASD. While the functional significance of PMBR and reduced PMBR signaling remains to be fully elucidated, these results underscore the importance of considering age as a factor when assessing motor cortical oscillations and group differences in children with ASD.
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Affiliation(s)
- William Gaetz
- Lurie Family Foundations' MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
| | - Edward Rhodes
- UK Dementia Research Institute, Imperial College London, London, UK
| | - Luke Bloy
- Lurie Family Foundations' MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Lisa Blaskey
- Lurie Family Foundations' MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Carissa R Jackel
- Division of Developmental and Behavioral Pediatrics, Children's Hospital of Philadelphia, USA
| | - Edward S Brodkin
- Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Amy Waldman
- Division of Neurology, Departments of Neurology and Pediatrics, Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - David Embick
- Department of Linguistics, University of Pennsylvania, Philadelphia, PA, USA
| | - Stephen Hall
- Brain Research and Imaging Centre, University of Plymouth, Devon, UK
| | - Timothy P L Roberts
- Lurie Family Foundations' MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, USA
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23
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Post-stimulus beta responses are modulated by task duration. Neuroimage 2019; 206:116288. [PMID: 31654762 PMCID: PMC6985901 DOI: 10.1016/j.neuroimage.2019.116288] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Revised: 09/12/2019] [Accepted: 10/16/2019] [Indexed: 02/08/2023] Open
Abstract
Modulation of beta-band neural oscillations during and following movement is a robust marker of brain function. In particular, the post-movement beta rebound (PMBR), which occurs on movement cessation, has been related to inhibition and connectivity in the healthy brain, and is perturbed in disease. However, to realise the potential of the PMBR as a biomarker, its modulation by task parameters must be characterised and its functional role determined. Here, we used MEG to image brain electrophysiology during and after a grip-force task, with the aim to characterise how task duration, in the form of an isometric contraction, modulates beta responses. Fourteen participants exerted a 30% maximum voluntary grip-force for 2, 5 and 10 s. Our results showed that the amplitude of the PMBR is modulated by task duration, with increasing duration significantly reducing PMBR amplitude and increasing its time-to-peak. No variation in the amplitude of the movement related beta decrease (MRBD) with task duration was observed. To gain insight into what may underlie these trial-averaged results, we used a Hidden Markov Model to identify the individual trial dynamics of a brain network encompassing bilateral sensorimotor areas. The rapidly evolving dynamics of this network demonstrated similar variation with task parameters to the ‘classical’ rebound, and we show that the modulation of the PMBR can be well-described in terms of increased frequency of beta events on a millisecond timescale rather than modulation of beta amplitude during this time period. Our results add to the emerging picture that, in the case of a carefully controlled paradigm, beta modulation can be systematically controlled by task parameters and such control can reveal new information as to the processes that generate the average beta timecourse. These findings will support design of clinically relevant paradigms and analysis pipelines in future use of the PMBR as a marker of neuropathology. The post-movement beta rebound is modulated by task duration. Increasing task duration reduces amplitude of the post-movement beta rebound. The modulation is explained by increased frequency of short-timescale beta events.
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24
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25
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Liddle PF. The Core Deficit of Classical Schizophrenia: Implications for Predicting the Functional Outcome of Psychotic Illness and Developing Effective Treatments. CANADIAN JOURNAL OF PSYCHIATRY. REVUE CANADIENNE DE PSYCHIATRIE 2019; 64:680-685. [PMID: 31434513 PMCID: PMC6783668 DOI: 10.1177/0706743719870515] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Many people suffering from psychotic illnesses experience persisting impairment of occupational and social function. Evidence assembled since the classical description of schizophrenia over a century ago indicates that both disorganization and impoverishment of mental activity are associated with persisting impairment. Longitudinal studies of young people at risk of schizophrenia reveal that both mental impoverishment and disorganization predict poor long-term outcome. These clinical features are related to cognitive impairments. Evidence from brain imaging indicates overlap in the brain abnormalities implicated in these phenomena, including impaired function of long-range connections between sensory cortex and the salience network, a network engaged in recruiting cerebral systems for processing of information salient to current circumstances. The evidence suggests that the common features underlying these two groups of symptoms might reflect a core pathological process distinguishing nonaffective from affective psychosis. This pathological process might therefore justifiably be designated the "core deficit" of classical schizophrenia. To develop more effective treatments to prevent persisting disability, we require the ability to identify individuals at risk at an early stage. Recent studies provide pointers toward effective strategies for identifying cases at risk of poor outcome. Accumulating evidence confirms that appreciable potential for neuroplastic change in the brain persists into adult life. Furthermore, brain function can be enhanced by targeted neuromodulation treatments. We now have promising tools not only for investigating the psychological and neural mechanisms that underlie persisting functional impairment but also for identifying individuals at risk and for harnessing brain plasticity to improve treatment.
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Affiliation(s)
- Peter F. Liddle
- Division of Psychiatry and Applied Psychology, Institute of Mental Health, University of Nottingham, Nottingham, United Kingdom
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26
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Hunt BAE, Liddle EB, Gascoyne LE, Magazzini L, Routley BC, Singh KD, Morris PG, Brookes MJ, Liddle PF. Attenuated Post-Movement Beta Rebound Associated With Schizotypal Features in Healthy People. Schizophr Bull 2019; 45:883-891. [PMID: 30239878 PMCID: PMC6581139 DOI: 10.1093/schbul/sby117] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
INTRODUCTION Schizophrenia and schizotypal personality disorder (SPD) lie on a single spectrum of mental illness and converging evidence suggests similarities in the etiology of the 2 conditions. However, schizotypy is a heterogeneous facet of personality in the healthy population and so may be seen as a bridge between health and mental illness. Neural evidence for such a continuity would have implications for the characterization and treatment of schizophrenia. Based on our previous work identifying a relationship between symptomology in schizophrenia and abnormal movement-induced electrophysiological response (the post-movement beta rebound [PMBR]), we predicted that if subclinical schizotypy arises from similar neural mechanisms to schizophrenia, schizotypy in healthy individuals would be associated with reduced PMBR. METHODS One-hundred sixteen participants completed a visuomotor task while their neural activity was recorded by magnetoencephalography. Partial correlations were computed between a measure of PMBR extracted from left primary motor cortex and scores on the Schizotypal Personality Questionnaire (SPQ), a self-report measure of schizotypal personality. Correlations between PMBR and SPQ factor scores measuring cognitive-perceptual, interpersonal and disorganization dimensions of schizotypy were also computed. Effects of site, age, and sex were controlled for. RESULTS We found a significant negative correlation between total SPQ score and PMBR. This was most strongly mediated by variance shared between interpersonal and disorganization factor scores. CONCLUSION These findings indicate a continuum of neural deficit between schizotypy and schizophrenia, with diminution of PMBR, previously reported in schizophrenia, also measurable in individuals with schizotypal features, particularly disorganization and impaired interpersonal relations.
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Affiliation(s)
- Benjamin A E Hunt
- Diagnostic Imaging, The Hospital for Sick Children, Toronto, ON, Canada
- Program in Neurosciences and Mental Health, The Hospital for Sick Children Research Institute, Toronto, ON, Canada
- The Sir Peter Mansfield Imaging Centre, University of Nottingham, Nottingham, UK
| | - Elizabeth B Liddle
- The Institute for Mental Health, University of Nottingham, Nottingham, UK
| | - Lauren E Gascoyne
- Program in Neurosciences and Mental Health, The Hospital for Sick Children Research Institute, Toronto, ON, Canada
| | - Lorenzo Magazzini
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, UK
| | - Bethany C Routley
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, UK
| | - Krish D Singh
- Cardiff University Brain Research Imaging Centre, School of Psychology, Cardiff University, Cardiff, UK
| | - Peter G Morris
- Program in Neurosciences and Mental Health, The Hospital for Sick Children Research Institute, Toronto, ON, Canada
| | - Matthew J Brookes
- Program in Neurosciences and Mental Health, The Hospital for Sick Children Research Institute, Toronto, ON, Canada
| | - Peter F Liddle
- The Institute for Mental Health, University of Nottingham, Nottingham, UK
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27
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O'Neill GC, Watkins RH, Ackerley R, Barratt EL, Sengupta A, Asghar M, Sanchez Panchuelo RM, Brookes MJ, Glover PM, Wessberg J, Francis ST. Imaging human cortical responses to intraneural microstimulation using magnetoencephalography. Neuroimage 2019; 189:329-340. [PMID: 30639839 PMCID: PMC6435103 DOI: 10.1016/j.neuroimage.2019.01.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Revised: 01/02/2019] [Accepted: 01/08/2019] [Indexed: 01/25/2023] Open
Abstract
The sensation of touch in the glabrous skin of the human hand is conveyed by thousands of fast-conducting mechanoreceptive afferents, which can be categorised into four distinct types. The spiking properties of these afferents in the periphery in response to varied tactile stimuli are well-characterised, but relatively little is known about the spatiotemporal properties of the neural representations of these different receptor types in the human cortex. Here, we use the novel methodological combination of single-unit intraneural microstimulation (INMS) with magnetoencephalography (MEG) to localise cortical representations of individual touch afferents in humans, by measuring the extracranial magnetic fields from neural currents. We found that by assessing the modulation of the beta (13-30 Hz) rhythm during single-unit INMS, significant changes in oscillatory amplitude occur in the contralateral primary somatosensory cortex within and across a group of fast adapting type I mechanoreceptive afferents, which corresponded well to the induced response from matched vibrotactile stimulation. Combining the spatiotemporal specificity of MEG with the selective single-unit stimulation of INMS enables the interrogation of the central representations of different aspects of tactile afferent signalling within the human cortices. The fundamental finding that single-unit INMS ERD responses are robust and consistent with natural somatosensory stimuli will permit us to more dynamically probe the central nervous system responses in humans, to address questions about the processing of touch from the different classes of mechanoreceptive afferents and the effects of varying the stimulus frequency and patterning.
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Affiliation(s)
- George C O'Neill
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK.
| | - Roger H Watkins
- Department of Physiology, University of Gothenburg, Gothenburg, Sweden
| | - Rochelle Ackerley
- Department of Physiology, University of Gothenburg, Gothenburg, Sweden; Aix Marseille Univ, CNRS, LNSC (Laboratoire de Neurosciences Sensorielles et Cognitives - UMR 7260), Marseille, France
| | - Eleanor L Barratt
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Ayan Sengupta
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Michael Asghar
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | | | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Paul M Glover
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Johan Wessberg
- Department of Physiology, University of Gothenburg, Gothenburg, Sweden
| | - Susan T Francis
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
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28
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Holmes N, Leggett J, Boto E, Roberts G, Hill RM, Tierney TM, Shah V, Barnes GR, Brookes MJ, Bowtell R. A bi-planar coil system for nulling background magnetic fields in scalp mounted magnetoencephalography. Neuroimage 2018; 181:760-774. [PMID: 30031934 PMCID: PMC6150951 DOI: 10.1016/j.neuroimage.2018.07.028] [Citation(s) in RCA: 64] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2018] [Revised: 06/20/2018] [Accepted: 07/12/2018] [Indexed: 01/13/2023] Open
Abstract
Small, commercially-available Optically Pumped Magnetometers (OPMs) can be used to construct a wearable Magnetoencephalography (MEG) system that allows large head movements to be made during recording. The small dynamic range of these sensors however means that movement in the residual static magnetic field found inside typical Magnetically Shielded Rooms (MSRs) can saturate the sensor outputs, rendering the data unusable. This problem can be ameliorated by using a set of electromagnetic coils to attenuate the spatially-varying remnant field. Here, an array of bi-planar coils, which produce an open and accessible scanning environment, was designed and constructed. The coils were designed using a harmonic minimisation method previously used for gradient coil design in Magnetic Resonance Imaging (MRI). Six coils were constructed to null Bx, By and Bz as well as the three dominant field gradients dBx/dz, dBy/dz and dBz/dz. The coils produce homogeneous (within ±5%) fields or field gradients over a volume of 40 × 40 × 40 cm3. This volume is sufficient to contain an array of OPMs, mounted in a 3D-printed scanner-cast, during basic and natural movements. Automated control of the coils using reference sensor measurements allows reduction of the largest component of the static field (Bx) from 21.8 ± 0.2 nT to 0.47 ± 0.08 nT. The largest gradient (dBx/dz) was reduced from 7.4 nT/m to 0.55 nT/m. High precision optical tracking allowed experiments involving controlled and measured head movements, which revealed that a rotation of the scanner-cast by ±34° and translation of ±9.7 cm of the OPMs in this field generated only a 1 nT magnetic field variation across the OPM array, when field nulling was applied. This variation could be further reduced to 0.04 nT by linear regression of field variations that were correlated with the measured motion parameters. To demonstrate the effectiveness of the bi-planar coil field cancellation system in a real MEG experiment, a novel measurement of retinotopy was investigated, where the stimulus remains fixed and head movements made by the subject shift the visual presentation to the lower left or right quadrants of the field of view. Left and right visual field stimulation produced the expected responses in the opposing hemisphere. This simple demonstration shows that the bi-planar coil system allows accurate OPM-MEG recordings to be made on an unrestrained subject.
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Affiliation(s)
- Niall Holmes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, NG7 2RD, UK
| | - James Leggett
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, NG7 2RD, UK
| | - Elena Boto
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, NG7 2RD, UK
| | - Gillian Roberts
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, NG7 2RD, UK
| | - Ryan M Hill
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, NG7 2RD, UK
| | - Tim M Tierney
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London, WC1N 3AR, UK
| | - Vishal Shah
- QuSpin Inc., 331 South 104th Street, Suite 130, Louisville, CO 80027, USA
| | - Gareth R Barnes
- Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London, WC1N 3AR, UK
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, NG7 2RD, UK
| | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, NG7 2RD, UK.
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29
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Gascoyne LE, Mullinger KJ, Robson SE, Kumar J, O'Neill GC, Palaniyappan L, Morris PG, Liddle EB, Brookes MJ, Liddle PF. Changes in electrophysiological markers of cognitive control after administration of galantamine. Neuroimage Clin 2018; 20:228-235. [PMID: 30090697 PMCID: PMC6078055 DOI: 10.1016/j.nicl.2018.07.019] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Revised: 06/12/2018] [Accepted: 07/21/2018] [Indexed: 02/01/2023]
Abstract
The healthy brain is able to maintain a stable balance between bottom-up sensory processing and top-down cognitive control. The neurotransmitter acetylcholine plays a substantial role in this. Disruption of this balance could contribute to symptoms occurring in psychosis, including subtle disruption of motor control and aberrant appropriation of salience to external stimuli; however the pathological mechanisms are poorly understood. On account of the role beta oscillations play in mediating cognitive control, investigation of beta oscillations is potentially informative about such mechanisms. Here, we used magnetoencephalography to investigate the effect of the acetylcholinesterase-inhibitor, galantamine, on beta oscillations within the sensorimotor region during both a sensorimotor task and a relevance-modulation task in healthy participants, employing a double blind randomized placebo controlled cross-over design. In the galantamine condition, we found a significant reduction in the post-movement beta rebound in the case of executed movements and also in a planned but not executed movement. In the latter case, the effect was significantly greater following task-relevant compared with irrelevant stimuli. The results suggest that the action of galantamine reduces the influence of top-down cognitive processing relative to bottom-up perceptual processing in a manner resembling changes previously reported in schizophrenia.
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Affiliation(s)
- Lauren E Gascoyne
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK.
| | - Karen J Mullinger
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - Siân E Robson
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - Jyothika Kumar
- Institute of Mental Health, Jubilee Campus, University of Nottingham, Nottingham, UK
| | - George C O'Neill
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - Lena Palaniyappan
- Department of Psychiatry & Robarts Research Institute, University of Western Ontario & Lawson Health Research Institute, London, ON, Canada
| | - Peter G Morris
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - Elizabeth B Liddle
- Institute of Mental Health, Jubilee Campus, University of Nottingham, Nottingham, UK
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - Peter F Liddle
- Institute of Mental Health, Jubilee Campus, University of Nottingham, Nottingham, UK.
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30
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Hadida J, Sotiropoulos SN, Abeysuriya RG, Woolrich MW, Jbabdi S. Bayesian Optimisation of Large-Scale Biophysical Networks. Neuroimage 2018; 174:219-236. [PMID: 29518570 PMCID: PMC6324723 DOI: 10.1016/j.neuroimage.2018.02.063] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2017] [Revised: 02/27/2018] [Accepted: 02/28/2018] [Indexed: 01/08/2023] Open
Abstract
The relationship between structure and function in the human brain is well established, but not yet well characterised. Large-scale biophysical models allow us to investigate this relationship, by leveraging structural information (e.g. derived from diffusion tractography) in order to couple dynamical models of local neuronal activity into networks of interacting regions distributed across the cortex. In practice however, these models are difficult to parametrise, and their simulation is often delicate and computationally expensive. This undermines the experimental aspect of scientific modelling, and stands in the way of comparing different parametrisations, network architectures, or models in general, with confidence. Here, we advocate the use of Bayesian optimisation for assessing the capabilities of biophysical network models, given a set of desired properties (e.g. band-specific functional connectivity); and in turn the use of this assessment as a principled basis for incremental modelling and model comparison. We adapt an optimisation method designed to cope with costly, high-dimensional, non-convex problems, and demonstrate its use and effectiveness. Using five parameters controlling key aspects of our model, we find that this method is able to converge to regions of high functional similarity with real MEG data, with very few samples given the number of parameters, without getting stuck in local extrema, and while building and exploiting a map of uncertainty defined smoothly across the parameter space. We compare the results obtained using different methods of structural connectivity estimation from diffusion tractography, and find that one method leads to better simulations.
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Affiliation(s)
- J Hadida
- Wellcome Centre for Integrative Neuroimaging (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, UK; Wellcome Centre for Integrative Neuroimaging (OHBA), Department of Psychiatry, University of Oxford, UK.
| | - S N Sotiropoulos
- Wellcome Centre for Integrative Neuroimaging (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, UK; Sir Peter Mansfield Imaging Centre (SPMIC), School of Medicine, University of Nottingham, UK
| | - R G Abeysuriya
- Wellcome Centre for Integrative Neuroimaging (OHBA), Department of Psychiatry, University of Oxford, UK
| | - M W Woolrich
- Wellcome Centre for Integrative Neuroimaging (OHBA), Department of Psychiatry, University of Oxford, UK
| | - S Jbabdi
- Wellcome Centre for Integrative Neuroimaging (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, UK
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Barratt EL, Francis ST, Morris PG, Brookes MJ. Mapping the topological organisation of beta oscillations in motor cortex using MEG. Neuroimage 2018; 181:831-844. [PMID: 29960087 PMCID: PMC6150950 DOI: 10.1016/j.neuroimage.2018.06.041] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2018] [Revised: 06/05/2018] [Accepted: 06/12/2018] [Indexed: 12/19/2022] Open
Abstract
The spatial topology of the human motor cortex has been well studied, particularly using functional Magnetic Resonance Imaging (fMRI) which allows spatial separation of haemodynamic responses arising from stimulation of different body parts, individual digits and even spatially separate areas of the same digit. However, the spatial organisation of electrophysiological responses, particularly neural oscillations (rhythmic changes in electrical potential across cellular assemblies) has been less well studied. Mapping the spatial signature of neural oscillations is possible using magnetoencephalography (MEG), however spatial differentiation of responses induced by movement of separate digits is a challenge, because the brain regions involved are separated by only a few millimetres. In this paper we first show, in simulation, how to optimise experimental design and beamformer spatial filtering techniques to increase the spatial specificity of MEG derived functional images. Combining this result with experimental data, we then capture the organisation of the post-movement beta band (13–30 Hz) oscillatory response to movement of digits 2 and 5 of the dominant hand, in individual subjects. By comparing these MEG results to ultra-high field (7T) fMRI, we also show significant spatial agreement between beta modulation and the blood oxygenation level dependent (BOLD) response. Our results show that, when using an optimised inverse solution and controlling subject movement (using custom fitted foam padding) the spatial resolution of MEG can be of order 3–5 mm. The method described offers exciting potential to understand better the cortical organisation of oscillations, and to probe such organisation in patient populations where those oscillations are known to be abnormal. Aim is to map the topological organisation of neural oscillations in motor cortex. MEG spatial resolution optimised by temporal separation of sources. Subject motion controlled using foam headcasts. Cortical representation of Digit 2 and Digit 5 separated spatially. Post movement beta rebound maps motortopically in agreement with BOLD responses.
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Affiliation(s)
- Eleanor L Barratt
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, United Kingdom
| | - Susan T Francis
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, United Kingdom
| | - Peter G Morris
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, United Kingdom
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, United Kingdom.
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32
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Moving magnetoencephalography towards real-world applications with a wearable system. Nature 2018; 555:657-661. [PMID: 29562238 PMCID: PMC6063354 DOI: 10.1038/nature26147] [Citation(s) in RCA: 359] [Impact Index Per Article: 59.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2017] [Accepted: 02/13/2018] [Indexed: 12/29/2022]
Abstract
Imaging human brain function with techniques such as magnetoencephalography typically requires a subject to perform tasks while their head remains still within a restrictive scanner. This artificial environment makes the technique inaccessible to many people, and limits the experimental questions that can be addressed. For example, it has been difficult to apply neuroimaging to investigation of the neural substrates of cognitive development in babies and children, or to study processes in adults that require unconstrained head movement (such as spatial navigation). Here we describe a magnetoencephalography system that can be worn like a helmet, allowing free and natural movement during scanning. This is possible owing to the integration of quantum sensors, which do not rely on superconducting technology, with a system for nulling background magnetic fields. We demonstrate human electrophysiological measurement at millisecond resolution while subjects make natural movements, including head nodding, stretching, drinking and playing a ball game. Our results compare well to those of the current state-of-the-art, even when subjects make large head movements. The system opens up new possibilities for scanning any subject or patient group, with myriad applications such as characterization of the neurodevelopmental connectome, imaging subjects moving naturally in a virtual environment and investigating the pathophysiology of movement disorders.
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Fry A, Mullinger KJ, O'Neill GC, Brookes MJ, Folland JP. The effect of physical fatigue on oscillatory dynamics of the sensorimotor cortex. Acta Physiol (Oxf) 2017; 220:370-381. [PMID: 27981752 DOI: 10.1111/apha.12843] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2016] [Revised: 08/15/2016] [Accepted: 12/07/2016] [Indexed: 11/28/2022]
Abstract
AIM While physical fatigue is known to arise in part from supraspinal mechanisms within the brain, exactly how brain activity is modulated during fatigue is not well understood. Therefore, this study examined how typical neural oscillatory responses to voluntary muscle contractions were affected by fatigue. METHODS Eleven healthy adults (age 27 ± 4 years) completed two experimental sessions in a randomized crossover design. Both sessions first assessed baseline maximal voluntary isometric wrist-flexion force (MVFb ). Participants then performed an identical series of fourteen test contractions (2 × 100%MVFb , 10 × 40%MVFb , 2 × 100%MVFb ) both before and after one of two interventions: forty 12-s contractions at 55%MVFb (fatigue intervention) or 5%MVFb (control intervention). Magnetoencephalography (MEG) was used to characterize both the movement-related mu and beta decrease (MRMD and MRBD) and the post-movement beta rebound (PMBR) within the contralateral sensorimotor cortex during the 40%MVFb test contractions, while the 100%MVFb test contractions were used to monitor physical fatigue. RESULTS The fatigue intervention induced a substantial physical fatigue that endured throughout the post-intervention measurements (28.9-29.5% decrease in MVF, P < 0.001). Fatigue had a significant effect on both PMBR (anova, session × time-point interaction: P = 0.018) and MRBD (P = 0.021): the magnitude of PMBR increased following the fatigue but not the control interventions, whereas MRBD was decreased post-control but not post-fatigue. Mu oscillations were unchanged throughout both sessions. CONCLUSION Physical fatigue resulted in an increased PMBR, and offset attenuations in MRBD associated with task habituation.
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Affiliation(s)
- A. Fry
- School of Sport, Exercise and Health Sciences; Loughborough University; Leicestershire UK
| | - K. J. Mullinger
- Sir Peter Mansfield Imaging Centre; School of Physics and Astronomy; University of Nottingham; University Park; Nottingham UK
- Birmingham University Imaging Centre; School of Psychology; University of Birmingham; Birmingham UK
| | - G. C. O'Neill
- Sir Peter Mansfield Imaging Centre; School of Physics and Astronomy; University of Nottingham; University Park; Nottingham UK
| | - M. J. Brookes
- Sir Peter Mansfield Imaging Centre; School of Physics and Astronomy; University of Nottingham; University Park; Nottingham UK
| | - J. P. Folland
- School of Sport, Exercise and Health Sciences; Loughborough University; Leicestershire UK
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Mullinger KJ, Cherukara MT, Buxton RB, Francis ST, Mayhew SD. Post-stimulus fMRI and EEG responses: Evidence for a neuronal origin hypothesised to be inhibitory. Neuroimage 2017; 157:388-399. [PMID: 28610902 DOI: 10.1016/j.neuroimage.2017.06.020] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2016] [Revised: 06/05/2017] [Accepted: 06/09/2017] [Indexed: 12/26/2022] Open
Abstract
Post-stimulus undershoots, negative responses following cessation of stimulation, are widely observed in functional magnetic resonance (fMRI) blood oxygenation level dependent (BOLD) data. However, the debate surrounding whether the origin of this response phase is neuronal or vascular, and whether it provides functionally relevant information, that is additional to what is contained in the primary response, means that undershoots are widely overlooked. We simultaneously recorded electroencephalography (EEG), BOLD and cerebral blood-flow (CBF) [obtained from arterial spin labelled (ASL) fMRI] fMRI responses to hemifield checkerboard stimulation to test the potential neural origin of the fMRI post-stimulus undershoot. The post-stimulus BOLD and CBF signal amplitudes in both contralateral and ipsilateral visual cortex depended on the post-stimulus power of the occipital 8-13Hz (alpha) EEG neuronal activity, such that trials with highest EEG power showed largest fMRI undershoots in contralateral visual cortex. This correlation in post-stimulus EEG-fMRI responses was not predicted by the primary response amplitude. In the contralateral visual cortex we observed a decrease in both cerebral rate of oxygen metabolism (CMRO2) and CBF during the post-stimulus phase. In addition, the coupling ratio (n) between CMRO2 and CBF was significantly lower during the positive contralateral primary response phase compared with the post-stimulus phase and we propose that this reflects an altered balance of excitatory and inhibitory neuronal activity. Together our data provide strong evidence that the post-stimulus phase of the BOLD response has a neural origin which reflects, at least partially, an uncoupling of the neuronal responses driving the primary and post-stimulus responses, explaining the uncoupling of the signals measured in the two response phases. We suggest our results are consistent with inhibitory processes driving the post-stimulus EEG and fMRI responses. We therefore propose that new methods are required to model the post-stimulus and primary responses independently, enabling separate investigation of response phases in cognitive function and neurological disease.
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Affiliation(s)
- K J Mullinger
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK; Birmingham University Imaging Centre, School of Psychology, University of Birmingham, Birmingham B15 2TT, UK.
| | - M T Cherukara
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK
| | - R B Buxton
- Department of Radiology, Center for Functional MRI, University of California, San Diego, La Jolla, CA, USA
| | - S T Francis
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, UK
| | - S D Mayhew
- Birmingham University Imaging Centre, School of Psychology, University of Birmingham, Birmingham B15 2TT, UK
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35
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Boto E, Meyer SS, Shah V, Alem O, Knappe S, Kruger P, Fromhold TM, Lim M, Glover PM, Morris PG, Bowtell R, Barnes GR, Brookes MJ. A new generation of magnetoencephalography: Room temperature measurements using optically-pumped magnetometers. Neuroimage 2017; 149:404-414. [PMID: 28131890 PMCID: PMC5562927 DOI: 10.1016/j.neuroimage.2017.01.034] [Citation(s) in RCA: 153] [Impact Index Per Article: 21.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2016] [Revised: 01/11/2017] [Accepted: 01/15/2017] [Indexed: 11/29/2022] Open
Abstract
Advances in the field of quantum sensing mean that magnetic field sensors, operating at room temperature, are now able to achieve sensitivity similar to that of cryogenically cooled devices (SQUIDs). This means that room temperature magnetoencephalography (MEG), with a greatly increased flexibility of sensor placement can now be considered. Further, these new sensors can be placed directly on the scalp surface giving, theoretically, a large increase in the magnitude of the measured signal. Here, we present recordings made using a single optically-pumped magnetometer (OPM) in combination with a 3D-printed head-cast designed to accurately locate and orient the sensor relative to brain anatomy. Since our OPM is configured as a magnetometer it is highly sensitive to environmental interference. However, we show that this problem can be ameliorated via the use of simultaneous reference sensor recordings. Using median nerve stimulation, we show that the OPM can detect both evoked (phase-locked) and induced (non-phase-locked oscillatory) changes when placed over sensory cortex, with signals ~4 times larger than equivalent SQUID measurements. Using source modelling, we show that our system allows localisation of the evoked response to somatosensory cortex. Further, source-space modelling shows that, with 13 sequential OPM measurements, source-space signal-to-noise ratio (SNR) is comparable to that from a 271-channel SQUID system. Our results highlight the opportunity presented by OPMs to generate uncooled, potentially low-cost, high SNR MEG systems.
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Affiliation(s)
- Elena Boto
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - Sofie S Meyer
- Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, United Kingdom
| | - Vishal Shah
- QuSpin Inc., 2011 Cherry Street, Unit 112, Louisville, CO 80027, USA
| | - Orang Alem
- QuSpin Inc., 2011 Cherry Street, Unit 112, Louisville, CO 80027, USA
| | - Svenja Knappe
- QuSpin Inc., 2011 Cherry Street, Unit 112, Louisville, CO 80027, USA
| | - Peter Kruger
- Midlands Ultracold Atom Research Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - T Mark Fromhold
- Midlands Ultracold Atom Research Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - Mark Lim
- Chalk Studios Ltd., 14 Windsor Street, London N1 8QG, United Kingdom
| | - Paul M Glover
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - Peter G Morris
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom
| | - Gareth R Barnes
- Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, 12 Queen Square, London WC1N 3BG, United Kingdom
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom.
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Fry A, Mullinger KJ, O'Neill GC, Barratt EL, Morris PG, Bauer M, Folland JP, Brookes MJ. Modulation of post-movement beta rebound by contraction force and rate of force development. Hum Brain Mapp 2016; 37:2493-511. [PMID: 27061243 PMCID: PMC4982082 DOI: 10.1002/hbm.23189] [Citation(s) in RCA: 50] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2015] [Revised: 02/12/2016] [Accepted: 03/09/2016] [Indexed: 11/30/2022] Open
Abstract
Movement induced modulation of the beta rhythm is one of the most robust neural oscillatory phenomena in the brain. In the preparation and execution phases of movement, a loss in beta amplitude is observed [movement related beta decrease (MRBD)]. This is followed by a rebound above baseline on movement cessation [post movement beta rebound (PMBR)]. These effects have been measured widely, and recent work suggests that they may have significant importance. Specifically, they have potential to form the basis of biomarkers for disease, and have been used in neuroscience applications ranging from brain computer interfaces to markers of neural plasticity. However, despite the robust nature of both MRBD and PMBR, the phenomena themselves are poorly understood. In this study, we characterise MRBD and PMBR during a carefully controlled isometric wrist flexion paradigm, isolating two fundamental movement parameters; force output, and the rate of force development (RFD). Our results show that neither altered force output nor RFD has a significant effect on MRBD. In contrast, PMBR was altered by both parameters. Higher force output results in greater PMBR amplitude, and greater RFD results in a PMBR which is higher in amplitude and shorter in duration. These findings demonstrate that careful control of movement parameters can systematically change PMBR. Further, for temporally protracted movements, the PMBR can be over 7 s in duration. This means accurate control of movement and judicious selection of paradigm parameters are critical in future clinical and basic neuroscientific studies of sensorimotor beta oscillations. Hum Brain Mapp 37:2493–2511, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc
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Affiliation(s)
- Adam Fry
- School of Sport, Exercise and Health Sciences, Loughborough University, Leicestershire, LE11 3TU, United Kingdom
| | - Karen J Mullinger
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, United Kingdom.,Birmingham University Imaging Centre, School of Psychology, University of Birmingham, Birmingham, B15 2TT, United Kingdom
| | - George C O'Neill
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, United Kingdom
| | - Eleanor L Barratt
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, United Kingdom
| | - Peter G Morris
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, United Kingdom
| | - Markus Bauer
- School of Psychology, University of Nottingham, University Park, Nottingham, NG7 2RD, United Kingdom
| | - Jonathan P Folland
- School of Sport, Exercise and Health Sciences, Loughborough University, Leicestershire, LE11 3TU, United Kingdom
| | - Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, United Kingdom
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