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Bastola S, Jahromi S, Chikara R, Stufflebeam SM, Ottensmeyer MP, De Novi G, Papadelis C, Alexandrakis G. Improved Dipole Source Localization from Simultaneous MEG-EEG Data by Combining a Global Optimization Algorithm with a Local Parameter Search: A Brain Phantom Study. Bioengineering (Basel) 2024; 11:897. [PMID: 39329639 PMCID: PMC11428344 DOI: 10.3390/bioengineering11090897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2024] [Revised: 09/03/2024] [Accepted: 09/04/2024] [Indexed: 09/28/2024] Open
Abstract
Dipole localization, a fundamental challenge in electromagnetic source imaging, inherently constitutes an optimization problem aimed at solving the inverse problem of electric current source estimation within the human brain. The accuracy of dipole localization algorithms is contingent upon the complexity of the forward model, often referred to as the head model, and the signal-to-noise ratio (SNR) of measurements. In scenarios characterized by low SNR, often corresponding to deep-seated sources, existing optimization techniques struggle to converge to global minima, thereby leading to the localization of dipoles at erroneous positions, far from their true locations. This study presents a novel hybrid algorithm that combines simulated annealing with the traditional quasi-Newton optimization method, tailored to address the inherent limitations of dipole localization under low-SNR conditions. Using a realistic head model for both electroencephalography (EEG) and magnetoencephalography (MEG), it is demonstrated that this novel hybrid algorithm enables significant improvements of up to 45% in dipole localization accuracy compared to the often-used dipole scanning and gradient descent techniques. Localization improvements are not only found for single dipoles but also in two-dipole-source scenarios, where sources are proximal to each other. The novel methodology presented in this work could be useful in various applications of clinical neuroimaging, particularly in cases where recordings are noisy or sources are located deep within the brain.
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Affiliation(s)
- Subrat Bastola
- Bioengineering Department, The University of Texas at Arlington, Arlington, TX 76019, USA; (S.J.); (R.C.); (C.P.); (G.A.)
| | - Saeed Jahromi
- Bioengineering Department, The University of Texas at Arlington, Arlington, TX 76019, USA; (S.J.); (R.C.); (C.P.); (G.A.)
- Neuroscience Research Center, Jane and John Justin Institute for Mind Health, Cook Children’s Health Care System, Fort Worth, TX 76104, USA
| | - Rupesh Chikara
- Bioengineering Department, The University of Texas at Arlington, Arlington, TX 76019, USA; (S.J.); (R.C.); (C.P.); (G.A.)
- Neuroscience Research Center, Jane and John Justin Institute for Mind Health, Cook Children’s Health Care System, Fort Worth, TX 76104, USA
| | - Steven M. Stufflebeam
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA;
| | - Mark P. Ottensmeyer
- Medical Device & Simulation Laboratory, Massachusetts General Hospital, Harvard Medical School, Cambridge, MA 02139, USA; (M.P.O.); (G.D.N.)
| | - Gianluca De Novi
- Medical Device & Simulation Laboratory, Massachusetts General Hospital, Harvard Medical School, Cambridge, MA 02139, USA; (M.P.O.); (G.D.N.)
| | - Christos Papadelis
- Bioengineering Department, The University of Texas at Arlington, Arlington, TX 76019, USA; (S.J.); (R.C.); (C.P.); (G.A.)
- Neuroscience Research Center, Jane and John Justin Institute for Mind Health, Cook Children’s Health Care System, Fort Worth, TX 76104, USA
| | - George Alexandrakis
- Bioengineering Department, The University of Texas at Arlington, Arlington, TX 76019, USA; (S.J.); (R.C.); (C.P.); (G.A.)
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Bonetti L, Brattico E, Carlomagno F, Cabral J, Stevner A, Deco G, Whybrow PC, Pearce M, Pantazis D, Vuust P, Kringelbach ML. Spatiotemporal whole-brain activity and functional connectivity of melodies recognition. Cereb Cortex 2024; 34:bhae320. [PMID: 39110413 PMCID: PMC11304985 DOI: 10.1093/cercor/bhae320] [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: 05/13/2024] [Revised: 07/12/2024] [Accepted: 07/26/2024] [Indexed: 08/10/2024] Open
Abstract
Music is a non-verbal human language, built on logical, hierarchical structures, that offers excellent opportunities to explore how the brain processes complex spatiotemporal auditory sequences. Using the high temporal resolution of magnetoencephalography, we investigated the unfolding brain dynamics of 70 participants during the recognition of previously memorized musical sequences compared to novel sequences matched in terms of entropy and information content. Measures of both whole-brain activity and functional connectivity revealed a widespread brain network underlying the recognition of the memorized auditory sequences, which comprised primary auditory cortex, superior temporal gyrus, insula, frontal operculum, cingulate gyrus, orbitofrontal cortex, basal ganglia, thalamus, and hippocampus. Furthermore, while the auditory cortex responded mainly to the first tones of the sequences, the activity of higher-order brain areas such as the cingulate gyrus, frontal operculum, hippocampus, and orbitofrontal cortex largely increased over time during the recognition of the memorized versus novel musical sequences. In conclusion, using a wide range of analytical techniques spanning from decoding to functional connectivity and building on previous works, our study provided new insights into the spatiotemporal whole-brain mechanisms for conscious recognition of auditory sequences.
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Affiliation(s)
- Leonardo Bonetti
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, 8000 Aarhus/Aalborg, Denmark
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, OX39BX Oxford, United Kingdom
- Department of Psychiatry, University of Oxford, OX37JX Oxford, United Kingdom
| | - Elvira Brattico
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, 8000 Aarhus/Aalborg, Denmark
- Department of Education, Psychology, Communication, University of Bari Aldo Moro, 70121 Bari, Italy
| | - Francesco Carlomagno
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, 8000 Aarhus/Aalborg, Denmark
| | - Joana Cabral
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, 8000 Aarhus/Aalborg, Denmark
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, OX39BX Oxford, United Kingdom
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057 Braga, Portugal
| | - Angus Stevner
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, 8000 Aarhus/Aalborg, Denmark
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, OX39BX Oxford, United Kingdom
| | - Gustavo Deco
- Computational and Theoretical Neuroscience Group, Center for Brain and Cognition, Universitat Pompeu Fabra, 08018 Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona, Spain
| | - Peter C Whybrow
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, 90095 Los Angeles, CA, United States
| | - Marcus Pearce
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, 8000 Aarhus/Aalborg, Denmark
| | - Dimitrios Pantazis
- McGovern Institute for Brain Research, Massachusetts Institute of Technology (MIT), 02139 Cambridge, MA, United States
| | - Peter Vuust
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, 8000 Aarhus/Aalborg, Denmark
| | - Morten L Kringelbach
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, 8000 Aarhus/Aalborg, Denmark
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, OX39BX Oxford, United Kingdom
- Department of Psychiatry, University of Oxford, OX37JX Oxford, United Kingdom
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Mohd Rashid MH, Ab Rani NS, Kannan M, Abdullah MW, Ab Ghani MA, Kamel N, Mustapha M. Emotion brain network topology in healthy subjects following passive listening to different auditory stimuli. PeerJ 2024; 12:e17721. [PMID: 39040935 PMCID: PMC11262303 DOI: 10.7717/peerj.17721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Accepted: 06/19/2024] [Indexed: 07/24/2024] Open
Abstract
A large body of research establishes the efficacy of musical intervention in many aspects of physical, cognitive, communication, social, and emotional rehabilitation. However, the underlying neural mechanisms for musical therapy remain elusive. This study aimed to investigate the potential neural correlates of musical therapy, focusing on the changes in the topology of emotion brain network. To this end, a Bayesian statistical approach and a cross-over experimental design were employed together with two resting-state magnetoencephalography (MEG) as controls. MEG recordings of 30 healthy subjects were acquired while listening to five auditory stimuli in random order. Two resting-state MEG recordings of each subject were obtained, one prior to the first stimulus (pre) and one after the final stimulus (post). Time series at the level of brain regions were estimated using depth-weighted minimum norm estimation (wMNE) source reconstruction method and the functional connectivity between these regions were computed. The resultant connectivity matrices were used to derive two topological network measures: transitivity and global efficiency which are important in gauging the functional segregation and integration of brain network respectively. The differences in these measures between pre- and post-stimuli resting MEG were set as the equivalence regions. We found that the network measures under all auditory stimuli were equivalent to the resting state network measures in all frequency bands, indicating that the topology of the functional brain network associated with emotional regulation in healthy subjects remains unchanged following these auditory stimuli. This suggests that changes in the emotion network topology may not be the underlying neural mechanism of musical therapy. Nonetheless, further studies are required to explore the neural mechanisms of musical interventions especially in the populations with neuropsychiatric disorders.
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Affiliation(s)
- Muhammad Hakimi Mohd Rashid
- Department of Basic Medical Sciences, Kulliyyah of Pharmacy, International Islamic University, Kuantan, Pahang, Malaysia
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu, Kelantan, Malaysia
| | - Nur Syairah Ab Rani
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu, Kelantan, Malaysia
| | - Mohammed Kannan
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu, Kelantan, Malaysia
- Department of Anatomy, Faculty of Medicine, Al Neelain University, Khartoum, Khartoum, Sudan
| | - Mohd Waqiyuddin Abdullah
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu, Kelantan, Malaysia
| | - Muhammad Amiri Ab Ghani
- Jabatan Al-Quran & Hadis, Kolej Islam Antarabangsa Sultan Ismail Petra, Nilam Puri, Kota Bharu, Kelantan, Malaysia
| | - Nidal Kamel
- Centre for Intelligent Signal & Imaging Research (CISIR), Electrical & Electronic Engineering Department, Universiti Teknologi PETRONAS, Seri Iskandar, Perak, Malaysia
| | - Muzaimi Mustapha
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu, Kelantan, Malaysia
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Jafarian A, Assem MK, Kocagoncu E, Lanskey JH, Williams R, Cheng Y, Quinn AJ, Pitt J, Raymont V, Lowe S, Singh KD, Woolrich M, Nobre AC, Henson RN, Friston KJ, Rowe JB. Reliability of dynamic causal modelling of resting-state magnetoencephalography. Hum Brain Mapp 2024; 45:e26782. [PMID: 38989630 PMCID: PMC11237883 DOI: 10.1002/hbm.26782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 06/20/2024] [Accepted: 06/30/2024] [Indexed: 07/12/2024] Open
Abstract
This study assesses the reliability of resting-state dynamic causal modelling (DCM) of magnetoencephalography (MEG) under conductance-based canonical microcircuit models, in terms of both posterior parameter estimates and model evidence. We use resting-state MEG data from two sessions, acquired 2 weeks apart, from a cohort with high between-subject variance arising from Alzheimer's disease. Our focus is not on the effect of disease, but on the reliability of the methods (as within-subject between-session agreement), which is crucial for future studies of disease progression and drug intervention. To assess the reliability of first-level DCMs, we compare model evidence associated with the covariance among subject-specific free energies (i.e., the 'quality' of the models) with versus without interclass correlations. We then used parametric empirical Bayes (PEB) to investigate the differences between the inferred DCM parameter probability distributions at the between subject level. Specifically, we examined the evidence for or against parameter differences (i) within-subject, within-session, and between-epochs; (ii) within-subject between-session; and (iii) within-site between-subjects, accommodating the conditional dependency among parameter estimates. We show that for data acquired close in time, and under similar circumstances, more than 95% of inferred DCM parameters are unlikely to differ, speaking to mutual predictability over sessions. Using PEB, we show a reciprocal relationship between a conventional definition of 'reliability' and the conditional dependency among inferred model parameters. Our analyses confirm the reliability and reproducibility of the conductance-based DCMs for resting-state neurophysiological data. In this respect, the implicit generative modelling is suitable for interventional and longitudinal studies of neurological and psychiatric disorders.
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Affiliation(s)
- Amirhossein Jafarian
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Foundation TrustCambridge Biomedical CampusCambridgeUK
| | - Melek Karadag Assem
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Foundation TrustCambridge Biomedical CampusCambridgeUK
| | - Ece Kocagoncu
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Foundation TrustCambridge Biomedical CampusCambridgeUK
| | - Juliette H. Lanskey
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Foundation TrustCambridge Biomedical CampusCambridgeUK
| | - Rebecca Williams
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Foundation TrustCambridge Biomedical CampusCambridgeUK
| | | | - Andrew J. Quinn
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of PsychiatryUniversity of OxfordOxfordUK
- Department of PsychologyUniversity of BirminghamBirminghamUK
| | - Jemma Pitt
- Department of PsychiatryUniversity of OxfordOxfordUK
| | | | - Stephen Lowe
- Lilly Centre for Clinical PharmacologySingaporeSingapore
| | - Krish D. Singh
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffUK
| | - Mark Woolrich
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of PsychiatryUniversity of OxfordOxfordUK
| | - Anna C. Nobre
- Department of PsychiatryUniversity of OxfordOxfordUK
- Department of Psychology and Center for Neurocognition and Behavior, Wu Tsai InstituteYale UniversityNew HavenConnecticutUSA
| | - Richard N. Henson
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
| | - Karl J. Friston
- Wellcome Centre for Human NeuroimagingUniversity College LondonLondonUK
| | - James B. Rowe
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Foundation TrustCambridge Biomedical CampusCambridgeUK
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Herff SA, Bonetti L, Cecchetti G, Vuust P, Kringelbach ML, Rohrmeier MA. Hierarchical syntax model of music predicts theta power during music listening. Neuropsychologia 2024; 199:108905. [PMID: 38740179 DOI: 10.1016/j.neuropsychologia.2024.108905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 03/07/2024] [Accepted: 05/06/2024] [Indexed: 05/16/2024]
Abstract
Linguistic research showed that the depth of syntactic embedding is reflected in brain theta power. Here, we test whether this also extends to non-linguistic stimuli, specifically music. We used a hierarchical model of musical syntax to continuously quantify two types of expert-annotated harmonic dependencies throughout a piece of Western classical music: prolongation and preparation. Prolongations can roughly be understood as a musical analogue to linguistic coordination between constituents that share the same function (e.g., 'pizza' and 'pasta' in 'I ate pizza and pasta'). Preparation refers to the dependency between two harmonies whereby the first implies a resolution towards the second (e.g., dominant towards tonic; similar to how the adjective implies the presence of a noun in 'I like spicy … '). Source reconstructed MEG data of sixty-five participants listening to the musical piece was then analysed. We used Bayesian Mixed Effects models to predict theta envelope in the brain, using the number of open prolongation and preparation dependencies as predictors whilst controlling for audio envelope. We observed that prolongation and preparation both carry independent and distinguishable predictive value for theta band fluctuation in key linguistic areas such as the Angular, Superior Temporal, and Heschl's Gyri, or their right-lateralised homologues, with preparation showing additional predictive value for areas associated with the reward system and prediction. Musical expertise further mediated these effects in language-related brain areas. Results show that predictions of precisely formalised music-theoretical models are reflected in the brain activity of listeners which furthers our understanding of the perception and cognition of musical structure.
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Affiliation(s)
- Steffen A Herff
- Sydney Conservatorium of Music, University of Sydney, Sydney, Australia; The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Sydney, Australia; Digital and Cognitive Musicology Lab, College of Humanities, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
| | - Leonardo Bonetti
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus/Aalborg, Denmark; Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom; Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Gabriele Cecchetti
- The MARCS Institute for Brain, Behaviour and Development, Western Sydney University, Sydney, Australia; Digital and Cognitive Musicology Lab, College of Humanities, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Peter Vuust
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus/Aalborg, Denmark
| | - Morten L Kringelbach
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music, Aarhus/Aalborg, Denmark; Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom; Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Martin A Rohrmeier
- Digital and Cognitive Musicology Lab, College of Humanities, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
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Pruitt T, Davenport EM, Proskovec AL, Maldjian JA, Liu H. Simultaneous MEG and EEG source imaging of electrophysiological activity in response to acute transcranial photobiomodulation. Front Neurosci 2024; 18:1368172. [PMID: 38817913 PMCID: PMC11137218 DOI: 10.3389/fnins.2024.1368172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 04/22/2024] [Indexed: 06/01/2024] Open
Abstract
Introduction Transcranial photobiomodulation (tPBM) is a non-invasive neuromodulation technique that improves human cognition. The effects of tPBM of the right forehead on neurophysiological activity have been previously investigated using EEG in sensor space. However, the spatial resolution of these studies is limited. Magnetoencephalography (MEG) is known to facilitate a higher spatial resolution of brain source images. This study aimed to image post-tPBM effects in brain space based on both MEG and EEG measurements across the entire human brain. Methods MEG and EEG scans were concurrently acquired for 6 min before and after 8-min of tPBM delivered using a 1,064-nm laser on the right forehead of 25 healthy participants. Group-level changes in both the MEG and EEG power spectral density with respect to the baseline (pre-tPBM) were quantified and averaged within each frequency band in the sensor space. Constrained modeling was used to generate MEG and EEG source images of post-tPBM, followed by cluster-based permutation analysis for family wise error correction (p < 0.05). Results The 8-min tPBM enabled significant increases in alpha (8-12 Hz) and beta (13-30 Hz) powers across multiple cortical regions, as confirmed by MEG and EEG source images. Moreover, tPBM-enhanced oscillations in the beta band were located not only near the stimulation site but also in remote cerebral regions, including the frontal, parietal, and occipital regions, particularly on the ipsilateral side. Discussion MEG and EEG results shown in this study demonstrated that tPBM modulates neurophysiological activity locally and in distant cortical areas. The EEG topographies reported in this study were consistent with previous observations. This study is the first to present MEG and EEG evidence of the electrophysiological effects of tPBM in the brain space, supporting the potential utility of tPBM in treating neurological diseases through the modulation of brain oscillations.
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Affiliation(s)
- Tyrell Pruitt
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, United States
| | | | - Amy L. Proskovec
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, United States
| | - Joseph A. Maldjian
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, United States
| | - Hanli Liu
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, United States
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López-Caballero F, Curtis M, Coffman BA, Salisbury DF. Is source-resolved magnetoencephalographic mismatch negativity a viable biomarker for early psychosis? Eur J Neurosci 2024; 59:1889-1906. [PMID: 37537883 PMCID: PMC10837325 DOI: 10.1111/ejn.16107] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 07/04/2023] [Accepted: 07/20/2023] [Indexed: 08/05/2023]
Abstract
Mismatch negativity (MMN) is an auditory event-related response reflecting the pre-attentive detection of novel stimuli and is a biomarker of cortical dysfunction in schizophrenia (SZ). MMN to pitch (pMMN) and to duration (dMMN) deviant stimuli are impaired in chronic SZ, but it is less clear if MMN is reduced in first-episode SZ, with inconsistent findings in scalp-level EEG studies. Here, we investigated the neural generators of pMMN and dMMN with MEG recordings in 26 first-episode schizophrenia spectrum (FEsz) and 26 matched healthy controls (C). We projected MEG inverse solutions into precise functionally meaningful auditory cortex areas. MEG-derived MMN sources were in bilateral primary auditory cortex (A1) and belt areas. In A1, pMMN FEsz reduction showed a trend towards statistical significance (F(1,50) = 3.31; p = .07), and dMMN was reduced in FEsz (F(1,50) = 4.11; p = .04). Hypothesis-driven comparisons at each hemisphere revealed dMMN reduction in FEsz occurred in the left (t(56) = 2.23; p = .03; d = .61) but not right (t(56) = 1.02; p = .31; d = .28) hemisphere, with a moderate effect size. The added precision of MEG source solution with high-resolution MRI and parcellation of A1 may be requisite to detect the emerging pathophysiology and indicates a critical role for left hemisphere pathology at psychosis onset. However, the moderate effect size in left A1, albeit larger than reported in scalp MMN meta-analyses, casts doubt on the clinical utility of MMN for differential diagnosis, as a majority of patients will overlap with the healthy individual's distribution.
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Affiliation(s)
- Fran López-Caballero
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Mark Curtis
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Brian A Coffman
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Dean F Salisbury
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
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Hao G, Yan H, Wang X, Gao R, Xue Y, Zhang X, Ni D, Shu W, Qiao L, He L, Yu T. The role of magnetoencephalography in preoperative localization and postoperative outcome prediction in patients with posterior cortical epilepsy. CNS Neurosci Ther 2024; 30:e14602. [PMID: 38332652 PMCID: PMC10853654 DOI: 10.1111/cns.14602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 12/16/2023] [Accepted: 01/01/2024] [Indexed: 02/10/2024] Open
Abstract
OBJECTIVE We aimed to explore the value of magnetoencephalography in the presurgical evaluation of patients with posterior cortex epilepsy. METHODS A total of 39 patients with posterior cortex epilepsy (PCE) and intact magnetoencephalography (MEG) images were reviewed from August 2019 to July 2022. MEG dipole clusters were classified into single clusters, multiple clusters, and scatter dipoles based on tightness criteria. The association of the surgical outcome with MEG dipole classifications was evaluated using Fisher's exact tests. RESULTS Among the 39 cases, there were 24 cases of single clusters (61.5%), nine cases of multiple clusters (23.1%), and six cases of scattered dipoles (15.4%). Patients with single dipole clusters were more likely to become seizure-free. Among single dipole cluster cases (n = 24), complete MEG dipole resection yielded a more favorable surgical outcome than incomplete resection (83.3% vs. 16.7%, p = 0.007). Patients with concordant MRI and MEG findings achieved a significantly more favorable surgical outcome than discordant patients (66.7% vs. 33.3%, p = 0.044), especially in single dipole cluster patients (87.5% vs. 25.0%, p = 0.005). SIGNIFICANCE MEG can provide additional valuable information regarding surgical candidate selection, epileptogenic zone localization, electrode implantation schedule, and final surgical planning in patients with posterior cortex epilepsy.
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Affiliation(s)
- Guiliang Hao
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Hao Yan
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Xueyuan Wang
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Runshi Gao
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Yansong Xue
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Xiating Zhang
- Department of Neurology, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Duanyu Ni
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Wei Shu
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Liang Qiao
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Liu He
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
| | - Tao Yu
- Department of Functional Neurosurgery, Beijing Institute of Functional Neurosurgery, Xuanwu HospitalCapital Medical UniversityBeijingChina
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9
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Eisenhauer S, Gonzalez Alam TRDJ, Cornelissen PL, Smallwood J, Jefferies E. Individual word representations dissociate from linguistic context along a cortical unimodal to heteromodal gradient. Hum Brain Mapp 2024; 45:e26607. [PMID: 38339897 PMCID: PMC10836172 DOI: 10.1002/hbm.26607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 11/30/2023] [Accepted: 01/15/2024] [Indexed: 02/12/2024] Open
Abstract
Language comprehension involves multiple hierarchical processing stages across time, space, and levels of representation. When processing a word, the sensory input is transformed into increasingly abstract representations that need to be integrated with the linguistic context. Thus, language comprehension involves both input-driven as well as context-dependent processes. While neuroimaging research has traditionally focused on mapping individual brain regions to the distinct underlying processes, recent studies indicate that whole-brain distributed patterns of cortical activation might be highly relevant for cognitive functions, including language. One such pattern, based on resting-state connectivity, is the 'principal cortical gradient', which dissociates sensory from heteromodal brain regions. The present study investigated the extent to which this gradient provides an organizational principle underlying language function, using a multimodal neuroimaging dataset of functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) recordings from 102 participants during sentence reading. We found that the brain response to individual representations of a word (word length, orthographic distance, and word frequency), which reflect visual; orthographic; and lexical properties, gradually increases towards the sensory end of the gradient. Although these properties showed opposite effect directions in fMRI and MEG, their association with the sensory end of the gradient was consistent across both neuroimaging modalities. In contrast, MEG revealed that properties reflecting a word's relation to its linguistic context (semantic similarity and position within the sentence) involve the heteromodal end of the gradient to a stronger extent. This dissociation between individual word and contextual properties was stable across earlier and later time windows during word presentation, indicating interactive processing of word representations and linguistic context at opposing ends of the principal gradient. To conclude, our findings indicate that the principal gradient underlies the organization of a range of linguistic representations while supporting a gradual distinction between context-independent and context-dependent representations. Furthermore, the gradient reveals convergent patterns across neuroimaging modalities (similar location along the gradient) in the presence of divergent responses (opposite effect directions).
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Affiliation(s)
- Susanne Eisenhauer
- Department of PsychologyUniversity of YorkYorkUK
- York Neuroimaging Centre, Innovation WayYorkUK
| | | | | | | | - Elizabeth Jefferies
- Department of PsychologyUniversity of YorkYorkUK
- York Neuroimaging Centre, Innovation WayYorkUK
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10
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McClaskey CM. Neural hyperactivity and altered envelope encoding in the central auditory system: Changes with advanced age and hearing loss. Hear Res 2024; 442:108945. [PMID: 38154191 PMCID: PMC10942735 DOI: 10.1016/j.heares.2023.108945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 12/04/2023] [Accepted: 12/22/2023] [Indexed: 12/30/2023]
Abstract
Temporal modulations are ubiquitous features of sound signals that are important for auditory perception. The perception of temporal modulations, or temporal processing, is known to decline with aging and hearing loss and negatively impact auditory perception in general and speech recognition specifically. However, neurophysiological literature also provides evidence of exaggerated or enhanced encoding of specifically temporal envelopes in aging and hearing loss, which may arise from changes in inhibitory neurotransmission and neuronal hyperactivity. This review paper describes the physiological changes to the neural encoding of temporal envelopes that have been shown to occur with age and hearing loss and discusses the role of disinhibition and neural hyperactivity in contributing to these changes. Studies in both humans and animal models suggest that aging and hearing loss are associated with stronger neural representations of both periodic amplitude modulation envelopes and of naturalistic speech envelopes, but primarily for low-frequency modulations (<80 Hz). Although the frequency dependence of these results is generally taken as evidence of amplified envelope encoding at the cortex and impoverished encoding at the midbrain and brainstem, there is additional evidence to suggest that exaggerated envelope encoding may also occur subcortically, though only for envelopes with low modulation rates. A better understanding of how temporal envelope encoding is altered in aging and hearing loss, and the contexts in which neural responses are exaggerated/diminished, may aid in the development of interventions, assistive devices, and treatment strategies that work to ameliorate age- and hearing-loss-related auditory perceptual deficits.
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Affiliation(s)
- Carolyn M McClaskey
- Department of Otolaryngology - Head and Neck Surgery, Medical University of South Carolina, 135 Rutledge Ave, MSC 550, Charleston, SC 29425, United States.
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11
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Illman M, Jaatela J, Vallinoja J, Nurmi T, Mäenpää H, Piitulainen H. Altered excitation-inhibition balance in the primary sensorimotor cortex to proprioceptive hand stimulation in cerebral palsy. Clin Neurophysiol 2024; 157:25-36. [PMID: 38039924 DOI: 10.1016/j.clinph.2023.10.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 10/13/2023] [Accepted: 10/27/2023] [Indexed: 12/03/2023]
Abstract
OBJECTIVE Our objective was to clarify the primary sensorimotor (SM1) cortex excitatory and inhibitory alterations in hemiplegic (HP) and diplegic (DP) cerebral palsy (CP) by quantifying SM1 cortex beta power suppression and rebound with magnetoencephalography (MEG). METHODS MEG was recorded from 16 HP and 12 DP adolescents, and their 32 healthy controls during proprioceptive stimulation of the index fingers evoked by a movement actuator. The related beta power changes were computed with Temporal Spectral Evolution (TSE). Peak strengths of beta suppression and rebound were determined from representative channels over the SM1 cortex. RESULTS Beta suppression was stronger contralateral to the stimulus and rebound was weaker ipsilateral to the stimulation in DP compared to controls. Beta modulation strengths did not differ significantly between HP and the control group. CONCLUSIONS The emphasized beta suppression in DP suggests less efficient proprioceptive processing in the SM1 contralateral to the stimulation. Their weak rebound further indicates reduced intra- and/or interhemispheric cortical inhibition, which is a potential neuronal mechanism for their bilateral motor impairments. SIGNIFICANCE The excitation-inhibition balance of the SM1 cortex related to proprioception is impaired in diplegic CP. Therefore, the cortical and behavioral proprioceptive deficits should be better diagnosed and considered to better target individualized effective rehabilitation in CP.
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Affiliation(s)
- Mia Illman
- Faculty of Sport and Health Sciences, University of Jyväskylä, P.O.BOX 35, FI-40014 Jyväskylä, Finland; Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, P.O.BOX 12200, FI-00760 AALTO, Espoo, Finland; Aalto NeuroImaging, Aalto University School of Science, P.O.BOX 12200, FI-00760 AALTO, Espoo, Finland.
| | - Julia Jaatela
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, P.O.BOX 12200, FI-00760 AALTO, Espoo, Finland
| | - Jaakko Vallinoja
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, P.O.BOX 12200, FI-00760 AALTO, Espoo, Finland
| | - Timo Nurmi
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, P.O.BOX 12200, FI-00760 AALTO, Espoo, Finland
| | - Helena Mäenpää
- Pediatric Neurology, New Children's Hospital, University of Helsinki and Helsinki University Hospital, FI-00029 Helsinki, Finland
| | - Harri Piitulainen
- Faculty of Sport and Health Sciences, University of Jyväskylä, P.O.BOX 35, FI-40014 Jyväskylä, Finland; Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, P.O.BOX 12200, FI-00760 AALTO, Espoo, Finland; Pediatric Neurology, New Children's Hospital, University of Helsinki and Helsinki University Hospital, FI-00029 Helsinki, Finland
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12
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Voets NL, Bartsch AJ, Plaha P. Functional MRI applications for intra-axial brain tumours: uses and nuances in surgical practise. Br J Neurosurg 2023; 37:1544-1559. [PMID: 36148501 DOI: 10.1080/02688697.2022.2123893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 09/07/2022] [Indexed: 11/02/2022]
Abstract
PURPOSE Functional MRI (fMRI) has well-established uses to inform risks and plan maximally safe approaches in neurosurgery. In the field of brain tumour surgery, however, fMRI is currently in a state of clinical equipoise due to debate around both its sensitivity and specificity. MATERIALS AND METHODS In this review, we summarise the role and our experience of fMRI in neurosurgery for gliomas and metastases. We discuss nuances in the conduct and interpretation of fMRI that, based on our practise, most directly impact fMRI's usefulness in the neurosurgical setting. RESULTS Illustrated examples in which fMRI in our hands directly influences the neurosurgical treatment of brain tumours include evaluating the probability and nature of functional risks, especially for language functions. These presurgical risk assessments, in turn, help to predict the resectability of tumours, select or deselect patients for awake surgery, indicate the need for neurophysiological monitoring and guide the optimal use of intra-operative stimulation mapping. A further emerging application of fMRI is in measuring functional adaptation of functional networks after (partial) surgery, of potential use in the timing of further surgery. CONCLUSIONS In appropriately selected patients with a clearly defined surgical question, fMRI offers a valuable complementary tool in the pre-surgical evaluation of brain tumours. However, there is a great need for standards in the administration and analysis of fMRI as much as in the techniques that it is commonly evaluated against. Surprisingly little data exists that evaluates the accuracy of fMRI not just against complementary methods, but in terms of its ultimate clinical aim of minimising post-surgical morbidity.
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Affiliation(s)
- Natalie L Voets
- Department of Neurosurgery, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- GenesisCare Ltd, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Andreas J Bartsch
- Department of Neuroradiology, University of Heidelberg, Heidelberg, Germany
| | - Puneet Plaha
- Department of Neurosurgery, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Nuffield Department of Neurosurgery, University of Oxford, Oxford, UK
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13
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Valt C, Quarto T, Tavella A, Romanelli F, Fazio L, Arcara G, Altamura M, Barrasso G, Bellomo A, Blasi G, Brudaglio F, Carofiglio A, D'Ambrosio E, Padalino FA, Rampino A, Saponaro A, Semisa D, Suma D, Pergola G, Bertolino A. Reduced magnetic mismatch negativity: a shared deficit in psychosis and related risk. Psychol Med 2023; 53:6037-6045. [PMID: 36321391 DOI: 10.1017/s003329172200321x] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
BACKGROUND Abnormal auditory processing of deviant stimuli, as reflected by mismatch negativity (MMN), is often reported in schizophrenia (SCZ). At present, it is still under debate whether this dysfunctional response is specific to the full-blown SCZ diagnosis or rather a marker of psychosis in general. The present study tested MMN in patients with SCZ, bipolar disorder (BD), first episode of psychosis (FEP), and in people at clinical high risk for psychosis (CHR). METHODS Source-based MEG activity evoked during a passive auditory oddball task was recorded from 135 patients grouped according to diagnosis (SCZ, BD, FEP, and CHR) and 135 healthy controls also divided into four subgroups, age- and gender-matched with diagnostic subgroups. The magnetic MMN (mMMN) was analyzed as event-related field (ERF), Theta power, and Theta inter-trial phase coherence (ITPC). RESULTS The clinical group as a whole showed reduced mMMN ERF amplitude, Theta power, and Theta ITPC, without any statistically significant interaction between diagnosis and mMMN reductions. The mMMN subgroup contrasts showed lower ERF amplitude in all the diagnostic subgroups. In the analysis of Theta frequency, SCZ showed significant power and ITPC reductions, while only indications of diminished ITPC were observed in CHR, but no significant decreases characterized BD and FEP. CONCLUSIONS Significant mMMN alterations in people experiencing psychosis, also for diagnoses other than SCZ, suggest that this neurophysiological response may be a feature shared across psychotic disorders. Additionally, reduced Theta ITPC may be associated with risk for psychosis.
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Affiliation(s)
- Christian Valt
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Tiziana Quarto
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
- Department of Humanities, University of Foggia, Foggia, Italy
| | | | | | - Leonardo Fazio
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
- Department of Medicine and Surgery, LUM University, Casamassima, Italy
| | | | - Mario Altamura
- Department of Clinical and Experimental Medicine, University of Foggia, Foggia, Italy
| | - Giuseppe Barrasso
- Department of Mental Health, ASL Barletta-Andria-Trani, Andria, Italy
| | - Antonello Bellomo
- Department of Clinical and Experimental Medicine, University of Foggia, Foggia, Italy
| | - Giuseppe Blasi
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
- Bari University Hospital, Bari, Italy
| | - Flora Brudaglio
- Department of Mental Health, ASL Barletta-Andria-Trani, Andria, Italy
| | | | - Enrico D'Ambrosio
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
- Bari University Hospital, Bari, Italy
- Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience - King's College London, London, UK
| | | | - Antonio Rampino
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
- Bari University Hospital, Bari, Italy
| | | | | | - Domenico Suma
- Department of Mental Health, ASL Brindisi, Brindisi, Italy
| | - Giulio Pergola
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Alessandro Bertolino
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
- Bari University Hospital, Bari, Italy
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14
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Pan R, Yang C, Li Z, Ren J, Duan Y. Magnetoencephalography-based approaches to epilepsy classification. Front Neurosci 2023; 17:1183391. [PMID: 37502686 PMCID: PMC10368885 DOI: 10.3389/fnins.2023.1183391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 06/12/2023] [Indexed: 07/29/2023] Open
Abstract
Epilepsy is a chronic central nervous system disorder characterized by recurrent seizures. Not only does epilepsy severely affect the daily life of the patient, but the risk of premature death in patients with epilepsy is three times higher than that of the normal population. Magnetoencephalography (MEG) is a non-invasive, high temporal and spatial resolution electrophysiological data that provides a valid basis for epilepsy diagnosis, and used in clinical practice to locate epileptic foci in patients with epilepsy. It has been shown that MEG helps to identify MRI-negative epilepsy, contributes to clinical decision-making in recurrent seizures after previous epilepsy surgery, that interictal MEG can provide additional localization information than scalp EEG, and complete excision of the stimulation area defined by the MEG has prognostic significance for postoperative seizure control. However, due to the complexity of the MEG signal, it is often difficult to identify subtle but critical changes in MEG through visual inspection, opening up an important area of research for biomedical engineers to investigate and implement intelligent algorithms for epilepsy recognition. At the same time, the use of manual markers requires significant time and labor costs, necessitating the development and use of computer-aided diagnosis (CAD) systems that use classifiers to automatically identify abnormal activity. In this review, we discuss in detail the results of applying various different feature extraction methods on MEG signals with different classifiers for epilepsy detection, subtype determination, and laterality classification. Finally, we also briefly look at the prospects of using MEG for epilepsy-assisted localization (spike detection, high-frequency oscillation detection) due to the unique advantages of MEG for functional area localization in epilepsy, and discuss the limitation of current research status and suggestions for future research. Overall, it is hoped that our review will facilitate the reader to quickly gain a general understanding of the problem of MEG-based epilepsy classification and provide ideas and directions for subsequent research.
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Affiliation(s)
- Ruoyao Pan
- Faculty of Environment and Life, Beijing University of Technology, Beijing, China
| | - Chunlan Yang
- Faculty of Environment and Life, Beijing University of Technology, Beijing, China
| | - Zhimei Li
- Department of Internal Neurology, Tiantan Hospital, Beijing, China
| | - Jiechuan Ren
- Department of Internal Neurology, Tiantan Hospital, Beijing, China
| | - Ying Duan
- Beijing Universal Medical Imaging Diagnostic Center, Beijing, China
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15
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Boon LI, Hillebrand A, Schoonheim MM, Twisk JW, Stam CJ, Berendse HW. Cortical and Subcortical Changes in MEG Activity Reflect Parkinson's Progression over a Period of 7 Years. Brain Topogr 2023:10.1007/s10548-023-00965-w. [PMID: 37154884 DOI: 10.1007/s10548-023-00965-w] [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: 10/25/2022] [Accepted: 04/15/2023] [Indexed: 05/10/2023]
Abstract
In this study of early functional changes in Parkinson's disease (PD), we aimed to provide a comprehensive assessment of the development of changes in both cortical and subcortical neurophysiological brain activity, including their association with clinical measures of disease severity. Repeated resting-state MEG recordings and clinical assessments were obtained in the context of a unique longitudinal cohort study over a seven-year period using a multiple longitudinal design. We used linear mixed-models to analyze the relationship between neurophysiological (spectral power and functional connectivity) and clinical data. At baseline, early-stage (drug-naïve) PD patients demonstrated spectral slowing compared to healthy controls in both subcortical and cortical brain regions, most outspoken in the latter. Over time, spectral slowing progressed in strong association with clinical measures of disease progression (cognitive and motor). Global functional connectivity was not different between groups at baseline and hardly changed over time. Therefore, investigation of associations with clinical measures of disease progression were not deemed useful. An analysis of individual connections demonstrated differences between groups at baseline (higher frontal theta, lower parieto-occipital alpha2 band functional connectivity) and over time in PD patients (increase in frontal delta and theta band functional connectivity). Our results suggest that spectral measures are promising candidates in the search for non-invasive markers of both early-stage PD and of the ongoing disease process.
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Affiliation(s)
- Lennard I Boon
- Department of Neurology, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands.
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands.
| | - Arjan Hillebrand
- Department of Neurology, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Jos W Twisk
- Department of Epidemiology and Biostatistics, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Cornelis J Stam
- Department of Neurology, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Henk W Berendse
- Department of Neurology, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
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16
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Spooner RK, Wilson TW. Spectral specificity of gamma-frequency transcranial alternating current stimulation over motor cortex during sequential movements. Cereb Cortex 2023; 33:5347-5360. [PMID: 36368895 PMCID: PMC10152093 DOI: 10.1093/cercor/bhac423] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 09/26/2022] [Accepted: 09/27/2022] [Indexed: 11/13/2022] Open
Abstract
Motor control requires the coordination of spatiotemporally precise neural oscillations in the beta and gamma range within the primary motor cortex (M1). Recent studies have shown that motor performance can be differentially modulated based on the spectral target of noninvasive transcranial alternating current stimulation (tACS), with gamma-frequency tACS improving motor performance. However, the spectral specificity for eliciting such improvements remains unknown. Herein, we derived the peak movement-related gamma frequency in 25 healthy adults using magnetoencephalography and a motor control paradigm. These individualized peak gamma frequencies were then used for personalized sessions of tACS. All participants completed 4 sessions of high-definition (HD)-tACS (sham, low-, peak-, and high-gamma frequency) over M1 for 20 min during the performance of sequential movements of varying complexity (e.g. tapping adjacent fingers or nonadjacent fingers). Our primary findings demonstrated that individualized tACS dosing over M1 leads to enhanced motor performance/learning (i.e. greatest reduction in time to complete motor sequences) compared to nonspecific gamma-tACS in humans, which suggests that personalized neuromodulation may be advantageous to optimize behavioral outcomes.
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Affiliation(s)
- Rachel K Spooner
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
- College of Medicine, University of Nebraska Medical Center (UMNC), Omaha, NE, United States
- Institute of Clinical Neuroscience and Medical Psychology, Heinrich-Heine University, Düsseldorf, Germany
| | - Tony W Wilson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, United States
- College of Medicine, University of Nebraska Medical Center (UMNC), Omaha, NE, United States
- Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, United States
- Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, United States
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17
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Hillebrand A, Holmes N, Sijsma N, O'Neill GC, Tierney TM, Liberton N, Stam AH, van Klink N, Stam CJ, Bowtell R, Brookes MJ, Barnes GR. Non-invasive measurements of ictal and interictal epileptiform activity using optically pumped magnetometers. Sci Rep 2023; 13:4623. [PMID: 36944674 PMCID: PMC10030968 DOI: 10.1038/s41598-023-31111-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 03/06/2023] [Indexed: 03/23/2023] Open
Abstract
Magneto- and electroencephalography (MEG/EEG) are important techniques for the diagnosis and pre-surgical evaluation of epilepsy. Yet, in current cryogen-based MEG systems the sensors are offset from the scalp, which limits the signal-to-noise ratio (SNR) and thereby the sensitivity to activity from deep structures such as the hippocampus. This effect is amplified in children, for whom adult-sized fixed-helmet systems are typically too big. Moreover, ictal recordings with fixed-helmet systems are problematic because of limited movement tolerance and/or logistical considerations. Optically Pumped Magnetometers (OPMs) can be placed directly on the scalp, thereby improving SNR and enabling recordings during seizures. We aimed to demonstrate the performance of OPMs in a clinical population. Seven patients with challenging cases of epilepsy underwent MEG recordings using a 12-channel OPM-system and a 306-channel cryogen-based whole-head system: three adults with known deep or weak (low SNR) sources of interictal epileptiform discharges (IEDs), along with three children with focal epilepsy and one adult with frequent seizures. The consistency of the recorded IEDs across the two systems was assessed. In one patient the OPMs detected IEDs that were not found with the SQUID-system, and in two patients no IEDs were found with either system. For the other patients the OPM data were remarkably consistent with the data from the cryogenic system, noting that these were recorded in different sessions, with comparable SNRs and IED-yields overall. Importantly, the wearability of OPMs enabled the recording of seizure activity in a patient with hyperkinetic movements during the seizure. The observed ictal onset and semiology were in agreement with previous video- and stereo-EEG recordings. The relatively affordable technology, in combination with reduced running and maintenance costs, means that OPM-based MEG could be used more widely than current MEG systems, and may become an affordable alternative to scalp EEG, with the potential benefits of increased spatial accuracy, reduced sensitivity to volume conduction/field spread, and increased sensitivity to deep sources. Wearable MEG thus provides an unprecedented opportunity for epilepsy, and given its patient-friendliness, we envisage that it will not only be used for presurgical evaluation of epilepsy patients, but also for diagnosis after a first seizure.
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Affiliation(s)
- Arjan Hillebrand
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081HV, Amsterdam, The Netherlands.
- Brain Imaging, Amsterdam Neuroscience, Amsterdam, The Netherlands.
- Systems and Network Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands.
| | - Niall Holmes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Ndedi Sijsma
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081HV, Amsterdam, The Netherlands
| | - George C O'Neill
- Wellcome Centre for Human Neuroimaging, Department of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - Tim M Tierney
- Wellcome Centre for Human Neuroimaging, Department of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
| | - Niels Liberton
- Department of Medical Technology, 3D Innovation Lab, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Anine H Stam
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081HV, Amsterdam, The Netherlands
| | - Nicole van Klink
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081HV, Amsterdam, The Netherlands
- Brain Imaging, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Neurodegeneration, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - 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
| | - Gareth R Barnes
- Wellcome Centre for Human Neuroimaging, Department of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
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18
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Meehan CE, Embury CM, Wiesman AI, Schantell M, Wolfson SL, O’Neill J, Swindells S, Johnson CM, May PE, Murman DL, Wilson TW. Convergent and divergent oscillatory aberrations during visuospatial processing in HIV-related cognitive impairment and Alzheimer's disease. Cereb Cortex 2023; 33:3181-3192. [PMID: 35855581 PMCID: PMC10016044 DOI: 10.1093/cercor/bhac268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 05/24/2022] [Accepted: 06/12/2022] [Indexed: 12/13/2022] Open
Abstract
Adults with HIV frequently develop a form of mild cognitive impairment known as HIV-associated neurocognitive disorder (HAND), but presumably cognitive decline in older persons with HIV could also be attributable to Alzheimer's disease (AD). However, distinguishing these two conditions in individual patients is exceedingly difficult, as the distinct neural and neuropsychological features are poorly understood and most studies to date have only investigated HAND or AD spectrum (ADS) disorders in isolation. The current study examined the neural dynamics underlying visuospatial processing using magnetoencephalography (MEG) in 31 biomarker-confirmed patients on the ADS, 26 older participants who met criteria for HAND, and 31 older cognitively normal controls. MEG data were examined in the time-frequency domain, and a data-driven approach was utilized to identify the neural dynamics underlying visuospatial processing. Both clinical groups (ADS/HAND) were significantly less accurate than controls on the task and exhibited stronger prefrontal theta oscillations compared to controls. Regarding disease-specific alterations, those with HAND exhibited stronger alpha oscillations than those on the ADS in frontoparietal and temporal cortices. These results indicate both common and unique neurophysiological alterations among those with ADS disorders and HAND in regions serving visuospatial processing and suggest the underlying neuropathological features are at least partially distinct.
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Affiliation(s)
- Chloe E Meehan
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE 68010, USA
- Department of Psychology, University of Nebraska – Omaha, Omaha, NE 68182, USA
| | - Christine M Embury
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE 68010, USA
| | - Alex I Wiesman
- Montreal Neurological Institute, McGill University, Montreal, QC H3A 2B4, Canada
| | - Mikki Schantell
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE 68010, USA
- College of Medicine, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Sara L Wolfson
- Geriatrics Medicine Clinic, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Jennifer O’Neill
- Department of Internal Medicine, Division of Infectious Diseases, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Susan Swindells
- Department of Internal Medicine, Division of Infectious Diseases, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Craig M Johnson
- Department of Radiology, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Pamela E May
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Daniel L Murman
- Department of Neurological Sciences, University of Nebraska Medical Center, Omaha, NE 68198, USA
- Memory Disorders & Behavioral Neurology Program, University of Nebraska Medical Center, Omaha, NE 68198, USA
| | - Tony W Wilson
- Corresponding author: Institute for Human Neuroscience, Boys Town National Research Hospital, 14090 Mother Teresa Ln., Boys Town, NE 68010, USA.
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19
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Li Y, Chen J, Sun J, Jiang P, Xiang J, Chen Q, Hu Z, Wang X. Changes in functional connectivity in newly diagnosed self-limited epilepsy with centrotemporal spikes and cognitive impairment: An MEG study. Brain Behav 2022; 12:e2830. [PMID: 36408856 PMCID: PMC9759146 DOI: 10.1002/brb3.2830] [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: 02/19/2022] [Revised: 09/23/2022] [Accepted: 11/03/2022] [Indexed: 11/22/2022] Open
Abstract
PURPOSE Our purpose was to explore the relationship between cognitive impairment and neural network changes in patients newly diagnosed with self-limited epilepsy with centrotemporal spikes (SeLECTS). METHODS The Wechsler Intelligence Scale for Children, fourth edition was used to divide all SeLECTS patients into two groups: patients with full-scale intelligence quotient (FSIQ) below 80 that corresponded to cognitive impairment, and patients with FSIQ above 80 that corresponded to a normal cognitive function. The data on the resting state were recorded using magnetoencephalography. The properties of the networks were analyzed using graph theory (GT) analysis. RESULTS The functional connectivity (FC) of the frontal cortex in patients with FSIQ < 80 was reduced in the 12-30 Hz frequency band, and the FC of the posterior cingulate cortex was reduced in the 80-250 and 250-500 Hz frequency bands. The GT analysis showed that patients in the FSIQ < 80 group had higher strength in the 8-12 and 12-30 Hz frequency bands than those in the healthy control and FSIQ > 80 group. However, the path length was reduced in the 80-250 Hz band, and the clustering coefficient was reduced in the 12-30, 80-250, and 250-500 Hz frequency bands. Moreover, the receiver operator characteristic analysis showed that the clustering coefficient in the 12-30 and 80-250 Hz frequency bands, as well as the path length in the 80-250 Hz frequency band possessed a good discriminative ability in distinguishing the FSIQ > 80 group. CONCLUSIONS SeLECTS patients with cognitive impairment in the early stage of the disease developed disordered networks in cognitive-related brain regions. The clustering coefficient in the 12-30 and 80-250 Hz frequency bands as well as the path length in the 80-250 Hz frequency band might be good indicators to distinguish the cognitive impairment of SeLECTS patients at the early stage.
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Affiliation(s)
- Yihan Li
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jinan Chen
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jintao Sun
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Ping Jiang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Jing Xiang
- MEG Center, Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - Qiqi Chen
- MEG Center, Nanjing Brain Hospital, Nanjing, Jiangsu, China
| | - Zheng Hu
- Department of Neurology, Nanjing Children's Hospital, Nanjing, Jiangsu, China
| | - Xiaoshan Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
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20
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Blohm G, Cheyne DO, Crawford JD. Parietofrontal oscillations show hand-specific interactions with top-down movement plans. J Neurophysiol 2022; 128:1518-1533. [PMID: 36321728 DOI: 10.1152/jn.00240.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
To generate a hand-specific reach plan, the brain must integrate hand-specific signals with the desired movement strategy. Although various neurophysiology/imaging studies have investigated hand-target interactions in simple reach-to-target tasks, the whole brain timing and distribution of this process remain unclear, especially for more complex, instruction-dependent motor strategies. Previously, we showed that a pro/anti pointing instruction influences magnetoencephalographic (MEG) signals in frontal cortex that then propagate recurrently through parietal cortex (Blohm G, Alikhanian H, Gaetz W, Goltz HC, DeSouza JF, Cheyne DO, Crawford JD. NeuroImage 197: 306-319, 2019). Here, we contrasted left versus right hand pointing in the same task to investigate 1) which cortical regions of interest show hand specificity and 2) which of those areas interact with the instructed motor plan. Eight bilateral areas, the parietooccipital junction (POJ), superior parietooccipital cortex (SPOC), supramarginal gyrus (SMG), medial/anterior interparietal sulcus (mIPS/aIPS), primary somatosensory/motor cortex (S1/M1), and dorsal premotor cortex (PMd), showed hand-specific changes in beta band power, with four of these (M1, S1, SMG, aIPS) showing robust activation before movement onset. M1, SMG, SPOC, and aIPS showed significant interactions between contralateral hand specificity and the instructed motor plan but not with bottom-up target signals. Separate hand/motor signals emerged relatively early and lasted through execution, whereas hand-motor interactions only occurred close to movement onset. Taken together with our previous results, these findings show that instruction-dependent motor plans emerge in frontal cortex and interact recurrently with hand-specific parietofrontal signals before movement onset to produce hand-specific motor behaviors.NEW & NOTEWORTHY The brain must generate different motor signals depending on which hand is used. The distribution and timing of hand use/instructed motor plan integration are not understood at the whole brain level. Using MEG we show that different action planning subnetworks code for hand usage and integrating hand use into a hand-specific motor plan. The timing indicates that frontal cortex first creates a general motor plan and then integrates hand specificity to produce a hand-specific motor plan.
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Affiliation(s)
- Gunnar Blohm
- Centre of Neuroscience Studies, Departments of Biomedical & Molecular Sciences, Mathematics & Statistics, and Psychology and School of Computing, Queen's University, Kingston, Ontario, Canada.,Centre for Vision Research, York University, Toronto, Ontario, Canada.,Canadian Action and Perception Network (CAPnet), Montreal, Quebec, Canada.,Vision: Science to Applications (VISTA) program, Departments of Psychology, Biology, and Kinesiology and Health Sciences and Neuroscience Graduate Diploma Program, York University, Toronto, Ontario, Canada
| | - Douglas O Cheyne
- Program in Neurosciences and Mental Health, The Hospital for Sick Children Research Institute, Toronto, Ontario, Canada
| | - J Douglas Crawford
- Centre for Vision Research, York University, Toronto, Ontario, Canada.,Canadian Action and Perception Network (CAPnet), Montreal, Quebec, Canada.,Vision: Science to Applications (VISTA) program, Departments of Psychology, Biology, and Kinesiology and Health Sciences and Neuroscience Graduate Diploma Program, York University, Toronto, Ontario, Canada
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21
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Pedersen M, Abbott DF, Jackson GD. Wearable OPM-MEG: A changing landscape for epilepsy. Epilepsia 2022; 63:2745-2753. [PMID: 35841260 PMCID: PMC9805039 DOI: 10.1111/epi.17368] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Revised: 07/13/2022] [Accepted: 07/14/2022] [Indexed: 01/09/2023]
Abstract
Magnetoencephalography with optically pumped magnometers (OPM-MEG) is an emerging and novel, cost-effective wearable system that can simultaneously record neuronal activity with high temporal resolution ("when" neuronal activity occurs) and spatial resolution ("where" neuronal activity occurs). This paper will first outline recent methodological advances in OPM-MEG compared to conventional superconducting quantum interference device (SQUID)-MEG before discussing how OPM-MEG can become a valuable and noninvasive clinical support tool in epilepsy surgery evaluation. Although OPM-MEG and SQUID-MEG share similar data features, OPM-MEG is a wearable design that fits children and adults, and it is also robust to head motion within a magnetically shielded room. This means that OPM-MEG can potentially extend the application of MEG into the neurobiology of severe childhood epilepsies with intellectual disabilities (e.g., epileptic encephalopathies) without sedation. It is worth noting that most OPM-MEG sensors are heated, which may become an issue with large OPM sensor arrays (OPM-MEG currently has fewer sensors than SQUID-MEG). Future implementation of triaxial sensors may alleviate the need for large OPM sensor arrays. OPM-MEG designs allowing both awake and sleep recording are essential for potential long-term epilepsy monitoring.
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Affiliation(s)
- Mangor Pedersen
- Department of Psychology and NeuroscienceAuckland University of TechnologyAucklandNew Zealand
| | - David F. Abbott
- Florey Institute of Neuroscience and Mental HealthMelbourneVictoriaAustralia,Department of Medicine, Austin Health and Florey Department of Neuroscience and Mental HealthUniversity of MelbourneMelbourneVictoriaAustralia
| | - Graeme D. Jackson
- Florey Institute of Neuroscience and Mental HealthMelbourneVictoriaAustralia,Department of Medicine, Austin Health and Florey Department of Neuroscience and Mental HealthUniversity of MelbourneMelbourneVictoriaAustralia
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22
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Dimitriadis SI. Universal Lifespan Trajectories of Source-Space Information Flow Extracted from Resting-State MEG Data. Brain Sci 2022; 12:1404. [PMID: 36291337 PMCID: PMC9599296 DOI: 10.3390/brainsci12101404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 07/15/2022] [Accepted: 07/22/2022] [Indexed: 02/15/2024] Open
Abstract
Source activity was extracted from resting-state magnetoencephalography data of 103 subjects aged 18-60 years. The directionality of information flow was computed from the regional time courses using delay symbolic transfer entropy and phase entropy. The analysis yielded a dynamic source connectivity profile, disentangling the direction, strength, and time delay of the underlying causal interactions, producing independent time delays for cross-frequency amplitude-to-amplitude and phase-to-phase coupling. The computation of the dominant intrinsic coupling mode (DoCM) allowed me to estimate the probability distribution of the DoCM independently of phase and amplitude. The results support earlier observations of a posterior-to-anterior information flow for phase dynamics in {α1, α2, β, γ} and an opposite flow (anterior to posterior) in θ. Amplitude dynamics reveal posterior-to-anterior information flow in {α1, α2, γ}, a sensory-motor β-oriented pattern, and an anterior-to-posterior pattern in {δ, θ}. The DoCM between intra- and cross-frequency couplings (CFC) are reported here for the first time and independently for amplitude and phase; in both domains {δ, θ, α1}, frequencies are the main contributors to DoCM. Finally, a novel brain age index (BAI) is introduced, defined as the ratio of the probability distribution of inter- over intra-frequency couplings. This ratio shows a universal age trajectory: a rapid rise from the end of adolescence, reaching a peak in adulthood, and declining slowly thereafter. The universal pattern is seen in the BAI of each frequency studied and for both amplitude and phase domains. No such universal age dependence was previously reported.
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Affiliation(s)
- Stavros I. Dimitriadis
- Neuroscience and Mental Health Research Institute (NMHI), College of Biomedical and Life Sciences, Cardiff University, Maindy Road, Cardiff CF24 4HQ, Wales, UK;
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Maindy Road, Cardiff CF24 HQ, Wales, UK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff School of Medicine, Cardiff University, Maindy Road, Cardiff CF24 4HQ, Wales, UK
- Neuroinformatics Group, School of Psychology, College of Biomedical and Life Sciences, Cardiff University, Maindy Road, Cardiff CF24 4HQ, Wales, UK
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Queens Road, Bristol BS8 1QU, Wales, UK
- Department of Clinical Psychology and Psychobiology, Faculty of Psychology, University of Barcelona, Passeig de la Vall d’Hebron, 171, 08035 Barcelona, Spain
- Institut de Neurociències, University of Barcelona, Campus Mundet, Edifici de Ponent, Passeig de la Vall d’Hebron, 171, 08035 Barcelona, Spain
- Integrative Neuroimaging Lab, 55133 Thessaloniki, Macedonia, Greece
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23
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Numan T, Breedt LC, Maciel BDAPC, Kulik SD, Derks J, Schoonheim MM, Klein M, de Witt Hamer PC, Miller JJ, Gerstner ER, Stufflebeam SM, Hillebrand A, Stam CJ, Geurts JJG, Reijneveld JC, Douw L. Regional healthy brain activity, glioma occurrence and symptomatology. Brain 2022; 145:3654-3665. [PMID: 36130310 PMCID: PMC9586543 DOI: 10.1093/brain/awac180] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 04/22/2022] [Accepted: 05/04/2022] [Indexed: 11/24/2022] Open
Abstract
It is unclear why exactly gliomas show preferential occurrence in certain brain areas. Increased spiking activity around gliomas leads to faster tumour growth in animal models, while higher non-invasively measured brain activity is related to shorter survival in patients. However, it is unknown how regional intrinsic brain activity, as measured in healthy controls, relates to glioma occurrence. We first investigated whether gliomas occur more frequently in regions with intrinsically higher brain activity. Second, we explored whether intrinsic cortical activity at individual patients’ tumour locations relates to tumour and patient characteristics. Across three cross-sectional cohorts, 413 patients were included. Individual tumour masks were created. Intrinsic regional brain activity was assessed through resting-state magnetoencephalography acquired in healthy controls and source-localized to 210 cortical brain regions. Brain activity was operationalized as: (i) broadband power; and (ii) offset of the aperiodic component of the power spectrum, which both reflect neuronal spiking of the underlying neuronal population. We additionally assessed (iii) the slope of the aperiodic component of the power spectrum, which is thought to reflect the neuronal excitation/inhibition ratio. First, correlation coefficients were calculated between group-level regional glioma occurrence, as obtained by concatenating tumour masks across patients, and group-averaged regional intrinsic brain activity. Second, intrinsic brain activity at specific tumour locations was calculated by overlaying patients’ individual tumour masks with regional intrinsic brain activity of the controls and was associated with tumour and patient characteristics. As proposed, glioma preferentially occurred in brain regions characterized by higher intrinsic brain activity in controls as reflected by higher offset. Second, intrinsic brain activity at patients’ individual tumour locations differed according to glioma subtype and performance status: the most malignant isocitrate dehydrogenase-wild-type glioblastoma patients had the lowest excitation/inhibition ratio at their individual tumour locations as compared to isocitrate dehydrogenase-mutant, 1p/19q-codeleted glioma patients, while a lower excitation/inhibition ratio related to poorer Karnofsky Performance Status, particularly in codeleted glioma patients. In conclusion, gliomas more frequently occur in cortical brain regions with intrinsically higher activity levels, suggesting that more active regions are more vulnerable to glioma development. Moreover, indices of healthy, intrinsic excitation/inhibition ratio at patients’ individual tumour locations may capture both tumour biology and patients’ performance status. These findings contribute to our understanding of the complex and bidirectional relationship between normal brain functioning and glioma growth, which is at the core of the relatively new field of ‘cancer neuroscience’.
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Affiliation(s)
- Tianne Numan
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands.,Cancer Center Amsterdam, Imaging and Biomarkers, Brain Tumor Center Amsterdam, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Systems and Network Neuroscience, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Brain Imaging, Amsterdam 1081 HV, The Netherlands
| | - Lucas C Breedt
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands.,Cancer Center Amsterdam, Imaging and Biomarkers, Brain Tumor Center Amsterdam, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Systems and Network Neuroscience, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Brain Imaging, Amsterdam 1081 HV, The Netherlands
| | - Bernardo de A P C Maciel
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands.,Cancer Center Amsterdam, Imaging and Biomarkers, Brain Tumor Center Amsterdam, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Systems and Network Neuroscience, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Brain Imaging, Amsterdam 1081 HV, The Netherlands
| | - Shanna D Kulik
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands.,Cancer Center Amsterdam, Imaging and Biomarkers, Brain Tumor Center Amsterdam, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Systems and Network Neuroscience, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Brain Imaging, Amsterdam 1081 HV, The Netherlands
| | - Jolanda Derks
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands.,Cancer Center Amsterdam, Imaging and Biomarkers, Brain Tumor Center Amsterdam, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Systems and Network Neuroscience, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Brain Imaging, Amsterdam 1081 HV, The Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Systems and Network Neuroscience, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Brain Imaging, Amsterdam 1081 HV, The Netherlands
| | - Martin Klein
- Cancer Center Amsterdam, Imaging and Biomarkers, Brain Tumor Center Amsterdam, Amsterdam 1081 HV, The Netherlands.,Department of Medical Psychology, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands
| | - Philip C de Witt Hamer
- Cancer Center Amsterdam, Imaging and Biomarkers, Brain Tumor Center Amsterdam, Amsterdam 1081 HV, The Netherlands.,Department of Neurosurgery, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands
| | - Julie J Miller
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Elizabeth R Gerstner
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Steven M Stufflebeam
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and MEG Center, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands
| | - Jeroen J G Geurts
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands
| | - Jaap C Reijneveld
- Cancer Center Amsterdam, Imaging and Biomarkers, Brain Tumor Center Amsterdam, Amsterdam 1081 HV, The Netherlands.,Department of Neurology, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands.,Department of Neurology, Stichting Epilepsie Instellingen Nederland, Heemstede 2103 SW, The Netherlands
| | - Linda Douw
- Department of Anatomy and Neurosciences, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam 1081 HV, The Netherlands.,Cancer Center Amsterdam, Imaging and Biomarkers, Brain Tumor Center Amsterdam, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Systems and Network Neuroscience, Amsterdam 1081 HV, The Netherlands.,Amsterdam Neuroscience, Brain Imaging, Amsterdam 1081 HV, The Netherlands.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
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24
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Abstract
Pain is an unpleasant sensory and emotional experience. Understanding the neural mechanisms of acute and chronic pain and the brain changes affecting pain factors is important for finding pain treatment methods. The emergence and progress of non-invasive neuroimaging technology can help us better understand pain at the neural level. Recent developments in identifying brain-based biomarkers of pain through advances in advanced imaging can provide some foundations for predicting and detecting pain. For example, a neurologic pain signature (involving brain regions that receive nociceptive afferents) and a stimulus intensity-independent pain signature (involving brain regions that do not show increased activity in proportion to noxious stimulus intensity) were developed based on multivariate modeling to identify processes related to the pain experience. However, an accurate and comprehensive review of common neuroimaging techniques for evaluating pain is lacking. This paper reviews the mechanism, clinical application, reliability, strengths, and limitations of common neuroimaging techniques for assessing pain to promote our further understanding of pain.
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Affiliation(s)
- Jing Luo
- Department of Sport Rehabilitation, Xian Physical Education University, Xian, China
- Department of Sport Rehabilitation, Shanghai University of Sport, Shanghai, China
| | - Hui-Qi Zhu
- Department of Sport Rehabilitation, Shanghai University of Sport, Shanghai, China
- Department of Sport Rehabilitation, Shenyang Sport University, Shenyang, China
| | - Bo Gou
- Department of Sport Rehabilitation, Xian Physical Education University, Xian, China.
| | - Xue-Qiang Wang
- Department of Sport Rehabilitation, Shanghai University of Sport, Shanghai, China.
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25
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Hakonen M, Nurmi T, Vallinoja J, Jaatela J, Piitulainen H. More comprehensive proprioceptive stimulation of the hand amplifies its cortical processing. J Neurophysiol 2022; 128:568-581. [PMID: 35858122 PMCID: PMC9423773 DOI: 10.1152/jn.00485.2021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Revised: 06/21/2022] [Accepted: 07/11/2022] [Indexed: 12/02/2022] Open
Abstract
Corticokinematic coherence (CKC) quantifies the phase coupling between limb kinematics and cortical neurophysiological signals reflecting proprioceptive feedback to the primary sensorimotor (SM1) cortex. We studied whether the CKC strength or cortical source location differs between proprioceptive stimulation (i.e., actuator-evoked movements) of right-hand digits (index, middle, ring, and little). Twenty-one volunteers participated in magnetoencephalography measurements during which three conditions were tested: 1) simultaneous stimulation of all four fingers at the same frequency, 2) stimulation of each finger separately at the same frequency, and 3) simultaneous stimulation of the fingers at finger-specific frequencies. CKC was computed between MEG responses and accelerations of the fingers recorded with three-axis accelerometers. CKC was stronger (P < 0.003) for the simultaneous (0.52 ± 0.02) than separate (0.45 ± 0.02) stimulation at the same frequency. Furthermore, CKC was weaker (P < 0.03) for the simultaneous stimulation at the finger-specific frequencies (0.38 ± 0.02) than for the separate stimulation. CKC source locations of the fingers were concentrated in the hand region of the SM1 cortex and did not follow consistent finger-specific somatotopic order. Our results indicate that proprioceptive afference from the fingers is processed in partly overlapping cortical neuronal circuits, which was demonstrated by the modulation of the finger-specific CKC strengths due to proprioceptive afference arising from simultaneous stimulation of the other fingers of the same hand as well as overlapping cortical source locations. Finally, comprehensive simultaneous proprioceptive stimulation of the hand would optimize functional cortical mapping to pinpoint the hand region, e.g., prior brain surgery.NEW & NOTEWORTHY Corticokinematic coherence (CKC) can be used to study cortical proprioceptive processing and localize proprioceptive hand representation. Our results indicate that proprioceptive stimulation delivered simultaneously at the same frequency to fingers (D2-D4) maximizes CKC strength allowing robust and fast localization of the human hand region in the sensorimotor cortex using MEG.
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Affiliation(s)
- Maria Hakonen
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Timo Nurmi
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
| | - Jaakko Vallinoja
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
| | - Julia Jaatela
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
| | - Harri Piitulainen
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
- Aalto NeuroImaging, Magnetoencephalography Core, Aalto University School of Science, Espoo, Finland
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26
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Li Y, Wang Y, Jiang P, Sun J, Chen Q, Wang X. Alterations in the default mode network in rolandic epilepsy with mild spike-wave index in non-rapid eye movement sleep. Front Neurosci 2022; 16:944391. [PMID: 36017188 PMCID: PMC9395966 DOI: 10.3389/fnins.2022.944391] [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: 05/15/2022] [Accepted: 07/25/2022] [Indexed: 11/25/2022] Open
Abstract
Purpose Rolandic epilepsy (RE) is one of the most common epilepsy syndromes during childhood. The aim of this study was to investigate the alterations in the default mode network (DMN) of RE patients whose spike-wave index (SWI) was within the 50–85% range during non-rapid eye movement (NREM) during sleep, as well as to detect early neuroimaging markers. Methods Resting-state data was recorded for each subject using magnetoencephalography (MEG). DMN-related brain regions were chosen as regions of interest. The spectral power and functional connectivity (FC) of the DMN were estimated through the use of minimum norm estimation (MNE) combined with Welch technique and corrected amplitude envelope correlation (AEC-c). Results The patient group included 20 patients with NREM phase 50% ≤ SWI < 85% (mild SWI group), and 18 typical RE patients (SWI < 50% group). At the regional level, the mild SWI group exhibited enhanced spectral power in the delta band of the bilateral posterial cingulate cortex and attenuated the spectral power in the alpha band of the bilateral posterial cingulate cortex. Enhanced spectral power in the bilateral precuneus (PCu) in the delta band and attenuated spectral power in the right lateral temporal cortex (LTC) in the alpha band were common across all RE patients. At the FC level, patients in the mild SWI group indicated increased AEC-c values between the bilateral posterial cingulate cortex in the delta band and between the left medial frontal cortex (MFC) and bilateral posterial cingulate cortex in the alpha band. Increased AEC-c values between the right PCu and left MFC in the delta band, and between the left PCu and right MFC in the theta band, were common across all RE patients. Moreover, the spectral power in the bilateral posterial cingulate cortex in the alpha band and the AEC-c value between the bilateral posterial cingulate cortex in the delta band demonstrated good discrimination ability. Conclusion The spectral power of the bilateral posterior cingulate cortex (PCC) in the alpha band and the AEC-c value between the bilateral PCC in the delta band may be promising indicators of early differentiation between mild SWI and typical RE.
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Affiliation(s)
- Yihan Li
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yingfan Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Ping Jiang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Jintao Sun
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Qiqi Chen
- MEG Center, Nanjing Brain Hospital, Nanjing, China
| | - Xiaoshan Wang
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
- *Correspondence: Xiaoshan Wang,
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27
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Hauk O, Stenroos M, Treder MS. Towards an objective evaluation of EEG/MEG source estimation methods - The linear approach. Neuroimage 2022; 255:119177. [PMID: 35390459 DOI: 10.1016/j.neuroimage.2022.119177] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Revised: 03/30/2022] [Accepted: 03/31/2022] [Indexed: 11/18/2022] Open
Abstract
The spatial resolution of EEG/MEG source estimates, often described in terms of source leakage in the context of the inverse problem, poses constraints on the inferences that can be drawn from EEG/MEG source estimation results. Software packages for EEG/MEG data analysis offer a large choice of source estimation methods but few tools to experimental researchers for methods evaluation and comparison. Here, we describe a framework and tools for objective and intuitive resolution analysis of EEG/MEG source estimation based on linear systems analysis, and apply those to the most widely used distributed source estimation methods such as L2-minimum-norm estimation (L2-MNE) and linearly constrained minimum variance (LCMV) beamformers. Within this framework it is possible to define resolution metrics that define meaningful aspects of source estimation results (such as localization accuracy in terms of peak localization error, PLE, and spatial extent in terms of spatial deviation, SD) that are relevant to the task at hand and can easily be visualized. At the core of this framework is the resolution matrix, which describes the potential leakage from and into point sources (point-spread and cross-talk functions, or PSFs and CTFs, respectively). Importantly, for linear methods these functions allow generalizations to multiple sources or complex source distributions. This paper provides a tutorial-style introduction into linear EEG/MEG source estimation and resolution analysis aimed at experimental (rather than methods-oriented) researchers. We used this framework to demonstrate how L2-MNE-type as well as LCMV beamforming methods can be evaluated in practice using software tools that have only recently become available for routine use. Our novel methods comparison includes PLE and SD for a larger number of methods than in similar previous studies, such as unweighted, depth-weighted and normalized L2-MNE methods (including dSPM, sLORETA, eLORETA) and two LCMV beamformers. The results demonstrate that some methods can achieve low and even zero PLE for PSFs. However, their SD as well as both PLE and SD for CTFs are far less optimal for all methods, in particular for deep cortical areas. We hope that our paper will encourage EEG/MEG researchers to apply this approach to their own tasks at hand.
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Affiliation(s)
- Olaf Hauk
- MRC Cognition and Brain Sciences Unit, University of Cambridge, 15 Chaucer Road, Cambridge CB2 7EF, UK.
| | - Matti Stenroos
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Matthias S Treder
- School of Computer Sciences and Informatics, Cardiff University, Cardiff, UK
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28
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Mylonas D, Sjøgård M, Shi Z, Baxter B, Hämäläinen M, Manoach DS, Khan S. A Novel Approach to Estimating the Cortical Sources of Sleep Spindles Using Simultaneous EEG/MEG. Front Neurol 2022; 13:871166. [PMID: 35785365 PMCID: PMC9243385 DOI: 10.3389/fneur.2022.871166] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 05/18/2022] [Indexed: 11/15/2022] Open
Abstract
Sleep spindles, defining oscillations of stage II non-rapid eye movement sleep (N2), mediate sleep-dependent memory consolidation. Spindles are disrupted in several neurodevelopmental, neuropsychiatric, and neurodegenerative disorders characterized by cognitive impairment. Increasing spindles can improve memory suggesting spindles as a promising physiological target for the development of cognitive enhancing therapies. This effort would benefit from more comprehensive and spatially precise methods to characterize spindles. Spindles, as detected with electroencephalography (EEG), are often widespread across electrodes. Available evidence, however, suggests that they act locally to enhance cortical plasticity in the service of memory consolidation. Here, we present a novel method to enhance the spatial specificity of cortical source estimates of spindles using combined EEG and magnetoencephalography (MEG) data constrained to the cortex based on structural MRI. To illustrate this method, we used simultaneous EEG and MEG recordings from 25 healthy adults during a daytime nap. We first validated source space spindle detection using only EEG data by demonstrating strong temporal correspondence with sensor space EEG spindle detection (gold standard). We then demonstrated that spindle source estimates using EEG alone, MEG alone and combined EEG/MEG are stable across nap sessions. EEG detected more source space spindles than MEG and each modality detected non-overlapping spindles that had distinct cortical source distributions. Source space EEG was more sensitive to spindles in medial frontal and lateral prefrontal cortex, while MEG was more sensitive to spindles in somatosensory and motor cortices. By combining EEG and MEG data this method leverages the differential spatial sensitivities of the two modalities to obtain a more comprehensive and spatially specific source estimation of spindles than possible with either modality alone.
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Affiliation(s)
- Dimitrios Mylonas
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Martin Sjøgård
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Zhaoyue Shi
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
- Carle Illinois Advanced Imaging Center, Carle Foundation Hospital, Urbana, IL, United States
| | - Bryan Baxter
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Matti Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Dara S. Manoach
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Sheraz Khan
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
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29
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Shu S, Luo S, Cao M, Xu K, Qin L, Zheng L, Xu J, Wang X, Gao JH. Informed MEG/EEG source imaging reveals the locations of interictal spikes missed by SEEG. Neuroimage 2022; 254:119132. [PMID: 35337964 DOI: 10.1016/j.neuroimage.2022.119132] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 02/18/2022] [Accepted: 03/21/2022] [Indexed: 11/19/2022] Open
Abstract
Determining the accurate locations of interictal spikes has been fundamental in the presurgical evaluation of epilepsy surgery. Stereo-electroencephalography (SEEG) is able to directly record cortical activity and localize interictal spikes. However, the main caveat of SEEG techniques is that they have limited spatial sampling (covering <5% of the whole brain), which may lead to missed spikes originating from brain regions that were not covered by SEEG. To address this problem, we propose a SEEG-informed minimum-norm estimates (SIMNE) method by combining SEEG with magnetoencephalography (MEG) or EEG. Specifically, the spike locations determined by SEEG offer as a priori information to guide MEG source reconstruction. Both computer simulations and experiments using data from five epilepsy patients were conducted to evaluate the performance of SIMNE. Our results demonstrate that SIMNE generates more accurate source estimation than a traditional minimum-norm estimates method and reveals the locations of spikes missed by SEEG, which would improve presurgical evaluation of the epileptogenic zone.
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Affiliation(s)
- Su Shu
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Shen Luo
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Miao Cao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Ke Xu
- Department of Neurosurgery, Sanbo Brain Hospital of Capital Medical University, Beijing 100093, China
| | - Lang Qin
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Li Zheng
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Jing Xu
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; Laboratory of Applied Brain and Cognitive Sciences, College of International Business, Shanghai International Studies University, Shanghai 201620, China
| | - Xiongfei Wang
- Department of Neurosurgery, Sanbo Brain Hospital of Capital Medical University, Beijing 100093, China
| | - Jia-Hong Gao
- Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing 100871, China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; McGovern Institute for Brain Research, Peking University, Beijing 100871, China; National Biomedical Imaging Center, Peking University, Beijing 100871, China.
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30
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Millán AP, van Straaten ECW, Stam CJ, Nissen IA, Idema S, Baayen JC, Van Mieghem P, Hillebrand A. Epidemic models characterize seizure propagation and the effects of epilepsy surgery in individualized brain networks based on MEG and invasive EEG recordings. Sci Rep 2022; 12:4086. [PMID: 35260657 PMCID: PMC8904850 DOI: 10.1038/s41598-022-07730-2] [Citation(s) in RCA: 5] [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: 09/12/2021] [Accepted: 02/24/2022] [Indexed: 11/08/2022] Open
Abstract
Epilepsy surgery is the treatment of choice for drug-resistant epilepsy patients. However, seizure-freedom is currently achieved in only 2/3 of the patients after surgery. In this study we have developed an individualized computational model based on MEG brain networks to explore seizure propagation and the efficacy of different virtual resections. Eventually, the goal is to obtain individualized models to optimize resection strategy and outcome. We have modelled seizure propagation as an epidemic process using the susceptible-infected (SI) model on individual brain networks derived from presurgical MEG. We included 10 patients who had received epilepsy surgery and for whom the surgery outcome at least one year after surgery was known. The model parameters were tuned in in order to reproduce the patient-specific seizure propagation patterns as recorded with invasive EEG. We defined a personalized search algorithm that combined structural and dynamical information to find resections that maximally decreased seizure propagation for a given resection size. The optimal resection for each patient was defined as the smallest resection leading to at least a 90% reduction in seizure propagation. The individualized model reproduced the basic aspects of seizure propagation for 9 out of 10 patients when using the resection area as the origin of epidemic spreading, and for 10 out of 10 patients with an alternative definition of the seed region. We found that, for 7 patients, the optimal resection was smaller than the resection area, and for 4 patients we also found that a resection smaller than the resection area could lead to a 100% decrease in propagation. Moreover, for two cases these alternative resections included nodes outside the resection area. Epidemic spreading models fitted with patient specific data can capture the fundamental aspects of clinically observed seizure propagation, and can be used to test virtual resections in silico. Combined with optimization algorithms, smaller or alternative resection strategies, that are individually targeted for each patient, can be determined with the ultimate goal to improve surgery outcome. MEG-based networks can provide a good approximation of structural connectivity for computational models of seizure propagation, and facilitate their clinical use.
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Affiliation(s)
- Ana P Millán
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
| | - Elisabeth C W van Straaten
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Ida A Nissen
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Sander Idema
- Department of Neurosurgery, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Johannes C Baayen
- Department of Neurosurgery, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Piet Van Mieghem
- Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Delft, The Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology and MEG Center, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
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31
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Zhang B, Wang F, Zhang Q, Naya Y. Distinct networks coupled with parietal cortex for spatial representations inside and outside the visual field. Neuroimage 2022; 252:119041. [PMID: 35231630 DOI: 10.1016/j.neuroimage.2022.119041] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 02/22/2022] [Accepted: 02/24/2022] [Indexed: 11/19/2022] Open
Abstract
Our mental representation of egocentric space is influenced by the disproportionate sensory perception of the body. Previous studies have focused on the neural architecture for egocentric representations within the visual field. However, the space representation underlying the body is still unclear. To address this problem, we applied both functional Magnitude Resonance Imaging (fMRI) and Magnetoencephalography (MEG) to a spatial-memory paradigm by using a virtual environment in which human participants remembered a target location left, right, or back relative to their own body. Both experiments showed larger involvement of the frontoparietal network in representing a retrieved target on the left/right side than on the back. Conversely, the medial temporal lobe (MTL)-parietal network was more involved in retrieving a target behind the participants. The MEG data showed an earlier activation of the MTL-parietal network than that of the frontoparietal network during retrieval of a target location. These findings suggest that the parietal cortex may represent the entire space around the self-body by coordinating two distinct brain networks.
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Affiliation(s)
- Bo Zhang
- School of Psychological and Cognitive Sciences, Peking University, No. 52, Haidian Road, Haidian District, Beijing 100805, China; Beijing Academy of Artificial Intelligence, Beijing, 100084, China; Tsinghua Laboratory of Brain and Intelligence, 160 Chengfu Rd., SanCaiTang Building, Haidian District, Beijing, 100084, China
| | - Fan Wang
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Sciences, 15 Datun Road, Beijing 100101, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Biophysics, Chinese Academy of Sciences, 15 Datun Road, Beijing 100101, China; University of Chinese Academy of Sciences, 19A Yuquan Road, Beijing 100049, China
| | - Qi Zhang
- School of Psychological and Cognitive Sciences, Peking University, No. 52, Haidian Road, Haidian District, Beijing 100805, China; School of Educational Science, Minnan Normal University, No. 36, Xianqianzhi Street, Zhangzhou 363000, China
| | - Yuji Naya
- School of Psychological and Cognitive Sciences, Peking University, No. 52, Haidian Road, Haidian District, Beijing 100805, China; IDG/McGovern Institute for Brain Research at Peking University, No. 52, Haidian Road, Haidian District, Beijing 100805, China; Center for Life Sciences, Peking University, No. 52, Haidian Road, Haidian District, Beijing 100805, China; Beijing Key Laboratory of Behavior and Mental Health, Peking University, No. 52, Haidian Road, Haidian District, Beijing 100805, China.
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32
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Illman MJ, Laaksonen K, Jousmäki V, Forss N, Piitulainen H. Reproducibility of Rolandic beta rhythm modulation in MEG and EEG. J Neurophysiol 2022; 127:559-570. [PMID: 35044809 PMCID: PMC8858683 DOI: 10.1152/jn.00267.2021] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/03/2022] Open
Abstract
The Rolandic beta rhythm, at ∼20 Hz, is generated in the somatosensory and motor cortices and is modulated by motor activity and sensory stimuli, causing a short lasting suppression that is followed by a rebound of the beta rhythm. The rebound reflects inhibitory changes in the primary sensorimotor (SMI) cortex, and thus it has been used as a biomarker to follow the recovery of patients with acute stroke. The longitudinal stability of beta rhythm modulation is a prerequisite for its use in long-term follow-ups. We quantified the reproducibility of beta rhythm modulation in healthy subjects in a 1-year-longitudinal study both for MEG and EEG at T0, 1 month (T1-month, n = 8) and 1 year (T1-year, n = 19). The beta rhythm (13–25 Hz) was modulated by fixed tactile and proprioceptive stimulations of the index fingers. The relative peak strengths of beta suppression and rebound did not differ significantly between the sessions, and intersession reproducibility was good or excellent according to intraclass correlation-coefficient values (0.70–0.96) both in MEG and EEG. Our results indicate that the beta rhythm modulation to tactile and proprioceptive stimulation is well reproducible within 1 year. These results support the use of beta modulation as a biomarker in long-term follow-up studies, e.g., to quantify the functional state of the SMI cortex during rehabilitation and drug interventions in various neurological impairments. NEW & NOTEWORTHY The present study demonstrates that beta rhythm modulation is highly reproducible in a group of healthy subjects within a year. Hence, it can be reliably used as a biomarker in longitudinal follow-up studies in different neurological patient groups to reflect changes in the functional state of the sensorimotor cortex.
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Affiliation(s)
- Mia Johanna Illman
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland.,Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Aalto, Espoo, Finland.,Aalto NeuroImaging, Aalto University School of Science, Aalto, Espoo, Finland
| | - Kristina Laaksonen
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Aalto, Espoo, Finland.,Department of Neurology, Helsinki University Hospital and Clinical Neurosciences, Neurology, University of Helsinki, Helsinki, Finland
| | - Veikko Jousmäki
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Aalto, Espoo, Finland.,Aalto NeuroImaging, Aalto University School of Science, Aalto, Espoo, Finland
| | - Nina Forss
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Aalto, Espoo, Finland.,Department of Neurology, Helsinki University Hospital and Clinical Neurosciences, Neurology, University of Helsinki, Helsinki, Finland
| | - Harri Piitulainen
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland.,Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Aalto, Espoo, Finland
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33
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Jaatela J, Aydogan DB, Nurmi T, Vallinoja J, Piitulainen H. Identification of Proprioceptive Thalamocortical Tracts in Children: Comparison of fMRI, MEG, and Manual Seeding of Probabilistic Tractography. Cereb Cortex 2022; 32:3736-3751. [PMID: 35040948 PMCID: PMC9433422 DOI: 10.1093/cercor/bhab444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 11/05/2021] [Accepted: 11/06/2021] [Indexed: 11/16/2022] Open
Abstract
Studying white matter connections with tractography is a promising approach to understand the development of different brain processes, such as proprioception. An emerging method is to use functional brain imaging to select the cortical seed points for tractography, which is considered to improve the functional relevance and validity of the studied connections. However, it is unknown whether different functional seeding methods affect the spatial and microstructural properties of the given white matter connection. Here, we compared functional magnetic resonance imaging, magnetoencephalography, and manual seeding of thalamocortical proprioceptive tracts for finger and ankle joints separately. We showed that all three seeding approaches resulted in robust thalamocortical tracts, even though there were significant differences in localization of the respective proprioceptive seed areas in the sensorimotor cortex, and in the microstructural properties of the obtained tracts. Our study shows that the selected functional or manual seeding approach might cause systematic biases to the studied thalamocortical tracts. This result may indicate that the obtained tracts represent different portions and features of the somatosensory system. Our findings highlight the challenges of studying proprioception in the developing brain and illustrate the need for using multimodal imaging to obtain a comprehensive view of the studied brain process.
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Affiliation(s)
- Julia Jaatela
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo FI-02150, Finland
| | - Dogu Baran Aydogan
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo FI-02150, Finland
- Department of Psychiatry, Helsinki University Hospital, Helsinki FI-00029, Finland
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio FI-70211, Finland
| | - Timo Nurmi
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo FI-02150, Finland
- Faculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä FI-40014, Finland
| | - Jaakko Vallinoja
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo FI-02150, Finland
| | - Harri Piitulainen
- Address correspondence to Harri Piitulainen, associate professor, Harri Piitulainen, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. BOX 35, FI-40014, Finland.
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34
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Nenonen J, Helle L, Jaiswal A, Bock E, Ille N, Bornfleth H. Sensitivity of a 29-Channel MEG Source Montage. Brain Sci 2022; 12:brainsci12010105. [PMID: 35053848 PMCID: PMC8773883 DOI: 10.3390/brainsci12010105] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Revised: 01/08/2022] [Accepted: 01/11/2022] [Indexed: 12/04/2022] Open
Abstract
In this paper, we study the performance of a source montage corresponding to 29 brain regions reconstructed from whole-head magnetoencephalographic (MEG) recordings, with the aim of facilitating the review of MEG data containing epileptiform discharges. Test data were obtained by superposing simulated signals from 100-nAm dipolar sources to a resting state MEG recording from a healthy subject. Simulated sources were placed systematically to different cortical locations for defining the optimal regularization for the source montage reconstruction and for assessing the detectability of the source activity from the 29-channel MEG source montage. The signal-to-noise ratio (SNR), computed for each source from the sensor-level and source-montage signals, was used as the evaluation parameter. Without regularization, the SNR from the simulated sources was larger in the sensor-level signals than in the source montage reconstructions. Setting the regularization to 2% increased the source montage SNR to the same level as the sensor-level SNR, improving the detectability of the simulated events from the source montage reconstruction. Sources producing a SNR of at least 15 dB were visually detectable from the source-montage signals. Such sources are located closer than about 75 mm from the MEG sensors, in practice covering all areas in the grey matter. The 29-channel source montage creates more focal signals compared to the sensor space and can significantly shorten the detection time of epileptiform MEG discharges for focus localization.
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Affiliation(s)
- Jukka Nenonen
- Megin Oy, Keilasatama 5, FI-02150 Espoo, Finland; (L.H.); (A.J.); (E.B.)
- Correspondence: ; Tel.: +358-9-756-2400
| | - Liisa Helle
- Megin Oy, Keilasatama 5, FI-02150 Espoo, Finland; (L.H.); (A.J.); (E.B.)
- Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, FI-00076 Aalto, Finland
| | - Amit Jaiswal
- Megin Oy, Keilasatama 5, FI-02150 Espoo, Finland; (L.H.); (A.J.); (E.B.)
- Department of Neuroscience and Biomedical Engineering, School of Science, Aalto University, FI-00076 Aalto, Finland
| | - Elizabeth Bock
- Megin Oy, Keilasatama 5, FI-02150 Espoo, Finland; (L.H.); (A.J.); (E.B.)
| | - Nicole Ille
- BESA GmbH, 82166 Gräfelfing, Germany; (N.I.); (H.B.)
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35
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MEG correlates of temporal regularity relevant to pitch perception in human auditory cortex. Neuroimage 2022; 249:118879. [PMID: 34999204 PMCID: PMC8883111 DOI: 10.1016/j.neuroimage.2022.118879] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 12/01/2021] [Accepted: 01/05/2022] [Indexed: 11/20/2022] Open
Abstract
We recorded neural responses in human participants to three types of pitch-evoking regular stimuli at rates below and above the lower limit of pitch using magnetoencephalography (MEG). These bandpass filtered (1–4 kHz) stimuli were harmonic complex tones (HC), click trains (CT), and regular interval noise (RIN). Trials consisted of noise-regular-noise (NRN) or regular-noise-regular (RNR) segments in which the repetition rate (or fundamental frequency F0) was either above (250 Hz) or below (20 Hz) the lower limit of pitch. Neural activation was estimated and compared at the senor and source levels. The pitch-relevant regular stimuli (F0 = 250 Hz) were all associated with marked evoked responses at around 140 ms after noise-to-regular transitions at both sensor and source levels. In particular, greater evoked responses to pitch-relevant stimuli than pitch-irrelevant stimuli (F0 = 20 Hz) were localized along the Heschl's sulcus around 140 ms. The regularity-onset responses for RIN were much weaker than for the other types of regular stimuli (HC, CT). This effect was localized over planum temporale, planum polare, and lateral Heschl's gyrus. Importantly, the effect of pitch did not interact with the stimulus type. That is, we did not find evidence to support different responses for different types of regular stimuli from the spatiotemporal cluster of the pitch effect (∼140 ms). The current data demonstrate cortical sensitivity to temporal regularity relevant to pitch that is consistently present across different pitch-relevant stimuli in the Heschl's sulcus between Heschl's gyrus and planum temporale, both of which have been identified as a “pitch center” based on different modalities.
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36
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Van Dyck D, Deconinck N, Aeby A, Baijot S, Coquelet N, Trotta N, Rovai A, Goldman S, Urbain C, Wens V, De Tiège X. Atypical resting-state functional brain connectivity in children with developmental coordination disorder. Neuroimage Clin 2021; 33:102928. [PMID: 34959048 PMCID: PMC8856907 DOI: 10.1016/j.nicl.2021.102928] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 12/06/2021] [Accepted: 12/22/2021] [Indexed: 12/21/2022]
Abstract
Children with developmental coordination disorder (DCD) present lower abilities to acquire and execute coordinated motor skills. DCD is frequently associated with visual perceptual (with or without motor component) impairments. This magnetoencephalography (MEG) study compares the brain resting-state functional connectivity (rsFC) and spectral power of children with and without DCD. 29 children with DCD and 28 typically developing (TD) peers underwent 2 × 5 min of resting-state MEG. Band-limited power envelope correlation and spectral power were compared between groups using a functional connectome of 59 nodes from eight resting-state networks. Correlation coefficients were calculated between fine and gross motor activity, visual perceptual and visuomotor abilities measures on the one hand, and brain rsFC and spectral power on the other hand. Nonparametric statistics were used. Significantly higher rsFC between nodes of the visual, attentional, frontoparietal, default-mode and cerebellar networks was observed in the alpha (maximum statistics, p = .0012) and the low beta (p = .0002) bands in children with DCD compared to TD peers. Lower visuomotor performance (copying figures) was associated with stronger interhemispheric rsFC within sensorimotor areas and power in the cerebellum (right lobule VIII). Children with DCD showed increased rsFC mainly in the dorsal extrastriate visual brain system and the cerebellum. However, this increase was not associated with their coordinated motor/visual perceptual abilities. This enhanced functional brain connectivity could thus reflect a characteristic brain trait of children with DCD compared to their TD peers. Moreover, an interhemispheric compensatory process might be at play to perform visuomotor task within the normative range.
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Affiliation(s)
- Dorine Van Dyck
- Laboratoire de Cartographie Fonctionnelle du Cerveau (LCFC), ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium; Department of Neurology, Hôpital Universitaire des Enfants Reine Fabiola (HUDERF), Université libre de Bruxelles (ULB), Brussels, Belgium.
| | - Nicolas Deconinck
- Department of Neurology, Hôpital Universitaire des Enfants Reine Fabiola (HUDERF), Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Alec Aeby
- Department of Neurology, Hôpital Universitaire des Enfants Reine Fabiola (HUDERF), Université libre de Bruxelles (ULB), Brussels, Belgium; Neuropsychology and Functional Neuroimaging Research Group (UR2NF) at Center for Research in Cognition and Neurosciences (CRCN) and ULB Neurosciences Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Simon Baijot
- Department of Neurology, Hôpital Universitaire des Enfants Reine Fabiola (HUDERF), Université libre de Bruxelles (ULB), Brussels, Belgium; Neuropsychology and Functional Neuroimaging Research Group (UR2NF) at Center for Research in Cognition and Neurosciences (CRCN) and ULB Neurosciences Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Nicolas Coquelet
- Laboratoire de Cartographie Fonctionnelle du Cerveau (LCFC), ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Nicola Trotta
- Laboratoire de Cartographie Fonctionnelle du Cerveau (LCFC), ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium; Clinics of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Antonin Rovai
- Laboratoire de Cartographie Fonctionnelle du Cerveau (LCFC), ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium; Clinics of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Serge Goldman
- Laboratoire de Cartographie Fonctionnelle du Cerveau (LCFC), ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium; Clinics of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Charline Urbain
- Laboratoire de Cartographie Fonctionnelle du Cerveau (LCFC), ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium; Neuropsychology and Functional Neuroimaging Research Group (UR2NF) at Center for Research in Cognition and Neurosciences (CRCN) and ULB Neurosciences Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Vincent Wens
- Laboratoire de Cartographie Fonctionnelle du Cerveau (LCFC), ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium; Clinics of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Xavier De Tiège
- Laboratoire de Cartographie Fonctionnelle du Cerveau (LCFC), ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium; Clinics of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium
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Jiang X, Ye S, Sohrabpour A, Bagić A, He B. Imaging the extent and location of spatiotemporally distributed epileptiform sources from MEG measurements. Neuroimage Clin 2021; 33:102903. [PMID: 34864288 PMCID: PMC8648830 DOI: 10.1016/j.nicl.2021.102903] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Revised: 11/26/2021] [Accepted: 11/27/2021] [Indexed: 11/23/2022]
Abstract
Non-invasive MEG/EEG source imaging provides valuable information about the epileptogenic brain areas which can be used to aid presurgical planning in focal epilepsy patients suffering from drug-resistant seizures. However, the source extent estimation for electrophysiological source imaging remains to be a challenge and is usually largely dependent on subjective choice. Our recently developed algorithm, fast spatiotemporal iteratively reweighted edge sparsity minimization (FAST-IRES) strategy, has been shown to objectively estimate extended sources from EEG recording, while it has not been applied to MEG recordings. In this work, through extensive numerical experiments and real data analysis in a group of focal drug-resistant epilepsy patients' interictal spikes, we demonstrated the ability of FAST-IRES algorithm to image the location and extent of underlying epilepsy sources from MEG measurements. Our results indicate the merits of FAST-IRES in imaging the location and extent of epilepsy sources for pre-surgical evaluation from MEG measurements.
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Affiliation(s)
- Xiyuan Jiang
- Department of Biomedical Engineering, Carnegie Mellon University, USA
| | - Shuai Ye
- Department of Biomedical Engineering, Carnegie Mellon University, USA
| | - Abbas Sohrabpour
- Department of Biomedical Engineering, Carnegie Mellon University, USA
| | - Anto Bagić
- University of Pittsburgh Comprehensive Epilepsy Center (UPCEC), University of Pittsburgh Medical School, USA
| | - Bin He
- Department of Biomedical Engineering, Carnegie Mellon University, USA.
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38
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Bonaiuto JJ, Little S, Neymotin SA, Jones SR, Barnes GR, Bestmann S. Laminar dynamics of high amplitude beta bursts in human motor cortex. Neuroimage 2021; 242:118479. [PMID: 34407440 PMCID: PMC8463839 DOI: 10.1016/j.neuroimage.2021.118479] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 08/12/2021] [Accepted: 08/14/2021] [Indexed: 12/28/2022] Open
Abstract
Motor cortical activity in the beta frequency range is one of the strongest and most studied movement-related neural signals. At the single trial level, beta band activity is often characterized by transient, high amplitude, bursting events rather than slowly modulating oscillations. The timing of these bursting events is tightly linked to behavior, suggesting a more dynamic functional role for beta activity than previously believed. However, the neural mechanisms underlying beta bursts in sensorimotor circuits are poorly understood. To address this, we here leverage and extend recent developments in high precision MEG for temporally resolved laminar analysis of burst activity, combined with a neocortical circuit model that simulates the biophysical generators of the electrical currents which drive beta bursts. This approach pinpoints the generation of beta bursts in human motor cortex to distinct excitatory synaptic inputs to deep and superficial cortical layers, which drive current flow in opposite directions. These laminar dynamics of beta bursts in motor cortex align with prior invasive animal recordings within the somatosensory cortex, and suggest a conserved mechanism for somatosensory and motor cortical beta bursts. More generally, we demonstrate the ability for uncovering the laminar dynamics of event-related neural signals in human non-invasive recordings. This provides important constraints to theories about the functional role of burst activity for movement control in health and disease, and crucial links between macro-scale phenomena measured in humans and micro-circuit activity recorded from animal models.
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Affiliation(s)
- James J Bonaiuto
- Institut des Sciences Cognitives Marc Jeannerod, CNRS UMR 5229, Bron, France; Université Claude Bernard Lyon 1, Université de Lyon, France; Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London (UCL), London, WC1N 3BG, UK; Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, University College London (UCL), London, WC1N 3BG, UK.
| | - Simon Little
- Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, University College London (UCL), London, WC1N 3BG, UK; Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Samuel A Neymotin
- Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA; Department of Neuroscience, Brown University, Providence, RI, USA; Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA
| | - Stephanie R Jones
- Department of Neuroscience, Brown University, Providence, RI, USA; Center for Neurorestoration and Neurotechnology, Providence VAMC, Providence, RI, USA
| | - Gareth R Barnes
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London (UCL), London, WC1N 3BG, UK
| | - Sven Bestmann
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, University College London (UCL), London, WC1N 3BG, UK; Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, University College London (UCL), London, WC1N 3BG, UK
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39
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Laohathai C, Ebersole JS, Mosher JC, Bagić AI, Sumida A, Von Allmen G, Funke ME. Practical Fundamentals of Clinical MEG Interpretation in Epilepsy. Front Neurol 2021; 12:722986. [PMID: 34721261 PMCID: PMC8551575 DOI: 10.3389/fneur.2021.722986] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 09/06/2021] [Indexed: 11/29/2022] Open
Abstract
Magnetoencephalography (MEG) is a neurophysiologic test that offers a functional localization of epileptic sources in patients considered for epilepsy surgery. The understanding of clinical MEG concepts, and the interpretation of these clinical studies, are very involving processes that demand both clinical and procedural expertise. One of the major obstacles in acquiring necessary proficiency is the scarcity of fundamental clinical literature. To fill this knowledge gap, this review aims to explain the basic practical concepts of clinical MEG relevant to epilepsy with an emphasis on single equivalent dipole (sECD), which is one the most clinically validated and ubiquitously used source localization method, and illustrate and explain the regional topology and source dynamics relevant for clinical interpretation of MEG-EEG.
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Affiliation(s)
- Christopher Laohathai
- Division of Child Neurology, Department of Pediatrics, McGovern Medical School at UTHealth, Houston, TX, United States
- Department of Neurology, Saint Louis University, Saint Louis, MO, United States
| | - John S. Ebersole
- Northeast Regional Epilepsy Group, Atlantic Health Neuroscience Institute, Summit, NJ, United States
| | - John C. Mosher
- Department of Neurology, McGovern Medical School at UTHealth, Houston, TX, United States
| | - Anto I. Bagić
- University of Pittsburgh Comprehensive Epilepsy Center (UPCEC), Department of Neurology, University of Pittsburgh Medical Center, Pittsburg, PA, United States
| | - Ai Sumida
- Department of Neurology, McGovern Medical School at UTHealth, Houston, TX, United States
| | - Gretchen Von Allmen
- Division of Child Neurology, Department of Pediatrics, McGovern Medical School at UTHealth, Houston, TX, United States
| | - Michael E. Funke
- Division of Child Neurology, Department of Pediatrics, McGovern Medical School at UTHealth, Houston, TX, United States
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40
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Flick G, Abdullah O, Pylkkänen L. From letters to composed concepts: A magnetoencephalography study of reading. Hum Brain Mapp 2021; 42:5130-5153. [PMID: 34402114 PMCID: PMC8449097 DOI: 10.1002/hbm.25608] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 06/23/2021] [Accepted: 07/20/2021] [Indexed: 11/30/2022] Open
Abstract
Language comprehension requires the recognition of individual words and the combination of their meanings to yield complex concepts or interpretations. This combinatory process often requires the insertion of unstated semantic material between words, based on thematic or feature knowledge. For example, the phrase horse barn is not interpreted as a blend of a horse and a barn, but specifically a barn where horses are kept. Previous neuroscientific evidence suggests that left posterior and anterior temporal cortex underpin thematic and feature‐based concept knowledge, respectively, but much remains unclear about how these areas contribute to combinatory language processing. Using magnetoencephalography, we contrasted source‐localized responses to modifier‐noun phrases involving thematic relations versus feature modifications, while also examining how lower‐level orthographic processing fed composition. Participants completed three procedures examining responses to letter‐strings, adjective‐noun phrases, and noun–noun combinations that varied the semantic relations between words. We found that sections of the left anterior temporal lobe, posterior temporal lobe, and cortex surrounding the angular gyrus were all engaged in the minimal composition of adjective‐noun phrases, a more distributed network than in most prior studies of minimal composition. Of these regions, only the left posterior temporal lobe was additionally sensitive to implicit thematic relations between composing words, suggesting that it houses a specialized relational processing component in a wider composition network. We additionally identified a left occipitotemporal progression from orthographic to lexical processing, feeding ventral anterior areas engaged in the combination of word meanings. Finally, by examining source signal leakage, we characterized the degree to which these responses could be distinguished from one another using source estimation.
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Affiliation(s)
- Graham Flick
- Department of Psychology, New York University, New York, New York, USA.,NYUAD Research Institute, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Osama Abdullah
- NYUAD Research Institute, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Liina Pylkkänen
- Department of Psychology, New York University, New York, New York, USA.,NYUAD Research Institute, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates.,Department of Linguistics, New York University, New York, New York, USA
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41
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Abstract
The perception of sensory events can be enhanced or suppressed by the surrounding spatial and temporal context in ways that facilitate the detection of novel objects and contribute to the perceptual constancy of those objects under variable conditions. In the auditory system, the phenomenon known as auditory enhancement reflects a general principle of contrast enhancement, in which a target sound embedded within a background sound becomes perceptually more salient if the background is presented first by itself. This effect is highly robust, producing an effective enhancement of the target of up to 25 dB (more than two orders of magnitude in intensity), depending on the task. Despite the importance of the effect, neural correlates of auditory contrast enhancement have yet to be identified in humans. Here, we used the auditory steady-state response to probe the neural representation of a target sound under conditions of enhancement. The probe was simultaneously modulated in amplitude with two modulation frequencies to distinguish cortical from subcortical responses. We found robust correlates for neural enhancement in the auditory cortical, but not subcortical, responses. Our findings provide empirical support for a previously unverified theory of auditory enhancement based on neural adaptation of inhibition and point to approaches for improving sensory prostheses for hearing loss, such as hearing aids and cochlear implants.
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Affiliation(s)
- Anahita H Mehta
- Department of Psychology, University of Minnesota, Minneapolis, MN 55455
| | - Lei Feng
- Department of Psychology, University of Minnesota, Minneapolis, MN 55455
| | - Andrew J Oxenham
- Department of Psychology, University of Minnesota, Minneapolis, MN 55455
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42
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Watching Movies Unfold, a Frame-by-Frame Analysis of the Associated Neural Dynamics. eNeuro 2021; 8:ENEURO.0099-21.2021. [PMID: 34193513 PMCID: PMC8272404 DOI: 10.1523/eneuro.0099-21.2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Revised: 05/21/2021] [Accepted: 06/02/2021] [Indexed: 12/02/2022] Open
Abstract
Our lives unfold as sequences of events. We experience these events as seamless, although they are composed of individual images captured in between the interruptions imposed by eye blinks and saccades. Events typically involve visual imagery from the real world (scenes), and the hippocampus is frequently engaged in this context. It is unclear, however, whether the hippocampus would be similarly responsive to unfolding events that involve abstract imagery. Addressing this issue could provide insights into the nature of its contribution to event processing, with relevance for theories of hippocampal function. Consequently, during magnetoencephalography (MEG), we had female and male humans watch highly matched unfolding movie events composed of either scene image frames that reflected the real world, or frames depicting abstract patterns. We examined the evoked neuronal responses to each image frame along the time course of the movie events. Only one difference between the two conditions was evident, and that was during the viewing of the first image frame of events, detectable across frontotemporal sensors. Further probing of this difference using source reconstruction revealed greater engagement of a set of brain regions across parietal, frontal, premotor, and cerebellar cortices, with the largest change in broadband (1–30 Hz) power in the hippocampus during scene-based movie events. Hippocampal engagement during the first image frame of scene-based events could reflect its role in registering a recognizable context perhaps based on templates or schemas. The hippocampus, therefore, may help to set the scene for events very early on.
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Van Dyck D, Deconinck N, Aeby A, Baijot S, Coquelet N, Trotta N, Rovai A, Goldman S, Urbain C, Wens V, De Tiège X. Resting-state functional brain connectivity is related to subsequent procedural learning skills in school-aged children. Neuroimage 2021; 240:118368. [PMID: 34242786 DOI: 10.1016/j.neuroimage.2021.118368] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 06/30/2021] [Accepted: 07/05/2021] [Indexed: 10/20/2022] Open
Abstract
This magnetoencephalography (MEG) study investigates how procedural sequence learning performance is related to prior brain resting-state functional connectivity (rsFC), and to what extent sequence learning induces rapid changes in brain rsFC in school-aged children. Procedural learning was assessed in 30 typically developing children (mean age ± SD: 9.99 years ± 1.35) using a serial reaction time task (SRTT). During SRTT, participants touched as quickly and accurately as possible a stimulus sequentially or randomly appearing in one of the quadrants of a touchscreen. Band-limited power envelope correlation (brain rsFC) was applied to MEG data acquired at rest pre- and post-learning. Correlation analyses were performed between brain rsFC and sequence-specific learning or response time indices. Stronger pre-learning interhemispheric rsFC between inferior parietal and primary somatosensory/motor areas correlated with better subsequent sequence learning performance and faster visuomotor response time. Faster response time was associated with post-learning decreased rsFC within the dorsal extra-striate visual stream and increased rsFC between temporo-cerebellar regions. In school-aged children, variations in functional brain architecture at rest within the sensorimotor network account for interindividual differences in sequence learning and visuomotor performance. After learning, rapid adjustments in functional brain architecture are associated with visuomotor performance but not sequence learning skills.
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Affiliation(s)
- Dorine Van Dyck
- Laboratoire de Cartographie fonctionnelle du Cerveau (LCFC), ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium; Department of Neurology, Hôpital Universitaire des Enfants Reine Fabiola (HUDERF), Université libre de Bruxelles (ULB), Brussels, Belgium.
| | - Nicolas Deconinck
- Department of Neurology, Hôpital Universitaire des Enfants Reine Fabiola (HUDERF), Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Alec Aeby
- Department of Neurology, Hôpital Universitaire des Enfants Reine Fabiola (HUDERF), Université libre de Bruxelles (ULB), Brussels, Belgium; Neuropsychology and Functional Neuroimaging Research Unit (UR2NF), Center for Research in Cognition and Neurosciences (CRCN) and ULB Neurosciences Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Simon Baijot
- Department of Neurology, Hôpital Universitaire des Enfants Reine Fabiola (HUDERF), Université libre de Bruxelles (ULB), Brussels, Belgium; Neuropsychology and Functional Neuroimaging Research Unit (UR2NF), Center for Research in Cognition and Neurosciences (CRCN) and ULB Neurosciences Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Nicolas Coquelet
- Laboratoire de Cartographie fonctionnelle du Cerveau (LCFC), ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Nicola Trotta
- Laboratoire de Cartographie fonctionnelle du Cerveau (LCFC), ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium; Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Antonin Rovai
- Laboratoire de Cartographie fonctionnelle du Cerveau (LCFC), ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium; Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Serge Goldman
- Laboratoire de Cartographie fonctionnelle du Cerveau (LCFC), ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium; Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Charline Urbain
- Laboratoire de Cartographie fonctionnelle du Cerveau (LCFC), ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium; Neuropsychology and Functional Neuroimaging Research Unit (UR2NF), Center for Research in Cognition and Neurosciences (CRCN) and ULB Neurosciences Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Vincent Wens
- Laboratoire de Cartographie fonctionnelle du Cerveau (LCFC), ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium; Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium
| | - Xavier De Tiège
- Laboratoire de Cartographie fonctionnelle du Cerveau (LCFC), ULB Neuroscience Institute (UNI), Université libre de Bruxelles (ULB), Brussels, Belgium; Department of Functional Neuroimaging, Service of Nuclear Medicine, CUB Hôpital Erasme, Université libre de Bruxelles (ULB), Brussels, Belgium
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Chaumon M, Puce A, George N. Statistical power: Implications for planning MEG studies. Neuroimage 2021; 233:117894. [PMID: 33737245 PMCID: PMC8148377 DOI: 10.1016/j.neuroimage.2021.117894] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 01/22/2021] [Accepted: 02/16/2021] [Indexed: 11/24/2022] Open
Abstract
Statistical power is key for robust, replicable science. Here, we systematically explored how numbers of trials and subjects affect statistical power in MEG sensor-level data. More specifically, we simulated "experiments" using the MEG resting-state dataset of the Human Connectome Project (HCP). We divided the data in two conditions, injected a dipolar source at a known anatomical location in the "signal condition", but not in the "noise condition", and detected significant differences at sensor level with classical paired t-tests across subjects, using amplitude, squared amplitude, and global field power (GFP) measures. Group-level detectability of these simulated effects varied drastically with anatomical origin. We thus examined in detail which spatial properties of the sources affected detectability, looking specifically at the distance from closest sensor and orientation of the source, and at the variability of these parameters across subjects. In line with previous single-subject studies, we found that the most detectable effects originate from source locations that are closest to the sensors and oriented tangentially with respect to the head surface. In addition, cross-subject variability in orientation also affected group-level detectability, boosting detection in regions where this variability was small and hindering detection in regions where it was large. Incidentally, we observed a considerable covariation of source position, orientation, and their cross-subject variability in individual brain anatomical space, making it difficult to assess the impact of each of these variables independently of one another. We thus also performed simulations where we controlled spatial properties independently of individual anatomy. These additional simulations confirmed the strong impact of distance and orientation and further showed that orientation variability across subjects affects detectability, whereas position variability does not. Importantly, our study indicates that strict unequivocal recommendations as to the ideal number of trials and subjects for any experiment cannot be realistically provided for neurophysiological studies and should be adapted according to the brain regions under study.
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Affiliation(s)
- Maximilien Chaumon
- Institut du Cerveau, ICM, Inserm U 1127, CNRS UMR 7225, Sorbonne Université, Centre MEG-EEG, Centre de NeuroImagerie Recherche (CENIR), 47 Boulevard de l'hôpital, 75013 Paris, France.
| | - Aina Puce
- Department of Psychological & Brain Sciences, Programs in Neuroscience, Cognitive Science, Indiana University, 1101 East 10th St, Bloomington, IN 47405, United States
| | - Nathalie George
- Institut du Cerveau, ICM, Inserm U 1127, CNRS UMR 7225, Sorbonne Université, Centre MEG-EEG, Centre de NeuroImagerie Recherche (CENIR), 47 Boulevard de l'hôpital, 75013 Paris, France
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45
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Huizeling E, Wang H, Holland C, Kessler K. Changes in theta and alpha oscillatory signatures of attentional control in older and middle age. Eur J Neurosci 2021; 54:4314-4337. [PMID: 33949008 DOI: 10.1111/ejn.15259] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 04/09/2021] [Accepted: 04/23/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND Recent behavioural research has reported age-related changes in the costs of refocusing attention from a temporal (rapid serial visual presentation) to a spatial (visual search) task. Using magnetoencephalography, we have now compared the neural signatures of attention refocusing between three age groups (19-30, 40-49 and 60+ years) and found differences in task-related modulation and cortical localisation of alpha and theta oscillations. Efficient, faster refocusing in the youngest group compared to both middle age and older groups was reflected in parietal theta effects that were significantly reduced in the older groups. Residual parietal theta activity in older individuals was beneficial to attentional refocusing and could reflect preserved attention mechanisms. Slowed refocusing of attention, especially when a target required consolidation, in the older and middle-aged adults was accompanied by a posterior theta deficit and increased recruitment of frontal (middle-aged and older groups) and temporal (older group only) areas, demonstrating a posterior to anterior processing shift. Theta but not alpha modulation correlated with task performance, suggesting that older adults' stronger and more widely distributed alpha power modulation could reflect decreased neural precision or dedifferentiation but requires further investigation. Our results demonstrate that older adults present with different alpha and theta oscillatory signatures during attentional control, reflecting cognitive decline and, potentially, also different cognitive strategies in an attempt to compensate for decline.
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Affiliation(s)
- Eleanor Huizeling
- Aston Research Centre for Healthy Ageing, Aston University, Birmingham, UK
- Institute of Health and Neurodevelopment, Aston University, Birmingham, UK
- Max Planck Institute for Psycholinguistics, Nijmegen, Netherlands
| | - Hongfang Wang
- Institute of Health and Neurodevelopment, Aston University, Birmingham, UK
| | - Carol Holland
- Aston Research Centre for Healthy Ageing, Aston University, Birmingham, UK
- Centre for Ageing Research, Division of Health Research, Lancaster University, Lancaster, UK
| | - Klaus Kessler
- Aston Research Centre for Healthy Ageing, Aston University, Birmingham, UK
- Institute of Health and Neurodevelopment, Aston University, Birmingham, UK
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Vivekananda U, Cao C, Liu W, Zhang J, Rugg-Gunn F, Walker MC, Litvak V, Sun B, Zhan S. The use of simultaneous stereo-electroencephalography and magnetoencephalography in localizing the epileptogenic focus in refractory focal epilepsy. Brain Commun 2021; 3:fcab072. [PMID: 33977268 PMCID: PMC8099997 DOI: 10.1093/braincomms/fcab072] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/27/2021] [Indexed: 11/12/2022] Open
Abstract
Both magnetoencephalography and stereo-electroencephalography are used in presurgical epilepsy assessment, with contrasting advantages and limitations. It is not known whether simultaneous stereo-electroencephalography-magnetoencephalography recording confers an advantage over both individual modalities, in particular whether magnetoencephalography can provide spatial context to epileptiform activity seen on stereo-electroencephalography. Twenty-four adult and paediatric patients who underwent stereo-electroencephalography study for pre-surgical evaluation of drug-resistant focal epilepsy, were recorded using simultaneous stereo-electroencephalography-magnetoencephalography, of which 14 had abnormal interictal activity during recording. The 14 patients were divided into two groups; those with detected superficial (n = 7) and deep (n = 7) brain interictal activity. Interictal spikes were independently identified in stereo-electroencephalography and magnetoencephalography. Magnetoencephalography dipoles were derived using a distributed inverse method. There was no significant difference between stereo-electroencephalography and magnetoencephalography in detecting superficial spikes (P = 0.135) and stereo-electroencephalography was significantly better at detecting deep spikes (P = 0.002). Mean distance across patients between stereo-electroencephalography channel with highest average spike amplitude and magnetoencephalography dipole was 20.7 ± 4.4 mm. for superficial sources, and 17.8 ± 3.7 mm. for deep sources, even though for some of the latter (n = 4) no magnetoencephalography spikes were detected and magnetoencephalography dipole was fitted to a stereo-electroencephalography interictal activity triggered average. Removal of magnetoencephalography dipole was associated with 1 year seizure freedom in 6/7 patients with superficial source, and 5/6 patients with deep source. Although stereo-electroencephalography has greater sensitivity in identifying interictal activity from deeper sources, a magnetoencephalography source can be localized using stereo-electroencephalography information, thereby providing useful whole brain context to stereo-electroencephalography and potential role in epilepsy surgery planning.
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Affiliation(s)
- Umesh Vivekananda
- Department of Clinical and Experimental Epilepsy, UCL, Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Chunyan Cao
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China.,Wellcome Centre for Human Neuroimaging, UCL, Queen Square, London WC1N 3AR, UK
| | - Wei Liu
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Jing Zhang
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Fergus Rugg-Gunn
- Department of Clinical and Experimental Epilepsy, UCL, Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Matthew C Walker
- Department of Clinical and Experimental Epilepsy, UCL, Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Vladimir Litvak
- Wellcome Centre for Human Neuroimaging, UCL, Queen Square, London WC1N 3AR, UK
| | - Bomin Sun
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
| | - Shikun Zhan
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai 200025, China
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Piastra MC, Nüßing A, Vorwerk J, Clerc M, Engwer C, Wolters CH. A comprehensive study on electroencephalography and magnetoencephalography sensitivity to cortical and subcortical sources. Hum Brain Mapp 2021; 42:978-992. [PMID: 33156569 PMCID: PMC7856654 DOI: 10.1002/hbm.25272] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Revised: 10/19/2020] [Accepted: 10/21/2020] [Indexed: 12/31/2022] Open
Abstract
Signal-to-noise ratio (SNR) maps are a good way to visualize electroencephalography (EEG) and magnetoencephalography (MEG) sensitivity. SNR maps extend the knowledge about the modulation of EEG and MEG signals by source locations and orientations and can therefore help to better understand and interpret measured signals as well as source reconstruction results thereof. Our work has two main objectives. First, we investigated the accuracy and reliability of EEG and MEG finite element method (FEM)-based sensitivity maps for three different head models, namely an isotropic three and four-compartment and an anisotropic six-compartment head model. As a result, we found that ignoring the cerebrospinal fluid leads to an overestimation of EEG SNR values. Second, we examined and compared EEG and MEG SNR mappings for both cortical and subcortical sources and their modulation by source location and orientation. Our results for cortical sources show that EEG sensitivity is higher for radial and deep sources and MEG for tangential ones, which are the majority of sources. As to the subcortical sources, we found that deep sources with sufficient tangential source orientation are recordable by the MEG. Our work, which represents the first comprehensive study where cortical and subcortical sources are considered in highly detailed FEM-based EEG and MEG SNR mappings, sheds a new light on the sensitivity of EEG and MEG and might influence the decision of brain researchers or clinicians in their choice of the best modality for their experiment or diagnostics, respectively.
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Affiliation(s)
- Maria Carla Piastra
- Institute for Biomagnetism and BiosignalanalysisUniversity of MünsterMünsterGermany
- Institute for Computational and Applied MathematicsUniversity of MünsterMünsterGermany
- Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical CenterNijmegenThe Netherlands
| | - Andreas Nüßing
- Institute for Biomagnetism and BiosignalanalysisUniversity of MünsterMünsterGermany
- Institute for Computational and Applied MathematicsUniversity of MünsterMünsterGermany
| | - Johannes Vorwerk
- Institute of Electrical and Biomedical Engineering, University for Health SciencesMedical Informatics and TechnologyHall in TirolAustria
| | - Maureen Clerc
- Inria Sophia Antipolis‐MediterranéeBiotFrance
- Université Côte d'AzurNiceFrance
| | - Christian Engwer
- Institute for Computational and Applied MathematicsUniversity of MünsterMünsterGermany
- Cluster of Excellence EXC 1003, Cells in Motion, CiM, University of MünsterMünsterGermany
| | - Carsten H. Wolters
- Institute for Biomagnetism and BiosignalanalysisUniversity of MünsterMünsterGermany
- Otto Creutzfeldt Center for Cognitive and Behavioral Neuroscience, University of MünsterMünsterGermany
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48
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Sometti D, Ballan C, Wang H, Braun C, Enck P. Effects of the antibiotic rifaximin on cortical functional connectivity are mediated through insular cortex. Sci Rep 2021; 11:4479. [PMID: 33627763 PMCID: PMC7904800 DOI: 10.1038/s41598-021-83994-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Accepted: 01/18/2021] [Indexed: 12/19/2022] Open
Abstract
It is well-known that antibiotics affect commensal gut bacteria; however, only recently evidence accumulated that gut microbiota (GM) can influence the central nervous system functions. Preclinical animal studies have repeatedly highlighted the effects of antibiotics on brain activity; however, translational studies in humans are still missing. Here, we present a randomized, double-blind, placebo-controlled study investigating the effects of 7 days intake of Rifaximin (non-absorbable antibiotic) on functional brain connectivity (fc) using magnetoencephalography. Sixteen healthy volunteers were tested before and after the treatment, during resting state (rs), and during a social stressor paradigm (Cyberball game—CBG), designed to elicit feelings of exclusion. Results confirm the hypothesis of an involvement of the insular cortex as a common node of different functional networks, thus suggesting its potential role as a central mediator of cortical fc alterations, following modifications of GM. Also, the Rifaximin group displayed lower connectivity in slow and fast beta bands (15 and 25 Hz) during rest, and higher connectivity in theta (7 Hz) during the inclusion condition of the CBG, compared with controls. Altogether these results indicate a modulation of Rifaximin on frequency-specific functional connectivity that could involve cognitive flexibility and memory processing.
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Affiliation(s)
- Davide Sometti
- MEG-Center, University of Tübingen, Tübingen, Germany. .,Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany. .,DiPSCo, Department of Psychology and Cognitive Science, University of Trento, Rovereto, Italy.
| | - Chiara Ballan
- MEG-Center, University of Tübingen, Tübingen, Germany.,DiPSCo, Department of Psychology and Cognitive Science, University of Trento, Rovereto, Italy
| | - Huiying Wang
- AAK, Department of Special Nutrition, AAK China Ltd, Shanghai, China
| | - Christoph Braun
- MEG-Center, University of Tübingen, Tübingen, Germany.,Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany.,DiPSCo, Department of Psychology and Cognitive Science, University of Trento, Rovereto, Italy.,CIMeC, Center for Mind/Brain Research, University of Trento, Trento, Italy
| | - Paul Enck
- Department of Internal Medicine VI, University Hospital, Tübingen, Germany
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49
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Kim JA, Davis KD. Magnetoencephalography: physics, techniques, and applications in the basic and clinical neurosciences. J Neurophysiol 2021; 125:938-956. [PMID: 33567968 DOI: 10.1152/jn.00530.2020] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Magnetoencephalography (MEG) is a technique used to measure the magnetic fields generated from neuronal activity in the brain. MEG has a high temporal resolution on the order of milliseconds and provides a more direct measure of brain activity when compared with hemodynamic-based neuroimaging methods such as magnetic resonance imaging and positron emission tomography. The current review focuses on basic features of MEG such as the instrumentation and the physics that are integral to the signals that can be measured, and the principles of source localization techniques, particularly the physics of beamforming and the techniques that are used to localize the signal of interest. In addition, we review several metrics that can be used to assess functional coupling in MEG and describe the advantages and disadvantages of each approach. Lastly, we discuss the current and future applications of MEG.
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Affiliation(s)
- Junseok A Kim
- Division of Brain, Imaging and Behaviour, Krembil Brain Institute, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Karen D Davis
- Division of Brain, Imaging and Behaviour, Krembil Brain Institute, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada.,Department of Surgery, University of Toronto, Toronto, Ontario, Canada
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50
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Bauer M, Buckley MG, Bast T. Individual differences in theta-band oscillations in a spatial memory network revealed by electroencephalography predict rapid place learning. Brain Neurosci Adv 2021; 5:23982128211002725. [PMID: 35174296 PMCID: PMC8842440 DOI: 10.1177/23982128211002725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Accepted: 02/24/2021] [Indexed: 11/30/2022] Open
Abstract
Spatial memory has been closely related to the medial temporal lobe and theta oscillations are thought to play a key role. However, it remains difficult to investigate medial temporal lobe activation related to spatial memory with non-invasive electrophysiological methods in humans. Here, we combined the virtual delayed-matching-to-place task, reverse-translated from the watermaze delayed-matching-to-place task in rats, with high-density electroencephalography recordings. Healthy young volunteers performed this computerised task in a virtual circular arena, which contained a hidden target whose location moved to a new place every four trials, allowing the assessment of rapid memory formation. Using behavioural measures as predictor variables for source reconstructed frequency-specific electroencephalography power, we found that inter-individual differences in ‘search preference’ during ‘probe trials’, a measure of one-trial place learning known from rodent studies to be particularly hippocampus-dependent, correlated predominantly with distinct theta-band oscillations (approximately 7 Hz), particularly in the right temporal lobe, the right striatum and inferior occipital cortex or cerebellum. This pattern was found during both encoding and retrieval/expression, but not in control analyses and could not be explained by motor confounds. Alpha-activity in sensorimotor and parietal cortex contralateral to the hand used for navigation also correlated (inversely) with search preference. This latter finding likely reflects movement-related factors associated with task performance, as well as a frequency difference in (ongoing) alpha-rhythm for high-performers versus low-performers that may contribute to these results indirectly. Relating inter-individual differences in ongoing brain activity to behaviour in a continuous rapid place-learning task that is suitable for a variety of populations, we could demonstrate that memory-related theta-band activity in temporal lobe can be measured with electroencephalography recordings. This approach holds great potential for further studies investigating the interactions within this network during encoding and retrieval, as well as neuromodulatory impacts and age-related changes.
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Affiliation(s)
- Markus Bauer
- School of Psychology and Neuroscience@Nottingham, University of Nottingham, Nottingham, UK
| | - Matthew G Buckley
- Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK
| | - Tobias Bast
- School of Psychology and Neuroscience@Nottingham, University of Nottingham, Nottingham, UK
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