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Erker TD, Arif Y, John JA, Embury CM, Kress KA, Springer SD, Okelberry HJ, McDonald KM, Picci G, Wiesman AI, Wilson TW. Neuromodulatory effects of parietal high-definition transcranial direct-current stimulation on network-level activity serving fluid intelligence. J Physiol 2024. [PMID: 38758592 DOI: 10.1113/jp286004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 04/26/2024] [Indexed: 05/18/2024] Open
Abstract
Fluid intelligence (Gf) involves rational thinking skills and requires the integration of information from different cortical regions to resolve novel complex problems. The effects of non-invasive brain stimulation on Gf have been studied in attempts to improve Gf, but such studies are rare and the few existing have reached conflicting conclusions. The parieto-frontal integration theory of intelligence (P-FIT) postulates that the parietal and frontal lobes play a critical role in Gf. To investigate the suggested role of parietal cortices, we applied high-definition transcranial direct current stimulation (HD-tDCS) to the left and right parietal cortices of 39 healthy adults (age 19-33 years) for 20 min in three separate sessions (left active, right active and sham). After completing the stimulation session, the participants completed a logical reasoning task based on Raven's Progressive Matrices during magnetoencephalography. Significant neural responses at the sensor level across all stimulation conditions were imaged using a beamformer. Whole-brain, spectrally constrained functional connectivity was then computed to examine the network-level activity. Behaviourally, we found that participants were significantly more accurate following left compared to right parietal stimulation. Regarding neural findings, we found significant HD-tDCS montage-related effects in brain networks thought to be critical for P-FIT, including parieto-occipital, fronto-occipital, fronto-parietal and occipito-cerebellar connectivity during task performance. In conclusion, our findings showed that left parietal stimulation improved abstract reasoning abilities relative to right parietal stimulation and support both P-FIT and the neural efficiency hypothesis. KEY POINTS: Abstract reasoning is a critical component of fluid intelligence and is known to be served by multispectral oscillatory activity in the fronto-parietal cortices. Recent studies have aimed to improve abstract reasoning abilities and fluid intelligence overall through behavioural training, but the results have been mixed. High-definition transcranial direct-current stimulation (HD-tDCS) applied to the parietal cortices modulated task performance and neural oscillations during abstract reasoning. Left parietal stimulation resulted in increased accuracy and decreased functional connectivity between occipital regions and frontal, parietal, and cerebellar regions. Future studies should investigate whether HD-tDCS alters abstract reasoning abilities in those who exhibit declines in performance, such as healthy ageing populations.
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Affiliation(s)
- Tara D Erker
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, Nebraska, USA
| | - Yasra Arif
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, Nebraska, USA
| | - Jason A John
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, Nebraska, USA
| | - Christine M Embury
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, Nebraska, USA
| | - Kennedy A Kress
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, Nebraska, USA
| | - Seth D Springer
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, Nebraska, USA
- College of Medicine, University of Nebraska Medical Center (UNMC), Omaha, Nebraska, USA
| | - Hannah J Okelberry
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, Nebraska, USA
| | - Kellen M McDonald
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, Nebraska, USA
- Department of Pharmacology & Neuroscience, Creighton University, Omaha, Nebraska, USA
| | - Giorgia Picci
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, Nebraska, USA
- Department of Pharmacology & Neuroscience, Creighton University, Omaha, Nebraska, USA
| | - Alex I Wiesman
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Tony W Wilson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, Nebraska, USA
- Department of Pharmacology & Neuroscience, Creighton University, Omaha, Nebraska, USA
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Noorizadeh N, Rezaie R, Varner JA, Wheless JW, Fulton SP, Mudigoudar BD, Nevill L, Holder CM, Narayana S. Concordance between Wada, Transcranial Magnetic Stimulation, and Magnetoencephalography for Determining Hemispheric Dominance for Language: A Retrospective Study. Brain Sci 2024; 14:336. [PMID: 38671988 PMCID: PMC11047819 DOI: 10.3390/brainsci14040336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Revised: 03/15/2024] [Accepted: 03/28/2024] [Indexed: 04/28/2024] Open
Abstract
Determination of language hemispheric dominance (HD) in patients undergoing evaluation for epilepsy surgery has traditionally relied on the sodium amobarbital (Wada) test. The emergence of non-invasive methods for determining language laterality has increasingly shown to be a viable alternative. In this study, we assessed the efficacy of transcranial magnetic stimulation (TMS) and magnetoencephalography (MEG), compared to the Wada test, in determining language HD in a sample of 12 patients. TMS-induced speech errors were classified as speech arrest, semantic, or performance errors, and the HD was based on the total number of errors in each hemisphere with equal weighting of all errors (classic) and with a higher weighting of speech arrests and semantic errors (weighted). Using MEG, HD for language was based on the spatial extent of long-latency activity sources localized to receptive language regions. Based on the classic and weighted language laterality index (LI) in 12 patients, TMS was concordant with the Wada in 58.33% and 66.67% of patients, respectively. In eight patients, MEG language mapping was deemed conclusive, with a concordance rate of 75% with the Wada test. Our results indicate that TMS and MEG have moderate and strong agreement, respectively, with the Wada test, suggesting they could be used as non-invasive substitutes.
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Affiliation(s)
- Negar Noorizadeh
- Division of Pediatric Neurology, Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN 38163, USA; (N.N.); (R.R.); (J.W.W.); (S.P.F.); (B.D.M.); (C.M.H.)
- Neuroscience Institute, Le Bonheur Children’s Hospital, Memphis, TN 38103, USA; (J.A.V.); (L.N.)
| | - Roozbeh Rezaie
- Division of Pediatric Neurology, Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN 38163, USA; (N.N.); (R.R.); (J.W.W.); (S.P.F.); (B.D.M.); (C.M.H.)
- Neuroscience Institute, Le Bonheur Children’s Hospital, Memphis, TN 38103, USA; (J.A.V.); (L.N.)
| | - Jackie A. Varner
- Neuroscience Institute, Le Bonheur Children’s Hospital, Memphis, TN 38103, USA; (J.A.V.); (L.N.)
| | - James W. Wheless
- Division of Pediatric Neurology, Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN 38163, USA; (N.N.); (R.R.); (J.W.W.); (S.P.F.); (B.D.M.); (C.M.H.)
- Neuroscience Institute, Le Bonheur Children’s Hospital, Memphis, TN 38103, USA; (J.A.V.); (L.N.)
| | - Stephen P. Fulton
- Division of Pediatric Neurology, Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN 38163, USA; (N.N.); (R.R.); (J.W.W.); (S.P.F.); (B.D.M.); (C.M.H.)
- Neuroscience Institute, Le Bonheur Children’s Hospital, Memphis, TN 38103, USA; (J.A.V.); (L.N.)
| | - Basanagoud D. Mudigoudar
- Division of Pediatric Neurology, Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN 38163, USA; (N.N.); (R.R.); (J.W.W.); (S.P.F.); (B.D.M.); (C.M.H.)
- Neuroscience Institute, Le Bonheur Children’s Hospital, Memphis, TN 38103, USA; (J.A.V.); (L.N.)
| | - Leigh Nevill
- Neuroscience Institute, Le Bonheur Children’s Hospital, Memphis, TN 38103, USA; (J.A.V.); (L.N.)
| | - Christen M. Holder
- Division of Pediatric Neurology, Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN 38163, USA; (N.N.); (R.R.); (J.W.W.); (S.P.F.); (B.D.M.); (C.M.H.)
- Neuroscience Institute, Le Bonheur Children’s Hospital, Memphis, TN 38103, USA; (J.A.V.); (L.N.)
| | - Shalini Narayana
- Division of Pediatric Neurology, Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN 38163, USA; (N.N.); (R.R.); (J.W.W.); (S.P.F.); (B.D.M.); (C.M.H.)
- Neuroscience Institute, Le Bonheur Children’s Hospital, Memphis, TN 38103, USA; (J.A.V.); (L.N.)
- Department of Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN 38163, USA
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Seijdel N, Schoffelen JM, Hagoort P, Drijvers L. Attention Drives Visual Processing and Audiovisual Integration During Multimodal Communication. J Neurosci 2024; 44:e0870232023. [PMID: 38199864 PMCID: PMC10919203 DOI: 10.1523/jneurosci.0870-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 12/20/2023] [Accepted: 12/21/2023] [Indexed: 01/12/2024] Open
Abstract
During communication in real-life settings, our brain often needs to integrate auditory and visual information and at the same time actively focus on the relevant sources of information, while ignoring interference from irrelevant events. The interaction between integration and attention processes remains poorly understood. Here, we use rapid invisible frequency tagging and magnetoencephalography to investigate how attention affects auditory and visual information processing and integration, during multimodal communication. We presented human participants (male and female) with videos of an actress uttering action verbs (auditory; tagged at 58 Hz) accompanied by two movie clips of hand gestures on both sides of fixation (attended stimulus tagged at 65 Hz; unattended stimulus tagged at 63 Hz). Integration difficulty was manipulated by a lower-order auditory factor (clear/degraded speech) and a higher-order visual semantic factor (matching/mismatching gesture). We observed an enhanced neural response to the attended visual information during degraded speech compared to clear speech. For the unattended information, the neural response to mismatching gestures was enhanced compared to matching gestures. Furthermore, signal power at the intermodulation frequencies of the frequency tags, indexing nonlinear signal interactions, was enhanced in the left frontotemporal and frontal regions. Focusing on the left inferior frontal gyrus, this enhancement was specific for the attended information, for those trials that benefitted from integration with a matching gesture. Together, our results suggest that attention modulates audiovisual processing and interaction, depending on the congruence and quality of the sensory input.
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Affiliation(s)
- Noor Seijdel
- Neurobiology of Language Department - The Communicative Brain, Max Planck Institute for Psycholinguistics, Nijmegen 6525 XD, The Netherlands
| | - Jan-Mathijs Schoffelen
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, 6525 HT, The Netherlands
| | - Peter Hagoort
- Neurobiology of Language Department - The Communicative Brain, Max Planck Institute for Psycholinguistics, Nijmegen 6525 XD, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, 6525 HT, The Netherlands
| | - Linda Drijvers
- Neurobiology of Language Department - The Communicative Brain, Max Planck Institute for Psycholinguistics, Nijmegen 6525 XD, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, 6525 HT, The Netherlands
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Santo-Angles A, Temudo A, Babushkin V, Sreenivasan KK. Effective connectivity of working memory performance: a DCM study of MEG data. Front Hum Neurosci 2024; 18:1339728. [PMID: 38501039 PMCID: PMC10944968 DOI: 10.3389/fnhum.2024.1339728] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 02/12/2024] [Indexed: 03/20/2024] Open
Abstract
Visual working memory (WM) engages several nodes of a large-scale network that includes frontal, parietal, and visual regions; however, little is understood about how these regions interact to support WM behavior. In particular, it is unclear whether network dynamics during WM maintenance primarily represent feedforward or feedback connections. This question has important implications for current debates about the relative roles of frontoparietal and visual regions in WM maintenance. In the current study, we investigated the network activity supporting WM using MEG data acquired while healthy subjects performed a multi-item delayed estimation WM task. We used computational modeling of behavior to discriminate correct responses (high accuracy trials) from two different types of incorrect responses (low accuracy and swap trials), and dynamic causal modeling of MEG data to measure effective connectivity. We observed behaviorally dependent changes in effective connectivity in a brain network comprising frontoparietal and early visual areas. In comparison with high accuracy trials, frontoparietal and frontooccipital networks showed disrupted signals depending on type of behavioral error. Low accuracy trials showed disrupted feedback signals during early portions of WM maintenance and disrupted feedforward signals during later portions of maintenance delay, while swap errors showed disrupted feedback signals during the whole delay period. These results support a distributed model of WM that emphasizes the role of visual regions in WM storage and where changes in large scale network configurations can have important consequences for memory-guided behavior.
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Affiliation(s)
- Aniol Santo-Angles
- Division of Science and Mathematics, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
- Center for Brain and Health, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Ainsley Temudo
- Division of Science and Mathematics, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Vahan Babushkin
- Division of Science and Mathematics, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Kartik K. Sreenivasan
- Division of Science and Mathematics, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
- Center for Brain and Health, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
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Askari P, Cardoso da Fonseca N, Pruitt T, Maldjian JA, Alick-Lindstrom S, Davenport EM. Magnetoencephalography (MEG) Data Processing in Epilepsy Patients with Implanted Responsive Neurostimulation (RNS) Devices. Brain Sci 2024; 14:173. [PMID: 38391747 PMCID: PMC10887328 DOI: 10.3390/brainsci14020173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 01/30/2024] [Accepted: 02/06/2024] [Indexed: 02/24/2024] Open
Abstract
Drug-resistant epilepsy (DRE) is often treated with surgery or neuromodulation. Specifically, responsive neurostimulation (RNS) is a widely used therapy that is programmed to detect abnormal brain activity and intervene with tailored stimulation. Despite the success of RNS, some patients require further interventions. However, having an RNS device in situ is a hindrance to the performance of neuroimaging techniques. Magnetoencephalography (MEG), a non-invasive neurophysiologic and functional imaging technique, aids epilepsy assessment and surgery planning. MEG performed post-RNS is complicated by signal distortions. This study proposes an independent component analysis (ICA)-based approach to enhance MEG signal quality, facilitating improved assessment for epilepsy patients with implanted RNS devices. Three epilepsy patients, two with RNS implants and one without, underwent MEG scans. Preprocessing included temporal signal space separation (tSSS) and an automated ICA-based approach with MNE-Python. Power spectral density (PSD) and signal-to-noise ratio (SNR) were analyzed, and MEG dipole analysis was conducted using single equivalent current dipole (SECD) modeling. The ICA-based noise removal preprocessing method substantially improved the signal-to-noise ratio (SNR) for MEG data from epilepsy patients with implanted RNS devices. Qualitative assessment confirmed enhanced signal readability and improved MEG dipole analysis. ICA-based processing markedly enhanced MEG data quality in RNS patients, emphasizing its clinical relevance.
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Affiliation(s)
- Pegah Askari
- Radiology Department, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- MEG Center of Excellence, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Biomedical Engineering Department, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Biomedical Engineering Department, The University of Texas at Arlington, Arlington, TX 76010, USA
| | - Natascha Cardoso da Fonseca
- Radiology Department, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- MEG Center of Excellence, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Tyrell Pruitt
- Radiology Department, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- MEG Center of Excellence, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Joseph A Maldjian
- Radiology Department, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- MEG Center of Excellence, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Biomedical Engineering Department, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Sasha Alick-Lindstrom
- Radiology Department, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- MEG Center of Excellence, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Neurology Department, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Elizabeth M Davenport
- Radiology Department, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- MEG Center of Excellence, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
- Biomedical Engineering Department, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
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Meltzer JA, Sivaratnam G, Deschamps T, Zadeh M, Li C, Farzan F, Francois-Nienaber A. Contrasting MEG effects of anodal and cathodal high-definition TDCS on sensorimotor activity during voluntary finger movements. Front Neuroimaging 2024; 3:1341732. [PMID: 38379832 PMCID: PMC10875011 DOI: 10.3389/fnimg.2024.1341732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 01/15/2024] [Indexed: 02/22/2024]
Abstract
Introduction Protocols for noninvasive brain stimulation (NIBS) are generally categorized as "excitatory" or "inhibitory" based on their ability to produce short-term modulation of motor-evoked potentials (MEPs) in peripheral muscles, when applied to motor cortex. Anodal and cathodal stimulation are widely considered excitatory and inhibitory, respectively, on this basis. However, it is poorly understood whether such polarity-dependent changes apply for neural signals generated during task performance, at rest, or in response to sensory stimulation. Methods To characterize such changes, we measured spontaneous and movement-related neural activity with magnetoencephalography (MEG) before and after high-definition transcranial direct-current stimulation (HD-TDCS) of the left motor cortex (M1), while participants performed simple finger movements with the left and right hands. Results Anodal HD-TDCS (excitatory) decreased the movement-related cortical fields (MRCF) localized to left M1 during contralateral right finger movements while cathodal HD-TDCS (inhibitory), increased them. In contrast, oscillatory signatures of voluntary motor output were not differentially affected by the two stimulation protocols, and tended to decrease in magnitude over the course of the experiment regardless. Spontaneous resting state oscillations were not affected either. Discussion MRCFs are thought to reflect reafferent proprioceptive input to motor cortex following movements. Thus, these results suggest that processing of incoming sensory information may be affected by TDCS in a polarity-dependent manner that is opposite that seen for MEPs-increases in cortical excitability as defined by MEPs may correspond to reduced responses to afferent input, and vice-versa.
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Affiliation(s)
- Jed A. Meltzer
- Rotman Research Institute, Baycrest Academy for Research and Education, Toronto, ON, Canada
- Departments of Psychology and Speech-language Pathology, University of Toronto, Toronto, ON, Canada
| | - Gayatri Sivaratnam
- Rotman Research Institute, Baycrest Academy for Research and Education, Toronto, ON, Canada
| | - Tiffany Deschamps
- Rotman Research Institute, Baycrest Academy for Research and Education, Toronto, ON, Canada
| | - Maryam Zadeh
- Rotman Research Institute, Baycrest Academy for Research and Education, Toronto, ON, Canada
| | - Catherine Li
- Rotman Research Institute, Baycrest Academy for Research and Education, Toronto, ON, Canada
| | - Faranak Farzan
- School of Mechatronic Systems Engineering, Simon Fraser University, Burnaby, BC, Canada
| | - Alex Francois-Nienaber
- Rotman Research Institute, Baycrest Academy for Research and Education, Toronto, ON, Canada
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Jourde HR, Merlo R, Brooks M, Rowe M, Coffey EBJ. The neurophysiology of closed-loop auditory stimulation in sleep: A magnetoencephalography study. Eur J Neurosci 2024; 59:613-640. [PMID: 37675803 DOI: 10.1111/ejn.16132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 08/01/2023] [Accepted: 08/08/2023] [Indexed: 09/08/2023]
Abstract
Closed-loop auditory stimulation (CLAS) is a brain modulation technique in which sounds are timed to enhance or disrupt endogenous neurophysiological events. CLAS of slow oscillation up-states in sleep is becoming a popular tool to study and enhance sleep's functions, as it increases slow oscillations, evokes sleep spindles and enhances memory consolidation of certain tasks. However, few studies have examined the specific neurophysiological mechanisms involved in CLAS, in part because of practical limitations to available tools. To evaluate evidence for possible models of how sound stimulation during brain up-states alters brain activity, we simultaneously recorded electro- and magnetoencephalography in human participants who received auditory stimulation across sleep stages. We conducted a series of analyses that test different models of pathways through which CLAS of slow oscillations may affect widespread neural activity that have been suggested in literature, using spatial information, timing and phase relationships in the source-localized magnetoencephalography data. The results suggest that auditory information reaches ventral frontal lobe areas via non-lemniscal pathways. From there, a slow oscillation is created and propagated. We demonstrate that while the state of excitability of tissue in auditory cortex and frontal ventral regions shows some synchrony with the electroencephalography (EEG)-recorded up-states that are commonly used for CLAS, it is the state of ventral frontal regions that is most critical for slow oscillation generation. Our findings advance models of how CLAS leads to enhancement of slow oscillations, sleep spindles and associated cognitive benefits and offer insight into how the effectiveness of brain stimulation techniques can be improved.
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Affiliation(s)
- Hugo R Jourde
- Concordia University, Montreal, Quebec, Canada
- International Laboratory for Brain, Music and Sound Research (BRAMS), Montreal, Quebec, Canada
- Centre for Research on Brain, Language and Music (CRBLM), Montreal, Quebec, Canada
- Quebec Bio-Imaging Network (QBIN), Sherbrooke, Quebec, Canada
| | | | - Mary Brooks
- Concordia University, Montreal, Quebec, Canada
- International Laboratory for Brain, Music and Sound Research (BRAMS), Montreal, Quebec, Canada
- Centre for Research on Brain, Language and Music (CRBLM), Montreal, Quebec, Canada
- Quebec Bio-Imaging Network (QBIN), Sherbrooke, Quebec, Canada
| | | | - Emily B J Coffey
- Concordia University, Montreal, Quebec, Canada
- International Laboratory for Brain, Music and Sound Research (BRAMS), Montreal, Quebec, Canada
- Centre for Research on Brain, Language and Music (CRBLM), Montreal, Quebec, Canada
- Quebec Bio-Imaging Network (QBIN), Sherbrooke, Quebec, Canada
- McGill University, Montreal, Quebec, Canada
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8
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Haraldsen IH, Hatlestad-Hall C, Marra C, Renvall H, Maestú F, Acosta-Hernández J, Alfonsin S, Andersson V, Anand A, Ayllón V, Babic A, Belhadi A, Birck C, Bruña R, Caraglia N, Carrarini C, Christensen E, Cicchetti A, Daugbjerg S, Di Bidino R, Diaz-Ponce A, Drews A, Giuffrè GM, Georges J, Gil-Gregorio P, Gove D, Govers TM, Hallock H, Hietanen M, Holmen L, Hotta J, Kaski S, Khadka R, Kinnunen AS, Koivisto AM, Kulashekhar S, Larsen D, Liljeström M, Lind PG, Marcos Dolado A, Marshall S, Merz S, Miraglia F, Montonen J, Mäntynen V, Øksengård AR, Olazarán J, Paajanen T, Peña JM, Peña L, Peniche DL, Perez AS, Radwan M, Ramírez-Toraño F, Rodríguez-Pedrero A, Saarinen T, Salas-Carrillo M, Salmelin R, Sousa S, Suyuthi A, Toft M, Toharia P, Tveitstøl T, Tveter M, Upreti R, Vermeulen RJ, Vecchio F, Yazidi A, Rossini PM. Intelligent digital tools for screening of brain connectivity and dementia risk estimation in people affected by mild cognitive impairment: the AI-Mind clinical study protocol. Front Neurorobot 2024; 17:1289406. [PMID: 38250599 PMCID: PMC10796757 DOI: 10.3389/fnbot.2023.1289406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 12/12/2023] [Indexed: 01/23/2024] Open
Abstract
More than 10 million Europeans show signs of mild cognitive impairment (MCI), a transitional stage between normal brain aging and dementia stage memory disorder. The path MCI takes can be divergent; while some maintain stability or even revert to cognitive norms, alarmingly, up to half of the cases progress to dementia within 5 years. Current diagnostic practice lacks the necessary screening tools to identify those at risk of progression. The European patient experience often involves a long journey from the initial signs of MCI to the eventual diagnosis of dementia. The trajectory is far from ideal. Here, we introduce the AI-Mind project, a pioneering initiative with an innovative approach to early risk assessment through the implementation of advanced artificial intelligence (AI) on multimodal data. The cutting-edge AI-based tools developed in the project aim not only to accelerate the diagnostic process but also to deliver highly accurate predictions regarding an individual's risk of developing dementia when prevention and intervention may still be possible. AI-Mind is a European Research and Innovation Action (RIA H2020-SC1-BHC-06-2020, No. 964220) financed between 2021 and 2026. First, the AI-Mind Connector identifies dysfunctional brain networks based on high-density magneto- and electroencephalography (M/EEG) recordings. Second, the AI-Mind Predictor predicts dementia risk using data from the Connector, enriched with computerized cognitive tests, genetic and protein biomarkers, as well as sociodemographic and clinical variables. AI-Mind is integrated within a network of major European initiatives, including The Virtual Brain, The Virtual Epileptic Patient, and EBRAINS AISBL service for sensitive data, HealthDataCloud, where big patient data are generated for advancing digital and virtual twin technology development. AI-Mind's innovation lies not only in its early prediction of dementia risk, but it also enables a virtual laboratory scenario for hypothesis-driven personalized intervention research. This article introduces the background of the AI-Mind project and its clinical study protocol, setting the stage for future scientific contributions.
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Affiliation(s)
| | | | - Camillo Marra
- Memory Clinic, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
- Department of Neuroscience, Catholic University of the Sacred Heart, Rome, Italy
| | - Hanna Renvall
- Department of Neuroscience and Biomedical Engineering, Aalto University, Helsinki, Finland
- BioMag Laboratory, HUS Medical Imaging Centre, Helsinki University Hospital, Helsinki University and Aalto University School of Science, Helsinki, Finland
| | - Fernando Maestú
- Centre for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Department of Experimental Psychology, Cognitive Psychology and Speech and Language Therapy, Universidad Complutense de Madrid, Pozuelo de Alarcón, Spain
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
| | | | - Soraya Alfonsin
- Centre for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Department of Experimental Psychology, Cognitive Psychology and Speech and Language Therapy, Universidad Complutense de Madrid, Pozuelo de Alarcón, Spain
| | | | - Abhilash Anand
- Performance and Assurance Solutions, Digital Solutions, DNV, Oslo, Norway
| | | | - Aleksandar Babic
- Healthcare Programme, Group Research and Development, DNV, Oslo, Norway
| | - Asma Belhadi
- Department of Computer Science, OsloMet—Oslo Metropolitan University, Oslo, Norway
- NordSTAR—Nordic Center for Sustainable and Trustworthy AI Research, Oslo, Norway
| | | | - Ricardo Bruña
- Centre for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
- Department of Radiology, Universidad Complutense de Madrid, Madrid, Spain
| | - Naike Caraglia
- Memory Clinic, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Claudia Carrarini
- Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele, Rome, Italy
| | | | - Americo Cicchetti
- The Graduate School of Health Economics and Management (ALTEMS), Catholic University of the Sacred Heart, Rome, Italy
| | - Signe Daugbjerg
- The Graduate School of Health Economics and Management (ALTEMS), Catholic University of the Sacred Heart, Rome, Italy
| | - Rossella Di Bidino
- The Graduate School of Health Economics and Management (ALTEMS), Catholic University of the Sacred Heart, Rome, Italy
| | | | - Ainar Drews
- IT Department, University of Oslo, Oslo, Norway
| | - Guido Maria Giuffrè
- Memory Clinic, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
- Department of Neuroscience, Catholic University of the Sacred Heart, Rome, Italy
| | | | - Pedro Gil-Gregorio
- Department of Geriatric Medicine, Hospital Universitario Clínico San Carlos, Madrid, Spain
- Department of Geriatrics, Fundación para la Investigación Biomédica del Hospital Clínico San Carlos, Madrid, Spain
| | | | - Tim M. Govers
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, Netherlands
| | - Harry Hallock
- Healthcare Programme, Group Research and Development, DNV, Oslo, Norway
| | - Marja Hietanen
- Division of Neuropsychology, HUS Neurocenter, Helsinki University Hospital and Helsinki University, Helsinki, Finland
| | - Lone Holmen
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Jaakko Hotta
- Department of Neurology, Helsinki University Hospital and Clinical Neurosciences, Neurology, University of Helsinki, Helsinki, Finland
| | - Samuel Kaski
- Department of Computer Science, Helsinki Institute of Information Technology, Aalto University, Helsinki, Finland
- Department of Computer Science, University of Manchester, Manchester, United Kingdom
| | - Rabindra Khadka
- Department of Computer Science, OsloMet—Oslo Metropolitan University, Oslo, Norway
- NordSTAR—Nordic Center for Sustainable and Trustworthy AI Research, Oslo, Norway
| | - Antti S. Kinnunen
- BioMag Laboratory, HUS Medical Imaging Centre, Helsinki University Hospital, Helsinki University and Aalto University School of Science, Helsinki, Finland
| | - Anne M. Koivisto
- Department of Neurology, Helsinki University Hospital and Clinical Neurosciences, Neurology, University of Helsinki, Helsinki, Finland
- Department of Neurosciences, University of Helsinki, Helsinki, Finland
- Neurocenter, Neurology, Kuopio University Hospital, Kuopio, Finland
| | - Shrikanth Kulashekhar
- BioMag Laboratory, HUS Medical Imaging Centre, Helsinki University Hospital, Helsinki University and Aalto University School of Science, Helsinki, Finland
| | - Denis Larsen
- Department of Computer Science, OsloMet—Oslo Metropolitan University, Oslo, Norway
- NordSTAR—Nordic Center for Sustainable and Trustworthy AI Research, Oslo, Norway
| | - Mia Liljeström
- Department of Neuroscience and Biomedical Engineering, Aalto University, Helsinki, Finland
- BioMag Laboratory, HUS Medical Imaging Centre, Helsinki University Hospital, Helsinki University and Aalto University School of Science, Helsinki, Finland
| | - Pedro G. Lind
- Department of Computer Science, OsloMet—Oslo Metropolitan University, Oslo, Norway
- NordSTAR—Nordic Center for Sustainable and Trustworthy AI Research, Oslo, Norway
| | - Alberto Marcos Dolado
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
- Neurology Department, Hospital Universitario Clínico San Carlos, Madrid, Spain
| | - Serena Marshall
- Healthcare Programme, Group Research and Development, DNV, Oslo, Norway
| | - Susanne Merz
- Department of Neuroscience and Biomedical Engineering, Aalto University, Helsinki, Finland
| | - Francesca Miraglia
- Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele, Rome, Italy
| | - Juha Montonen
- BioMag Laboratory, HUS Medical Imaging Centre, Helsinki University Hospital, Helsinki University and Aalto University School of Science, Helsinki, Finland
| | - Ville Mäntynen
- BioMag Laboratory, HUS Medical Imaging Centre, Helsinki University Hospital, Helsinki University and Aalto University School of Science, Helsinki, Finland
| | | | - Javier Olazarán
- Neurology Service, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Teemu Paajanen
- Finnish Institute of Occupational Health, Helsinki, Finland
| | | | | | | | - Ana S. Perez
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Mohamed Radwan
- Department of Computer Science, OsloMet—Oslo Metropolitan University, Oslo, Norway
- NordSTAR—Nordic Center for Sustainable and Trustworthy AI Research, Oslo, Norway
| | - Federico Ramírez-Toraño
- Centre for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Department of Experimental Psychology, Cognitive Psychology and Speech and Language Therapy, Universidad Complutense de Madrid, Pozuelo de Alarcón, Spain
| | - Andrea Rodríguez-Pedrero
- Centre for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain
- Department of Experimental Psychology, Cognitive Psychology and Speech and Language Therapy, Universidad Complutense de Madrid, Pozuelo de Alarcón, Spain
| | - Timo Saarinen
- BioMag Laboratory, HUS Medical Imaging Centre, Helsinki University Hospital, Helsinki University and Aalto University School of Science, Helsinki, Finland
| | - Mario Salas-Carrillo
- Institute of Sanitary Investigation (IdISSC), San Carlos University Hospital, Madrid, Spain
- Memory Unit, Department of Geriatrics, Hospital Clínico San Carlos, Madrid, Spain
| | - Riitta Salmelin
- Department of Neuroscience and Biomedical Engineering, Aalto University, Helsinki, Finland
| | - Sonia Sousa
- School of Digital Technologies, Tallinn University, Tallinn, Estonia
| | - Abdillah Suyuthi
- Performance and Assurance Solutions, Digital Solutions, DNV, Oslo, Norway
| | - Mathias Toft
- Department of Neurology, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Pablo Toharia
- Center for Computational Simulation, Universidad Politécnica de Madrid, Madrid, Spain
| | | | - Mats Tveter
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Ramesh Upreti
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Robin J. Vermeulen
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, Netherlands
| | - Fabrizio Vecchio
- Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele, Rome, Italy
- Department of Theoretical and Applied Sciences, eCampus University, Como, Italy
| | - Anis Yazidi
- Department of Computer Science, OsloMet—Oslo Metropolitan University, Oslo, Norway
- NordSTAR—Nordic Center for Sustainable and Trustworthy AI Research, Oslo, Norway
| | - Paolo Maria Rossini
- Department of Neuroscience and Neurorehabilitation, IRCCS San Raffaele, Rome, Italy
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Nakanishi S, Tamura S, Hirano S, Takahashi J, Kitajima K, Takai Y, Mitsudo T, Togao O, Nakao T, Onitsuka T, Hirano Y. Abnormal phase entrainment of low- and high-gamma-band auditory steady-state responses in schizophrenia. Front Neurosci 2023; 17:1277733. [PMID: 37942136 PMCID: PMC10627971 DOI: 10.3389/fnins.2023.1277733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 10/09/2023] [Indexed: 11/10/2023] Open
Abstract
Introduction Gamma-band oscillatory deficits have attracted considerable attention as promising biomarkers of schizophrenia (SZ). Notably, a reduced auditory steady-state response (ASSR) in the low gamma band (40 Hz) is widely recognized as a robust finding among SZ patients. However, a comprehensive investigation into the potential utility of the high-gamma-band ASSR in detecting altered neural oscillations in SZ has not yet been conducted. Methods The present study aimed to assess the ASSR using magnetoencephalography (MEG) data obtained during steady-state stimuli at frequencies of 20, 30, 40, and 80 Hz from 23 SZ patients and 21 healthy controls (HCs). To evaluate the ASSR, we examined the evoked power and phase-locking factor (PLF) in the time-frequency domain for both the primary and secondary auditory cortices. Furthermore, we calculated the phase-locking angle (PLA) to examine oscillatory phase lead or delay in SZ patients. Taking advantage of the high spatial resolution of MEG, we also focused on the hemispheric laterality of low- and high-gamma-band ASSR deficits in SZ. Results We found abnormal phase delay in the 40 Hz ASSR within the bilateral auditory cortex of SZ patients. Regarding the 80 Hz ASSR, our investigation identified an aberrant phase lead in the left secondary auditory cortex in SZ, accompanied by reduced evoked power in both auditory cortices. Discussion Given that abnormal phase lead on 80 Hz ASSR exhibited the highest discriminative power between HC and SZ, we propose that the examination of PLA in the 80 Hz ASSR holds significant promise as a robust candidate for identifying neurophysiological endophenotypes associated with SZ. Furthermore, the left-hemisphere phase lead observed in the deficits of 80 Hz PLA aligns with numerous prior studies, which have consistently proposed that SZ is characterized by left-lateralized brain dysfunctions.
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Affiliation(s)
- Shoichiro Nakanishi
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Shunsuke Tamura
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
- Department of Psychiatry, Division of Clinical Neuroscience, Faculty of Medicine, University of Miyazaki, Miyazaki, Japan
| | - Shogo Hirano
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Junichi Takahashi
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Kazutoshi Kitajima
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Yoshifumi Takai
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Takako Mitsudo
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Osamu Togao
- Department of Molecular Imaging and Diagnosis, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Tomohiro Nakao
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Toshiaki Onitsuka
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
- National Hospital Organization Sakakibara Hospital, Mie, Japan
| | - Yoji Hirano
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
- Department of Psychiatry, Division of Clinical Neuroscience, Faculty of Medicine, University of Miyazaki, Miyazaki, Japan
- Institute of Industrial Science, The University of Tokyo, Tokyo, Japan
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10
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Okazaki M, Yumoto M, Kaneko Y, Maruo K. Correlation of motor-auditory cross-modal and auditory unimodal N1 and mismatch responses of schizophrenic patients and normal subjects: an MEG study. Front Psychiatry 2023; 14:1217307. [PMID: 37886112 PMCID: PMC10598755 DOI: 10.3389/fpsyt.2023.1217307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 09/25/2023] [Indexed: 10/28/2023] Open
Abstract
Introduction It has been suggested that the positive symptoms of schizophrenic patients (hallucinations, delusions, and passivity experience) are caused by dysfunction of their internal and external sensory prediction errors. This is often discussed as related to dysfunction of the forward model that executes self-monitoring. Several reports have suggested that dysfunction of the forward model in schizophrenia causes misattributions of self-generated thoughts and actions to external sources. There is some evidence that the forward model can be measured using the electroencephalography (EEG) and magnetoencephalography (MEG) components such as N1 (m) and mismatch negativity (MMN) (m). The objective in this MEG study is to investigate differences in the N1m and MMNm-like activity generated in motor-auditory cross-modal tasks in normal control (NC) subjects and schizophrenic (SC) patients, and compared that activity with N1m and MMNm in the auditory unimodal task. Methods The N1m and MMNm/MMNm-like activity were recorded in 15 SC patients and 12 matched NC subjects. The N1m-attenuation effects and peak amplitude of MMNm/MMNm-like activity of the NC and SC groups were compared. Additionally, correlations between MEG measures (N1m suppression rate, MMNm, and MMNm-like activity) and clinical variables (Positive and Negative Syndrome Scale (PANSS) scores and antipsychotic drug (APD) dosages) in SC patients were investigated. Results It was found that (i) there was no significant difference in N1m-attenuation for the NC and SC groups, and that (ii) MMNm in the unimodal task in the SC group was significantly smaller than that in the NC group. Further, the MMNm-like activity in the cross-modal task was smaller than that of the MMNm in the unimodal task in the NC group, but there was no significant difference in the SC group. The PANSS positive symptoms and general psychopathology score were moderately negatively correlated with the amplitudes of the MMNm-like activity, and the APD dosage was moderately negatively correlated with the N1m suppression rate. However, none of these correlations reached statistical significance. Discussion The findings suggest that schizophrenic patients perform altered predictive processes differently from healthy subjects in latencies reflecting MMNm, depending on whether they are under forward model generation or not. This may support the hypothesis that schizophrenic patients tend to misattribute their inner experience to external agents, thus leading to the characteristic schizophrenia symptoms.
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Affiliation(s)
- Mitsutoshi Okazaki
- Department of Psychiatry, National Center Hospital of Neurology and Psychiatry, Kodaira, Japan
- Department of Psychiatry, Ome Municipal General Hospital, Ome, Japan
| | - Masato Yumoto
- Department of Clinical Engineering, Faculty of Medical Science and Technology, Gunma Paz University, Takasaki, Japan
| | - Yuu Kaneko
- Department of Neurosurgery, National Center Hospital of Neurology and Psychiatry, Kodaira, Japan
| | - Kazushi Maruo
- Department of Biostatistics, Faculty of Medicine, University of Tsukuba, Tsukuba, Japan
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Onishi H, Yokosawa K. Differential working memory function between phonological and visuospatial strategies: a magnetoencephalography study using a same visual task. Front Hum Neurosci 2023; 17:1218437. [PMID: 37680265 PMCID: PMC10480614 DOI: 10.3389/fnhum.2023.1218437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Accepted: 08/08/2023] [Indexed: 09/09/2023] Open
Abstract
Previous studies have reported that, in working memory, the processing of visuospatial information and phonological information have different neural bases. However, in these studies, memory items were presented via different modalities. Therefore, the modality in which the memory items were presented and the strategy for memorizing them were not rigorously distinguished. In the present study, we explored the neural basis of two working memory strategies. Nineteen right-handed young adults memorized seven sequential directions presented visually in a task in which the memory strategy was either visuospatial or phonological (visuospatial/phonological condition). Source amplitudes of theta-band (5-7 Hz) rhythm were estimated from magnetoencephalography during the maintenance period and further analyzed using cluster-based permutation tests. Behavioral results revealed that the accuracy rates showed no significant differences between conditions, while the reaction time in the phonological condition was significantly longer than that in the visuospatial condition. Theta activity in the phonological condition was significantly greater than that in the visuospatial condition, and the cluster in spatio-temporal matrix with p < 5% difference extended to right prefrontal regions in the early maintenance period and right occipito-parietal regions in the late maintenance period. The theta activity results did not indicate strategy-specific neural bases but did reveal the dynamics of executive function required for phonological processing. The functions seemed to move from attention control and inhibition control in the prefrontal region to inhibition of irrelevant information in the occipito-parietal region.
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Affiliation(s)
- Hayate Onishi
- Graduate School of Health Sciences, Hokkaido University, Sapporo, Japan
| | - Koichi Yokosawa
- Faculty of Health Sciences, Hokkaido University, Sapporo, Japan
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12
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O'Reilly JA, Zhu JD, Sowman PF. Localized estimation of electromagnetic sources underlying event-related fields using recurrent neural networks. J Neural Eng 2023; 20:046035. [PMID: 37567215 DOI: 10.1088/1741-2552/acef94] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 08/10/2023] [Indexed: 08/13/2023]
Abstract
Objective. To use a recurrent neural network (RNN) to reconstruct neural activity responsible for generating noninvasively measured electromagnetic signals.Approach. Output weights of an RNN were fixed as the lead field matrix from volumetric source space computed using the boundary element method with co-registered structural magnetic resonance images and magnetoencephalography (MEG). Initially, the network was trained to minimise mean-squared-error loss between its outputs and MEG signals, causing activations in the penultimate layer to converge towards putative neural source activations. Subsequently, L1 regularisation was applied to the final hidden layer, and the model was fine-tuned, causing it to favour more focused activations. Estimated source signals were then obtained from the outputs of the last hidden layer. We developed and validated this approach with simulations before applying it to real MEG data, comparing performance with beamformers, minimum-norm estimate, and mixed-norm estimate source reconstruction methods.Main results. The proposed RNN method had higher output signal-to-noise ratios and comparable correlation and error between estimated and simulated sources. Reconstructed MEG signals were also equal or superior to the other methods regarding their similarity to ground-truth. When applied to MEG data recorded during an auditory roving oddball experiment, source signals estimated with the RNN were generally biophysically plausible and consistent with expectations from the literature.Significance. This work builds on recent developments of RNNs for modelling event-related neural responses by incorporating biophysical constraints from the forward model, thus taking a significant step towards greater biological realism and introducing the possibility of exploring how input manipulations may influence localised neural activity.
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Affiliation(s)
- Jamie A O'Reilly
- School of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok 10520, Thailand
| | - Judy D Zhu
- School of Psychological Sciences, Macquarie University, Sydney, New South Wales 2109, Australia
| | - Paul F Sowman
- School of Psychological Sciences, Macquarie University, Sydney, New South Wales 2109, Australia
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Vidaurre C, Gurunandan K, Idaji MJ, Nolte G, Gómez M, Villringer A, Müller KR, Nikulin VV. Novel multivariate methods to track frequency shifts of neural oscillations in EEG/MEG recordings. Neuroimage 2023; 276:120178. [PMID: 37236554 DOI: 10.1016/j.neuroimage.2023.120178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 03/09/2023] [Accepted: 05/17/2023] [Indexed: 05/28/2023] Open
Abstract
Instantaneous and peak frequency changes in neural oscillations have been linked to many perceptual, motor, and cognitive processes. Yet, the majority of such studies have been performed in sensor space and only occasionally in source space. Furthermore, both terms have been used interchangeably in the literature, although they do not reflect the same aspect of neural oscillations. In this paper, we discuss the relation between instantaneous frequency, peak frequency, and local frequency, the latter also known as spectral centroid. Furthermore, we propose and validate three different methods to extract source signals from multichannel data whose (instantaneous, local, or peak) frequency estimate is maximally correlated to an experimental variable of interest. Results show that the local frequency might be a better estimate of frequency variability than instantaneous frequency under conditions with low signal-to-noise ratio. Additionally, the source separation methods based on local and peak frequency estimates, called LFD and PFD respectively, provide more stable estimates than the decomposition based on instantaneous frequency. In particular, LFD and PFD are able to recover the sources of interest in simulations performed with a realistic head model, providing higher correlations with an experimental variable than multiple linear regression. Finally, we also tested all decomposition methods on real EEG data from a steady-state visual evoked potential paradigm and show that the recovered sources are located in areas similar to those previously reported in other studies, thus providing further validation of the proposed methods.
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Affiliation(s)
- C Vidaurre
- Ikerbasque, Basque Foundation for Science, Plaza Euskadi 5, 48009 Bilbao, Spain; Tecnalia Research and Innovation, Neuroengineering Group, Health Unit, Donostia, Spain; Dept. of Statistics, Computer Science and Mathematics, Public University of Navarre, Pamplona, Spain.
| | - K Gurunandan
- MRC Cognition and Brain Sciences Unit, University of Cambridge, UK; BCBL. Basque Center on Cognition, Brain and Language, Donostia-San Sebastián, Spain
| | - M Jamshidi Idaji
- Machine Learning Group, Technische Universität Berlin, 10587 Berlin, Germany; BIFOLD-Berlin Institute for the Foundations of Learning and Data, Germany; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - G Nolte
- Dept. of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - M Gómez
- Dept. of Statistics, Computer Science and Mathematics, Public University of Navarre, Pamplona, Spain
| | - A Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - K-R Müller
- Machine Learning Group, Technische Universität Berlin, 10587 Berlin, Germany; BIFOLD-Berlin Institute for the Foundations of Learning and Data, Germany; Department of Artificial Intelligence, Korea University, Anam-dong, Seongbuk-gu, Seoul 02841, South Korea; Max Planck Institute for Informatics, Stuhlsatzenhausweg, 66123 Saarbrücken, Germany
| | - V V Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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14
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Boerger TF, Pahapill P, Butts AM, Arocho-Quinones E, Raghavan M, Krucoff MO. Large-scale brain networks and intra-axial tumor surgery: a narrative review of functional mapping techniques, critical needs, and scientific opportunities. Front Hum Neurosci 2023; 17:1170419. [PMID: 37520929 PMCID: PMC10372448 DOI: 10.3389/fnhum.2023.1170419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 05/16/2023] [Indexed: 08/01/2023] Open
Abstract
In recent years, a paradigm shift in neuroscience has been occurring from "localizationism," or the idea that the brain is organized into separately functioning modules, toward "connectomics," or the idea that interconnected nodes form networks as the underlying substrates of behavior and thought. Accordingly, our understanding of mechanisms of neurological function, dysfunction, and recovery has evolved to include connections, disconnections, and reconnections. Brain tumors provide a unique opportunity to probe large-scale neural networks with focal and sometimes reversible lesions, allowing neuroscientists the unique opportunity to directly test newly formed hypotheses about underlying brain structural-functional relationships and network properties. Moreover, if a more complete model of neurological dysfunction is to be defined as a "disconnectome," potential avenues for recovery might be mapped through a "reconnectome." Such insight may open the door to novel therapeutic approaches where previous attempts have failed. In this review, we briefly delve into the most clinically relevant neural networks and brain mapping techniques, and we examine how they are being applied to modern neurosurgical brain tumor practices. We then explore how brain tumors might teach us more about mechanisms of global brain dysfunction and recovery through pre- and postoperative longitudinal connectomic and behavioral analyses.
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Affiliation(s)
- Timothy F. Boerger
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Peter Pahapill
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Alissa M. Butts
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States
- Mayo Clinic, Rochester, MN, United States
| | - Elsa Arocho-Quinones
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Manoj Raghavan
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Max O. Krucoff
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States
- Department of Biomedical Engineering, Medical College of Wisconsin, Marquette University, Milwaukee, WI, United States
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15
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Jann K, Ishii R, Takahashi S, Ikeda S. Editorial: Neuromodulation in basic, translational and clinical research in psychiatry, volume II. Front Hum Neurosci 2023; 17:1212625. [PMID: 37275342 PMCID: PMC10237012 DOI: 10.3389/fnhum.2023.1212625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 05/03/2023] [Indexed: 06/07/2023] Open
Affiliation(s)
- Kay Jann
- USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, United States
| | - Ryouhei Ishii
- Department of Occupational Therapy, Graduate School of Rehabilitation Science, Osaka Metropolitan University, Habikino, Japan
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Japan
| | - Shun Takahashi
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Suita, Japan
| | - Sunichiro Ikeda
- Department of Neuropsychiatry, Kansai Medical University, Osaka, Japan
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16
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Hecker L, Tebartz van Elst L, Kornmeier J. Source localization using recursively applied and projected MUSIC with flexible extent estimation. Front Neurosci 2023; 17:1170862. [PMID: 37255753 PMCID: PMC10225686 DOI: 10.3389/fnins.2023.1170862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 04/17/2023] [Indexed: 06/01/2023] Open
Abstract
Magneto- and electroencephalography (M/EEG) are widespread techniques to measure neural activity in-vivo at a high temporal resolution but low spatial resolution. Locating the neural sources underlying the M/EEG poses an inverse problem, which is ill-posed. We developed a new method based on Recursive Application of Multiple Signal Classification (MUSIC). Our proposed method is able to recover not only the locations but, in contrast to other inverse solutions, also the extent of active brain regions flexibly (FLEX-MUSIC). This is achieved by allowing it to search not only for single dipoles but also dipole clusters of increasing extent to find the best fit during each recursion. FLEX-MUSIC achieved the highest accuracy for both single dipole and extended sources compared to all other methods tested. Remarkably, FLEX-MUSIC was capable to accurately estimate the level of sparsity in the source space (r = 0.82), whereas all other approaches tested failed to do so (r ≤ 0.18). The average computation time of FLEX-MUSIC was considerably lower compared to a popular Bayesian approach and comparable to that of another recursive MUSIC approach and eLORETA. FLEX-MUSIC produces only few errors and was capable to reliably estimate the extent of sources. The accuracy and low computation time of FLEX-MUSIC renders it an improved technique to solve M/EEG inverse problems both in neuroscience research and potentially in pre-surgery diagnostic in epilepsy.
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Affiliation(s)
- Lukas Hecker
- Department of Psychiatry and Psychotherapy, University of Freiburg Medical Center, Freiburg, Germany
- Department of Psychosomatic Medicine and Psychotherapy, University of Freiburg Medical Center, Freiburg, Germany
- Perception and Cognition Lab, Institute for Frontier Areas of Psychology and Mental Health, Freiburg, Germany
- Faculty of Biology, University of Freiburg, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Ludger Tebartz van Elst
- Department of Psychiatry and Psychotherapy, University of Freiburg Medical Center, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Jürgen Kornmeier
- Department of Psychiatry and Psychotherapy, University of Freiburg Medical Center, Freiburg, Germany
- Perception and Cognition Lab, Institute for Frontier Areas of Psychology and Mental Health, Freiburg, Germany
- Faculty of Biology, University of Freiburg, Freiburg, Germany
- Faculty of Medicine, University of Freiburg, Freiburg, Germany
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Moharramipour A, Takahashi T, Kitazawa S. Distinctive modes of cortical communications in tactile temporal order judgment. Cereb Cortex 2023; 33:2982-2996. [PMID: 35811300 DOI: 10.1093/cercor/bhac255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2022] [Revised: 06/03/2022] [Accepted: 06/04/2022] [Indexed: 11/12/2022] Open
Abstract
Temporal order judgment of two successive tactile stimuli delivered to our hands is often inverted when we cross our hands. The present study aimed to identify time-frequency profiles of the interactions across the cortical network associated with the crossed-hand tactile temporal order judgment task using magnetoencephalography. We found that the interactions across the cortical network were channeled to a low-frequency band (5-10 Hz) when the hands were uncrossed. However, the interactions became activated in a higher band (12-18 Hz) when the hands were crossed. The participants with fewer inverted judgments relied mainly on the higher band, whereas those with more frequent inverted judgments (reversers) utilized both. Moreover, reversers showed greater cortical interactions in the higher band when their judgment was correct compared to when it was inverted. Overall, the results show that the cortical network communicates in two distinctive frequency modes during the crossed-hand tactile temporal order judgment task. A default mode of communications in the low-frequency band encourages inverted judgments, and correct judgment is robustly achieved by recruiting the high-frequency mode.
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Affiliation(s)
- Ali Moharramipour
- Dynamic Brain Network Laboratory, Graduate School of Frontier Biosciences, Osaka University, 1-3 Yamadaoka, Suita, Osaka 565-0871, Japan
- Laboratory for Consciousness, Center for Brain Science (CBS), RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0106, Japan
| | - Toshimitsu Takahashi
- Department of Physiology, Dokkyo Medical University, 880 Kitakobayashi, Mibu, Shimotsuga, Tochigi 321-0293, Japan
| | - Shigeru Kitazawa
- Dynamic Brain Network Laboratory, Graduate School of Frontier Biosciences, Osaka University, 1-3 Yamadaoka, Suita, Osaka 565-0871, Japan
- Department of Brain Physiology, Graduate School of Medicine, Osaka University, 1-3 Yamakaoka, Suita, Osaka 565-0871, Japan
- Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology, 1-4 Yamadaoka, Suita, Osaka 565-0871, Japan
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18
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Torres-Simon L, Cuesta P, del Cerro-Leon A, Chino B, Orozco LH, Marsh EB, Gil P, Maestu F. The effects of white matter hyperintensities on MEG power spectra in population with mild cognitive impairment. Front Hum Neurosci 2023; 17:1068216. [PMID: 36875239 PMCID: PMC9977191 DOI: 10.3389/fnhum.2023.1068216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 01/23/2023] [Indexed: 02/17/2023] Open
Abstract
Cerebrovascular disease is responsible for up to 20% of cases of dementia worldwide, but also it is a major comorbid contributor to the progression of other neurodegenerative diseases, like Alzheimer's disease. White matter hyperintensities (WMH) are the most prevalent imaging marker in cerebrovascular disease. The presence and progression of WMH in the brain have been associated with general cognitive impairment and the risk to develop all types of dementia. The aim of this piece of work is the assessment of brain functional differences in an MCI population based on the WMH volume. One-hundred and twenty-nine individuals with mild cognitive impairment (MCI) underwent a neuropsychological evaluation, MRI assessment (T1 and Flair), and MEG recordings (5 min of eyes closed resting state). Those participants were further classified into vascular MCI (vMCI; n = 61, mean age 75 ± 4 years, 35 females) or non-vascular MCI (nvMCI; n = 56, mean age 72 ± 5 years, 36 females) according to their WMH total volume, assessed with an automatic detection toolbox, LST (SPM12). We used a completely data-driven approach to evaluate the differences in the power spectra between the groups. Interestingly, three clusters emerged: One cluster with widespread larger theta power and two clusters located in both temporal regions with smaller beta power for vMCI compared to nvMCI. Those power signatures were also associated with cognitive performance and hippocampal volume. Early identification and classification of dementia pathogenesis is a crucially important goal for the search for more effective management approaches. These findings could help to understand and try to palliate the contribution of WMH to particular symptoms in mixed dementia progress.
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Affiliation(s)
- Lucia Torres-Simon
- Center of Cognitive and Computational Neuroscience, Universidad Complutense de Madrid (UCM), Madrid, Spain
- Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid (UCM), Madrid, Spain
| | - Pablo Cuesta
- Center of Cognitive and Computational Neuroscience, Universidad Complutense de Madrid (UCM), Madrid, Spain
- Department of Radiology, Rehabilitation, and Physiotherapy, Universidad Complutense de Madrid (UCM), Madrid, Spain
- Instituto de investigación Sanitaria San Carlos (IdISSC), Madrid, Spain
| | - Alberto del Cerro-Leon
- Center of Cognitive and Computational Neuroscience, Universidad Complutense de Madrid (UCM), Madrid, Spain
- Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid (UCM), Madrid, Spain
| | - Brenda Chino
- Center of Cognitive and Computational Neuroscience, Universidad Complutense de Madrid (UCM), Madrid, Spain
- Institute of Neuroscience, Autonomous University of Barcelona (UAB), Barcelona, Spain
| | - Lucia H. Orozco
- Center of Cognitive and Computational Neuroscience, Universidad Complutense de Madrid (UCM), Madrid, Spain
| | - Elisabeth B. Marsh
- Department of Neurology, The Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Pedro Gil
- Instituto de investigación Sanitaria San Carlos (IdISSC), Madrid, Spain
- Department of Geriatric Medicine, Hospital Universitario San Carlos, Madrid, Spain
| | - Fernando Maestu
- Center of Cognitive and Computational Neuroscience, Universidad Complutense de Madrid (UCM), Madrid, Spain
- Department of Experimental Psychology, Cognitive Processes and Speech Therapy, Universidad Complutense de Madrid (UCM), Madrid, Spain
- Instituto de investigación Sanitaria San Carlos (IdISSC), Madrid, Spain
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19
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Poghosyan V, Ioannou S, Al-Amri KM, Al-Mashhadi SA, Al-Mohammed F, Al-Otaibi T, Al-Saeed W. Spatiotemporal profile of altered neural reactivity to food images in obesity: Reward system is altered automatically and predicts efficacy of weight loss intervention. Front Neurosci 2023; 17:948063. [PMID: 36845430 PMCID: PMC9944082 DOI: 10.3389/fnins.2023.948063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 01/24/2023] [Indexed: 02/10/2023] Open
Abstract
Introduction Obesity presents a significant public health problem. Brain plays a central role in etiology and maintenance of obesity. Prior neuroimaging studies have found that individuals with obesity exhibit altered neural responses to images of food within the brain reward system and related brain networks. However, little is known about the dynamics of these neural responses or their relationship to later weight change. In particular, it is unknown if in obesity, the altered reward response to food images emerges early and automatically, or later, in the controlled stage of processing. It also remains unclear if the pretreatment reward system reactivity to food images is predictive of subsequent weight loss intervention outcome. Methods In this study, we presented high-calorie and low-calorie food, and nonfood images to individuals with obesity, who were then prescribed lifestyle changes, and matched normal-weight controls, and examined neural reactivity using magnetoencephalography (MEG). We performed whole-brain analysis to explore and characterize large-scale dynamics of brain systems affected in obesity, and tested two specific hypotheses: (1) in obese individuals, the altered reward system reactivity to food images occurs early and automatically, and (2) pretreatment reward system reactivity predicts the outcome of lifestyle weight loss intervention, with reduced activity associated with successful weight loss. Results We identified a distributed set of brain regions and their precise temporal dynamics that showed altered response patterns in obesity. Specifically, we found reduced neural reactivity to food images in brain networks of reward and cognitive control, and elevated reactivity in regions of attentional control and visual processing. The hypoactivity in reward system emerged early, in the automatic stage of processing (< 150 ms post-stimulus). Reduced reward and attention responsivity, and elevated neural cognitive control were predictive of weight loss after six months in treatment. Discussion In summary, we have identified, for the first time with high temporal resolution, the large-scale dynamics of brain reactivity to food images in obese versus normal-weight individuals, and have confirmed both our hypotheses. These findings have important implications for our understanding of neurocognition and eating behavior in obesity, and can facilitate development of novel integrated treatment strategies, including tailored cognitive-behavioral and pharmacological therapies.
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Affiliation(s)
- Vahe Poghosyan
- Department of Neurophysiology, National Neuroscience Institute, King Fahad Medical City, Riyadh, Saudi Arabia,*Correspondence: Vahe Poghosyan,
| | - Stephanos Ioannou
- Department of Physiological Sciences, Alfaisal University, Riyadh, Saudi Arabia
| | - Khalid M. Al-Amri
- Obesity, Endocrinology and Metabolism Center, King Fahad Medical City, Riyadh, Saudi Arabia
| | - Sufana A. Al-Mashhadi
- Research Unit, National Neuroscience Institute, King Fahad Medical City, Riyadh, Saudi Arabia
| | - Fedaa Al-Mohammed
- Department of Neurophysiology, National Neuroscience Institute, King Fahad Medical City, Riyadh, Saudi Arabia
| | - Tahani Al-Otaibi
- Department of Neurophysiology, National Neuroscience Institute, King Fahad Medical City, Riyadh, Saudi Arabia
| | - Wjoud Al-Saeed
- Research Unit, National Neuroscience Institute, King Fahad Medical City, Riyadh, Saudi Arabia
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20
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Partamian H, Tabbal J, Hassan M, Karameh F. Analysis of task-related MEG functional brain networks using dynamic mode decomposition. J Neural Eng 2023; 20. [PMID: 36538817 DOI: 10.1088/1741-2552/acad28] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Accepted: 12/20/2022] [Indexed: 12/24/2022]
Abstract
Objective.Functional connectivity networks explain the different brain states during the diverse motor, cognitive, and sensory functions. Extracting connectivity network configurations and their temporal evolution is crucial for understanding brain function during diverse behavioral tasks.Approach.In this study, we introduce the use of dynamic mode decomposition (DMD) to extract the dynamics of brain networks. We compared DMD with principal component analysis (PCA) using real magnetoencephalography data during motor and memory tasks.Main results.The framework generates dominant connectivity brain networks and their time dynamics during simple tasks, such as button press and left-hand movement, as well as more complex tasks, such as picture naming and memory tasks. Our findings show that the proposed methodology with both the PCA-based and DMD-based approaches extracts similar dominant connectivity networks and their corresponding temporal dynamics.Significance.We believe that the proposed methodology with both the PCA and the DMD approaches has a very high potential for deciphering the spatiotemporal dynamics of electrophysiological brain network states during tasks.
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Affiliation(s)
- Hmayag Partamian
- Electrical and Computer Engineering, American University of Beirut (AUB), Beirut, Lebanon
| | - Judie Tabbal
- MINDig, Rennes F-35000, France.,Institut des Neurosciences Cliniques de Rennes (INCR), Rennes, France
| | - Mahmoud Hassan
- Institut des Neurosciences Cliniques de Rennes (INCR), Rennes, France.,School of Science and Engineering, Reykjavik University, Reykjavik, Iceland
| | - Fadi Karameh
- Electrical and Computer Engineering, American University of Beirut (AUB), Beirut, Lebanon
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21
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Levy J, Jääskeläinen IP, Taylor MJ. Editorial: Magnetoencephalography for social science. Front Syst Neurosci 2023; 16:1105923. [PMID: 36685288 PMCID: PMC9846595 DOI: 10.3389/fnsys.2022.1105923] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 12/06/2022] [Indexed: 01/06/2023] Open
Affiliation(s)
- Jonathan Levy
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland,Ivcher School of Psychology, Reichman University, Herzliya, Israel,*Correspondence: Jonathan Levy ✉
| | - Iiro P. Jääskeläinen
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Margot J. Taylor
- Departments of Medical Imaging and Psychology, University of Toronto, Toronto, ON, Canada,Diagnostic Imaging, Hospital for Sick Children, Toronto, ON, Canada
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22
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Witjes B, Ottenheym LA, Huygen FJPM, de Vos CC. A Review of Effects of Spinal Cord Stimulation on Spectral Features in Resting-State Electroencephalography. Neuromodulation 2023; 26:35-42. [PMID: 35551867 DOI: 10.1016/j.neurom.2022.04.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 02/14/2022] [Accepted: 03/21/2022] [Indexed: 01/11/2023]
Abstract
BACKGROUND Spinal cord stimulation (SCS) is an effective therapy for patients with refractory chronic pain syndromes. Although studies have shown that SCS has both spinal and supraspinal effects, the current understanding of cortical effects is still limited. Neuroimaging techniques, such as magnetoencephalography (MEG) and electroencephalography (EEG), combined here as M/EEG, can reveal modulations in ongoing resting-state cortical activity. We aim to provide an overview of available literature on resting-state M/EEG in patients with chronic pain who have been treated with SCS. MATERIALS AND METHODS We searched multiple online data bases for studies on SCS, chronic pain, and resting-state M/EEG. Primary outcome measures were changes in spectral features, combined with brain regions in which these changes occurred. RESULTS We included eight studies reporting various SCS paradigms (tonic, burst, high-dose, and high-frequency stimulation) and revealing heterogeneity in outcome parameters. We summarized changes in cortical activity in various frequency bands: theta (4-7 Hz), alpha (7-12 Hz), beta (13-30 Hz), and gamma (30-44 Hz). In multiple studies, the somatosensory cortex showed modulation of cortical activity under tonic, burst, and high-frequency stimulation. Changes in connectivity were found in the dorsal anterior cingulate cortex, dorsolateral prefrontal cortex, and parahippocampus. CONCLUSIONS The large heterogeneity observed in outcome measures is probably caused by the large variety in study designs, stimulation paradigms, and spectral features studied. Paresthesia-free paradigms have been compared with tonic stimulation in multiple studies. These studies suggest modulation of medial, lateral, and descending pathways for paresthesia-free stimulation, whereas tonic stimulation predominantly modulates lateral and descending pathways. Moreover, multiple studies have reported an increased alpha peak frequency, increased alpha power, and/or decreased theta power when SCS was compared with baseline, indicating modulation of thalamocortical pathways. Further studies with well-defined groups of responders and nonresponders to SCS are recommended to independently study the cortical effects of pain relief and SCS.
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23
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Sato J, Safar K, Vogan VM, Taylor MJ. Functional connectivity changes during working memory in autism spectrum disorder: A two-year longitudinal MEG study. Neuroimage Clin 2023; 37:103364. [PMID: 36878149 PMCID: PMC9999263 DOI: 10.1016/j.nicl.2023.103364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 02/04/2023] [Accepted: 02/25/2023] [Indexed: 03/06/2023]
Abstract
Working memory impairments have been reported in adults with autism spectrum disorder (ASD) and associated with functional outcomes and social difficulties. However, little is known about the developmental trajectory of working memory in youth with ASD. The current magnetoencephalography (MEG) study is the first to examine the longitudinal development over two years of working memory networks in youth with ASD. We analysed MEG data from 32 children and adolescents with and without ASD (64 datasets; 7-14 years), all tested twice at a two-year interval, during a visual n-back task, with two loads (1- and 2-back). We performed a whole-brain functional connectivity analysis to examine the networks during the successful recognition of visual stimuli. We demonstrate that youth with ASD show decreased connectivity in the theta frequency (4-7 Hz) in the higher memory load (2-back) condition compared to typically developing (TD) controls. This hypo-connected theta network was anchored in primary visual areas with connections to frontal, parietal and limbic regions. These network differences were found despite similar task performance between ASD and TD groups. Within the TD group, we found an increase in alpha (8-14 Hz) connectivity at Time 2 compared to Time 1 in both the 1- and 2-back conditions. These findings demonstrate the continued development of working memory mechanisms over middle childhood, which were not apparent in youth with ASD. Together, our findings support a network-based approach to understanding atypical neural functioning in ASD and the developmental trajectories of working memory processes over middle childhood.
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Affiliation(s)
- Julie Sato
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, ON, Canada; Neuroscience & Mental Health Program, The Hospital for Sick Children Research Institute, Toronto, ON, Canada.
| | - Kristina Safar
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, ON, Canada; Neuroscience & Mental Health Program, The Hospital for Sick Children Research Institute, Toronto, ON, Canada
| | - Vanessa M Vogan
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, ON, Canada; Department of Applied Psychology and Human Development, Ontario Institute for Studies in Education, Toronto, ON, Canada
| | - Margot J Taylor
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, ON, Canada; Neuroscience & Mental Health Program, The Hospital for Sick Children Research Institute, Toronto, ON, Canada; Department of Medical Imaging, University of Toronto, Toronto, ON, Canada; Department of Psychology, University of Toronto, Toronto, ON, Canada
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24
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Fosque LJ, Alipour A, Zare M, Williams-García RV, Beggs JM, Ortiz G. Quasicriticality explains variability of human neural dynamics across life span. Front Comput Neurosci 2022; 16:1037550. [PMID: 36532868 PMCID: PMC9747757 DOI: 10.3389/fncom.2022.1037550] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 10/27/2022] [Indexed: 08/26/2023] Open
Abstract
Aging impacts the brain's structural and functional organization and over time leads to various disorders, such as Alzheimer's disease and cognitive impairment. The process also impacts sensory function, bringing about a general slowing in various perceptual and cognitive functions. Here, we analyze the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) resting-state magnetoencephalography (MEG) dataset-the largest aging cohort available-in light of the quasicriticality framework, a novel organizing principle for brain functionality which relates information processing and scaling properties of brain activity to brain connectivity and stimulus. Examination of the data using this framework reveals interesting correlations with age and gender of test subjects. Using simulated data as verification, our results suggest a link between changes to brain connectivity due to aging and increased dynamical fluctuations of neuronal firing rates. Our findings suggest a platform to develop biomarkers of neurological health.
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Affiliation(s)
- Leandro J. Fosque
- Department of Physics, Indiana University, Bloomington, IN, United States
| | - Abolfazl Alipour
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, United States
| | | | | | - John M. Beggs
- Department of Physics, Indiana University, Bloomington, IN, United States
| | - Gerardo Ortiz
- Department of Physics, Indiana University, Bloomington, IN, United States
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25
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Zhang J, Xiang J, Luo L, Shui R. Editorial: EEG/MEG based diagnosis for psychiatric disorders. Front Hum Neurosci 2022; 16:1061176. [PMID: 36405077 PMCID: PMC9667892 DOI: 10.3389/fnhum.2022.1061176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 10/20/2022] [Indexed: 01/25/2023] Open
Affiliation(s)
- Junpeng Zhang
- Department of Automation, College of Electrical Engineering, Sichuan University, Chengdu, China,*Correspondence: Junpeng Zhang
| | - Jing Xiang
- Departments of Pediatrics and Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - Lizhu Luo
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Rui Shui
- Department of Automation, College of Electrical Engineering, Sichuan University, Chengdu, China
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26
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Zhao TC, Corrigan NM, Yarnykh VL, Kuhl PK. Development of executive function-relevant skills is related to both neural structure and function in infants. Dev Sci 2022; 25:e13323. [PMID: 36114705 PMCID: PMC9620956 DOI: 10.1111/desc.13323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 04/26/2022] [Accepted: 08/25/2022] [Indexed: 01/13/2023]
Abstract
The development of skills related to executive function (EF) in infancy, including their emergence, underlying neural mechanisms, and interconnections to other cognitive skills, is an area of increasing research interest. Here, we report on findings from a multidimensional dataset demonstrating that infants' behavioral performance on a flexible learning task improved across development and that the task performance is highly correlated with both neural structure and neural function. The flexible learning task probed infants' ability to learn two different associations, concurrently, over 16 trials, requiring multiple skills relevant to EF. We examined infants' neural structure by measuring myelin density in the brain, using a novel macromolecular proton fraction (MPF) mapping method. We further examined an important neural function of speech processing by characterizing the mismatch response (MMR) to speech contrasts using magnetoencephalography (MEG). All measurements were performed longitudinally in monolingual English-learning infants at 7- and 11-months of age. At the group level, 11-month-olds, but not 7-month-olds, demonstrated evidence of learning both associations in the behavioral task. Myelin density in the prefrontal region at 7 months of age was found to be highly predictive of behavioral task performance at 11 months of age, suggesting that myelination may support the development of these skills. Furthermore, a machine-learning regression analysis revealed that individual differences in the behavioral task are predicted by concurrent neural speech processing at both ages, suggesting that these skills do not develop in isolation. Together, these cross-modality results revealed novel insights into EF-related skills. HIGHLIGHT: Monolingual infants demonstrated flexible learning on a task requiring executive function skills at 11 months, but not at 7 months. Infants' myelin density at 7 months is highly predictive of their behavioral performance in the flexible learning task at 11 months of age. Individual differences in the flexible learning task performance are also correlated with concurrent neural processing of speech at both ages.
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Affiliation(s)
- T. Christina Zhao
- Institute for Learning & Brain Sciences, University of Washington, Seattle, Washington, USA
- Department of Speech and Hearing Sciences, University of Washington, Seattle, Washington, USA
| | - Neva M. Corrigan
- Institute for Learning & Brain Sciences, University of Washington, Seattle, Washington, USA
| | - Vasily L. Yarnykh
- Department of Radiology, University of Washington, Seattle, Washington, USA
| | - Patricia K. Kuhl
- Institute for Learning & Brain Sciences, University of Washington, Seattle, Washington, USA
- Department of Speech and Hearing Sciences, University of Washington, Seattle, Washington, USA
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27
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Herfurth K, Harpaz Y, Roesch J, Mueller N, Walther K, Kaltenhaeuser M, Pauli E, Goldstein A, Hamer H, Buchfelder M, Doerfler A, Prell J, Rampp S. Localization of beta power decrease as measure for lateralization in pre-surgical language mapping with magnetoencephalography, compared with functional magnetic resonance imaging and validated by Wada test. Front Hum Neurosci 2022; 16:996989. [PMID: 36393988 PMCID: PMC9644652 DOI: 10.3389/fnhum.2022.996989] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 10/04/2022] [Indexed: 11/04/2023] Open
Abstract
Objective: Atypical patterns of language lateralization due to early reorganizational processes constitute a challenge in the pre-surgical evaluation of patients with pharmaco-resistant epilepsy. There is no consensus on an optimal analysis method used for the identification of language dominance in MEG. This study examines the concordance between MEG source localization of beta power desynchronization and fMRI with regard to lateralization and localization of expressive and receptive language areas using a visual verb generation task. Methods: Twenty-five patients with pharmaco-resistant epilepsy, including six patients with atypical language lateralization, and ten right-handed controls obtained MEG and fMRI language assessment. Fourteen patients additionally underwent the Wada test. We analyzed MEG beta power desynchronization in sensor (controls) and source space (patients and controls). Beta power decrease between 13 and 35 Hz was localized applying Dynamic Imaging of Coherent Sources Beamformer technique. Statistical inferences were grounded on cluster-based permutation testing for single subjects. Results: Event-related desynchronization of beta power in MEG was seen within the language-dominant frontal and temporal lobe and within the premotor cortex. Our analysis pipeline consistently yielded left language dominance with high laterality indices in controls. Language lateralization in MEG and Wada test agreed in all 14 patients for inferior frontal, temporal and parietal language areas (Cohen's Kappa = 1, p < 0.001). fMRI agreed with Wada test in 12 out of 14 cases (85.7%) for Broca's area (Cohen's Kappa = 0.71, p = 0.024), while the agreement for temporal and temporo-parietal language areas were non-significant. Concordance between MEG and fMRI laterality indices was highest within the inferior frontal gyrus, with an agreement in 19/24 cases (79.2%), and non-significant for Wernicke's area. Spatial agreement between fMRI and MEG varied considerably between subjects and brain regions with the lowest Euclidean distances within the inferior frontal region of interest. Conclusion: Localizing the desynchronization of MEG beta power using a verb generation task is a promising tool for the identification of language dominance in the pre-surgical evaluation of epilepsy patients. The overall agreement between MEG and fMRI was lower than expected and might be attributed to differences within the baseline condition. A larger sample size and an adjustment of the experimental designs are needed to draw further conclusions.
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Affiliation(s)
- Kirsten Herfurth
- Department of Neurosurgery, University Hospital Erlangen, Erlangen, Germany
- Department of Neurosurgery, University Hospital Halle, Halle (Saale), Germany
| | - Yuval Harpaz
- The Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat Gan, Israel
| | - Julie Roesch
- Department of Neuroradiology, University Hospital Erlangen, Erlangen, Germany
| | - Nadine Mueller
- Epilepsy Center, Department of Neurology, University Hospital Erlangen, Erlangen, Germany
| | - Katrin Walther
- Epilepsy Center, Department of Neurology, University Hospital Erlangen, Erlangen, Germany
| | | | - Elisabeth Pauli
- Epilepsy Center, Department of Neurology, University Hospital Erlangen, Erlangen, Germany
| | - Abraham Goldstein
- The Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat Gan, Israel
| | - Hajo Hamer
- Epilepsy Center, Department of Neurology, University Hospital Erlangen, Erlangen, Germany
| | - Michael Buchfelder
- Department of Neurosurgery, University Hospital Erlangen, Erlangen, Germany
| | - Arnd Doerfler
- Department of Neuroradiology, University Hospital Erlangen, Erlangen, Germany
| | - Julian Prell
- Department of Neurosurgery, University Hospital Halle, Halle (Saale), Germany
| | - Stefan Rampp
- Department of Neurosurgery, University Hospital Erlangen, Erlangen, Germany
- Department of Neurosurgery, University Hospital Halle, Halle (Saale), Germany
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28
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Fernández-Rubio G, Carlomagno F, Vuust P, Kringelbach ML, Bonetti L. Associations between abstract working memory abilities and brain activity underlying long-term recognition of auditory sequences. PNAS Nexus 2022; 1:pgac216. [PMID: 36714830 PMCID: PMC9802106 DOI: 10.1093/pnasnexus/pgac216] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 09/26/2022] [Indexed: 02/01/2023]
Abstract
Memory is a complex cognitive process composed of several subsystems, namely short- and long-term memory and working memory (WM). Previous research has shown that adequate interaction between subsystems is crucial for successful memory processes such as encoding, storage, and manipulation of information. However, few studies have investigated the relationship between different subsystems at the behavioral and neural levels. Thus, here we assessed the relationship between individual WM abilities and brain activity underlying the recognition of previously memorized auditory sequences. First, recognition of previously memorized versus novel auditory sequences was associated with a widespread network of brain areas comprising the cingulate gyrus, hippocampus, insula, inferior temporal cortex, frontal operculum, and orbitofrontal cortex. Second, we observed positive correlations between brain activity underlying auditory sequence recognition and WM. We showed a sustained positive correlation in the medial cingulate gyrus, a brain area that was widely involved in the auditory sequence recognition. Remarkably, we also observed positive correlations in the inferior temporal, temporal-fusiform, and postcentral gyri, brain areas that were not strongly associated with auditory sequence recognition. In conclusion, we discovered positive correlations between WM abilities and brain activity underlying long-term recognition of auditory sequences, providing new evidence on the relationship between memory subsystems. Furthermore, we showed that high WM performers recruited a larger brain network including areas associated with visual processing (i.e., inferior temporal, temporal-fusiform, and postcentral gyri) for successful auditory memory recognition.
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Affiliation(s)
- Gemma Fernández-Rubio
- To whom correspondence should be addressed: Building 1710, Universitetsbyen 3, 8000 Aarhus C, Denmark:
| | | | - Peter Vuust
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music Aarhus/Aalborg, 8000 Aarhus, Denmark
| | - Morten L Kringelbach
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music Aarhus/Aalborg, 8000 Aarhus, Denmark,Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford OX3 9BX, UK,Department of Psychiatry, University of Oxford, Oxford OX1 2JD, UK
| | - Leonardo Bonetti
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University & The Royal Academy of Music Aarhus/Aalborg, 8000 Aarhus, Denmark,Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford OX3 9BX, UK,Department of Psychiatry, University of Oxford, Oxford OX1 2JD, UK
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29
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Davenport EM, Urban JE, Vaughan C, DeSimone JC, Wagner B, Espeland MA, Powers AK, Whitlow CT, Stitzel JD, Maldjian JA. MEG measured delta waves increase in adolescents after concussion. Brain Behav 2022; 12:e2720. [PMID: 36053126 PMCID: PMC9480906 DOI: 10.1002/brb3.2720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 05/22/2022] [Accepted: 06/24/2022] [Indexed: 11/22/2022] Open
Abstract
INTRODUCTION The purpose of this study is to determine if delta waves, measured by magnetoencephalography (MEG), increase in adolescents due to a sports concussion. METHODS Twenty-four adolescents (age 14-17) completed pre- and postseason MRI and MEG scanning. MEG whole-brain delta power was calculated for each subject and normalized by the subject's total power. In eight high school football players diagnosed with a concussion during the season (mean age = 15.8), preseason delta power was subtracted from their postseason scan. In eight high school football players without a concussion (mean age = 15.7), preseason delta power was subtracted from postseason delta power and in eight age-matched noncontact controls (mean age = 15.9), baseline delta power was subtracted from a 4-month follow-up scan. ANOVA was used to compare the mean differences between preseason and postseason scans for the three groups of players, with pairwise comparisons based on Student's t-test method. RESULTS Players with concussions had significantly increased delta wave power at their postseason scans than nonconcussed players (p = .018) and controls (p = .027). CONCLUSION We demonstrate that a single concussion during the season in adolescent subjects can increase MEG measured delta frequency power at their postseason scan. This adds to the growing body of literature indicating increased delta power following a concussion.
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Affiliation(s)
- Elizabeth M Davenport
- Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, Texas.,Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Jillian E Urban
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina.,Virginia Tech-Wake Forest School of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Christopher Vaughan
- Department of Neurosurgery, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Jesse C DeSimone
- Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, Texas.,Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Ben Wagner
- Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, Texas.,Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Mark A Espeland
- Department of Radiology-Neuroradiology, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Alexander K Powers
- Clinical and Translational Science Institute, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Christopher T Whitlow
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina.,Childress Institute for Pediatric Trauma, Wake Forest School of Medicine, Winston-Salem, North Carolina.,Division of Pediatric Neuropsychology, Children's National Health System, Washington, District of Columbia
| | - Joel D Stitzel
- Department of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina.,Virginia Tech-Wake Forest School of Biomedical Engineering, Wake Forest School of Medicine, Winston-Salem, North Carolina.,Division of Pediatric Neuropsychology, Children's National Health System, Washington, District of Columbia.,Division of Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Joseph A Maldjian
- Advanced Neuroscience Imaging Research (ANSIR) Laboratory, University of Texas Southwestern Medical Center, Dallas, Texas.,Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas
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30
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Kubon J, Romagnano V, Sokolov AN, Fallgatter AJ, Braun C, Pavlova MA. Neural circuits underpinning face tuning in male depression. Cereb Cortex 2022; 33:3827-3839. [PMID: 35989312 DOI: 10.1093/cercor/bhac310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 07/15/2022] [Accepted: 07/15/2022] [Indexed: 11/13/2022] Open
Abstract
Reading bodies and faces is essential for efficient social interactions, though it may be thought-provoking for individuals with depression. Yet aberrations in the face sensitivity and underwriting neural circuits are not well understood, in particular, in male depression. Here, we use cutting-edge analyses of time course and dynamic topography of gamma oscillatory neuromagnetic cortical activity during administration of a task with Arcimboldo-like images. No difference in face tuning was found between individuals with depression and their neurotypical peers. Furthermore, this behavioral outcome nicely dovetails with magnetoencephalographic data: at early processing stages, the gamma oscillatory response to images resembling a face was rather similar in patients and controls. These bursts originated primarily from the right medioventral occipital cortex and lateral occipital cortex. At later processing stages, however, its topography altered remarkably in depression with profound engagement of the frontal circuits. Yet the primary difference in depressive individuals as compared with their neurotypical peers occurred over the left middle temporal cortices, a part of the social brain, engaged in feature integration and meaning retrieval. The outcome suggests compensatory recruitment of neural resources in male depression.
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Affiliation(s)
- Julian Kubon
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), Medical School and University Hospital, Eberhard Karls University of Tübingen, Calwerstr. 14, 72076 Tübingen, Germany
| | - Valentina Romagnano
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), Medical School and University Hospital, Eberhard Karls University of Tübingen, Calwerstr. 14, 72076 Tübingen, Germany
| | - Alexander N Sokolov
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), Medical School and University Hospital, Eberhard Karls University of Tübingen, Calwerstr. 14, 72076 Tübingen, Germany
| | - Andreas J Fallgatter
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), Medical School and University Hospital, Eberhard Karls University of Tübingen, Calwerstr. 14, 72076 Tübingen, Germany
| | - Christoph Braun
- MEG Center, Medical School and University Hospital, Eberhard Karls University of Tübingen, Otfried Müller Str. 47, 72076 Tübingen, Germany
| | - Marina A Pavlova
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), Medical School and University Hospital, Eberhard Karls University of Tübingen, Calwerstr. 14, 72076 Tübingen, Germany
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31
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Arutiunian V, Arcara G, Buyanova I, Gomozova M, Dragoy O. The age-related changes in 40 Hz Auditory Steady-State Response and sustained Event-Related Fields to the same amplitude-modulated tones in typically developing children: A magnetoencephalography study. Hum Brain Mapp 2022; 43:5370-5383. [PMID: 35833318 PMCID: PMC9812253 DOI: 10.1002/hbm.26013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Revised: 06/24/2022] [Accepted: 06/24/2022] [Indexed: 01/15/2023] Open
Abstract
Recent studies have revealed that gamma-band oscillatory and transient evoked potentials may change with age during childhood. It is hypothesized that these changes can be associated with a maturation of GABAergic neurotransmission and, subsequently, the age-related changes of excitation-inhibition balance in the neural circuits. One of the reliable paradigms for investigating these effects in the auditory cortex is 40 Hz Auditory Steady-State Response (ASSR), where participants are presented with the periodic auditory stimuli. It is known that such stimuli evoke two types of responses in magnetoencephalography (MEG)-40 Hz steady-state gamma response (or 40 Hz ASSR) and auditory evoked response called sustained Event-Related Field (ERF). Although several studies have been conducted in children, focusing on the changes of 40 Hz ASSR with age, almost nothing is known about the age-related changes of the sustained ERF to the same periodic stimuli and their relationships with changes in the gamma strength. Using MEG, we investigated the association between 40 Hz steady-state gamma response and sustained ERF response to the same stimuli and also their age-related changes in the group of 30 typically developing 7-to-12-year-old children. The results revealed a tight relationship between 40 Hz ASSR and ERF, indicating that the age-related increase in strength of 40 Hz ASSR was associated with the age-related decrease of the amplitude of ERF. These effects were discussed in the light of the maturation of the GABAergic system and excitation-inhibition balance development, which may contribute to the changes in ASSR and ERF.
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Affiliation(s)
| | | | | | | | - Olga Dragoy
- Center for Language and BrainHSE UniversityMoscowRussia,Institute of LinguisticsRussian Academy of SciencesMoscowRussia
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32
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Fred AL, Kumar SN, Kumar Haridhas A, Ghosh S, Purushothaman Bhuvana H, Sim WKJ, Vimalan V, Givo FAS, Jousmäki V, Padmanabhan P, Gulyás B. A Brief Introduction to Magnetoencephalography (MEG) and Its Clinical Applications. Brain Sci 2022; 12:brainsci12060788. [PMID: 35741673 PMCID: PMC9221302 DOI: 10.3390/brainsci12060788] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 06/01/2022] [Accepted: 06/08/2022] [Indexed: 11/30/2022] Open
Abstract
Magnetoencephalography (MEG) plays a pivotal role in the diagnosis of brain disorders. In this review, we have investigated potential MEG applications for analysing brain disorders. The signal-to-noise ratio (SNRMEG = 2.2 db, SNREEG < 1 db) and spatial resolution (SRMEG = 2−3 mm, SREEG = 7−10 mm) is higher for MEG than EEG, thus MEG potentially facilitates accurate monitoring of cortical activity. We found that the direct electrophysiological MEG signals reflected the physiological status of neurological disorders and play a vital role in disease diagnosis. Single-channel connectivity, as well as brain network analysis, using MEG data acquired during resting state and a given task has been used for the diagnosis of neurological disorders such as epilepsy, Alzheimer’s, Parkinsonism, autism, and schizophrenia. The workflow of MEG and its potential applications in the diagnosis of disease and therapeutic planning are also discussed. We forecast that computer-aided algorithms will play a prominent role in the diagnosis and prediction of neurological diseases in the future. The outcome of this narrative review will aid researchers to utilise MEG in diagnostics.
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Affiliation(s)
- Alfred Lenin Fred
- Department of CSE, Mar Ephraem College of Engineering and Technology, Marthandam 629171, Tamil Nadu, India; (A.L.F.); (F.A.S.G.)
| | | | - Ajay Kumar Haridhas
- Department of ECE, Mar Ephraem College of Engineering and Technology, Marthandam 629171, Tamil Nadu, India;
| | - Sayantan Ghosh
- Department of Integrative Biology, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India;
| | - Harishita Purushothaman Bhuvana
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
| | - Wei Khang Jeremy Sim
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
| | - Vijayaragavan Vimalan
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
| | - Fredin Arun Sedly Givo
- Department of CSE, Mar Ephraem College of Engineering and Technology, Marthandam 629171, Tamil Nadu, India; (A.L.F.); (F.A.S.G.)
| | - Veikko Jousmäki
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Aalto NeuroImaging, Department of Neuroscience and Biomedical Engineering, Aalto University, 12200 Espoo, Finland
| | - Parasuraman Padmanabhan
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
- Correspondence: (P.P.); (B.G.)
| | - Balázs Gulyás
- Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore; (H.P.B.); (W.K.J.S.); (V.V.); (V.J.)
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore
- Department of Clinical Neuroscience, Karolinska Institute, 17176 Stockholm, Sweden
- Correspondence: (P.P.); (B.G.)
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33
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Liang S, Mody M. Abnormal Brain Oscillations in Developmental Disorders: Application of Resting State EEG and MEG in Autism Spectrum Disorder and Fragile X Syndrome. Front Neuroimaging 2022; 1:903191. [PMID: 37555160 PMCID: PMC10406242 DOI: 10.3389/fnimg.2022.903191] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 04/29/2022] [Indexed: 08/10/2023]
Abstract
Autism Spectrum Disorder (ASD) and Fragile X Syndrome (FXS) are neurodevelopmental disorders with similar clinical and behavior symptoms and partially overlapping and yet distinct neurobiological origins. It is therefore important to distinguish these disorders from each other as well as from typical development. Examining disruptions in functional connectivity often characteristic of neurodevelopment disorders may be one approach to doing so. This review focuses on EEG and MEG studies of resting state in ASD and FXS, a neuroimaging paradigm frequently used with difficult-to-test populations. It compares the brain regions and frequency bands that appear to be impacted, either in power or connectivity, in each disorder; as well as how these abnormalities may result in the observed symptoms. It argues that the findings in these studies are inconsistent and do not fit neatly into existing models of ASD and FXS, then highlights the gaps in the literature and recommends future avenues of inquiry.
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Affiliation(s)
- Sophia Liang
- College of Arts and Sciences, Harvard University, Cambridge, MA, United States
| | - Maria Mody
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States
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34
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Kiefer CM, Ito J, Weidner R, Boers F, Shah NJ, Grün S, Dammers J. Revealing Whole-Brain Causality Networks During Guided Visual Searching. Front Neurosci 2022; 16:826083. [PMID: 35250461 PMCID: PMC8894880 DOI: 10.3389/fnins.2022.826083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 01/17/2022] [Indexed: 11/24/2022] Open
Abstract
In our daily lives, we use eye movements to actively sample visual information from our environment ("active vision"). However, little is known about how the underlying mechanisms are affected by goal-directed behavior. In a study of 31 participants, magnetoencephalography was combined with eye-tracking technology to investigate how interregional interactions in the brain change when engaged in two distinct forms of active vision: freely viewing natural images or performing a guided visual search. Regions of interest with significant fixation-related evoked activity (FRA) were identified with spatiotemporal cluster permutation testing. Using generalized partial directed coherence, we show that, in response to fixation onset, a bilateral cluster consisting of four regions (posterior insula, transverse temporal gyri, superior temporal gyrus, and supramarginal gyrus) formed a highly connected network during free viewing. A comparable network also emerged in the right hemisphere during the search task, with the right supramarginal gyrus acting as a central node for information exchange. The results suggest that all four regions are vital to visual processing and guiding attention. Furthermore, the right supramarginal gyrus was the only region where activity during fixations on the search target was significantly negatively correlated with search response times. Based on our findings, we hypothesize that, following a fixation, the right supramarginal gyrus supplies the right supplementary eye field (SEF) with new information to update the priority map guiding the eye movements during the search task.
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Affiliation(s)
- Christian M. Kiefer
- Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Jülich GmbH, Jülich, Germany
- Institute of Neuroscience and Medicine (INM-6), Institute for Advanced Simulation (IAS-6), Forschungszentrum Jülich GmbH, Jülich, Germany
- Faculty of Mathematics, Computer Science and Natural Sciences, RWTH Aachen University, Aachen, Germany
- Jülich Aachen Research Alliance (JARA)-Brain – Institute Brain Structure and Function, Institute of Neuroscience and Medicine (INM-10), Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Junji Ito
- Institute of Neuroscience and Medicine (INM-6), Institute for Advanced Simulation (IAS-6), Forschungszentrum Jülich GmbH, Jülich, Germany
- Jülich Aachen Research Alliance (JARA)-Brain – Institute Brain Structure and Function, Institute of Neuroscience and Medicine (INM-10), Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Ralph Weidner
- Institute of Neuroscience and Medicine (INM-3), Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Frank Boers
- Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Jülich GmbH, Jülich, Germany
| | - N. Jon Shah
- Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Jülich GmbH, Jülich, Germany
- Institute of Neuroscience and Medicine (INM-11), Jülich Aachen Research Alliance (JARA), Forschungszentrum Jülich GmbH, Jülich, Germany
- Jülich Aachen Research Alliance (JARA)-Brain – Translational Medicine, Aachen, Germany
- Department of Neurology, University Hospital RWTH Aachen, Aachen, Germany
| | - Sonja Grün
- Institute of Neuroscience and Medicine (INM-6), Institute for Advanced Simulation (IAS-6), Forschungszentrum Jülich GmbH, Jülich, Germany
- Jülich Aachen Research Alliance (JARA)-Brain – Institute Brain Structure and Function, Institute of Neuroscience and Medicine (INM-10), Forschungszentrum Jülich GmbH, Jülich, Germany
- Theoretical Systems Neurobiology, RWTH Aachen University, Aachen, Germany
| | - Jürgen Dammers
- Institute of Neuroscience and Medicine (INM-4), Forschungszentrum Jülich GmbH, Jülich, Germany
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Pourmotabbed H, de Jongh Curry AL, Clarke DF, Tyler-Kabara EC, Babajani-Feremi A. Reproducibility of graph measures derived from resting-state MEG functional connectivity metrics in sensor and source spaces. Hum Brain Mapp 2022; 43:1342-1357. [PMID: 35019189 PMCID: PMC8837594 DOI: 10.1002/hbm.25726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 10/29/2021] [Accepted: 11/11/2021] [Indexed: 11/30/2022] Open
Abstract
Prior studies have used graph analysis of resting‐state magnetoencephalography (MEG) to characterize abnormal brain networks in neurological disorders. However, a present challenge for researchers is the lack of guidance on which network construction strategies to employ. The reproducibility of graph measures is important for their use as clinical biomarkers. Furthermore, global graph measures should ideally not depend on whether the analysis was performed in the sensor or source space. Therefore, MEG data of the 89 healthy subjects of the Human Connectome Project were used to investigate test–retest reliability and sensor versus source association of global graph measures. Atlas‐based beamforming was used for source reconstruction, and functional connectivity (FC) was estimated for both sensor and source signals in six frequency bands using the debiased weighted phase lag index (dwPLI), amplitude envelope correlation (AEC), and leakage‐corrected AEC. Reliability was examined over multiple network density levels achieved with proportional weight and orthogonal minimum spanning tree thresholding. At a 100% density, graph measures for most FC metrics and frequency bands had fair to excellent reliability and significant sensor versus source association. The greatest reliability and sensor versus source association was obtained when using amplitude metrics. Reliability was similar between sensor and source spaces when using amplitude metrics but greater for the source than the sensor space in higher frequency bands when using the dwPLI. These results suggest that graph measures are useful biomarkers, particularly for investigating functional networks based on amplitude synchrony.
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Affiliation(s)
- Haatef Pourmotabbed
- Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, Texas, USA.,Magnetoencephalography Laboratory, Dell Children's Medical Center, Austin, Texas, USA.,Department of Biomedical Engineering, University of Memphis, Memphis, Tennessee, USA
| | - Amy L de Jongh Curry
- Department of Biomedical Engineering, University of Memphis, Memphis, Tennessee, USA
| | - Dave F Clarke
- Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, Texas, USA
| | - Elizabeth C Tyler-Kabara
- Department of Neurosurgery, Dell Medical School, University of Texas at Austin, Austin, Texas, USA
| | - Abbas Babajani-Feremi
- Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, Texas, USA.,Magnetoencephalography Laboratory, Dell Children's Medical Center, Austin, Texas, USA.,Department of Neurosurgery, Dell Medical School, University of Texas at Austin, Austin, Texas, USA
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Roberts TPL, Bloy L, Liu S, Ku M, Blaskey L, Jackel C. Magnetoencephalography Studies of the Envelope Following Response During Amplitude-Modulated Sweeps: Diminished Phase Synchrony in Autism Spectrum Disorder. Front Hum Neurosci 2022; 15:787229. [PMID: 34975438 PMCID: PMC8714804 DOI: 10.3389/fnhum.2021.787229] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 11/01/2021] [Indexed: 11/13/2022] Open
Abstract
Prevailing theories of the neural basis of at least a subset of individuals with autism spectrum disorder (ASD) include an imbalance of excitatory and inhibitory neurotransmission. These circuitry imbalances are commonly probed in adults using auditory steady-state responses (ASSR, driven at 40 Hz) to elicit coherent electrophysiological responses (EEG/MEG) from intact circuitry. Challenges to the ASSR methodology occur during development, where the optimal ASSR driving frequency may be unknown. An alternative approach (more agnostic to driving frequency) is the amplitude-modulated (AM) sweep in which the amplitude of a tone (with carrier frequency 500 Hz) is modulated as a sweep from 10 to 100 Hz over the course of ∼15 s. Phase synchrony of evoked responses, measured via intra-trial coherence, is recorded (by EEG or MEG) as a function of frequency. We applied such AM sweep stimuli bilaterally to 40 typically developing and 80 children with ASD, aged 6–18 years. Diagnoses were confirmed by DSM-5 criteria as well as autism diagnostic observation schedule (ADOS) observational assessment. Stimuli were presented binaurally during MEG recording and consisted of 20 AM swept stimuli (500 Hz carrier; sweep 10–100 Hz up and down) with a duration of ∼30 s each. Peak intra-trial coherence values and peak response frequencies of source modeled responses (auditory cortex) were examined. First, the phase synchrony or inter-trial coherence (ITC) of the ASSR is diminished in ASD; second, hemispheric bias in the ASSR, observed in typical development (TD), is maintained in ASD, and third, that the frequency at which the peak response is obtained varies on an individual basis, in part dependent on age, and with altered developmental trajectories in ASD vs. TD. Finally, there appears an association between auditory steady-state phase synchrony (taken as a proxy of neuronal circuitry integrity) and clinical assessment of language ability/impairment. We concluded that (1) the AM sweep stimulus provides a mechanism for probing ASSR in an unbiased fashion, during developmental maturation of peak response frequency, (2) peak frequencies vary, in part due to developmental age, and importantly, (3) ITC at this peak frequency is diminished in ASD, with the degree of ITC disturbance related to clinically assessed language impairment.
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Affiliation(s)
- Timothy P L Roberts
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Luke Bloy
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Song Liu
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Matthew Ku
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Lisa Blaskey
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Carissa Jackel
- Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA, United States
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37
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Ahlfors SP, Graham S, Alho J, Joseph RM, McGuiggan NM, Nayal Z, Hämäläinen MS, Khan S, Kenet T. Magnetoencephalography and electroencephalography can both detect differences in cortical responses to vibrotactile stimuli in individuals on the autism spectrum. Front Psychiatry 2022; 13:902332. [PMID: 35990048 PMCID: PMC9388788 DOI: 10.3389/fpsyt.2022.902332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 07/18/2022] [Indexed: 11/28/2022] Open
Abstract
Autism Spectrum (AS) is defined primarily by differences in social interactions, with impairments in sensory processing also characterizing the condition. In the search for neurophysiological biomarkers associated with traits relevant to the condition, focusing on sensory processing offers a path that is likely to be translatable across populations with different degrees of ability, as well as into animal models and across imaging modalities. In a prior study, a somatosensory neurophysiological signature of AS was identified using magnetoencephalography (MEG). Specifically, source estimation results showed differences between AS and neurotypically developing (NTD) subjects in the brain response to 25-Hz vibrotactile stimulation of the right fingertips, with lower inter-trial coherence (ITC) observed in the AS group. Here, we examined whether these group differences can be detected without source estimation using scalp electroencephalography (EEG), which is more commonly available in clinical settings than MEG, and therefore offers a greater potential for clinical translation. To that end, we recorded simultaneous whole-head MEG and EEG in 14 AS and 10 NTD subjects (age 15-28 years) using the same vibrotactile paradigm. Based on the scalp topographies, small sets of left hemisphere MEG and EEG sensors showing the maximum overall ITC were selected for group comparisons. Significant differences between the AS and NTD groups in ITC at 25 Hz as well as at 50 Hz were recorded in both MEG and EEG sensor data. For each measure, the mean ITC was lower in the AS than in the NTD group. EEG ITC values correlated with behaviorally assessed somatosensory sensation avoiding scores. The results show that information about ITC from MEG and EEG signals have substantial overlap, and thus EEG sensor-based ITC measures of the AS somatosensory processing biomarker previously identified using source localized MEG data have a potential to be developed into clinical use in AS, thanks to the higher accessibility to EEG in clinical settings.
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Affiliation(s)
- Seppo P Ahlfors
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States.,Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Steven Graham
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Jussi Alho
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Robert M Joseph
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, United States
| | - Nicole M McGuiggan
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Zein Nayal
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Matti S Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States.,Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Sheraz Khan
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States.,Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States.,Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Tal Kenet
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States.,Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
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Shiota Y, Soma D, Hirosawa T, Yoshimura Y, Tanaka S, Hasegawa C, Yaoi K, Iwasaki S, Kameya M, Yokoyama S, Kikuchi M. Alterations in brain networks in children with sub-threshold autism spectrum disorder: A magnetoencephalography study. Front Psychiatry 2022; 13:959763. [PMID: 35990060 PMCID: PMC9390481 DOI: 10.3389/fpsyt.2022.959763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 07/15/2022] [Indexed: 11/28/2022] Open
Abstract
Individuals with sub-threshold autism spectrum disorder (ASD) are those who have social communication difficulties but do not meet the full ASD diagnostic criteria. ASD is associated with an atypical brain network; however, no studies have focused on sub-threshold ASD. Here, we used the graph approach to investigate alterations in the brain networks of children with sub-threshold ASD, independent of a clinical diagnosis. Graph theory is an effective approach for characterizing the properties of complex networks on a large scale. Forty-six children with ASD and 31 typically developing children were divided into three groups (i.e., ASD-Unlikely, ASD-Possible, and ASD-Probable groups) according to their Social Responsiveness Scale scores. We quantified magnetoencephalographic signals using a graph-theoretic index, the phase lag index, for every frequency band. Resultantly, the ASD-Probable group had significantly lower small-worldness (SW) in the delta, theta, and beta bands than the ASD-Unlikely group. Notably, the ASD-Possible group exhibited significantly higher SW than the ASD-Probable group and significantly lower SW than the ASD-Unlikely group in the delta band only. To our knowledge, this was the first report of the atypical brain network associated with sub-threshold ASD. Our findings indicate that magnetoencephalographic signals using graph theory may be useful in detecting sub-threshold ASD.
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Affiliation(s)
- Yuka Shiota
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University, and University of Fukui, Kanazawa, Japan.,Japan Society for the Promotion of Science, Tokyo, Japan.,Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Daiki Soma
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
| | - Tetsu Hirosawa
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University, and University of Fukui, Kanazawa, Japan.,Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Yuko Yoshimura
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University, and University of Fukui, Kanazawa, Japan.,Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan.,Institute of Human and Social Sciences, Kanazawa University, Kanazawa, Japan
| | - Sanae Tanaka
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University, and University of Fukui, Kanazawa, Japan.,Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Chiaki Hasegawa
- Japan Society for the Promotion of Science, Tokyo, Japan.,Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan.,Department of Cognitive Science, Macquarie University, Sydney, NSW, Australia
| | - Ken Yaoi
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University, and University of Fukui, Kanazawa, Japan.,Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Sumie Iwasaki
- Japan Society for the Promotion of Science, Tokyo, Japan.,Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Masafumi Kameya
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
| | - Shigeru Yokoyama
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University, and University of Fukui, Kanazawa, Japan.,Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Mitsuru Kikuchi
- United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University, and University of Fukui, Kanazawa, Japan.,Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan.,Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
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Kvamme TL, Sarmanlu M, Bailey C, Overgaard M. Neurofeedback Modulation of the Sound-induced Flash Illusion Using Parietal Cortex Alpha Oscillations Reveals Dependency on Prior Multisensory Congruency. Neuroscience 2021; 482:1-17. [PMID: 34838934 DOI: 10.1016/j.neuroscience.2021.11.028] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 11/12/2021] [Accepted: 11/19/2021] [Indexed: 01/27/2023]
Abstract
Spontaneous neural oscillations are key predictors of perceptual decisions to bind multisensory signals into a unified percept. Research links decreased alpha power in the posterior cortices to attention and audiovisual binding in the sound-induced flash illusion (SIFI) paradigm. This suggests that controlling alpha oscillations would be a way of controlling audiovisual binding. In the present feasibility study we used MEG-neurofeedback to train one group of subjects to increase left/right and another to increase right/left alpha power ratios in the parietal cortex. We tested for changes in audiovisual binding in a SIFI paradigm where flashes appeared in both hemifields. Results showed that the neurofeedback induced a significant asymmetry in alpha power for the left/right group, not seen for the right/left group. Corresponding asymmetry changes in audiovisual binding in illusion trials (with 2, 3, and 4 beeps paired with 1 flash) were not apparent. Exploratory analyses showed that neurofeedback training effects were present for illusion trials with the lowest numeric disparity (i.e., 2 beeps and 1 flash trials) only if the previous trial had high congruency (2 beeps and 2 flashes). Our data suggest that the relation between parietal alpha power (an index of attention) and its effect on audiovisual binding is dependent on the learned causal structure in the previous stimulus. The present results suggests that low alpha power biases observers towards audiovisual binding when they have learned that audiovisual signals originate from a common origin, consistent with a Bayesian causal inference account of multisensory perception.
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Affiliation(s)
- Timo L Kvamme
- Cognitive Neuroscience Research Unit, CFIN/MINDLab, Aarhus University, Aarhus, Denmark.
| | - Mesud Sarmanlu
- Cognitive Neuroscience Research Unit, CFIN/MINDLab, Aarhus University, Aarhus, Denmark
| | - Christopher Bailey
- Cognitive Neuroscience Research Unit, CFIN/MINDLab, Aarhus University, Aarhus, Denmark
| | - Morten Overgaard
- Cognitive Neuroscience Research Unit, CFIN/MINDLab, Aarhus University, Aarhus, Denmark
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Mossad SI, Young JM, Wong SM, Dunkley BT, Hunt BAE, Pang EW, Taylor MJ. The Very Preterm Brain at Rest: Longitudinal Social-Cognitive Network Connectivity During Childhood. Soc Cogn Affect Neurosci 2021; 17:377-386. [PMID: 34654932 PMCID: PMC8972272 DOI: 10.1093/scan/nsab110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Revised: 08/22/2021] [Accepted: 10/15/2021] [Indexed: 11/20/2022] Open
Abstract
Very preterm (VPT: ≤32 weeks of gestational age) birth poses an increased risk for social and cognitive morbidities that persist throughout life. Resting-state functional network connectivity studies provide information about the intrinsic capacity for cognitive processing. We studied the following four social–cognitive resting-state networks: the default mode, salience, frontal-parietal and language networks. We examined functional connectivity using magnetoencephalography with individual head localization using each participant’s MRI at 6 (n = 40) and 8 (n = 40) years of age compared to age- and sex-matched full-term (FT) born children (n = 38 at 6 years and n = 43 at 8 years). VPT children showed increased connectivity compared to FT children in the gamma band (30–80 Hz) at 6 years within the default mode network (DMN), and between the DMN and the salience, frontal-parietal and language networks, pointing to more diffuse, less segregated processing across networks at this age. At 8 years, VPT children had more social and academic difficulties. Increased DMN connectivity at 6 years was associated with social and working memory difficulties at 8 years. Therefore, we suggest that increased DMN connectivity contributes to the observed emerging social and cognitive morbidities in school age.
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Affiliation(s)
- Sarah I Mossad
- Department of Psychology, Hospital for Sick Children, Canada
| | - Julia M Young
- Department of Psychology, Hospital for Sick Children, Canada
| | - Simeon M Wong
- Neurosciences & Mental Health, SickKids Research Institute, Canada.,Institute of Biomaterials and Biomedical Engineering, University of Toronto, Canada
| | - Benjamin T Dunkley
- Neurosciences & Mental Health, SickKids Research Institute, Canada.,Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, ON, Canada.,Department of Medical Imaging, University of Toronto, Canada
| | - Benjamin A E Hunt
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Elizabeth W Pang
- Neurosciences & Mental Health, SickKids Research Institute, Canada.,Division of Neurology, Hospital for Sick Children, Toronto, Canada
| | - Margot J Taylor
- Neurosciences & Mental Health, SickKids Research Institute, Canada.,Department of Psychology, University of Toronto, Canada.,Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, ON, Canada
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41
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Tai RY, Zhu JD, Chen CC, Hsieh YW, Cheng CH. Modulation of Functional Connectivity in Response to Mirror Visual Feedback in Stroke Survivors: An MEG Study. Brain Sci 2021; 11:brainsci11101284. [PMID: 34679347 PMCID: PMC8533793 DOI: 10.3390/brainsci11101284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 09/15/2021] [Accepted: 09/25/2021] [Indexed: 11/21/2022] Open
Abstract
Background. Several brain regions are activated in response to mirror visual feedback (MVF). However, less is known about how these brain areas and their connectivity are modulated in stroke patients. This study aimed to explore the effects of MVF on brain functional connectivity in stroke patients. Materials and Methods. We enrolled 15 stroke patients who executed Bilateral-No mirror, Bilateral-Mirror, and Unilateral-Mirror conditions. The coherence values among five brain regions of interest in four different frequency bands were calculated from magnetoencephalographic signals. We examined the differences in functional connectivity of each two brain areas between the Bilateral-No mirror and Bilateral-Mirror conditions and between the Bilateral-Mirror and Unilateral-Mirror conditions. Results. The functional connectivity analyses revealed significantly stronger connectivity between the posterior cingulate cortex and primary motor cortex in the beta band (adjusted p = 0.04) and possibly stronger connectivity between the precuneus and primary visual cortex in the theta band (adjusted p = 0.08) in the Bilateral-Mirror condition than those in the Bilateral-No mirror condition. However, the comparisons between the Bilateral-Mirror and Unilateral-Mirror conditions revealed no significant differences in cortical coherence in all frequency bands. Conclusions. Providing MVF to stroke patients may modulate the lesioned primary motor cortex through visuospatial and attentional cortical networks.
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Affiliation(s)
- Ruei-Yi Tai
- Department of Neurology, Taipei Medical University Hospital, Taipei 110, Taiwan;
- Taipei Neuroscience Institute, Taipei Medical University, Taipei 110, Taiwan
| | - Jun-Ding Zhu
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei 112, Taiwan;
| | - Chih-Chi Chen
- Department of Physical Medicine and Rehabilitation, Chang Gung Memorial Hospital, Linkou 333, Taiwan;
- School of Medicine, College of Medicine, Chang Gung University, Taoyuan 333, Taiwan
| | - Yu-Wei Hsieh
- Department of Physical Medicine and Rehabilitation, Chang Gung Memorial Hospital, Linkou 333, Taiwan;
- Department of Occupational Therapy and Graduate Institute of Behavioral Sciences, College of Medicine, Chang Gung University, Taoyuan 333, Taiwan
- Healthy Aging Research Center, Chang Gung University, Taoyuan 333, Taiwan
- Correspondence: (Y.-W.H.); (C.-H.C.); Tel.: +8863-211-8800 (ext. 3820) (Y.-W.H.); +8863-211-8800 (ext. 3854) (C.-H.C.)
| | - Chia-Hsiung Cheng
- Department of Occupational Therapy and Graduate Institute of Behavioral Sciences, College of Medicine, Chang Gung University, Taoyuan 333, Taiwan
- Healthy Aging Research Center, Chang Gung University, Taoyuan 333, Taiwan
- Department of Psychiatry, Chang Gung Memorial Hospital, Linkou 333, Taiwan
- Correspondence: (Y.-W.H.); (C.-H.C.); Tel.: +8863-211-8800 (ext. 3820) (Y.-W.H.); +8863-211-8800 (ext. 3854) (C.-H.C.)
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Hsu CH, Wu YN. Application of Empirical Mode Decomposition for Decoding Perception of Faces Using Magnetoencephalography. Sensors (Basel) 2021; 21:s21186235. [PMID: 34577441 PMCID: PMC8472346 DOI: 10.3390/s21186235] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 09/14/2021] [Accepted: 09/14/2021] [Indexed: 11/16/2022]
Abstract
Neural decoding is useful to explore the timing and source location in which the brain encodes information. Higher classification accuracy means that an analysis is more likely to succeed in extracting useful information from noises. In this paper, we present the application of a nonlinear, nonstationary signal decomposition technique—the empirical mode decomposition (EMD), on MEG data. We discuss the fundamental concepts and importance of nonlinear methods when it comes to analyzing brainwave signals and demonstrate the procedure on a set of open-source MEG facial recognition task dataset. The improved clarity of data allowed further decoding analysis to capture distinguishing features between conditions that were formerly over-looked in the existing literature, while raising interesting questions concerning hemispheric dominance to the encoding process of facial and identity information.
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Lin SH, Cheng CH, Wu CY, Liu CT, Chen CL, Hsieh YW. Mirror Visual Feedback Induces M1 Excitability by Disengaging Functional Connections of Perceptuo-Motor-Attentional Processes during Asynchronous Bimanual Movement: A Magnetoencephalographic Study. Brain Sci 2021; 11:1092. [PMID: 34439711 DOI: 10.3390/brainsci11081092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 08/09/2021] [Accepted: 08/16/2021] [Indexed: 12/02/2022] Open
Abstract
Mirror visual feedback (MVF) has been shown to increase the excitability of the primary motor cortex (M1) during asynchronous bimanual movement. However, the functional networks underlying this process remain unclear. We recruited 16 healthy volunteers to perform asynchronous bimanual movement, that is, their left hand performed partial range of movement while their right hand performed normal full range of movement. Their ongoing brain activities were recorded by whole-head magnetoencephalography during the movement. Participants were required to keep both hands stationary in the control condition. In the other two conditions, participants were required to perform asynchronous bimanual movement with MVF (Asy_M) and without MVF (Asy_w/oM). Greater M1 excitability was found under Asy_M than under Asy_w/oM. More importantly, when receiving MVF, the visual cortex reduced its functional connection to brain regions associated with perceptuo-motor-attentional process (i.e., M1, superior temporal gyrus, and dorsolateral prefrontal cortex). This is the first study to demonstrate a global functional network of MVF during asynchronous bimanual movement, providing a foundation for future research to examine the neural mechanisms of mirror illusion in motor control.
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Chen PY, Hsu HY, Chao YP, Nouchi R, Wang PN, Cheng CH. Altered mismatch response of inferior parietal lobule in amnestic mild cognitive impairment: A magnetoencephalographic study. CNS Neurosci Ther 2021; 27:1136-1145. [PMID: 34347358 PMCID: PMC8446215 DOI: 10.1111/cns.13691] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 05/16/2021] [Accepted: 05/20/2021] [Indexed: 12/31/2022] Open
Abstract
Background Mismatch negativity (MMN) reflects the functional integrity of sensory memory function. With the advantages of independence of individual's focused attention and behavioral cooperation, this neurophysiological signal is particularly suitable for investigating elderly with cognitive decline such as amnestic mild cognitive impairment (aMCI). However, the existing results remain substantially inconsistent whether these patients show deficits of MMN. In order to reconcile the previous disputes, the present study used magnetoencephalography combined with distributed source imaging methods to determine the source‐level magnetic mismatch negativity (MMNm) in aMCI. Methods A total of 26 healthy controls (HC) and 26 patients with aMCI underwent an auditory oddball paradigm during the MEG recordings. MMNm amplitudes and latencies in the bilateral superior temporal gyrus, inferior frontal gyrus, and inferior parietal lobule (IPL) were compared between HC and aMCI groups. The correlations of MMNm responses with performance of auditory/verbal memory tests were examined. Finally, MMNm and its combination with verbal/auditory memory tests were submitted to receiver operating characteristic (ROC) curve analysis. Results Compared to HC, patients with aMCI showed significantly delayed MMNm latencies in the IPL. Among the patients with aMCI, longer MMNm latencies of left IPL were associated with lower scores of Chinese Version Verbal Learning Test (CVVLT). The ROC curve analysis revealed that the combination of MMNm latencies of left IPL and CVVLT scores yielded a moderate accuracy in the discrimination of aMCI from HC at an individual level. Conclusions Our data suggest dysfunctional MMNm in patients with aMCI, particularly in the IPL.
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Affiliation(s)
- Pin-Yu Chen
- Department of Occupational Therapy and Graduate Institute of Behavioral Sciences, Chang Gung University, Taoyuan, Taiwan.,Laboratory of Brain Imaging and Neural Dynamics (BIND Lab), Chang Gung University, Taoyuan, Taiwan
| | - Hui-Yun Hsu
- Department of Occupational Therapy and Graduate Institute of Behavioral Sciences, Chang Gung University, Taoyuan, Taiwan.,Laboratory of Brain Imaging and Neural Dynamics (BIND Lab), Chang Gung University, Taoyuan, Taiwan
| | - Yi-Ping Chao
- Graduate Institute of Biomedical Engineering, Chang Gung University, Taoyuan, Taiwan.,Department of Neurology, Chang Gung Memorial Hospital, Linkou, Taiwan
| | - Rui Nouchi
- Institute of Development, Aging and Cancer (IDAC), Tohoku University, Sendai, Japan.,Smart Aging Research Center (S.A.R.C), Tohoku University, Sendai, Japan
| | - Pei-Ning Wang
- Division of General Neurology, Department of Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Neurology, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chia-Hsiung Cheng
- Department of Occupational Therapy and Graduate Institute of Behavioral Sciences, Chang Gung University, Taoyuan, Taiwan.,Laboratory of Brain Imaging and Neural Dynamics (BIND Lab), Chang Gung University, Taoyuan, Taiwan.,Healthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan.,Department of Psychiatry, Chang Gung Memorial Hospital, Linkou, Taiwan
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Rodríguez-González V, Gómez C, Hoshi H, Shigihara Y, Hornero R, Poza J. Exploring the Interactions Between Neurophysiology and Cognitive and Behavioral Changes Induced by a Non-pharmacological Treatment: A Network Approach. Front Aging Neurosci 2021; 13:696174. [PMID: 34393759 PMCID: PMC8358307 DOI: 10.3389/fnagi.2021.696174] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Accepted: 07/13/2021] [Indexed: 11/24/2022] Open
Abstract
Dementia due to Alzheimer's disease (AD) is a neurological syndrome which has an increasing impact on society, provoking behavioral, cognitive, and functional impairments. AD lacks an effective pharmacological intervention; thereby, non-pharmacological treatments (NPTs) play an important role, as they have been proven to ameliorate AD symptoms. Nevertheless, results associated with NPTs are patient-dependent, and new tools are needed to predict their outcome and to improve their effectiveness. In the present study, 19 patients with AD underwent an NPT for 83.1 ± 38.9 days (mean ± standard deviation). The NPT was a personalized intervention with physical, cognitive, and memory stimulation. The magnetoencephalographic activity was recorded at the beginning and at the end of the NPT to evaluate the neurophysiological state of each patient. Additionally, the cognitive (assessed by means of the Mini-Mental State Examination, MMSE) and behavioral (assessed in terms of the Dementia Behavior Disturbance Scale, DBD-13) status were collected before and after the NPT. We analyzed the interactions between cognitive, behavioral, and neurophysiological data by generating diverse association networks, able to intuitively characterize the relationships between variables of a different nature. Our results suggest that the NPT remarkably changed the structure of the association network, reinforcing the interactions between the DBD-13 and the neurophysiological parameters. We also found that the changes in cognition and behavior are related to the changes in spectral-based neurophysiological parameters. Furthermore, our results support the idea that MEG-derived parameters can predict NPT outcome; specifically, a lesser degree of AD neurophysiological alterations (i.e., neural oscillatory slowing, decreased variety of spectral components, and increased neural signal regularity) predicts a better NPT prognosis. This study provides deeper insights into the relationships between neurophysiology and both, cognitive and behavioral status, proving the potential of network-based methodology as a tool to further understand the complex interactions elicited by NPTs.
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Affiliation(s)
| | - Carlos Gómez
- Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
| | - Hideyuki Hoshi
- Precision Medicine Centre, Hokuto Hospital, Obihiro, Japan
| | | | - Roberto Hornero
- Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
- IMUVA, Instituto de Investigación en Matemáticas, Universidad de Valladolid, Valladolid, Spain
| | - Jesús Poza
- Biomedical Engineering Group, Universidad de Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid, Spain
- IMUVA, Instituto de Investigación en Matemáticas, Universidad de Valladolid, Valladolid, Spain
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Kheirkhah M, Baumbach P, Leistritz L, Witte OW, Walter M, Gilbert JR, Zarate Jr. CA, Klingner CM. The Right Hemisphere Is Responsible for the Greatest Differences in Human Brain Response to High-Arousing Emotional versus Neutral Stimuli: A MEG Study. Brain Sci 2021; 11:960. [PMID: 34439579 PMCID: PMC8412101 DOI: 10.3390/brainsci11080960] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2021] [Revised: 07/09/2021] [Accepted: 07/16/2021] [Indexed: 11/17/2022] Open
Abstract
Studies investigating human brain response to emotional stimuli-particularly high-arousing versus neutral stimuli-have obtained inconsistent results. The present study was the first to combine magnetoencephalography (MEG) with the bootstrapping method to examine the whole brain and identify the cortical regions involved in this differential response. Seventeen healthy participants (11 females, aged 19 to 33 years; mean age, 26.9 years) were presented with high-arousing emotional (pleasant and unpleasant) and neutral pictures, and their brain responses were measured using MEG. When random resampling bootstrapping was performed for each participant, the greatest differences between high-arousing emotional and neutral stimuli during M300 (270-320 ms) were found to occur in the right temporo-parietal region. This finding was observed in response to both pleasant and unpleasant stimuli. The results, which may be more robust than previous studies because of bootstrapping and examination of the whole brain, reinforce the essential role of the right hemisphere in emotion processing.
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Affiliation(s)
- Mina Kheirkhah
- Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20814, USA; (J.R.G.); (C.A.Z.)
- Biomagnetic Center, Jena University Hospital, 07747 Jena, Germany;
- Department of Psychiatry and Psychotherapy, Jena University Hospital, 07743 Jena, Germany;
| | - Philipp Baumbach
- Department of Anesthesiology and Intensive Care Medicine, Jena University Hospital, 07747 Jena, Germany;
| | - Lutz Leistritz
- Institute of Medical Statistics, Computer and Data Sciences, Jena University Hospital, 07740 Jena, Germany;
| | - Otto W. Witte
- Hans Berger Department of Neurology, Jena University Hospital, 07747 Jena, Germany;
| | - Martin Walter
- Department of Psychiatry and Psychotherapy, Jena University Hospital, 07743 Jena, Germany;
| | - Jessica R. Gilbert
- Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20814, USA; (J.R.G.); (C.A.Z.)
| | - Carlos A. Zarate Jr.
- Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20814, USA; (J.R.G.); (C.A.Z.)
| | - Carsten M. Klingner
- Biomagnetic Center, Jena University Hospital, 07747 Jena, Germany;
- Hans Berger Department of Neurology, Jena University Hospital, 07747 Jena, Germany;
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47
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Horowitz AJ, Guger C, Korostenskaja M. What External Variables Affect Sensorimotor Rhythm Brain-Computer Interface (SMR-BCI) Performance? HCA Healthc J Med 2021; 2:143-162. [PMID: 37427002 PMCID: PMC10324824 DOI: 10.36518/2689-0216.1188] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Description Sensorimotor rhythm-based brain-computer interfaces (SMR-BCIs) are used for the acquisition and translation of motor imagery-related brain signals into machine control commands, bypassing the usual central nervous system output. The selection of optimal external variable configuration can maximize SMR-BCI performance in both healthy and disabled people. This performance is especially important now when the BCI is targeted for everyday use in the environment beyond strictly regulated laboratory settings. In this review article, we summarize and critically evaluate the current body of knowledge pertaining to the effect of the external variables on SMR-BCI performance. When assessing the relationship between SMR-BCI performance and external variables, we broadly characterize them as elements that are less dependent on the BCI user and originate from beyond the user. These elements include such factors as BCI type, distractors, training, visual and auditory feedback, virtual reality and magneto electric feedback, proprioceptive and haptic feedback, carefulness of electroencephalography (EEG) system assembling and positioning of EEG electrodes as well as recording-related artifacts. At the end of this review paper, future developments are proposed regarding the research into the effects of external variables on SMR-BCI performance. We believe that our critical review will be of value for academic BCI scientists and developers and clinical professionals working in the field of BCIs as well as for SMR-BCI users.
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Affiliation(s)
- Alex J. Horowitz
- Functional Brain Mapping and Brain Computer Interface Lab, Neuroscience Institute, AdventHealth Orlando, Orlando, FL,
USA
- University of Central Florida/HCA Healthcare GME Consortium, Gainesville, Florida
| | | | - Milena Korostenskaja
- Functional Brain Mapping and Brain Computer Interface Lab, Neuroscience Institute, AdventHealth Orlando, Orlando, FL,
USA
- MEG Lab, AdventHealth for Children, Orlando, FL,
USA
- Department of Psychology, College of Arts and Sciences, University of North Florida, Jacksonville, FL,
USA
- Comprehensive Epilepsy Center, AdventHealth Orlando, Orlando, FL,
USA
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48
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Chan HL, Low I, Chen LF, Chen YS, Chu IT, Hsieh JC. A novel beamformer-based imaging of phase-amplitude coupling (BIPAC) unveiling the inter-regional connectivity of emotional prosody processing in women with primary dysmenorrhea. J Neural Eng 2021; 18. [PMID: 33691295 DOI: 10.1088/1741-2552/abed83] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 03/10/2021] [Indexed: 12/30/2022]
Abstract
Objective. Neural communication or the interactions of brain regions play a key role in the formation of functional neural networks. A type of neural communication can be measured in the form of phase-amplitude coupling (PAC), which is the coupling between the phase of low-frequency oscillations and the amplitude of high-frequency oscillations. This paper presents a beamformer-based imaging method, beamformer-based imaging of PAC (BIPAC), to quantify the strength of PAC between a seed region and other brain regions.Approach. A dipole is used to model the ensemble of neural activity within a group of nearby neurons and represents a mixture of multiple source components of cortical activity. From ensemble activity at each brain location, the source component with the strongest coupling to the seed activity is extracted, while unrelated components are suppressed to enhance the sensitivity of coupled-source estimation.Main results. In evaluations using simulation data sets, BIPAC proved advantageous with regard to estimation accuracy in source localization, orientation, and coupling strength. BIPAC was also applied to the analysis of magnetoencephalographic signals recorded from women with primary dysmenorrhea in an implicit emotional prosody experiment. In response to negative emotional prosody, auditory areas revealed strong PAC with the ventral auditory stream and occipitoparietal areas in the theta-gamma and alpha-gamma bands, which may respectively indicate the recruitment of auditory sensory memory and attention reorientation. Moreover, patients with more severe pain experience appeared to have stronger coupling between auditory areas and temporoparietal regions.Significance. Our findings indicate that the implicit processing of emotional prosody is altered by menstrual pain experience. The proposed BIPAC is feasible and applicable to imaging inter-regional connectivity based on cross-frequency coupling estimates. The experimental results also demonstrate that BIPAC is capable of revealing autonomous brain processing and neurodynamics, which are more subtle than active and attended task-driven processing.
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Affiliation(s)
- Hui-Ling Chan
- Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Intan Low
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Integrated Brain Research Unit, Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Li-Fen Chen
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Integrated Brain Research Unit, Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan.,Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yong-Sheng Chen
- Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Ian-Ting Chu
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Jen-Chuen Hsieh
- Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Integrated Brain Research Unit, Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
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49
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Mossad SI, Vandewouw MM, Smith ML, Taylor MJ. The preterm social brain: altered functional networks for Theory of Mind in very preterm children. Brain Commun 2021; 3:fcaa237. [PMID: 33615217 PMCID: PMC7882208 DOI: 10.1093/braincomms/fcaa237] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 11/17/2020] [Accepted: 11/19/2020] [Indexed: 01/19/2023] Open
Abstract
Neurodevelopmental difficulties emerge in very preterm born children (<32-week gestation) in infancy and continue to early adulthood but little is known about their social-cognitive development. This study utilized the complementary methodological advantages of both functional MRI and magnetoencephalography to examine the neural underpinnings of Theory of Mind in very preterm birth. Theory of Mind, one of the core social-cognitive skills, is the ability to attribute mental states to others, and is crucial for predicting others’ behaviours in social interactions. Eighty-three children (40 very preterm born, 24 boys, age = 8.7 ± 0.5 years, and 43 full-term born, 22 boys, age = 8.6 ± 0.5 years) completed the study. In functional MRI, both groups recruited classic Theory of Mind areas, without significant group differences. However, reduced Theory of Mind connectivity in the very preterm born group was found in magnetoencephalography in distinct theta, alpha and beta-band networks anchored in a set of brain regions that comprise the social brain. These networks included regions such as the angular gyrus, the medial pre-frontal cortex, the superior temporal gyrus and the temporal poles. Very preterm born children showed increased connectivity compared to controls in a network anchored in the occipital gyri rather than classical social-processing regions. Very preterm born children made significantly more attribution errors and mis-construed the social scenarios. Findings offer novel insight into the neural networks, supporting social cognition in very preterm born children and highlight the importance of multimodal neuroimaging to interrogate the social brain in clinical populations.
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Affiliation(s)
- Sarah I Mossad
- Department of Psychology, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
| | - Marlee M Vandewouw
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada.,Neurosciences & Mental Health, SickKids Research Institute, Toronto, ON M5G 0A4, Canada
| | - Mary Lou Smith
- Department of Psychology, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada.,Department of Psychology, University of Toronto, Toronto, ON M5S 3G3, Canada
| | - Margot J Taylor
- Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada.,Neurosciences & Mental Health, SickKids Research Institute, Toronto, ON M5G 0A4, Canada.,Department of Psychology, University of Toronto, Toronto, ON M5S 3G3, Canada
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50
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Roberts TPL, Bloy L, Liu S, Ku M, Blaskey L, Jackel C. Magnetoencephalography Studies of the Envelope Following Response During Amplitude-Modulated Sweeps: Diminished Phase Synchrony in Autism Spectrum Disorder. Front Hum Neurosci 2021. [PMID: 34975438 DOI: 10.3389/fnhum.2021a.787229] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2023] Open
Abstract
Prevailing theories of the neural basis of at least a subset of individuals with autism spectrum disorder (ASD) include an imbalance of excitatory and inhibitory neurotransmission. These circuitry imbalances are commonly probed in adults using auditory steady-state responses (ASSR, driven at 40 Hz) to elicit coherent electrophysiological responses (EEG/MEG) from intact circuitry. Challenges to the ASSR methodology occur during development, where the optimal ASSR driving frequency may be unknown. An alternative approach (more agnostic to driving frequency) is the amplitude-modulated (AM) sweep in which the amplitude of a tone (with carrier frequency 500 Hz) is modulated as a sweep from 10 to 100 Hz over the course of ∼15 s. Phase synchrony of evoked responses, measured via intra-trial coherence, is recorded (by EEG or MEG) as a function of frequency. We applied such AM sweep stimuli bilaterally to 40 typically developing and 80 children with ASD, aged 6-18 years. Diagnoses were confirmed by DSM-5 criteria as well as autism diagnostic observation schedule (ADOS) observational assessment. Stimuli were presented binaurally during MEG recording and consisted of 20 AM swept stimuli (500 Hz carrier; sweep 10-100 Hz up and down) with a duration of ∼30 s each. Peak intra-trial coherence values and peak response frequencies of source modeled responses (auditory cortex) were examined. First, the phase synchrony or inter-trial coherence (ITC) of the ASSR is diminished in ASD; second, hemispheric bias in the ASSR, observed in typical development (TD), is maintained in ASD, and third, that the frequency at which the peak response is obtained varies on an individual basis, in part dependent on age, and with altered developmental trajectories in ASD vs. TD. Finally, there appears an association between auditory steady-state phase synchrony (taken as a proxy of neuronal circuitry integrity) and clinical assessment of language ability/impairment. We concluded that (1) the AM sweep stimulus provides a mechanism for probing ASSR in an unbiased fashion, during developmental maturation of peak response frequency, (2) peak frequencies vary, in part due to developmental age, and importantly, (3) ITC at this peak frequency is diminished in ASD, with the degree of ITC disturbance related to clinically assessed language impairment.
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Affiliation(s)
- Timothy P L Roberts
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Luke Bloy
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Song Liu
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Matthew Ku
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Lisa Blaskey
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Carissa Jackel
- Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA, United States
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