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Jiao M, Xian X, Wang B, Zhang Y, Yang S, Chen S, Sun H, Liu F. XDL-ESI: Electrophysiological Sources Imaging via explainable deep learning framework with validation on simultaneous EEG and iEEG. Neuroimage 2024; 299:120802. [PMID: 39173694 DOI: 10.1016/j.neuroimage.2024.120802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Revised: 08/17/2024] [Accepted: 08/19/2024] [Indexed: 08/24/2024] Open
Abstract
Electroencephalography (EEG) or Magnetoencephalography (MEG) source imaging aims to estimate the underlying activated brain sources to explain the observed EEG/MEG recordings. Solving the inverse problem of EEG/MEG Source Imaging (ESI) is challenging due to its ill-posed nature. To achieve a unique solution, it is essential to apply sophisticated regularization constraints to restrict the solution space. Traditionally, the design of regularization terms is based on assumptions about the spatiotemporal structure of the underlying source dynamics. In this paper, we propose a novel paradigm for ESI via an Explainable Deep Learning framework, termed as XDL-ESI, which connects the iterative optimization algorithm with deep learning architecture by unfolding the iterative updates with neural network modules. The proposed framework has the advantages of (1) establishing a data-driven approach to model the source solution structure instead of using hand-crafted regularization terms; (2) improving the robustness of source solutions by introducing a topological loss that leverages the geometric spatial information applying varying penalties on distinct localization errors; (3) improving the reconstruction efficiency and interpretability as it inherits the advantages from both the iterative optimization algorithms (interpretability) and deep learning approaches (function approximation). The proposed XDL-ESI framework provides an efficient, accurate, and interpretable paradigm to solve the ESI inverse problem with satisfactory performance in both simulated data and real clinical data. Specially, this approach is further validated using simultaneous EEG and intracranial EEG (iEEG).
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Affiliation(s)
- Meng Jiao
- Department of Systems and Enterprises, Stevens Institute of Technology, Hoboken, NJ, 07030, United States
| | - Xiaochen Xian
- H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, United States
| | - Boyu Wang
- Department of Computer Science, University of Western Ontario, Ontario, N6A 3K7, Canada
| | - Yu Zhang
- Department of Bioengineering, Lehigh University, Bethlehem, PA, 18015, United States
| | - Shihao Yang
- Department of Systems and Enterprises, Stevens Institute of Technology, Hoboken, NJ, 07030, United States
| | - Spencer Chen
- Department of Neurosurgery, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, 08901, United States
| | - Hai Sun
- Department of Neurosurgery, Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ, 08901, United States
| | - Feng Liu
- Department of Systems and Enterprises, Stevens Institute of Technology, Hoboken, NJ, 07030, United States; Semcer Center for Healthcare Innovation, Stevens Institute of Technology, Hoboken, NJ, 07030, United States.
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Chen Y, Green HL, Berman JI, Putt ME, Otten K, Mol K, McNamee M, Allison O, Kuschner ES, Kim M, Bloy L, Liu S, Yount T, Roberts TPL, Christopher Edgar J. Functional and structural maturation of auditory cortex from 2 months to 2 years old. Clin Neurophysiol 2024; 166:232-243. [PMID: 39213880 DOI: 10.1016/j.clinph.2024.08.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2024] [Revised: 08/07/2024] [Accepted: 08/09/2024] [Indexed: 09/04/2024]
Abstract
BACKGROUND In school-age children, the myelination of the auditory radiation thalamocortical pathway is associated with the latency of auditory evoked responses, with the myelination of thalamocortical axons facilitating the rapid propagation of acoustic information. Little is known regarding this auditory system function-structure association in infants and toddlers. METHODS AND PARTICIPANTS The present study tested the hypothesis that maturation of auditory radiation white-matter microstructure (e.g., fractional anisotropy (FA); measured using diffusion-weighted MRI) is associated with the latency of the infant auditory response (the P2m response, measured using magnetoencephalography, MEG) in a cross-sectional (N = 47, 2 to 24 months, 19 females) as well as longitudinal cohort (N = 18, 2 to 29 months, 8 females) of typically developing infants and toddlers. Of 18 longitudinal infants, 2 infants had data from 3 timepoints and 16 infants had data from 2 timepoints. RESULTS In the cross-sectional sample, non-linear maturation of P2m latency and auditory radiation diffusion measures were observed. Auditory radiation diffusion accounted for significant variance in P2m latency, even after removing the variance associated with age in both P2m latency and auditory radiation diffusion measures. In the longitudinal sample, latency and FA associations could be observed at the level of a single child. CONCLUSIONS Findings provide strong support for the hypothesis that an increase in thalamocortical neural conduction velocity, due to increased axon diameter and/or myelin maturation, contributes to a decrease in the infant P2m auditory evoked response latency. SIGNIFICANCE Infant multimodal brain imaging identifies brain mechanisms contributing to the rapid changes in neural circuit activity during the first two years of life.
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Affiliation(s)
- Yuhan Chen
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
| | - Heather L Green
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Jeffrey I Berman
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Mary E Putt
- Department of Biostatistics, Epidemiology & Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Katharina Otten
- Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Faculty of Medicine, RWTH Aachen University, Aachen, 52074, Germany
| | - Kylie Mol
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Marybeth McNamee
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Olivia Allison
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Emily S Kuschner
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Mina Kim
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Luke Bloy
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Song Liu
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Tess Yount
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Timothy P L Roberts
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - J Christopher Edgar
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
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Larionova E, Garakh Z. Spelling principles matter: An ERP study investigating the processing of different types of pseudohomophones. Brain Res 2024; 1839:149012. [PMID: 38772521 DOI: 10.1016/j.brainres.2024.149012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 05/15/2024] [Accepted: 05/16/2024] [Indexed: 05/23/2024]
Abstract
Spelling in any writing system is governed by fundamental principles. We examined the processing of two types of pseudohomophones constructed from words whose spellings are based on different principles - on the traditional principle of writing, requiring memorization of their spelling, and on the morphological principle, allowing the determination of their spelling from another word with the same morpheme (root) to examine the dependence of the occurrence of orthography-phonology conflict on spelling principles. Event-related potentials were recorded from 22 volunteers during silent reading. Pseudohomophones based on the morphological principle increased the N400 amplitude, emphasizing semantic and morphological processing importance. The P600 component showed significant effects for differentiating words and pseudohomophones based on the traditional principle, predominantly indicating the involvement of memory and reanalysis processes. Source reconstruction demonstrates that both pseudohomophones activate the left inferior frontal gyrus. However, pseudohomophones based on the traditional principle additionally activate the right and left postcentral gyrus, indicating the involvement of additional areas in the differentiation process. The earlier differences for stimuli based on the morphological principle indicate access to smaller units (morphemes), whereas stimuli based on the traditional principle require whole word processing. Our findings underscore the significant role of spelling principles in orthographic processing.
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Affiliation(s)
- Ekaterina Larionova
- Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, Moscow, Russian Federation.
| | - Zhanna Garakh
- Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, Moscow, Russian Federation
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O'Reilly JA, Zhu JD, Sowman PF. Localized estimation of event-related neural source activity from simultaneous MEG-EEG with a recurrent neural network. Neural Netw 2024; 180:106731. [PMID: 39303603 DOI: 10.1016/j.neunet.2024.106731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Revised: 09/05/2024] [Accepted: 09/10/2024] [Indexed: 09/22/2024]
Abstract
Estimating intracranial current sources underlying the electromagnetic signals observed from extracranial sensors is a perennial challenge in non-invasive neuroimaging. Established solutions to this inverse problem treat time samples independently without considering the temporal dynamics of event-related brain processes. This paper describes current source estimation from simultaneously recorded magneto- and electro-encephalography (MEEG) using a recurrent neural network (RNN) that learns sequential relationships from neural data. The RNN was trained in two phases: (1) pre-training and (2) transfer learning with L1 regularization applied to the source estimation layer. Performance of using scaled labels derived from MEEG, magnetoencephalography (MEG), or electroencephalography (EEG) were compared, as were results from volumetric source space with free dipole orientation and surface source space with fixed dipole orientation. Exact low-resolution electromagnetic tomography (eLORETA) and mixed-norm L1/L2 (MxNE) source estimation methods were also applied to these data for comparison with the RNN method. The RNN approach outperformed other methods in terms of output signal-to-noise ratio, correlation and mean-squared error metrics evaluated against reference event-related field (ERF) and event-related potential (ERP) waveforms. Using MEEG labels with fixed-orientation surface sources produced the most consistent estimates. To estimate sources of ERF and ERP waveforms, the RNN generates temporal dynamics within its internal computational units, driven by sequential structure in neural data used as training labels. It thus provides a data-driven model of computational transformations from psychophysiological events into corresponding event-related neural signals, which is unique among MEEG source reconstruction solutions.
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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, New South Wales, 2109, Australia
| | - Paul F Sowman
- School of Psychological Sciences, Macquarie University, New South Wales, 2109, Australia; School of Clinical Sciences, Auckland University of Technology, Auckland, 1142, New Zealand
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Monchy N, Modolo J, Houvenaghel JF, Voytek B, Duprez J. Changes in electrophysiological aperiodic activity during cognitive control in Parkinson's disease. Brain Commun 2024; 6:fcae306. [PMID: 39301291 PMCID: PMC11411214 DOI: 10.1093/braincomms/fcae306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Revised: 07/01/2024] [Accepted: 09/05/2024] [Indexed: 09/22/2024] Open
Abstract
Cognitive symptoms in Parkinson's disease are common and can significantly affect patients' quality of life. Therefore, there is an urgent clinical need to identify a signature derived from behavioural and/or neuroimaging indicators that could predict which patients are at increased risk for early and rapid cognitive decline. Recently, converging evidence identified that aperiodic activity of the EEG reflects meaningful physiological information associated with age, development, cognitive and perceptual states or pathologies. In this study, we aimed to investigate aperiodic activity in Parkinson's disease during cognitive control and characterize its possible association with behaviour. Here, we recorded high-density EEG in 30 healthy controls and 30 Parkinson's disease patients during a Simon task. We analysed task-related behavioural data in the context of the activation-suppression model and extracted aperiodic parameters (offset, exponent) at both scalp and source levels. Our results showed lower behavioural performances in cognitive control as well as higher offsets in patients in the parieto-occipital areas, suggesting increased excitability in Parkinson's disease. A small congruence effect on aperiodic parameters in pre- and post-central brain areas was also found, possibly associated with task execution. Significant differences in aperiodic parameters between the resting-state, pre- and post-stimulus phases were seen across the whole brain, which confirmed that the observed changes in aperiodic activity are linked to task execution. No correlation was found between aperiodic activity and behaviour or clinical features. Our findings provide evidence that EEG aperiodic activity in Parkinson's disease is characterized by greater offsets, and that aperiodic parameters differ depending on arousal state. However, our results do not support the hypothesis that the behaviour-related differences observed in Parkinson's disease are related to aperiodic changes. Overall, this study highlights the importance of considering aperiodic activity contributions in brain disorders and further investigating the relationship between aperiodic activity and behaviour.
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Affiliation(s)
- Noémie Monchy
- LTSI-U1099, University of Rennes, Rennes F-35000, France
| | - Julien Modolo
- LTSI-U1099, University of Rennes, Rennes F-35000, France
| | - Jean-François Houvenaghel
- LTSI-U1099, University of Rennes, Rennes F-35000, France
- Department of Neurology, Rennes University Hospital, Rennes 35033, France
| | - Bradley Voytek
- Department of Cognitive Science, Halıcıoğlu Data Science Institute, University of California, San Diego, La Jolla, CA, USA
| | - Joan Duprez
- LTSI-U1099, University of Rennes, Rennes F-35000, France
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Samoylov I, Arcara G, Buyanova I, Davydova E, Pereverzeva D, Sorokin A, Tyushkevich S, Mamokhina U, Danilina K, Dragoy O, Arutiunian V. Altered neural synchronization in response to 2 Hz amplitude-modulated tones in the auditory cortex of children with Autism Spectrum Disorder: An MEG study. Int J Psychophysiol 2024; 203:112405. [PMID: 39053734 DOI: 10.1016/j.ijpsycho.2024.112405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Revised: 05/13/2024] [Accepted: 07/17/2024] [Indexed: 07/27/2024]
Abstract
OBJECTIVE Some studies have hypothesized that atypical neural synchronization at the delta frequency band in the auditory cortex is associated with phonological and language skills in children with Autism Spectrum Disorder (ASD), but it is still poorly understood. This study investigated this neural activity and addressed the relationships between auditory response and behavioral measures of children with ASD. METHODS We used magnetoencephalography and individual brain models to investigate 2 Hz Auditory Steady-State Response (ASSR) in 20 primary-school-aged children with ASD and 20 age-matched typically developing (TD) controls. RESULTS First, we found a between-group difference in the localization of the auditory response, so as the topology of 2 Hz ASSR was more superior and posterior in TD children when comparing to children with ASD. Second, the power of 2 Hz ASSR was reduced in the ASD group. Finally, we observed a significant association between the amplitude of neural response and language skills in children with ASD. CONCLUSIONS The study provided the evidence of reduced neural response in children with ASD and its relation to language skills. SIGNIFICANCE These findings may inform future interventions targeting auditory and language impairments in ASD population.
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Affiliation(s)
- Ilya Samoylov
- Center for Language and Brain, HSE University, Moscow, Russia.
| | | | - Irina Buyanova
- Center for Language and Brain, HSE University, Moscow, Russia; University of Otago, Dunedin, New Zealand
| | - Elizaveta Davydova
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Moscow, Russia; Chair of Differential Psychology and Psychophysiology, Moscow State University of Psychology and Education, Moscow, Russia
| | - Darya Pereverzeva
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Moscow, Russia
| | - Alexander Sorokin
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Moscow, Russia; Haskins Laboratories, New Haven, CT, USA
| | - Svetlana Tyushkevich
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Moscow, Russia
| | - Uliana Mamokhina
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Moscow, Russia
| | - Kamilla Danilina
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Moscow, Russia; Scientific Research and Practical Center for Pediatric Psychoneurology, Moscow, Russia
| | - Olga Dragoy
- Center for Language and Brain, HSE University, Moscow, Russia; Institute of Linguistics, Russian Academy of Sciences, Moscow, Russia
| | - Vardan Arutiunian
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, Seattle, WA, USA
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Mahjoory K, Bahmer A, Henry MJ. Convolutional neural networks can identify brain interactions involved in decoding spatial auditory attention. PLoS Comput Biol 2024; 20:e1012376. [PMID: 39116183 PMCID: PMC11335149 DOI: 10.1371/journal.pcbi.1012376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 08/20/2024] [Accepted: 07/30/2024] [Indexed: 08/10/2024] Open
Abstract
Human listeners have the ability to direct their attention to a single speaker in a multi-talker environment. The neural correlates of selective attention can be decoded from a single trial of electroencephalography (EEG) data. In this study, leveraging the source-reconstructed and anatomically-resolved EEG data as inputs, we sought to employ CNN as an interpretable model to uncover task-specific interactions between brain regions, rather than simply to utilize it as a black box decoder. To this end, our CNN model was specifically designed to learn pairwise interaction representations for 10 cortical regions from five-second inputs. By exclusively utilizing these features for decoding, our model was able to attain a median accuracy of 77.56% for within-participant and 65.14% for cross-participant classification. Through ablation analysis together with dissecting the features of the models and applying cluster analysis, we were able to discern the presence of alpha-band-dominated inter-hemisphere interactions, as well as alpha- and beta-band dominant interactions that were either hemisphere-specific or were characterized by a contrasting pattern between the right and left hemispheres. These interactions were more pronounced in parietal and central regions for within-participant decoding, but in parietal, central, and partly frontal regions for cross-participant decoding. These findings demonstrate that our CNN model can effectively utilize features known to be important in auditory attention tasks and suggest that the application of domain knowledge inspired CNNs on source-reconstructed EEG data can offer a novel computational framework for studying task-relevant brain interactions.
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Affiliation(s)
- Keyvan Mahjoory
- Max Planck Institute for Empirical Aesthetics, Frankfurt am Main, Germany
| | - Andreas Bahmer
- RheinMain University of Applied Sciences Campus Ruesselsheim, Wiesbaden, Germany
| | - Molly J. Henry
- Max Planck Institute for Empirical Aesthetics, Frankfurt am Main, Germany
- Department of Psychology, Toronto Metropolitan University, Toronto, Ontario, Canada
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Mohd Rashid MH, Ab Rani NS, Kannan M, Abdullah MW, Ab Ghani MA, Kamel N, Mustapha M. Emotion brain network topology in healthy subjects following passive listening to different auditory stimuli. PeerJ 2024; 12:e17721. [PMID: 39040935 PMCID: PMC11262303 DOI: 10.7717/peerj.17721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Accepted: 06/19/2024] [Indexed: 07/24/2024] Open
Abstract
A large body of research establishes the efficacy of musical intervention in many aspects of physical, cognitive, communication, social, and emotional rehabilitation. However, the underlying neural mechanisms for musical therapy remain elusive. This study aimed to investigate the potential neural correlates of musical therapy, focusing on the changes in the topology of emotion brain network. To this end, a Bayesian statistical approach and a cross-over experimental design were employed together with two resting-state magnetoencephalography (MEG) as controls. MEG recordings of 30 healthy subjects were acquired while listening to five auditory stimuli in random order. Two resting-state MEG recordings of each subject were obtained, one prior to the first stimulus (pre) and one after the final stimulus (post). Time series at the level of brain regions were estimated using depth-weighted minimum norm estimation (wMNE) source reconstruction method and the functional connectivity between these regions were computed. The resultant connectivity matrices were used to derive two topological network measures: transitivity and global efficiency which are important in gauging the functional segregation and integration of brain network respectively. The differences in these measures between pre- and post-stimuli resting MEG were set as the equivalence regions. We found that the network measures under all auditory stimuli were equivalent to the resting state network measures in all frequency bands, indicating that the topology of the functional brain network associated with emotional regulation in healthy subjects remains unchanged following these auditory stimuli. This suggests that changes in the emotion network topology may not be the underlying neural mechanism of musical therapy. Nonetheless, further studies are required to explore the neural mechanisms of musical interventions especially in the populations with neuropsychiatric disorders.
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Affiliation(s)
- Muhammad Hakimi Mohd Rashid
- Department of Basic Medical Sciences, Kulliyyah of Pharmacy, International Islamic University, Kuantan, Pahang, Malaysia
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu, Kelantan, Malaysia
| | - Nur Syairah Ab Rani
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu, Kelantan, Malaysia
| | - Mohammed Kannan
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu, Kelantan, Malaysia
- Department of Anatomy, Faculty of Medicine, Al Neelain University, Khartoum, Khartoum, Sudan
| | - Mohd Waqiyuddin Abdullah
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu, Kelantan, Malaysia
| | - Muhammad Amiri Ab Ghani
- Jabatan Al-Quran & Hadis, Kolej Islam Antarabangsa Sultan Ismail Petra, Nilam Puri, Kota Bharu, Kelantan, Malaysia
| | - Nidal Kamel
- Centre for Intelligent Signal & Imaging Research (CISIR), Electrical & Electronic Engineering Department, Universiti Teknologi PETRONAS, Seri Iskandar, Perak, Malaysia
| | - Muzaimi Mustapha
- Department of Neurosciences, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian, Kota Bharu, Kelantan, Malaysia
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Afnan J, Cai Z, Lina JM, Abdallah C, Delaire E, Avigdor T, Ros V, Hedrich T, von Ellenrieder N, Kobayashi E, Frauscher B, Gotman J, Grova C. EEG/MEG source imaging of deep brain activity within the maximum entropy on the mean framework: Simulations and validation in epilepsy. Hum Brain Mapp 2024; 45:e26720. [PMID: 38994740 PMCID: PMC11240147 DOI: 10.1002/hbm.26720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 04/16/2024] [Accepted: 05/06/2024] [Indexed: 07/13/2024] Open
Abstract
Electro/Magneto-EncephaloGraphy (EEG/MEG) source imaging (EMSI) of epileptic activity from deep generators is often challenging due to the higher sensitivity of EEG/MEG to superficial regions and to the spatial configuration of subcortical structures. We previously demonstrated the ability of the coherent Maximum Entropy on the Mean (cMEM) method to accurately localize the superficial cortical generators and their spatial extent. Here, we propose a depth-weighted adaptation of cMEM to localize deep generators more accurately. These methods were evaluated using realistic MEG/high-density EEG (HD-EEG) simulations of epileptic activity and actual MEG/HD-EEG recordings from patients with focal epilepsy. We incorporated depth-weighting within the MEM framework to compensate for its preference for superficial generators. We also included a mesh of both hippocampi, as an additional deep structure in the source model. We generated 5400 realistic simulations of interictal epileptic discharges for MEG and HD-EEG involving a wide range of spatial extents and signal-to-noise ratio (SNR) levels, before investigating EMSI on clinical HD-EEG in 16 patients and MEG in 14 patients. Clinical interictal epileptic discharges were marked by visual inspection. We applied three EMSI methods: cMEM, depth-weighted cMEM and depth-weighted minimum norm estimate (MNE). The ground truth was defined as the true simulated generator or as a drawn region based on clinical information available for patients. For deep sources, depth-weighted cMEM improved the localization when compared to cMEM and depth-weighted MNE, whereas depth-weighted cMEM did not deteriorate localization accuracy for superficial regions. For patients' data, we observed improvement in localization for deep sources, especially for the patients with mesial temporal epilepsy, for which cMEM failed to reconstruct the initial generator in the hippocampus. Depth weighting was more crucial for MEG (gradiometers) than for HD-EEG. Similar findings were found when considering depth weighting for the wavelet extension of MEM. In conclusion, depth-weighted cMEM improved the localization of deep sources without or with minimal deterioration of the localization of the superficial sources. This was demonstrated using extensive simulations with MEG and HD-EEG and clinical MEG and HD-EEG for epilepsy patients.
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Affiliation(s)
- Jawata Afnan
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, Canada
- Integrated Program in Neuroscience, McGill University, Montréal, Québec, Canada
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Zhengchen Cai
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Jean-Marc Lina
- Physnum Team, Centre De Recherches Mathématiques, Montréal, Québec, Canada
- Electrical Engineering Department, École De Technologie Supérieure, Montréal, Québec, Canada
- Center for Advanced Research in Sleep Medicine, Sacré-Coeur Hospital, Montréal, Québec, Canada
| | - Chifaou Abdallah
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, Canada
- Integrated Program in Neuroscience, McGill University, Montréal, Québec, Canada
- Analytical Neurophysiology Lab, Department of Neurology, Duke University School of Medicine, Durham, North Carolina, USA
| | - Edouard Delaire
- Multimodal Functional Imaging Lab, Department of Physics and Concordia School of Health, Concordia University, Montréal, Québec, Canada
| | - Tamir Avigdor
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, Canada
- Integrated Program in Neuroscience, McGill University, Montréal, Québec, Canada
- Analytical Neurophysiology Lab, Department of Neurology, Duke University School of Medicine, Durham, North Carolina, USA
| | - Victoria Ros
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Tanguy Hedrich
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, Canada
| | - Nicolas von Ellenrieder
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Eliane Kobayashi
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Birgit Frauscher
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
- Analytical Neurophysiology Lab, Department of Neurology, Duke University School of Medicine, Durham, North Carolina, USA
| | - Jean Gotman
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
| | - Christophe Grova
- Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, Montréal, Québec, Canada
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montréal, Québec, Canada
- Physnum Team, Centre De Recherches Mathématiques, Montréal, Québec, Canada
- Multimodal Functional Imaging Lab, Department of Physics and Concordia School of Health, Concordia University, Montréal, Québec, Canada
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Démas J, Bourguignon M, Bailly R, Bouvier S, Brochard S, Dinomais M, Van Bogaert P. Test-retest reliability of corticokinematic coherence in young children with cerebral palsy: An observational longitudinal study. Neurophysiol Clin 2024; 54:102965. [PMID: 38547685 DOI: 10.1016/j.neucli.2024.102965] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 02/27/2024] [Accepted: 02/27/2024] [Indexed: 06/24/2024] Open
Abstract
OBJECTIVES To assess the test-retest reliability of the corticokinematic coherence (CKC), an electrophysiological marker of proprioception, in children with cerebral palsy (CP). METHODS Electroencephalography (EEG) signals from 15 children with unilateral or bilateral CP aged 23 to 53 months were recorded in two sessions 3 months apart using 128-channel EEG caps. During each session, children's fingers were moved at 2 Hz by an experimenter, in separate recordings for the more-affected (MA) and less-affected (LA) hands. The CKC was computed at the electrode and source levels, at movement frequency F0 (2 Hz) and its first harmonic F1 (4 Hz). A two-way mixed-effects model intraclass-correlation coefficient (ICC) was computed for the maximum CKC strength across electrodes at F0 and F1 obtained during the two sessions. RESULTS ICC of the CKC strength acquired from LA and MA hands pooled together were respectively 0.51 (95% CI: 0.30-0.68) at F0 and 0.96 (95% CI: 0.93-0.98) at F1. The mean distances separating the CKC peaks in the source space at the two evaluation times were in the order of a centimeter. CONCLUSION CKC is a robust electrophysiologic marker to study the longitudinal changes in cortical processing of proprioceptive afferences in young children with CP.
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Affiliation(s)
- Josselin Démas
- Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS), Université d'Angers, France; Instituts de formation du Centre Hospitalier de Laval, France.
| | - Mathieu Bourguignon
- Laboratoire de Neuroanatomie et Neuroimagerie translationnelles (LN2T), UNI - ULB Neuroscience Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium; Laboratory of neurophysiology and movement biomechanics (LNMB), UNI - ULB Neuroscience Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium
| | - Rodolphe Bailly
- INSERM UMR 1101, LaTIM, Brest, France; Western Britany University, Brest, France; Pediatric rehabilitation department, Fondation Ildys, Brest, France Brussels, Belgium
| | - Sandra Bouvier
- INSERM UMR 1101, LaTIM, Brest, France; Western Britany University, Brest, France
| | - Sylvain Brochard
- INSERM UMR 1101, LaTIM, Brest, France; Western Britany University, Brest, France; Pediatric rehabilitation department, Fondation Ildys, Brest, France Brussels, Belgium
| | - Mickael Dinomais
- Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS), Université d'Angers, France; Département de Médecine Physique et de Réadaptation, CHU d'Angers -Les Capucins, France
| | - Patrick Van Bogaert
- Laboratoire Angevin de Recherche en Ingénierie des Systèmes (LARIS), Université d'Angers, France; Unité de Neuropédiatrie et de Neurochirurgie de l'enfant, CHU d'Angers, France
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11
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Otten K, Edgar JC, Green HL, Mol K, McNamee M, Kuschner ES, Kim M, Liu S, Huang H, Nordt M, Konrad K, Chen Y. The maturation of infant and toddler visual cortex neural activity and associations with fine motor performance. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.11.598480. [PMID: 38915536 PMCID: PMC11195154 DOI: 10.1101/2024.06.11.598480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Our understanding of how visual cortex neural processes mature during infancy and toddlerhood is limited. Using magnetoencephalography (MEG), the present study investigated the development of visual evoked responses (VERs) in both cross-sectional and longitudinal samples of infants and toddlers 2 months to 3 years. Brain space analyses focused on N1m and P1m latency, as well as the N1m-to-P1m amplitude. Associations between VER measures and developmental quotient (DQ) scores in the cognitive/visual and fine motor domains were also examined. Results showed a nonlinear decrease in N1m and P1m latency as a function of age, characterized by rapid changes followed by slower progression, with the N1m latency plateauing at 6-7 months and the P1m latency plateauing at 8-9 months. The N1m-to-P1m amplitude also exhibited a non-linear decrease, with strong responses observed in younger infants (∼2-3 months) and then a gradual decline. Associations between N1m and P1m latency and fine motor DQ scores were observed, suggesting that infants with faster visual processing may be better equipped to perform fine motor tasks. The present findings advance our understanding of the maturation of the infant visual system and highlight the relationship between the maturation of visual system and fine motor skills. Highlights The infant N1m and P1m latency shows a nonlinear decrease.N1m latency decreases precede P1m latency decreases.N1m-to-P1m amplitude shows a nonlinear decrease, with stronger responses in younger than older infants.N1m and P1m latency are associated with fine motor DQ.
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12
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Chen Y, Green HL, Berman JI, Putt ME, Otten K, Mol KL, McNamee M, Allison O, Kuschner ES, Kim M, Bloy L, Liu S, Yount T, Roberts TPL, Edgar JC. Functional and structural maturation of auditory cortex from 2 months to 2 years old. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.05.597426. [PMID: 38895425 PMCID: PMC11185738 DOI: 10.1101/2024.06.05.597426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
In school-age children, the myelination of the auditory radiation thalamocortical pathway is associated with the latency of auditory evoked responses, with the myelination of thalamocortical axons facilitating the rapid propagation of acoustic information. Little is known regarding this auditory system function-structure association in infants and toddlers. The present study tested the hypothesis that maturation of auditory radiation white-matter microstructure (e.g., fractional anisotropy (FA); measured using diffusion-weighted MRI) is associated with the latency of the infant auditory response (P2m measured using magnetoencephalography, MEG) in a cross-sectional (2 to 24 months) as well as longitudinal cohort (2 to 29 months) of typically developing infants and toddlers. In the cross-sectional sample, non-linear maturation of P2m latency and auditory radiation diffusion measures were observed. After removing the variance associated with age in both P2m latency and auditory radiation diffusion measures, auditory radiation still accounted for significant variance in P2m latency. In the longitudinal sample, latency and FA associations could be observed at the level of a single child. Findings provide strong support for a contribution of auditory radiation white matter to rapid cortical auditory encoding processes in infants.
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13
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Arutiunian V, Arcara G, Buyanova I, Fedorov M, Davydova E, Pereverzeva D, Sorokin A, Tyushkevich S, Mamokhina U, Danilina K, Dragoy O. Abnormalities in both stimulus-induced and baseline MEG alpha oscillations in the auditory cortex of children with Autism Spectrum Disorder. Brain Struct Funct 2024; 229:1225-1242. [PMID: 38683212 DOI: 10.1007/s00429-024-02802-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2023] [Accepted: 04/22/2024] [Indexed: 05/01/2024]
Abstract
The neurobiology of Autism Spectrum Disorder (ASD) is hypothetically related to the imbalance between neural excitation (E) and inhibition (I). Different studies have revealed that alpha-band (8-12 Hz) activity in magneto- and electroencephalography (MEG and EEG) may reflect E and I processes and, thus, can be of particular interest in ASD research. Previous findings indicated alterations in event-related and baseline alpha activity in different cortical systems in individuals with ASD, and these abnormalities were associated with core and co-occurring conditions of ASD. However, the knowledge on auditory alpha oscillations in this population is limited. This MEG study investigated stimulus-induced (Event-Related Desynchronization, ERD) and baseline alpha-band activity (both periodic and aperiodic) in the auditory cortex and also the relationships between these neural activities and behavioral measures of children with ASD. Ninety amplitude-modulated tones were presented to two groups of children: 20 children with ASD (5 girls, Mage = 10.03, SD = 1.7) and 20 typically developing controls (9 girls, Mage = 9.11, SD = 1.3). Children with ASD had a bilateral reduction of alpha-band ERD, reduced baseline aperiodic-adjusted alpha power, and flattened aperiodic exponent in comparison to TD children. Moreover, lower raw baseline alpha power and aperiodic offset in the language-dominant left auditory cortex were associated with better language skills of children with ASD measured in formal assessment. The findings highlighted the alterations of E / I balance metrics in response to basic auditory stimuli in children with ASD and also provided evidence for the contribution of low-level processing to language difficulties in ASD.
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Affiliation(s)
- Vardan Arutiunian
- Center for Child Health, Behavior and Development, Seattle Children's Research Institute, 1920 Terry Ave, Seattle, WA, 98101, United States of America.
| | | | - Irina Buyanova
- Center for Language and Brain, HSE University, Moscow, Russia
- University of Otago, Dunedin, New Zealand
| | - Makar Fedorov
- Center for Language and Brain, HSE University, Nizhny Novgorod, Russia
| | - Elizaveta Davydova
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Moscow, Russia
- Chair of Differential Psychology and Psychophysiology, Moscow State University of Psychology and Education, Moscow, Russia
| | - Darya Pereverzeva
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Moscow, Russia
| | - Alexander Sorokin
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Moscow, Russia
- Haskins Laboratories, New Haven, CT, United States of America
| | - Svetlana Tyushkevich
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Moscow, Russia
| | - Uliana Mamokhina
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Moscow, Russia
| | - Kamilla Danilina
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Moscow, Russia
- Scientific Research and Practical Center of Pediatric Psychoneurology, Moscow, Russia
| | - Olga Dragoy
- Center for Language and Brain, HSE University, Moscow, Russia
- Institute of Linguistics, Russian Academy of Sciences, Moscow, Russia
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14
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Weglage A, Layer N, Meister H, Müller V, Lang-Roth R, Walger M, Sandmann P. Changes in visually and auditory attended audiovisual speech processing in cochlear implant users: A longitudinal ERP study. Hear Res 2024; 447:109023. [PMID: 38733710 DOI: 10.1016/j.heares.2024.109023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 03/25/2024] [Accepted: 04/26/2024] [Indexed: 05/13/2024]
Abstract
Limited auditory input, whether caused by hearing loss or by electrical stimulation through a cochlear implant (CI), can be compensated by the remaining senses. Specifically for CI users, previous studies reported not only improved visual skills, but also altered cortical processing of unisensory visual and auditory stimuli. However, in multisensory scenarios, it is still unclear how auditory deprivation (before implantation) and electrical hearing experience (after implantation) affect cortical audiovisual speech processing. Here, we present a prospective longitudinal electroencephalography (EEG) study which systematically examined the deprivation- and CI-induced alterations of cortical processing of audiovisual words by comparing event-related potentials (ERPs) in postlingually deafened CI users before and after implantation (five weeks and six months of CI use). A group of matched normal-hearing (NH) listeners served as controls. The participants performed a word-identification task with congruent and incongruent audiovisual words, focusing their attention on either the visual (lip movement) or the auditory speech signal. This allowed us to study the (top-down) attention effect on the (bottom-up) sensory cortical processing of audiovisual speech. When compared to the NH listeners, the CI candidates (before implantation) and the CI users (after implantation) exhibited enhanced lipreading abilities and an altered cortical response at the N1 latency range (90-150 ms) that was characterized by a decreased theta oscillation power (4-8 Hz) and a smaller amplitude in the auditory cortex. After implantation, however, the auditory-cortex response gradually increased and developed a stronger intra-modal connectivity. Nevertheless, task efficiency and activation in the visual cortex was significantly modulated in both groups by focusing attention on the visual as compared to the auditory speech signal, with the NH listeners additionally showing an attention-dependent decrease in beta oscillation power (13-30 Hz). In sum, these results suggest remarkable deprivation effects on audiovisual speech processing in the auditory cortex, which partially reverse after implantation. Although even experienced CI users still show distinct audiovisual speech processing compared to NH listeners, pronounced effects of (top-down) direction of attention on (bottom-up) audiovisual processing can be observed in both groups. However, NH listeners but not CI users appear to show enhanced allocation of cognitive resources in visually as compared to auditory attended audiovisual speech conditions, which supports our behavioural observations of poorer lipreading abilities and reduced visual influence on audition in NH listeners as compared to CI users.
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Affiliation(s)
- Anna Weglage
- Head and Neck Surgery, Audiology and Pediatric Audiology, Cochlear Implant Centre, University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Otorhinolaryngology, Germany.
| | - Natalie Layer
- Head and Neck Surgery, Audiology and Pediatric Audiology, Cochlear Implant Centre, University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Otorhinolaryngology, Germany
| | - Hartmut Meister
- Head and Neck Surgery, Audiology and Pediatric Audiology, Cochlear Implant Centre, University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Otorhinolaryngology, Germany; Jean-Uhrmacher-Institute for Clinical ENT Research, University of Cologne, Germany
| | - Verena Müller
- Head and Neck Surgery, Audiology and Pediatric Audiology, Cochlear Implant Centre, University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Otorhinolaryngology, Germany
| | - Ruth Lang-Roth
- Head and Neck Surgery, Audiology and Pediatric Audiology, Cochlear Implant Centre, University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Otorhinolaryngology, Germany
| | - Martin Walger
- Head and Neck Surgery, Audiology and Pediatric Audiology, Cochlear Implant Centre, University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Otorhinolaryngology, Germany; Jean-Uhrmacher-Institute for Clinical ENT Research, University of Cologne, Germany
| | - Pascale Sandmann
- Department of Otolaryngology, Head and Neck Surgery, Carl von Ossietzky University of Oldenburg, Germany; Research Center Neurosensory Science University of Oldenburg, Germany; Cluster of Excellence "Hearing4all", University of Oldenburg, Germany
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15
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Nora A, Rinkinen O, Renvall H, Service E, Arkkila E, Smolander S, Laasonen M, Salmelin R. Impaired Cortical Tracking of Speech in Children with Developmental Language Disorder. J Neurosci 2024; 44:e2048232024. [PMID: 38589232 PMCID: PMC11140678 DOI: 10.1523/jneurosci.2048-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 03/25/2024] [Accepted: 03/26/2024] [Indexed: 04/10/2024] Open
Abstract
In developmental language disorder (DLD), learning to comprehend and express oneself with spoken language is impaired, but the reason for this remains unknown. Using millisecond-scale magnetoencephalography recordings combined with machine learning models, we investigated whether the possible neural basis of this disruption lies in poor cortical tracking of speech. The stimuli were common spoken Finnish words (e.g., dog, car, hammer) and sounds with corresponding meanings (e.g., dog bark, car engine, hammering). In both children with DLD (10 boys and 7 girls) and typically developing (TD) control children (14 boys and 3 girls), aged 10-15 years, the cortical activation to spoken words was best modeled as time-locked to the unfolding speech input at ∼100 ms latency between sound and cortical activation. Amplitude envelope (amplitude changes) and spectrogram (detailed time-varying spectral content) of the spoken words, but not other sounds, were very successfully decoded based on time-locked brain responses in bilateral temporal areas; based on the cortical responses, the models could tell at ∼75-85% accuracy which of the two sounds had been presented to the participant. However, the cortical representation of the amplitude envelope information was poorer in children with DLD compared with TD children at longer latencies (at ∼200-300 ms lag). We interpret this effect as reflecting poorer retention of acoustic-phonetic information in short-term memory. This impaired tracking could potentially affect the processing and learning of words as well as continuous speech. The present results offer an explanation for the problems in language comprehension and acquisition in DLD.
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Affiliation(s)
- Anni Nora
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo FI-00076, Finland
- Aalto NeuroImaging (ANI), Aalto University, Espoo FI-00076, Finland
| | - Oona Rinkinen
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo FI-00076, Finland
- Aalto NeuroImaging (ANI), Aalto University, Espoo FI-00076, Finland
| | - Hanna Renvall
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo FI-00076, Finland
- Aalto NeuroImaging (ANI), Aalto University, Espoo FI-00076, Finland
- BioMag Laboratory, HUS Diagnostic Center, Helsinki University Hospital, Helsinki FI-00029, Finland
| | - Elisabet Service
- Department of Linguistics and Languages, Centre for Advanced Research in Experimental and Applied Linguistics (ARiEAL), McMaster University, Hamilton, Ontario L8S 4L8, Canada
- Department of Psychology and Logopedics, University of Helsinki, Helsinki FI-00014, Finland
| | - Eva Arkkila
- Department of Otorhinolaryngology and Phoniatrics, Head and Neck Center, Helsinki University Hospital and University of Helsinki, Helsinki FI-00014, Finland
| | - Sini Smolander
- Department of Otorhinolaryngology and Phoniatrics, Head and Neck Center, Helsinki University Hospital and University of Helsinki, Helsinki FI-00014, Finland
- Research Unit of Logopedics, University of Oulu, Oulu FI-90014, Finland
- Department of Logopedics, University of Eastern Finland, Joensuu FI-80101, Finland
| | - Marja Laasonen
- Department of Otorhinolaryngology and Phoniatrics, Head and Neck Center, Helsinki University Hospital and University of Helsinki, Helsinki FI-00014, Finland
- Department of Logopedics, University of Eastern Finland, Joensuu FI-80101, Finland
| | - Riitta Salmelin
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo FI-00076, Finland
- Aalto NeuroImaging (ANI), Aalto University, Espoo FI-00076, Finland
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16
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Hoshi H, Ishii A, Shigihara Y, Yoshikawa T. Binocularly suppressed stimuli induce brain activities related to aesthetic emotions. Front Neurosci 2024; 18:1339479. [PMID: 38855441 PMCID: PMC11159128 DOI: 10.3389/fnins.2024.1339479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 04/16/2024] [Indexed: 06/11/2024] Open
Abstract
Introduction Aesthetic emotions are a class of emotions aroused by evaluating aesthetically appealing objects or events. While evolutionary aesthetics suggests the adaptive roles of these emotions, empirical assessments are lacking. Previous neuroscientific studies have demonstrated that visual stimuli carrying evolutionarily important information induce neural responses even when presented non-consciously. To examine the evolutionary importance of aesthetic emotions, we conducted a neuroscientific study using magnetoencephalography (MEG) to measure induced neural responses to non-consciously presented portrait paintings categorised as biological and non-biological and examined associations between the induced responses and aesthetic ratings. Methods MEG and pre-rating data were collected from 23 participants. The pre-rating included visual analogue scales for object saliency, facial saliency, liking, and beauty scores, in addition to 'biologi-ness,' which was used for subcategorising stimuli into biological and non-biological. The stimuli were presented non-consciously using a continuous flash suppression paradigm or consciously using binocular presentation without flashing masks, while dichotomic behavioural responses were obtained (beauty or non-beauty). Time-frequency decomposed MEG data were used for correlation analysis with pre-rating scores for each category. Results Behavioural data revealed that saliency scores of non-consciously presented stimuli influenced dichotomic responses (beauty or non-beauty). MEG data showed that non-consciously presented portrait paintings induced spatiotemporally distributed low-frequency brain activities associated with aesthetic ratings, which were distinct between the biological and non-biological categories and conscious and non-conscious conditions. Conclusion Aesthetic emotion holds evolutionary significance for humans. Neural pathways are sensitive to visual images that arouse aesthetic emotion in distinct ways for biological and non-biological categories, which are further influenced by consciousness. These differences likely reflect the diversity in mechanisms of aesthetic processing, such as processing fluency, active elaboration, and predictive processing. The aesthetic processing of non-conscious stimuli appears to be characterised by fluency-driven affective processing, while top-down regulatory processes are suppressed. This study provides the first empirical evidence supporting the evolutionary significance of aesthetic processing.
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Affiliation(s)
- Hideyuki Hoshi
- Department of Sports Medicine, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
- Precision Medicine Centre, Hokuto Hospital, Obihiro, Japan
| | - Akira Ishii
- Department of Sports Medicine, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | | | - Takahiro Yoshikawa
- Department of Sports Medicine, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
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17
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Pruitt T, Davenport EM, Proskovec AL, Maldjian JA, Liu H. Simultaneous MEG and EEG source imaging of electrophysiological activity in response to acute transcranial photobiomodulation. Front Neurosci 2024; 18:1368172. [PMID: 38817913 PMCID: PMC11137218 DOI: 10.3389/fnins.2024.1368172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 04/22/2024] [Indexed: 06/01/2024] Open
Abstract
Introduction Transcranial photobiomodulation (tPBM) is a non-invasive neuromodulation technique that improves human cognition. The effects of tPBM of the right forehead on neurophysiological activity have been previously investigated using EEG in sensor space. However, the spatial resolution of these studies is limited. Magnetoencephalography (MEG) is known to facilitate a higher spatial resolution of brain source images. This study aimed to image post-tPBM effects in brain space based on both MEG and EEG measurements across the entire human brain. Methods MEG and EEG scans were concurrently acquired for 6 min before and after 8-min of tPBM delivered using a 1,064-nm laser on the right forehead of 25 healthy participants. Group-level changes in both the MEG and EEG power spectral density with respect to the baseline (pre-tPBM) were quantified and averaged within each frequency band in the sensor space. Constrained modeling was used to generate MEG and EEG source images of post-tPBM, followed by cluster-based permutation analysis for family wise error correction (p < 0.05). Results The 8-min tPBM enabled significant increases in alpha (8-12 Hz) and beta (13-30 Hz) powers across multiple cortical regions, as confirmed by MEG and EEG source images. Moreover, tPBM-enhanced oscillations in the beta band were located not only near the stimulation site but also in remote cerebral regions, including the frontal, parietal, and occipital regions, particularly on the ipsilateral side. Discussion MEG and EEG results shown in this study demonstrated that tPBM modulates neurophysiological activity locally and in distant cortical areas. The EEG topographies reported in this study were consistent with previous observations. This study is the first to present MEG and EEG evidence of the electrophysiological effects of tPBM in the brain space, supporting the potential utility of tPBM in treating neurological diseases through the modulation of brain oscillations.
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Affiliation(s)
- Tyrell Pruitt
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, United States
| | | | - Amy L. Proskovec
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, United States
| | - Joseph A. Maldjian
- Department of Radiology, UT Southwestern Medical Center, Dallas, TX, United States
| | - Hanli Liu
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, United States
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18
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Xu W, Li X, Parviainen T, Nokia M. Neural correlates of retrospective memory confidence during face-name associative learning. Cereb Cortex 2024; 34:bhae194. [PMID: 38801420 PMCID: PMC11411154 DOI: 10.1093/cercor/bhae194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 04/18/2024] [Accepted: 04/23/2024] [Indexed: 05/29/2024] Open
Abstract
The ability to accurately assess one's own memory performance during learning is essential for adaptive behavior, but the brain mechanisms underlying this metamemory function are not well understood. We investigated the neural correlates of memory accuracy and retrospective memory confidence in a face-name associative learning task using magnetoencephalography in healthy young adults (n = 32). We found that high retrospective confidence was associated with stronger occipital event-related fields during encoding and widespread event-related fields during retrieval compared to low confidence. On the other hand, memory accuracy was linked to medial temporal activities during both encoding and retrieval, but only in low-confidence trials. A decrease in oscillatory power at alpha/beta bands in the parietal regions during retrieval was associated with higher memory confidence. In addition, representational similarity analysis at the single-trial level revealed distributed but differentiable neural activities associated with memory accuracy and confidence during both encoding and retrieval. In summary, our study unveiled distinct neural activity patterns related to memory confidence and accuracy during associative learning and underscored the crucial role of parietal regions in metamemory.
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Affiliation(s)
- Weiyong Xu
- Department of Psychology, University of Jyväskylä, Mattilanniemi 6, 40014, Jyväskylä, Finland
- Jyväskylä Centre for Interdisciplinary Brain Research, University of Jyväskylä, Mattilanniemi 6, 40014, Jyväskylä, Finland
| | - Xueqiao Li
- Department of Psychology, University of Jyväskylä, Mattilanniemi 6, 40014, Jyväskylä, Finland
- Jyväskylä Centre for Interdisciplinary Brain Research, University of Jyväskylä, Mattilanniemi 6, 40014, Jyväskylä, Finland
| | - Tiina Parviainen
- Department of Psychology, University of Jyväskylä, Mattilanniemi 6, 40014, Jyväskylä, Finland
- Jyväskylä Centre for Interdisciplinary Brain Research, University of Jyväskylä, Mattilanniemi 6, 40014, Jyväskylä, Finland
| | - Miriam Nokia
- Department of Psychology, University of Jyväskylä, Mattilanniemi 6, 40014, Jyväskylä, Finland
- Jyväskylä Centre for Interdisciplinary Brain Research, University of Jyväskylä, Mattilanniemi 6, 40014, Jyväskylä, Finland
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19
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Ahlfors SP, Graham S, Bharadwaj H, Mamashli F, Khan S, Joseph RM, Losh A, Pawlyszyn S, McGuiggan NM, Vangel M, Hämäläinen MS, Kenet T. No Differences in Auditory Steady-State Responses in Children with Autism Spectrum Disorder and Typically Developing Children. J Autism Dev Disord 2024; 54:1947-1960. [PMID: 36932270 PMCID: PMC11463296 DOI: 10.1007/s10803-023-05907-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/23/2022] [Indexed: 03/19/2023]
Abstract
Auditory steady-state response (ASSR) has been studied as a potential biomarker for abnormal auditory sensory processing in autism spectrum disorder (ASD), with mixed results. Motivated by prior somatosensory findings of group differences in inter-trial coherence (ITC) between ASD and typically developing (TD) individuals at twice the steady-state stimulation frequency, we examined ASSR at 25 and 50 as well as 43 and 86 Hz in response to 25-Hz and 43-Hz auditory stimuli, respectively, using magnetoencephalography. Data were recorded from 22 ASD and 31 TD children, ages 6-17 years. ITC measures showed prominent ASSRs at the stimulation and double frequencies, without significant group differences. These results do not support ASSR as a robust ASD biomarker of abnormal auditory processing in ASD. Furthermore, the previously observed atypical double-frequency somatosensory response in ASD did not generalize to the auditory modality. Thus, the hypothesis about modality-independent abnormal local connectivity in ASD was not supported.
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Affiliation(s)
- Seppo P Ahlfors
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.
- Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, 149 13th Street, Rm. 2301, Charlestown, MA, 02129, USA.
| | - Steven Graham
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Hari Bharadwaj
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
- Department of Speech, Language, and Hearing Sciences, Boston University, Boston, MA, USA
- Department of Speech, Language, & Hearing Sciences and Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA
| | - Fahimeh Mamashli
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Sheraz Khan
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Robert M Joseph
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA
| | - Ainsley Losh
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Stephanie Pawlyszyn
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Nicole M McGuiggan
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Mark Vangel
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Matti S Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
| | - Tal Kenet
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
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20
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Nakamura K, Hoshi H, Kobayashi M, Fukasawa K, Ichikawa S, Shigihara Y. Dorsal brain activity reflects the severity of menopausal symptoms. Menopause 2024; 31:399-407. [PMID: 38626372 PMCID: PMC11465762 DOI: 10.1097/gme.0000000000002347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 01/16/2024] [Indexed: 04/18/2024]
Abstract
OBJECTIVE The severity of menopausal symptoms, despite being triggered by hormonal imbalance, does not directly correspond to hormone levels in the blood; thus, the level of unpleasantness is assessed using subjective questionnaires in clinical practice. To provide better treatments, alternative objective assessments have been anticipated to support medical interviews and subjective assessments. This study aimed to develop a new objective measurement for assessing unpleasantness. METHODS Fourteen participants with menopausal symptoms and two age-matched participants who visited our outpatient section were enrolled. Resting-state brain activity was measured using magnetoencephalography. The level of unpleasantness of menopausal symptoms was measured using the Kupperman Kohnenki Shogai Index. The blood level of follicle-stimulating hormone and luteinizing hormone were also measured. Correlation analyses were performed between the oscillatory power of brain activity, index score, and hormone levels. RESULTS The level of unpleasantness of menopausal symptoms was positively correlated with high-frequency oscillatory powers in the parietal and bordering cortices (alpha; P = 0.016, beta; P = 0.015, low gamma; P = 0.010). The follicle-stimulating hormone blood level was correlated with high-frequency oscillatory powers in the dorsal part of the cortex (beta; P = 0.008, beta; P = 0.005, low gamma; P = 0.017), whereas luteinizing hormone blood level was not correlated. CONCLUSION Resting-state brain activity can serve as an objective measurement of unpleasantness associated with menopausal symptoms, which aids the selection of appropriate treatment and monitors its outcome.
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Affiliation(s)
- Kohei Nakamura
- From the Department of Gynecology, Kumagaya General Hospital, 4 Chome-5-1 Nakanishi, Kumagaya, Saitama, 360-8567, Japan
- Genomics Unit, Keio Cancer Center, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Hideyuki Hoshi
- Precision Medicine Centre, Hokuto Hospital, Kisen-7-5 Inadacho, Obihiro, Hokkaido, 080-0833, Japan
| | - Momoko Kobayashi
- Precision Medicine Centre, Kumagaya General Hospital, 4 Chome-5-1 Nakanishi, Kumagaya, Saitama, 360-8567, Japan
| | - Keisuke Fukasawa
- Clinical Laboratory, Kumagaya General Hospital, 4 Chome-5-1 Nakanishi, Kumagaya, Saitama, 360-8567, Japan
| | - Sayuri Ichikawa
- Clinical Laboratory, Kumagaya General Hospital, 4 Chome-5-1 Nakanishi, Kumagaya, Saitama, 360-8567, Japan
| | - Yoshihito Shigihara
- Precision Medicine Centre, Hokuto Hospital, Kisen-7-5 Inadacho, Obihiro, Hokkaido, 080-0833, Japan
- Precision Medicine Centre, Kumagaya General Hospital, 4 Chome-5-1 Nakanishi, Kumagaya, Saitama, 360-8567, Japan
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21
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Areces-Gonzalez A, Paz-Linares D, Riaz U, Wang Y, Li M, Razzaq FA, Bosch-Bayard JF, Gonzalez-Moreira E, Ontivero-Ortega M, Galan-Garcia L, Martínez-Montes E, Minati L, Valdes-Sosa MJ, Bringas-Vega ML, Valdes-Sosa PA. CiftiStorm pipeline: facilitating reproducible EEG/MEG source connectomics. Front Neurosci 2024; 18:1237245. [PMID: 38680452 PMCID: PMC11047451 DOI: 10.3389/fnins.2024.1237245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 02/22/2024] [Indexed: 05/01/2024] Open
Abstract
We present CiftiStorm, an electrophysiological source imaging (ESI) pipeline incorporating recently developed methods to improve forward and inverse solutions. The CiftiStorm pipeline produces Human Connectome Project (HCP) and megconnectome-compliant outputs from dataset inputs with varying degrees of spatial resolution. The input data can range from low-sensor-density electroencephalogram (EEG) or magnetoencephalogram (MEG) recordings without structural magnetic resonance imaging (sMRI) to high-density EEG/MEG recordings with an HCP multimodal sMRI compliant protocol. CiftiStorm introduces a numerical quality control of the lead field and geometrical corrections to the head and source models for forward modeling. For the inverse modeling, we present a Bayesian estimation of the cross-spectrum of sources based on multiple priors. We facilitate ESI in the T1w/FSAverage32k high-resolution space obtained from individual sMRI. We validate this feature by comparing CiftiStorm outputs for EEG and MRI data from the Cuban Human Brain Mapping Project (CHBMP) acquired with technologies a decade before the HCP MEG and MRI standardized dataset.
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Affiliation(s)
- Ariosky Areces-Gonzalez
- The Clinical Hospital of Chengdu Brain Sciences Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- School of Technical Sciences, University “Hermanos Saiz Montes de Oca” of Pinar del Río, Pinar del Rio, Cuba
| | - Deirel Paz-Linares
- The Clinical Hospital of Chengdu Brain Sciences Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Department of Neuroinformatics, Cuban Neurosciences Center, Havana, Cuba
| | - Usama Riaz
- The Clinical Hospital of Chengdu Brain Sciences Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Ying Wang
- The Clinical Hospital of Chengdu Brain Sciences Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Min Li
- The Clinical Hospital of Chengdu Brain Sciences Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Hangzhou Dianzi University, Hangzhou, Zhejiang, China
| | - Fuleah A. Razzaq
- The Clinical Hospital of Chengdu Brain Sciences Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Jorge F. Bosch-Bayard
- McGill Centre for Integrative Neurosciences MCIN, LudmerCentre for Mental Health, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Eduardo Gonzalez-Moreira
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, United States
| | | | | | | | - Marlis Ontivero-Ortega
- The Clinical Hospital of Chengdu Brain Sciences Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Department of Neuroinformatics, Cuban Neurosciences Center, Havana, Cuba
| | | | | | - Ludovico Minati
- The Clinical Hospital of Chengdu Brain Sciences Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Center for Mind/Brain Sciences (CIMeC), University of Trento, Trento, Italy
| | | | - Maria L. Bringas-Vega
- The Clinical Hospital of Chengdu Brain Sciences Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Department of Neuroinformatics, Cuban Neurosciences Center, Havana, Cuba
| | - Pedro A. Valdes-Sosa
- The Clinical Hospital of Chengdu Brain Sciences Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- Department of Neuroinformatics, Cuban Neurosciences Center, Havana, Cuba
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22
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Rué‐Queralt J, Fluhr H, Tourbier S, Aleman‐Gómez Y, Pascucci D, Yerly J, Glomb K, Plomp G, Hagmann P. Connectome spectrum electromagnetic tomography: A method to reconstruct electrical brain source networks at high-spatial resolution. Hum Brain Mapp 2024; 45:e26638. [PMID: 38520365 PMCID: PMC10960556 DOI: 10.1002/hbm.26638] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 02/01/2024] [Accepted: 02/13/2024] [Indexed: 03/25/2024] Open
Abstract
Connectome spectrum electromagnetic tomography (CSET) combines diffusion MRI-derived structural connectivity data with well-established graph signal processing tools to solve the M/EEG inverse problem. Using simulated EEG signals from fMRI responses, and two EEG datasets on visual-evoked potentials, we provide evidence supporting that (i) CSET captures realistic neurophysiological patterns with better accuracy than state-of-the-art methods, (ii) CSET can reconstruct brain responses more accurately and with more robustness to intrinsic noise in the EEG signal. These results demonstrate that CSET offers high spatio-temporal accuracy, enabling neuroscientists to extend their research beyond the current limitations of low sampling frequency in functional MRI and the poor spatial resolution of M/EEG.
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Affiliation(s)
- Joan Rué‐Queralt
- Department of RadiologyLausanne University Hospital and University of Lausanne (CHUV‐UNIL)LausanneSwitzerland
- Department of PsychologyUniversity of FribourgFribourgSwitzerland
- Center for ImagingEPFLLausanneSwitzerland
| | - Hugo Fluhr
- Department of RadiologyLausanne University Hospital and University of Lausanne (CHUV‐UNIL)LausanneSwitzerland
| | - Sebastien Tourbier
- Department of RadiologyLausanne University Hospital and University of Lausanne (CHUV‐UNIL)LausanneSwitzerland
| | - Yasser Aleman‐Gómez
- Department of RadiologyLausanne University Hospital and University of Lausanne (CHUV‐UNIL)LausanneSwitzerland
- Department of PsychiatryLausanne University HospitalLausanneSwitzerland
| | | | - Jérôme Yerly
- Department of Diagnostic and Interventional RadiologyLausanne University HospitalLausanneSwitzerland
- Center for Biomedical ImagingEPFLLausanneSwitzerland
| | - Katharina Glomb
- Department of NeurologyCharité University Medicine Berlin and Berlin Institute of HealthBerlinGermany
| | - Gijs Plomp
- Department of PsychologyUniversity of FribourgFribourgSwitzerland
| | - Patric Hagmann
- Department of RadiologyLausanne University Hospital and University of Lausanne (CHUV‐UNIL)LausanneSwitzerland
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23
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Ma YY, Gao Y, Wu HQ, Liang XY, Li Y, Lu H, Liu CZ, Ning XL. OPM-MEG Measuring Phase Synchronization on Source Time Series: Application in Rhythmic Median Nerve Stimulation. IEEE Trans Neural Syst Rehabil Eng 2024; 32:1426-1434. [PMID: 38530717 DOI: 10.1109/tnsre.2024.3381173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/28/2024]
Abstract
The magnetoencephalogram (MEG) based on array optically pumped magnetometers (OPMs) has the potential of replacing conventional cryogenic superconducting quantum interference device. Phase synchronization is a common method for measuring brain oscillations and functional connectivity. Verifying the feasibility and fidelity of OPM-MEG in measuring phase synchronization will help its widespread application in the study of aforementioned neural mechanisms. The analysis method on source-level time series can weaken the influence of instantaneous field spread effect. In this paper, the OPM-MEG was used for measuring the evoked responses of 20Hz rhythmic and arrhythmic median nerve stimulation, and the inter-trial phase synchronization (ITPS) and inter-reginal phase synchronization (IRPS) of primary somatosensory cortex (SI) and secondary somatosensory cortex (SII) were analysed. The results find that under rhythmic condition, the evoked responses of SI and SII show continuous oscillations and the effect of resetting phase. The values of ITPS and IRPS significantly increase at the stimulation frequency of 20Hz and its harmonic of 40Hz, whereas the arrhythmic stimulation does not exhibit this phenomenon. Moreover, in the initial stage of stimulation, the ITPS and IRPS values are significantly higher at Mu rhythm in the rhythmic condition compared to arrhythmic. In conclusion, the results demonstrate the ability of OPM-MEG in measuring phase pattern and functional connectivity on source-level, and may also prove beneficial for the study on the mechanism of rhythmic stimulation therapy for rehabilitation.
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24
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López-Caballero F, Curtis M, Coffman BA, Salisbury DF. Is source-resolved magnetoencephalographic mismatch negativity a viable biomarker for early psychosis? Eur J Neurosci 2024; 59:1889-1906. [PMID: 37537883 PMCID: PMC10837325 DOI: 10.1111/ejn.16107] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 07/04/2023] [Accepted: 07/20/2023] [Indexed: 08/05/2023]
Abstract
Mismatch negativity (MMN) is an auditory event-related response reflecting the pre-attentive detection of novel stimuli and is a biomarker of cortical dysfunction in schizophrenia (SZ). MMN to pitch (pMMN) and to duration (dMMN) deviant stimuli are impaired in chronic SZ, but it is less clear if MMN is reduced in first-episode SZ, with inconsistent findings in scalp-level EEG studies. Here, we investigated the neural generators of pMMN and dMMN with MEG recordings in 26 first-episode schizophrenia spectrum (FEsz) and 26 matched healthy controls (C). We projected MEG inverse solutions into precise functionally meaningful auditory cortex areas. MEG-derived MMN sources were in bilateral primary auditory cortex (A1) and belt areas. In A1, pMMN FEsz reduction showed a trend towards statistical significance (F(1,50) = 3.31; p = .07), and dMMN was reduced in FEsz (F(1,50) = 4.11; p = .04). Hypothesis-driven comparisons at each hemisphere revealed dMMN reduction in FEsz occurred in the left (t(56) = 2.23; p = .03; d = .61) but not right (t(56) = 1.02; p = .31; d = .28) hemisphere, with a moderate effect size. The added precision of MEG source solution with high-resolution MRI and parcellation of A1 may be requisite to detect the emerging pathophysiology and indicates a critical role for left hemisphere pathology at psychosis onset. However, the moderate effect size in left A1, albeit larger than reported in scalp MMN meta-analyses, casts doubt on the clinical utility of MMN for differential diagnosis, as a majority of patients will overlap with the healthy individual's distribution.
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Affiliation(s)
- Fran López-Caballero
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Mark Curtis
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Brian A Coffman
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Dean F Salisbury
- Clinical Neurophysiology Research Laboratory, Western Psychiatric Hospital, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
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25
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Salillas E, Luisi C, Arcara G, Varlı EN, d'Avella D, Semenza C. Verb generation for presurgical mapping: Gaining specificity. J Neuropsychol 2024; 18 Suppl 1:183-204. [PMID: 38062895 DOI: 10.1111/jnp.12355] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 11/10/2023] [Accepted: 11/15/2023] [Indexed: 04/13/2024]
Abstract
Verb generation is among the most frequently used tasks in presurgical mapping. Because this task involves many processes, the overall brain effects are not specific. While it is necessary to identify the whole network involving noun comprehension or semantic retrieval and lexical selection to produce the verb, isolation of those components is also crucial. Here, we present data from four patients undergoing presurgical brain mapping. The study implied a reanalysis of magnetoencephalography data with a recategorization of the used items. It aimed to extract the task component that relies on the inferior frontal gyrus (IFG). The task could be applied with higher specificity when targeting frontal areas. For that, we based item classification on the selection demands imposed by the noun. It is a robust finding that the IFG carries out this selection and that a quantitative index can be calculated for each noun, which depends on the selection effort (Proceedings of the National Academy of Sciences of the United States of America, 1997; 94(26):14792-14797, Proceedings of the National Academy of Sciences of the United States of America, 1998; 95(26):15855-15860). Data showed focality and specificity, with a correlation between this derived index and source activations in the inferior frontal gyrus for all patients. Strikingly, we detected when the right-hemisphere homologue area was involved in the selection process in two patients showing reorganization or language right lateralization. The present data are a step towards a dissection of broad specific tasks frequently used in presurgical protocols.
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Affiliation(s)
- Elena Salillas
- Department of Psychology and Sociology, Universidad de Zaragoza, Zaragoza, Spain
| | - Concetta Luisi
- Neurology, Epilepsy and Movement Disorders, Bambino Gesù Children's Hospital, IRCCS, Full Member of European Reference Network EpiCARE, IRCCS, Rome, Italy
| | | | - Elif Nur Varlı
- Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Domenico d'Avella
- Academic Neurosurgery, Department of Neuroscience, University of Padova, Padova, Italy
| | - Carlo Semenza
- Padova Neuroscience Center, University of Padova, Padova, Italy
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26
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Moradi N, Goodyear BG, Sotero RC. Deep EEG source localization via EMD-based fMRI high spatial frequency. PLoS One 2024; 19:e0299284. [PMID: 38427616 PMCID: PMC10906834 DOI: 10.1371/journal.pone.0299284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Accepted: 02/07/2024] [Indexed: 03/03/2024] Open
Abstract
Brain imaging with a high-spatiotemporal resolution is crucial for accurate brain-function mapping. Electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are two popular neuroimaging modalities with complementary features that record brain function with high temporal and spatial resolution, respectively. One popular non-invasive way to obtain data with both high spatial and temporal resolutions is to combine the fMRI activation map and EEG data to improve the spatial resolution of the EEG source localization. However, using the whole fMRI map may cause spurious results for the EEG source localization, especially for deep brain regions. Considering the head's conductivity, deep regions' sources with low activity are unlikely to be detected by the EEG electrodes at the scalp. In this study, we use fMRI's high spatial-frequency component to identify the local high-intensity activations that are most likely to be captured by the EEG. The 3D Empirical Mode Decomposition (3D-EMD), a data-driven method, is used to decompose the fMRI map into its spatial-frequency components. Different validation measurements for EEG source localization show improved performance for the EEG inverse-modeling informed by the fMRI's high-frequency spatial component compared to the fMRI-informed EEG source-localization methods. The level of improvement varies depending on the voxels' intensity and their distribution. Our experimental results also support this conclusion.
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Affiliation(s)
- Narges Moradi
- Biomedical Engineering Department, University of Calgary, Calgary, AB, Canada
- Department of Radiology, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Bradley G. Goodyear
- Department of Radiology, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Roberto C. Sotero
- Department of Radiology, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
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27
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Falter-Wagner CM, Kiefer CM, Bailey AJ, Vogeley K, Dammers J. Perceptual Grouping in Autism Spectrum Disorder: An Exploratory Magnetoencephalography Study. J Autism Dev Disord 2024; 54:1101-1112. [PMID: 36512195 PMCID: PMC10907473 DOI: 10.1007/s10803-022-05844-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/21/2022] [Indexed: 12/15/2022]
Abstract
Visual information is organised according to visual grouping principles. In visual grouping tasks individuals with ASD have shown equivocal performance. We explored neural correlates of Gestalt grouping in individuals with and without ASD. Neuromagnetic activity of individuals with (15) and without (18) ASD was compared during a visual grouping task testing grouping by proximity versus similarity. Individuals without ASD showed stronger evoked responses with earlier peaks in response to both grouping types indicating an earlier neuronal differentiation between grouping principles in individuals without ASD. In contrast, individuals with ASD showed particularly prolonged processing of grouping by similarity suggesting a high demand of neural resources. The neuronal processing differences found could explain less efficient grouping performance observed behaviourally in ASD.
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Affiliation(s)
| | - Christian M Kiefer
- Institute of Neuroscience and Medicine, INM-4, Forschungszentrum Jülich, Jülich, Germany
- Faculty of Mathematics, Computer Science and Natural Sciences, RWTH Aachen University, Aachen, Germany
| | - Anthony J Bailey
- UBC Department of Psychiatry, University of British Columbia, 2255 Westbrook Mall, Vancouver, BC, V6T 2A1, Canada
| | - Kai Vogeley
- Department of Psychiatry and Psychotherapy, University Hospital Cologne, Cologne, Germany
- Institute of Neurosciences and Medicine-Cognitive Neuroscience, INM-3, Forschungszentrum Jülich, Jülich, Germany
| | - Jürgen Dammers
- Institute of Neuroscience and Medicine, INM-4, Forschungszentrum Jülich, Jülich, Germany.
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28
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Xu F, Li Y, Wang Y, Wang S, Sun F, Wang X. Interictal magnetic signals in new-onset Rolandic epilepsy may help with timing of treatment selection. Epilepsia Open 2024; 9:368-379. [PMID: 38145506 PMCID: PMC10839299 DOI: 10.1002/epi4.12884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 11/03/2023] [Accepted: 12/15/2023] [Indexed: 12/27/2023] Open
Abstract
OBJECTIVE With research progress on Rolandic epilepsy (RE), its "benign" nature has been phased out. Clinicians are exhibiting an increasing tendency toward a more assertive treatment approach for RE. Nonetheless, in clinical practice, delayed treatment remains common because of the "self-limiting" nature of RE. Therefore, this study aimed to identify an imaging marker to aid treatment decisions and select a more appropriate time for initiating therapy for RE. METHODS We followed up with children newly diagnosed with RE, classified them into medicated and non-medicated groups according to the follow-up results, and compared them with matched healthy controls. Before beginning follow-up visits, interictal magnetic data were collected using magnetoencephalography in treatment-naïve recently diagnosed patients. The spectral power of the whole brain during initial diagnosis was determined using minimum normative estimation combined with the Welch technique. RESULTS A difference was observed in the magnetic source intensity within the left caudal anterior cingulate and precentral and postcentral gyri in the delta band between the medicated and non-medicated groups. The results revealed good discriminatory ability within the receiver operator characteristic curve. In the medicated group, there was a specific change in the frontotemporal magnetic source intensity, which shifted from high to low frequencies, compared with the healthy control group. SIGNIFICANCE The intensity of the precentral gyrus magnetic source within the delta band showed good specificity. Considering the rigor of initial treatment, the intensity of the precentral gyrus magnetic source can provide some help as an imaging marker for initial RE treatment, particularly for the timing of treatment initiation.
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Affiliation(s)
- Fengyuan Xu
- Country Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Yihan Li
- Country Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Yingfan Wang
- Country Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Siyi Wang
- Country Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Fangling Sun
- Country Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
| | - Xiaoshan Wang
- Country Department of NeurologyThe Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina
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29
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Hoshi H, Hirata Y, Fukasawa K, Kobayashi M, Shigihara Y. Oscillatory characteristics of resting-state magnetoencephalography reflect pathological and symptomatic conditions of cognitive impairment. Front Aging Neurosci 2024; 16:1273738. [PMID: 38352236 PMCID: PMC10861731 DOI: 10.3389/fnagi.2024.1273738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 01/12/2024] [Indexed: 02/16/2024] Open
Abstract
Background Dementia and mild cognitive impairment are characterised by symptoms of cognitive decline, which are typically assessed using neuropsychological assessments (NPAs), such as the Mini-Mental State Examination (MMSE) and Frontal Assessment Battery (FAB). Magnetoencephalography (MEG) is a novel clinical assessment technique that measures brain activities (summarised as oscillatory parameters), which are associated with symptoms of cognitive impairment. However, the relevance of MEG and regional cerebral blood flow (rCBF) data obtained using single-photon emission computed tomography (SPECT) has not been examined using clinical datasets. Therefore, this study aimed to investigate the relationships among MEG oscillatory parameters, clinically validated biomarkers computed from rCBF, and NPAs using outpatient data retrieved from hospital records. Methods Clinical data from 64 individuals with mixed pathological backgrounds were retrieved and analysed. MEG oscillatory parameters, including relative power (RP) from delta to high gamma bands, mean frequency, individual alpha frequency, and Shannon's spectral entropy, were computed for each cortical region. For SPECT data, three pathological parameters-'severity', 'extent', and 'ratio'-were computed using an easy z-score imaging system (eZIS). As for NPAs, the MMSE and FAB scores were retrieved. Results MEG oscillatory parameters were correlated with eZIS parameters. The eZIS parameters associated with Alzheimer's disease pathology were reflected in theta power augmentation and slower shift of the alpha peak. Moreover, MEG oscillatory parameters were found to reflect NPAs. Global slowing and loss of diversity in neural oscillatory components correlated with MMSE and FAB scores, whereas the associations between eZIS parameters and NPAs were sparse. Conclusion MEG oscillatory parameters correlated with both SPECT (i.e. eZIS) parameters and NPAs, supporting the clinical validity of MEG oscillatory parameters as pathological and symptomatic indicators. The findings indicate that various components of MEG oscillatory characteristics can provide valuable pathological and symptomatic information, making MEG data a rich resource for clinical examinations of patients with cognitive impairments. SPECT (i.e. eZIS) parameters showed no correlations with NPAs. The results contributed to a better understanding of the characteristics of electrophysiological and pathological examinations for patients with cognitive impairments, which will help to facilitate their co-use in clinical application, thereby improving patient care.
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Affiliation(s)
- Hideyuki Hoshi
- Precision Medicine Centre, Hokuto Hospital, Obihiro, Japan
| | - Yoko Hirata
- Department of Neurosurgery, Kumagaya General Hospital, Kumagaya, Japan
| | | | - Momoko Kobayashi
- Precision Medicine Centre, Kumagaya General Hospital, Kumagaya, Japan
| | - Yoshihito Shigihara
- Precision Medicine Centre, Hokuto Hospital, Obihiro, Japan
- Precision Medicine Centre, Kumagaya General Hospital, Kumagaya, Japan
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30
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Corsi MC, Sorrentino P, Schwartz D, George N, Gollo LL, Chevallier S, Hugueville L, Kahn AE, Dupont S, Bassett DS, Jirsa V, De Vico Fallani F. Measuring neuronal avalanches to inform brain-computer interfaces. iScience 2024; 27:108734. [PMID: 38226174 PMCID: PMC10788504 DOI: 10.1016/j.isci.2023.108734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 10/18/2023] [Accepted: 12/12/2023] [Indexed: 01/17/2024] Open
Abstract
Large-scale interactions among multiple brain regions manifest as bursts of activations called neuronal avalanches, which reconfigure according to the task at hand and, hence, might constitute natural candidates to design brain-computer interfaces (BCIs). To test this hypothesis, we used source-reconstructed magneto/electroencephalography during resting state and a motor imagery task performed within a BCI protocol. To track the probability that an avalanche would spread across any two regions, we built an avalanche transition matrix (ATM) and demonstrated that the edges whose transition probabilities significantly differed between conditions hinged selectively on premotor regions in all subjects. Furthermore, we showed that the topology of the ATMs allows task-decoding above the current gold standard. Hence, our results suggest that neuronal avalanches might capture interpretable differences between tasks that can be used to inform brain-computer interfaces.
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Affiliation(s)
- Marie-Constance Corsi
- Sorbonne Université, Institut du cerveau - Paris Brain Institute - ICM, CNRS, Inserm, APHP, Hôpital de la Pitié Salpêtrière, Paris, France
- Inria, Aramis Team, Paris, France
| | - Pierpaolo Sorrentino
- Institut de Neuroscience des Systèmes, Aix-Marseille University, Inserm, Marseille, France
| | - Denis Schwartz
- Institut du Cerveau - Paris Brain Institute, ICM, Inserm U 1127, CNRS UMR 7225, Sorbonne Université, CENIR, Centre MEG-EEG, Paris, France
| | - Nathalie George
- Sorbonne Université, Institut du cerveau - Paris Brain Institute - ICM, CNRS, Inserm, APHP, Hôpital de la Pitié Salpêtrière, Paris, France
- Institut du Cerveau - Paris Brain Institute, ICM, Inserm U 1127, CNRS UMR 7225, Sorbonne Université, CENIR, Centre MEG-EEG, Paris, France
| | - Leonardo L. Gollo
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria 3168, Australia
| | | | - Laurent Hugueville
- Institut de Neuroscience des Systèmes, Aix-Marseille University, Inserm, Marseille, France
| | - Ari E. Kahn
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, USA
| | - Sophie Dupont
- Sorbonne Université, Institut du cerveau - Paris Brain Institute - ICM, CNRS, Inserm, APHP, Hôpital de la Pitié Salpêtrière, Paris, France
| | | | - Viktor Jirsa
- Institut de Neuroscience des Systèmes, Aix-Marseille University, Inserm, Marseille, France
| | - Fabrizio De Vico Fallani
- Sorbonne Université, Institut du cerveau - Paris Brain Institute - ICM, CNRS, Inserm, APHP, Hôpital de la Pitié Salpêtrière, Paris, France
- Inria, Aramis Team, Paris, France
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Das D, Shaw ME, Hämäläinen MS, Dykstra AR, Doll L, Gutschalk A. A role for retro-splenial cortex in the task-related P3 network. Clin Neurophysiol 2024; 157:96-109. [PMID: 38091872 DOI: 10.1016/j.clinph.2023.11.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 10/12/2023] [Accepted: 11/19/2023] [Indexed: 12/26/2023]
Abstract
OBJECTIVE The P3 is an event-related response observed in relation to task-relevant sensory events. Despite its ubiquitous presence, the neural generators of the P3 are controversial and not well identified. METHODS We compared source analysis of combined magneto- and electroencephalography (M/EEG) data with functional magnetic resonance imaging (fMRI) and simulation studies to better understand the sources of the P3 in an auditory oddball paradigm. RESULTS Our results suggest that the dominant source of the classical, postero-central P3 lies in the retro-splenial cortex of the ventral cingulate gyrus. A second P3 source in the anterior insular cortex contributes little to the postero-central maximum. Multiple other sources in the auditory, somatosensory, and anterior midcingulate cortex are active in an overlapping time window but can be functionally dissociated based on their activation time courses. CONCLUSIONS The retro-splenial cortex is a dominant source of the parietal P3 maximum in EEG. SIGNIFICANCE These results provide a new perspective for the interpretation of the extensive research based on the P3 response.
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Affiliation(s)
- Diptyajit Das
- Department of Neurology, Ruprecht-Karls-Universität Heidelberg, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany
| | - Marnie E Shaw
- College of Engineering & Computer Science, Australian National University, Canberra, Australia
| | - Matti S Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, USA; Harvard, MIT Division of Health Science and Technology, USA; Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Finland
| | - Andrew R Dykstra
- Department of Biomedical Engineering, University of Miami, Coral Gables, USA
| | - Laura Doll
- Department of Neurology, Ruprecht-Karls-Universität Heidelberg, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany
| | - Alexander Gutschalk
- Department of Neurology, Ruprecht-Karls-Universität Heidelberg, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany.
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Paitel ER, Nielson KA. Cerebellar EEG source localization reveals age-related compensatory activity moderated by genetic risk for Alzheimer's disease. Psychophysiology 2023; 60:e14395. [PMID: 37493042 DOI: 10.1111/psyp.14395] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 06/24/2023] [Accepted: 07/03/2023] [Indexed: 07/27/2023]
Abstract
The apolipoprotein-E (APOE) ε4 allele is the greatest genetic risk factor for late-onset Alzheimer's disease (AD), but alone it is not sufficiently predictive. Because neuropathological changes associated with AD begin decades before cognitive symptoms, neuroimaging of healthy, cognitively intact ε4 carriers (ε4+) may enable early characterization of patterns associated with risk for future decline. Research in the cerebral cortex highlights a period of compensatory recruitment in elders and ε4+, which serves to maintain cognitive functioning. Yet, AD-related changes may occur even earlier in the cerebellum. Advances in electroencephalography (EEG) source localization now allow effective modeling of cerebellar activity. Importantly, healthy aging and AD are associated with declines in both cerebellar functions and executive functioning (EF). However, it is not known whether cerebellar activity can detect pre-symptomatic AD risk. Thus, the current study analyzed cerebellar EEG source localization during an EF-dependent stop-signal task (i.e., inhibitory control) in healthy, intact older adults (Mage = 80 years; 20 ε4+, 25 ε4-). Task performance was comparable between groups. Older age predicted greater activity in left crus II and lobule VIIb during the P300 window (i.e., performance evaluation), consistent with age-related compensation. Age*ε4 moderations specifically showed that compensatory patterns were evident only in ε4-, suggesting that cerebellar compensatory resources may already be depleted in healthy ε4+ elders. Thus, the posterolateral cerebellum is sensitive to AD-related neural deficits in healthy elders. Characterization of these patterns may be essential for the earliest possible detection of AD risk, which would enable critical early intervention prior to symptom onset.
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Affiliation(s)
- Elizabeth R Paitel
- Department of Psychology, Marquette University, Milwaukee, Wisconsin, USA
| | - Kristy A Nielson
- Department of Psychology, Marquette University, Milwaukee, Wisconsin, USA
- Department of Neurology, Center for Imaging Research, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
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Alho J, Samuelsson JG, Khan S, Mamashli F, Bharadwaj H, Losh A, McGuiggan NM, Graham S, Nayal Z, Perrachione TK, Joseph RM, Stoodley CJ, Hämäläinen MS, Kenet T. Both stronger and weaker cerebro-cerebellar functional connectivity patterns during processing of spoken sentences in autism spectrum disorder. Hum Brain Mapp 2023; 44:5810-5827. [PMID: 37688547 PMCID: PMC10619366 DOI: 10.1002/hbm.26478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 08/11/2023] [Accepted: 08/20/2023] [Indexed: 09/11/2023] Open
Abstract
Cerebellar differences have long been documented in autism spectrum disorder (ASD), yet the extent to which such differences might impact language processing in ASD remains unknown. To investigate this, we recorded brain activity with magnetoencephalography (MEG) while ASD and age-matched typically developing (TD) children passively processed spoken meaningful English and meaningless Jabberwocky sentences. Using a novel source localization approach that allows higher resolution MEG source localization of cerebellar activity, we found that, unlike TD children, ASD children showed no difference between evoked responses to meaningful versus meaningless sentences in right cerebellar lobule VI. ASD children also had atypically weak functional connectivity in the meaningful versus meaningless speech condition between right cerebellar lobule VI and several left-hemisphere sensorimotor and language regions in later time windows. In contrast, ASD children had atypically strong functional connectivity for in the meaningful versus meaningless speech condition between right cerebellar lobule VI and primary auditory cortical areas in an earlier time window. The atypical functional connectivity patterns in ASD correlated with ASD severity and the ability to inhibit involuntary attention. These findings align with a model where cerebro-cerebellar speech processing mechanisms in ASD are impacted by aberrant stimulus-driven attention, which could result from atypical temporal information and predictions of auditory sensory events by right cerebellar lobule VI.
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Affiliation(s)
- Jussi Alho
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - John G. Samuelsson
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Harvard‐MIT Division of Health Sciences and Technology, Massachusetts Institute of TechnologyCambridgeMassachusettsUSA
| | - Sheraz Khan
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Fahimeh Mamashli
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Hari Bharadwaj
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of Speech, Language, and Hearing Sciences, and Weldon School of Biomedical EngineeringPurdue UniversityWest LafayetteIndianaUSA
| | - Ainsley Losh
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Nicole M. McGuiggan
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Steven Graham
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Zein Nayal
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Tyler K. Perrachione
- Department of Speech, Language, and Hearing SciencesBoston UniversityBostonMassachusettsUSA
| | - Robert M. Joseph
- Department of Anatomy and NeurobiologyBoston University School of MedicineBostonMassachusettsUSA
| | - Catherine J. Stoodley
- Department of PsychologyCollege of Arts and Sciences, American UniversityWashingtonDCUSA
| | - Matti S. Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Department of RadiologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Tal Kenet
- Department of NeurologyMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
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Sunaga M, Takei Y, Kato Y, Tagawa M, Suto T, Hironaga N, Sakurai N, Fukuda M. The Characteristics of Power Spectral Density in Bipolar Disorder at the Resting State. Clin EEG Neurosci 2023; 54:574-583. [PMID: 34677105 DOI: 10.1177/15500594211050487] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Bipolar disorder (BD) is a common psychiatric disorder, but its pathophysiology is not fully elucidated. The current study focused on its electrophysiological characteristics, especially power spectral density (PSD). Resting state with eyes opened magnetoencephalography data were collected from 21 patients with BD and 22 healthy controls. The whole brain's PSD was calculated from source reconstructed waveforms at each frequency band (delta: 1-3 Hz, theta: 4-7 Hz, alpha: 8-12 Hz, low beta: 13-19 Hz, high beta: 20-29 Hz, and gamma: 30-80 Hz). We compared PSD values on the marked vertices at each frequency band between healthy and patient groups using a Mann-Whitney rank test to examine the relationship between significantly different PSD and clinical measures. The PSD in patients with BD was significantly decreased in lower frequency bands, mainly in the default mode network (DMN) areas (bilateral medial prefrontal cortex, bilateral precuneus, left inferior parietal lobe, and right temporal cortex in the alpha band) and salience network areas (SAL; left anterior insula [AI] at the delta band, anterior cingulate cortex at the theta band, and right AI at the alpha band). No significant differences in PSD were observed at low beta and high beta. PSD was not correlated with age or other clinical scales. Altered PSDs of the DMN and SAL were observed in the delta, theta, and alpha bands. These alterations contribute to the vulnerability of BD through the disturbance of self-referential mental activity and switching between the default mode and frontoparietal networks.
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Affiliation(s)
- Masakazu Sunaga
- Gunma Prefectural Psychiatric Medical Center, Isesaki, Japan
| | - Yuichi Takei
- Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Yutaka Kato
- Gunma University Graduate School of Medicine, Maebashi, Japan
- Tsutsuji Mental Hospital, Tatebayashi, Japan
| | - Minami Tagawa
- Gunma Prefectural Psychiatric Medical Center, Isesaki, Japan
- Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Tomohiro Suto
- Gunma Prefectural Psychiatric Medical Center, Isesaki, Japan
| | | | - Noriko Sakurai
- Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Masato Fukuda
- Gunma University Graduate School of Medicine, Maebashi, Japan
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Rodríguez-González V, Núñez P, Gómez C, Shigihara Y, Hoshi H, Tola-Arribas MÁ, Cano M, Guerrero Á, García-Azorín D, Hornero R, Poza J. Connectivity-based Meta-Bands: A new approach for automatic frequency band identification in connectivity analyses. Neuroimage 2023; 280:120332. [PMID: 37619796 DOI: 10.1016/j.neuroimage.2023.120332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Revised: 07/05/2023] [Accepted: 08/14/2023] [Indexed: 08/26/2023] Open
Abstract
The majority of electroencephalographic (EEG) and magnetoencephalographic (MEG) studies filter and analyse neural signals in specific frequency ranges, known as "canonical" frequency bands. However, this segmentation, is not exempt from limitations, mainly due to the lack of adaptation to the neural idiosyncrasies of each individual. In this study, we introduce a new data-driven method to automatically identify frequency ranges based on the topological similarity of the frequency-dependent functional neural network. The resting-state neural activity of 195 cognitively healthy subjects from three different databases (MEG: 123 subjects; EEG1: 27 subjects; EEG2: 45 subjects) was analysed. In a first step, MEG and EEG signals were filtered with a narrow-band filter bank (1 Hz bandwidth) from 1 to 70 Hz with a 0.5 Hz step. Next, the connectivity in each of these filtered signals was estimated using the orthogonalized version of the amplitude envelope correlation to obtain the frequency-dependent functional neural network. Finally, a community detection algorithm was used to identify communities in the frequency domain showing a similar network topology. We have called this approach the "Connectivity-based Meta-Bands" (CMB) algorithm. Additionally, two types of synthetic signals were used to configure the hyper-parameters of the CMB algorithm. We observed that the classical approaches to band segmentation are partially aligned with the underlying network topologies at group level for the MEG signals, but they are missing individual idiosyncrasies that may be biasing previous studies, as revealed by our methodology. On the other hand, the sensitivity of EEG signals to reflect this underlying frequency-dependent network structure is limited, revealing a simpler frequency parcellation, not aligned with that defined by the "canonical" frequency bands. To the best of our knowledge, this is the first study that proposes an unsupervised band segmentation method based on the topological similarity of functional neural network across frequencies. This methodology fully accounts for subject-specific patterns, providing more robust and personalized analyses, and paving the way for new studies focused on exploring the frequency-dependent structure of brain connectivity.
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Affiliation(s)
- Víctor Rodríguez-González
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III (CIBER-BBN), Spain.
| | - Pablo Núñez
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III (CIBER-BBN), Spain; Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium
| | - Carlos Gómez
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III (CIBER-BBN), Spain
| | | | | | - Miguel Ángel Tola-Arribas
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III (CIBER-BBN), Spain; Servicio de Neurología. Hospital Universitario Río Hortega, Valladolid, Spain
| | - Mónica Cano
- Servicio de Neurología. Hospital Universitario Río Hortega, Valladolid, Spain
| | - Ángel Guerrero
- Hospital Clínico Universitario, Valladolid, Spain; Department of Medicine, University of Valladolid, Spain
| | | | - Roberto Hornero
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III (CIBER-BBN), Spain; IMUVA, Instituto de Investigación en Matemáticas, University of Valladolid, Spain
| | - Jesús Poza
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III (CIBER-BBN), Spain; IMUVA, Instituto de Investigación en Matemáticas, University of Valladolid, Spain
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Das D, Shaw ME, Hämäläinen MS, Dykstra AR, Doll L, Gutschalk A. A role for retro-splenial cortex in the task-related P3 network. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.03.530970. [PMID: 36945516 PMCID: PMC10028840 DOI: 10.1101/2023.03.03.530970] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
Objective The P3 is an event-related response observed in relation to task-relevant sensory events. Despite its ubiquitous presence, the neural generators of the P3 are controversial and not well identified. Methods We compared source analysis of combined magneto- and electroencephalography (M/EEG) data with functional magnetic resonance imaging (fMRI) and simulation studies to better understand the sources of the P3 in an auditory oddball paradigm. Results Our results suggest that the dominant source of the classical, postero-central P3 lies in the retro-splenial cortex of the ventral cingulate gyrus. A second P3 source in the anterior insular cortex contributes little to the postero-central maximum. Multiple other sources in the auditory, somatosensory, and anterior midcingulate cortex are active in an overlapping time window but can be functionally dissociated based on their activation time courses. Conclusion The retro-splenial cortex is a dominant source of the parietal P3 maximum in EEG. Significance These results provide a new perspective for the interpretation of the extensive research based on the P3 response.
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Affiliation(s)
- Diptyajit Das
- Department of Neurology, Ruprecht-Karls-Universität Heidelberg, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany
| | - Marnie E. Shaw
- College of Engineering & Computer Science, Australian National University, Canberra, Australia
| | - Matti S. Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, USA
- Harvard, MIT Division of Health Science and Technology, USA
- Department of Neuroscience and Biomedical Engineering, Aalto University school of Science, Finland
| | - Andrew R. Dykstra
- Department of Biomedical Engineering, University of Miami, Coral Gables, USA
| | - Laura Doll
- Department of Neurology, Ruprecht-Karls-Universität Heidelberg, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany
| | - Alexander Gutschalk
- Department of Neurology, Ruprecht-Karls-Universität Heidelberg, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany
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Liu K, Wang Z, Yu Z, Xiao B, Yu H, Wu W. WRA-MTSI: A Robust Extended Source Imaging Algorithm Based on Multi-Trial EEG. IEEE Trans Biomed Eng 2023; 70:2809-2821. [PMID: 37027281 DOI: 10.1109/tbme.2023.3265376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/08/2023]
Abstract
OBJECTIVE Reconstructing brain activities from electroencephalography (EEG) signals is crucial for studying brain functions and their abnormalities. However, since EEG signals are nonstationary and vulnerable to noise, brain activities reconstructed from single-trial EEG data are often unstable, and significant variability may occur across different EEG trials even for the same cognitive task. METHODS In an effort to leverage the shared information across the EEG data of multiple trials, this paper proposes a multi-trial EEG source imaging method based on Wasserstein regularization, termed WRA-MTSI. In WRA-MTSI, Wasserstein regularization is employed to perform multi-trial source distribution similarity learning, and the structured sparsity constraint is enforced to enable accurate estimation of the source extents, locations and time series. The resulting optimization problem is solved by a computationally efficient algorithm based on the alternating direction method of multipliers (ADMM). RESULTS Both numerical simulations and real EEG data analysis demonstrate that WRA-MTSI outperforms existing single-trial ESI methods (e.g., wMNE, LORETA, SISSY, and SBL) in mitigating the influence of artifacts in EEG data. Moreover, WRA-MTSI yields superior performance compared to other state-of-the-art multi-trial ESI methods (e.g., group lasso, the dirty model, and MTW) in estimating source extents. CONCLUSION AND SIGNIFICANCE WRA-MTSI may serve as an effective robust EEG source imaging method in the presence of multi-trial noisy EEG data.
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Layer N, Abdel-Latif KHA, Radecke JO, Müller V, Weglage A, Lang-Roth R, Walger M, Sandmann P. Effects of noise and noise reduction on audiovisual speech perception in cochlear implant users: An ERP study. Clin Neurophysiol 2023; 154:141-156. [PMID: 37611325 DOI: 10.1016/j.clinph.2023.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 06/19/2023] [Accepted: 07/14/2023] [Indexed: 08/25/2023]
Abstract
OBJECTIVE Hearing with a cochlear implant (CI) is difficult in noisy environments, but the use of noise reduction algorithms, specifically ForwardFocus, can improve speech intelligibility. The current event-related potentials (ERP) study examined the electrophysiological correlates of this perceptual improvement. METHODS Ten bimodal CI users performed a syllable-identification task in auditory and audiovisual conditions, with syllables presented from the front and stationary noise presented from the sides. Brainstorm was used for spatio-temporal evaluation of ERPs. RESULTS CI users revealed an audiovisual benefit as reflected by shorter response times and greater activation in temporal and occipital regions at P2 latency. However, in auditory and audiovisual conditions, background noise hampered speech processing, leading to longer response times and delayed auditory-cortex-activation at N1 latency. Nevertheless, activating ForwardFocus resulted in shorter response times, reduced listening effort and enhanced superior-frontal-cortex-activation at P2 latency, particularly in audiovisual conditions. CONCLUSIONS ForwardFocus enhances speech intelligibility in audiovisual speech conditions by potentially allowing the reallocation of attentional resources to relevant auditory speech cues. SIGNIFICANCE This study shows for CI users that background noise and ForwardFocus differentially affect spatio-temporal cortical response patterns, both in auditory and audiovisual speech conditions.
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Affiliation(s)
- Natalie Layer
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Otorhinolaryngology, Head and Neck Surgery, Audiology and Pediatric Audiology, Cochlear Implant Center, Germany.
| | | | - Jan-Ole Radecke
- Dept. of Psychiatry and Psychotherapy, University of Lübeck, Germany; Center for Brain, Behaviour and Metabolism (CBBM), University of Lübeck, Germany
| | - Verena Müller
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Otorhinolaryngology, Head and Neck Surgery, Audiology and Pediatric Audiology, Cochlear Implant Center, Germany
| | - Anna Weglage
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Otorhinolaryngology, Head and Neck Surgery, Audiology and Pediatric Audiology, Cochlear Implant Center, Germany
| | - Ruth Lang-Roth
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Otorhinolaryngology, Head and Neck Surgery, Audiology and Pediatric Audiology, Cochlear Implant Center, Germany
| | - Martin Walger
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Otorhinolaryngology, Head and Neck Surgery, Audiology and Pediatric Audiology, Cochlear Implant Center, Germany; Jean-Uhrmacher-Institute for Clinical ENT Research, University of Cologne, Germany
| | - Pascale Sandmann
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Otorhinolaryngology, Head and Neck Surgery, Audiology and Pediatric Audiology, Cochlear Implant Center, Germany; Department of Otolaryngology, Head and Neck Surgery, University of Oldenburg, Oldenburg, Germany
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Arutiunian V, Arcara G, Buyanova I, Buivolova O, Davydova E, Pereverzeva D, Sorokin A, Tyushkevich S, Mamokhina U, Danilina K, Dragoy O. Event-Related Desynchronization of MEG Alpha-Band Oscillations during Simultaneous Presentation of Audio and Visual Stimuli in Children with Autism Spectrum Disorder. Brain Sci 2023; 13:1313. [PMID: 37759914 PMCID: PMC10526124 DOI: 10.3390/brainsci13091313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 09/07/2023] [Accepted: 09/12/2023] [Indexed: 09/29/2023] Open
Abstract
Alpha-band (8-12 Hz) event-related desynchronization (ERD) or a decrease in alpha power in electro- and magnetoencephalography (EEG and MEG) reflects the involvement of a neural tissue in information processing. It is known that most children with autism spectrum disorder (ASD) have difficulties in information processing, and, thus, investigation of alpha oscillations is of particular interest in this population. Previous studies have demonstrated alterations in this neural activity in individuals with ASD; however, little is known about alpha ERD during simultaneous presentation of auditory and visual stimuli in children with and without ASD. As alpha oscillations are intimately related to attention, and attention deficit is one of the common co-occurring conditions of ASD, we predict that children with ASD can have altered alpha ERD in one of the sensory domains. In the present study, we used MEG to investigate alpha ERD in groups of 20 children with ASD and 20 age-matched typically developing controls. Simple amplitude-modulated tones were presented together with a fixation cross appearing on the screen. The results showed that children with ASD had a bilateral reduction in alpha-band ERD in the auditory but not visual cortex. Moreover, alterations in the auditory cortex were associated with a higher presence of autistic traits measured in behavioral assessment.
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Affiliation(s)
- Vardan Arutiunian
- Center for Child Health, Behavior and Development, Seattle Children’s Research Institute, 1920 Terry Ave., Seattle, WA 98101, USA
| | - Giorgio Arcara
- IRCCS San Camillo Hospital, 70 Via Alberoni, Lido, 30126 Venice, Italy;
| | - Irina Buyanova
- Center for Language and Brain, HSE University, 3 Krivokolenny Pereulok, 101000 Moscow, Russia; (I.B.); (O.B.); (O.D.)
| | - Olga Buivolova
- Center for Language and Brain, HSE University, 3 Krivokolenny Pereulok, 101000 Moscow, Russia; (I.B.); (O.B.); (O.D.)
| | - Elizaveta Davydova
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, 19 Architectora Vlasova Str., 117335 Moscow, Russia; (E.D.); (D.P.); (A.S.); (S.T.); (U.M.); (K.D.)
- Chair of Differential Psychology and Psychophysiology, Moscow State University of Psychology and Education, 2A Shelepikhinaskaya Naberezhnaya, 123290 Moscow, Russia
| | - Darya Pereverzeva
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, 19 Architectora Vlasova Str., 117335 Moscow, Russia; (E.D.); (D.P.); (A.S.); (S.T.); (U.M.); (K.D.)
| | - Alexander Sorokin
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, 19 Architectora Vlasova Str., 117335 Moscow, Russia; (E.D.); (D.P.); (A.S.); (S.T.); (U.M.); (K.D.)
- Haskins Laboratories, 300 George St., New Haven, CT 06511, USA
| | - Svetlana Tyushkevich
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, 19 Architectora Vlasova Str., 117335 Moscow, Russia; (E.D.); (D.P.); (A.S.); (S.T.); (U.M.); (K.D.)
| | - Uliana Mamokhina
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, 19 Architectora Vlasova Str., 117335 Moscow, Russia; (E.D.); (D.P.); (A.S.); (S.T.); (U.M.); (K.D.)
| | - Kamilla Danilina
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, 19 Architectora Vlasova Str., 117335 Moscow, Russia; (E.D.); (D.P.); (A.S.); (S.T.); (U.M.); (K.D.)
- Scientific Research and Practical Center of Pediatric Psychoneurology, 74 Michurinskiy Prospekt, 119602 Moscow, Russia
| | - Olga Dragoy
- Center for Language and Brain, HSE University, 3 Krivokolenny Pereulok, 101000 Moscow, Russia; (I.B.); (O.B.); (O.D.)
- Institute of Linguistics, Russian Academy of Sciences, 1/1 Bolshoy Kislovsky Ln, 125009 Moscow, Russia
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40
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Zheng L, Liao P, Wu X, Cao M, Cui W, Lu L, Xu H, Zhu L, Lyu B, Wang X, Teng P, Wang J, Vogrin S, Plummer C, Luan G, Gao JH. An artificial intelligence-based pipeline for automated detection and localisation of epileptic sources from magnetoencephalography. J Neural Eng 2023; 20:046036. [PMID: 37615416 DOI: 10.1088/1741-2552/acef92] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 08/10/2023] [Indexed: 08/25/2023]
Abstract
Objective.Magnetoencephalography (MEG) is a powerful non-invasive diagnostic modality for presurgical epilepsy evaluation. However, the clinical utility of MEG mapping for localising epileptic foci is limited by its low efficiency, high labour requirements, and considerable interoperator variability. To address these obstacles, we proposed a novel artificial intelligence-based automated magnetic source imaging (AMSI) pipeline for automated detection and localisation of epileptic sources from MEG data.Approach.To expedite the analysis of clinical MEG data from patients with epilepsy and reduce human bias, we developed an autolabelling method, a deep-learning model based on convolutional neural networks and a hierarchical clustering method based on a perceptual hash algorithm, to enable the coregistration of MEG and magnetic resonance imaging, the detection and clustering of epileptic activity, and the localisation of epileptic sources in a highly automated manner. We tested the capability of the AMSI pipeline by assessing MEG data from 48 epilepsy patients.Main results.The AMSI pipeline was able to rapidly detect interictal epileptiform discharges with 93.31% ± 3.87% precision based on a 35-patient dataset (with sevenfold patientwise cross-validation) and robustly rendered accurate localisation of epileptic activity with a lobar concordance of 87.18% against interictal and ictal stereo-electroencephalography findings in a 13-patient dataset. We also showed that the AMSI pipeline accomplishes the necessary processes and delivers objective results within a much shorter time frame (∼12 min) than traditional manual processes (∼4 h).Significance.The AMSI pipeline promises to facilitate increased utilisation of MEG data in the clinical analysis of patients with epilepsy.
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Affiliation(s)
- Li Zheng
- Beijing City Key Laboratory of Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, People's Republic of China
- Changping Laboratory, Beijing, People's Republic of China
| | - Pan Liao
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China
| | - Xiuwen Wu
- Changping Laboratory, Beijing, People's Republic of China
- Center for Biomedical Engineering, University of Science and Technology of China, Anhui, People's Republic of China
| | - Miao Cao
- Beijing City Key Laboratory of Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, People's Republic of China
- Changping Laboratory, Beijing, People's Republic of China
| | - Wei Cui
- Center for Biomedical Engineering, University of Science and Technology of China, Anhui, People's Republic of China
| | - Lingxi Lu
- Center for the Cognitive Science of Language, Beijing Language and Culture University, Beijing, People's Republic of China
| | - Hui Xu
- Beijing City Key Laboratory of Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, People's Republic of China
| | - Linlin Zhu
- Beijing City Key Laboratory of Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, People's Republic of China
| | - Bingjiang Lyu
- Changping Laboratory, Beijing, People's Republic of China
| | - Xiongfei Wang
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, People's Republic of China
- Beijing Key Laboratory of Epilepsy, Capital Medical University, Beijing, People's Republic of China
| | - Pengfei Teng
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Jing Wang
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, People's Republic of China
| | - Simon Vogrin
- Department of Neuroimaging, Swinburne University of Technology, Melbourne, Australia
| | - Chris Plummer
- Department of Neuroimaging, Swinburne University of Technology, Melbourne, Australia
| | - Guoming Luan
- Department of Neurosurgery, Sanbo Brain Hospital, Capital Medical University, Beijing, People's Republic of China
- Beijing Key Laboratory of Epilepsy, Capital Medical University, Beijing, People's Republic of China
| | - Jia-Hong Gao
- Beijing City Key Laboratory of Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, People's Republic of China
- Changping Laboratory, Beijing, People's Republic of China
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People's Republic of China
- McGovern Institute for Brain Research, Peking University, Beijing, People's Republic of China
- National Biomedical Imaging Center, Peking University, Beijing, People's Republic of China
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Chen Y, Green HL, Putt ME, Allison O, Kuschner ES, Kim M, Blaskey L, Mol K, McNamee M, Bloy L, Liu S, Huang H, Roberts TPL, Edgar JC. Maturation of auditory cortex neural responses during infancy and toddlerhood. Neuroimage 2023; 275:120163. [PMID: 37178820 PMCID: PMC11463054 DOI: 10.1016/j.neuroimage.2023.120163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 04/28/2023] [Accepted: 05/09/2023] [Indexed: 05/15/2023] Open
Abstract
The infant auditory system rapidly matures across the first years of life, with a primary goal of obtaining ever-more-accurate real-time representations of the external world. Our understanding of how left and right auditory cortex neural processes develop during infancy, however, is meager, with few studies having the statistical power to detect potential hemisphere and sex differences in primary/secondary auditory cortex maturation. Using infant magnetoencephalography (MEG) and a cross-sectional study design, left and right auditory cortex P2m responses to pure tones were examined in 114 typically developing infants and toddlers (66 males, 2 to 24 months). Non-linear maturation of P2m latency was observed, with P2m latencies decreasing rapidly as a function of age during the first year of life, followed by slower changes between 12 and 24 months. Whereas in younger infants auditory tones were encoded more slowly in the left than right hemisphere, similar left and right P2m latencies were observed by ∼21 months of age due to faster maturation rate in the left than right hemisphere. No sex differences in the maturation of the P2m responses were observed. Finally, an earlier left than right hemisphere P2m latency predicted better language performance in older infants (12 to 24 months). Findings indicate the need to consider hemisphere when examining the maturation of auditory cortex neural activity in infants and toddlers and show that the pattern of left-right hemisphere P2m maturation is associated with language performance.
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Affiliation(s)
- Yuhan Chen
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States.
| | - Heather L Green
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States
| | - Mary E Putt
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Olivia Allison
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States
| | - Emily S Kuschner
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Mina Kim
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States
| | - Lisa Blaskey
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Kylie Mol
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States
| | - Marybeth McNamee
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States
| | - Luke Bloy
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States
| | - Song Liu
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States
| | - Hao Huang
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - Timothy P L Roberts
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
| | - J Christopher Edgar
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA 19104, United States; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States
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Pascarella A, Mikulan E, Sciacchitano F, Sarasso S, Rubino A, Sartori I, Cardinale F, Zauli F, Avanzini P, Nobili L, Pigorini A, Sorrentino A. An in-vivo validation of ESI methods with focal sources. Neuroimage 2023:120219. [PMID: 37307867 DOI: 10.1016/j.neuroimage.2023.120219] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 05/05/2023] [Accepted: 06/02/2023] [Indexed: 06/14/2023] Open
Abstract
Electrophysiological source imaging (ESI) aims at reconstructing the precise origin of brain activity from measurements of the electric field on the scalp. Across laboratories/research centers/hospitals, ESI is performed with different methods, partly due to the ill-posedness of the underlying mathematical problem. However, it is difficult to find systematic comparisons involving a wide variety of methods. Further, existing comparisons rarely take into account the variability of the results with respect to the input parameters. Finally, comparisons are typically performed using either synthetic data, or in-vivo data where the ground-truth is only roughly known. We use an in-vivo high-density EEG dataset recorded during intracranial single pulse electrical stimulation, in which the true sources are substantially dipolar and their locations are precisely known. We compare ten different ESI methods, using their implementation in the MNE-Python package: MNE, dSPM, LORETA, sLORETA, eLORETA, LCMV beamformers, irMxNE, Gamma Map, SESAME and dipole fitting. We perform comparisons under multiple choices of input parameters, to assess the accuracy of the best reconstruction, as well as the impact of such parameters on the localization performance. Best reconstructions often fall within 1 cm from the true source, with most accurate methods hitting an average localization error of 1.2 cm and outperforming least accurate ones erring by 2.5 cm. As expected, dipolar and sparsity-promoting methods tend to outperform distributed methods. For several distributed methods, the best regularization parameter turned out to be the one in principle associated with low SNR, despite the high SNR of the available dataset. Depth weighting played no role for two out of the six methods implementing it. Sensitivity to input parameters varied widely between methods. While one would expect high variability being associated with low localization error at the best solution, this is not always the case, with some methods producing highly variable results and high localization error, and other methods producing stable results with low localization error. In particular, recent dipolar and sparsity-promoting methods provide significantly better results than older distributed methods. As we repeated the tests with "conventional" (32 channels) and dense (64, 128, 256 channels) EEG recordings, we observed little impact of the number of channels on localization accuracy; however, for distributed methods denser montages provide smaller spatial dispersion. Overall findings confirm that EEG is a reliable technique for localization of point sources and therefore reinforce the importance that ESI may have in the clinical context, especially when applied to identify the surgical target in potential candidates for epilepsy surgery.
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Affiliation(s)
| | - Ezequiel Mikulan
- Department of Biomedical and Clinical Sciences "L. Sacco",Università degli Studi di Milano, Milan, Italy
| | | | - Simone Sarasso
- Department of Biomedical and Clinical Sciences "L. Sacco",Università degli Studi di Milano, Milan, Italy
| | - Annalisa Rubino
- Department of Neurosciences, Center for Epilepsy Surgery "C. Munari", Hospital Niguarda, Milan, Italy
| | - Ivana Sartori
- Department of Neurosciences, Center for Epilepsy Surgery "C. Munari", Hospital Niguarda, Milan, Italy
| | - Francesco Cardinale
- Department of Neurosciences, Center for Epilepsy Surgery "C. Munari", Hospital Niguarda, Milan, Italy
| | - Flavia Zauli
- Department of Biomedical and Clinical Sciences "L. Sacco",Università degli Studi di Milano, Milan, Italy
| | | | - Lino Nobili
- Child Neuropsychiatry Unit, IRCCS "G. Gaslini" Institute, Genoa, Italy; DINOGMI, Università degli Studi di Genova, Genoa, Italy
| | - Andrea Pigorini
- Department of Biomedical, Surgical and Dental Sciences, Università degli Studi di Milano, Milan, Italy
| | - Alberto Sorrentino
- Department of Mathematics, Università degli Studi di Genova, Genoa, Italy.
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Babajani-Feremi A, Pourmotabbed H, Schraegle WA, Calley CS, Clarke DF, Papanicolaou AC. MEG language mapping using a novel automatic ECD algorithm in comparison with MNE, dSPM, and DICS beamformer. Front Neurosci 2023; 17:1151885. [PMID: 37332870 PMCID: PMC10272516 DOI: 10.3389/fnins.2023.1151885] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Accepted: 04/24/2023] [Indexed: 06/20/2023] Open
Abstract
Introduction The single equivalent current dipole (sECD) is the standard clinical procedure for presurgical language mapping in epilepsy using magnetoencephalography (MEG). However, the sECD approach has not been widely used in clinical assessments, mainly because it requires subjective judgements in selecting several critical parameters. To address this limitation, we developed an automatic sECD algorithm (AsECDa) for language mapping. Methods The localization accuracy of the AsECDa was evaluated using synthetic MEG data. Subsequently, the reliability and efficiency of AsECDa were compared to three other common source localization methods using MEG data recorded during two sessions of a receptive language task in 21 epilepsy patients. These methods include minimum norm estimation (MNE), dynamic statistical parametric mapping (dSPM), and dynamic imaging of coherent sources (DICS) beamformer. Results For the synthetic single dipole MEG data with a typical signal-to-noise ratio, the average localization error of AsECDa was less than 2 mm for simulated superficial and deep dipoles. For the patient data, AsECDa showed better test-retest reliability (TRR) of the language laterality index (LI) than MNE, dSPM, and DICS beamformer. Specifically, the LI calculated with AsECDa revealed excellent TRR between the two MEG sessions across all patients (Cor = 0.80), while the LI for MNE, dSPM, DICS-event-related desynchronization (ERD) in the alpha band, and DICS-ERD in the low beta band ranged lower (Cor = 0.71, 0.64, 0.54, and 0.48, respectively). Furthermore, AsECDa identified 38% of patients with atypical language lateralization (i.e., right lateralization or bilateral), compared to 73%, 68%, 55%, and 50% identified by DICS-ERD in the low beta band, DICS-ERD in the alpha band, MNE, and dSPM, respectively. Compared to other methods, AsECDa's results were more consistent with previous studies that reported atypical language lateralization in 20-30% of epilepsy patients. Discussion Our study suggests that AsECDa is a promising approach for presurgical language mapping, and its fully automated nature makes it easy to implement and reliable for clinical evaluations.
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Affiliation(s)
- Abbas Babajani-Feremi
- Department of Neurology, University of Florida, Gainesville, FL, United States
- Magnetoencephalography (MEG) Lab, The Norman Fixel Institute of Neurological Diseases, University of Florida Health, Gainesville, FL, United States
- Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, TX, United States
| | - Haatef Pourmotabbed
- Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, TX, United States
| | - William A. Schraegle
- Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, TX, United States
- Comprehensive Pediatric Epilepsy Center, Dell Children’s Medical Center, Austin, TX, United States
- Department of Pediatrics, Dell Medical School, University of Texas at Austin, Austin, TX, United States
| | - Clifford S. Calley
- Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, TX, United States
- Comprehensive Pediatric Epilepsy Center, Dell Children’s Medical Center, Austin, TX, United States
- Department of Pediatrics, Dell Medical School, University of Texas at Austin, Austin, TX, United States
- Department of Neurosurgery, Dell Medical School, University of Texas at Austin, Austin, TX, United States
| | - Dave F. Clarke
- Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, TX, United States
- Comprehensive Pediatric Epilepsy Center, Dell Children’s Medical Center, Austin, TX, United States
- Department of Pediatrics, Dell Medical School, University of Texas at Austin, Austin, TX, United States
- Department of Neurosurgery, Dell Medical School, University of Texas at Austin, Austin, TX, United States
| | - Andrew C. Papanicolaou
- Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN, United States
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Xu F, Xu Y, Wang Y, Niu K, Li Y, Wang P, Li Y, Sun J, Chen Q, Wang X. Language-related brain areas in childhood epilepsy with centrotemporal spikes studied with MEG. Clin Neurophysiol 2023; 152:11-21. [PMID: 37257319 DOI: 10.1016/j.clinph.2023.05.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 05/05/2023] [Accepted: 05/10/2023] [Indexed: 06/02/2023]
Abstract
OBJECTIVE Children with self-limited epilepsy with centrotemporal spikes (SeLECTS) typically indicate cognitive impairment with widespread speech impairment. We explored how epilepsy affects language-related brain areas and areas in their vicinity. METHODS Twenty-two children with SeLECTS and declined verbal comprehension (DVC), 21 with SeLECTS and normal verbal comprehension (NVC), and 23 healthy controls (HCs) underwent high-sampling magnetoencephalography recordings. According to a previous study, 24 language-related regions of interest were selected bilaterally, and the relative spectral power was estimated using a minimum norm estimate. RESULTS The highest mean power spectral density was observed in the delta band for the DVC group, in the theta band for the NVC group, and in the alpha band for HCs within language-specific brain regions. The distinctions between the DVC and NVC groups in the delta and theta frequency bands were primarily concentrated in the right linguistic brain area. CONCLUSIONS Children with SeLECTS may have developmental problems in language-related brain areas, with different developmental levels observed in the DVC, NVC, and HC groups. The DVC group could have inferior speech comprehension due to a more significant number of seizures and more left-sided spike locations. SIGNIFICANCE Children having SeLECTS showed impaired brain maturation, leading to associated language impairment.
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Affiliation(s)
- Fengyuan Xu
- Country Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yue Xu
- Country Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yingfan Wang
- Country Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Kai Niu
- Country Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yihan Li
- Country Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Pengfei Wang
- Country Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yanzhang Li
- Country Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Jintao Sun
- Country Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Qiqi Chen
- Country MEG Center, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Xiaoshan Wang
- Country Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
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Kaufman M, Zion Golumbic E. Listening to two speakers: Capacity and tradeoffs in neural speech tracking during Selective and Distributed Attention. Neuroimage 2023; 270:119984. [PMID: 36854352 DOI: 10.1016/j.neuroimage.2023.119984] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 02/06/2023] [Accepted: 02/24/2023] [Indexed: 02/27/2023] Open
Abstract
Speech comprehension is severely compromised when several people talk at once, due to limited perceptual and cognitive resources. In such circumstances, top-down attention mechanisms can actively prioritize processing of task-relevant speech. However, behavioral and neural evidence suggest that this selection is not exclusive, and the system may have sufficient capacity to process additional speech input as well. Here we used a data-driven approach to contrast two opposing hypotheses regarding the system's capacity to co-represent competing speech: Can the brain represent two speakers equally or is the system fundamentally limited, resulting in tradeoffs between them? Neural activity was measured using magnetoencephalography (MEG) as human participants heard concurrent speech narratives and engaged in two tasks: Selective Attention, where only one speaker was task-relevant and Distributed Attention, where both speakers were equally relevant. Analysis of neural speech-tracking revealed that both tasks engaged a similar network of brain regions involved in auditory processing, attentional control and speech processing. Interestingly, during both Selective and Distributed Attention the neural representation of competing speech showed a bias towards one speaker. This is in line with proposed 'bottlenecks' for co-representation of concurrent speech and suggests that good performance on distributed attention tasks may be achieved by toggling attention between speakers over time.
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Affiliation(s)
- Maya Kaufman
- The Gonda Center for Multidisciplinary Brain Research, Bar Ilan University, Ramat Gan, Israel
| | - Elana Zion Golumbic
- The Gonda Center for Multidisciplinary Brain Research, Bar Ilan University, Ramat Gan, Israel.
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Allouch S, Kabbara A, Duprez J, Khalil M, Modolo J, Hassan M. Effect of channel density, inverse solutions and connectivity measures on EEG resting-state networks reconstruction: A simulation study. Neuroimage 2023; 271:120006. [PMID: 36914106 DOI: 10.1016/j.neuroimage.2023.120006] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 02/06/2023] [Accepted: 03/07/2023] [Indexed: 03/13/2023] Open
Abstract
Along with the study of brain activity evoked by external stimuli, the past two decades witnessed an increased interest in characterizing the spontaneous brain activity occurring during resting conditions. The identification of connectivity patterns in this so-called "resting-state" has been the subject of a great number of electrophysiology-based studies, using the Electro/Magneto-Encephalography (EEG/MEG) source connectivity method. However, no consensus has been reached yet regarding a unified (if possible) analysis pipeline, and several involved parameters and methods require cautious tuning. This is particularly challenging when different analytical choices induce significant discrepancies in results and drawn conclusions, thereby hindering the reproducibility of neuroimaging research. Hence, our objective in this study was to shed light on the effect of analytical variability on outcome consistency by evaluating the implications of parameters involved in the EEG source connectivity analysis on the accuracy of resting-state networks (RSNs) reconstruction. We simulated, using neural mass models, EEG data corresponding to two RSNs, namely the default mode network (DMN) and dorsal attentional network (DAN). We investigated the impact of five channel densities (19, 32, 64, 128, 256), three inverse solutions (weighted minimum norm estimate (wMNE), exact low-resolution brain electromagnetic tomography (eLORETA), and linearly constrained minimum variance (LCMV) beamforming) and four functional connectivity measures (phase-locking value (PLV), phase-lag index (PLI), and amplitude envelope correlation (AEC) with and without source leakage correction), on the correspondence between reconstructed and reference networks. We showed that, with different analytical choices related to the number of electrodes, source reconstruction algorithm, and functional connectivity measure, high variability is present in the results. More specifically, our results show that a higher number of EEG channels significantly increased the accuracy of the reconstructed networks. Additionally, our results showed significant variability in the performance of the tested inverse solutions and connectivity measures. Such methodological variability and absence of analysis standardization represent a critical issue for neuroimaging studies that should be prioritized. We believe that this work could be useful for the field of electrophysiology connectomics, by increasing awareness regarding the challenge of variability in methodological approaches and its implications on reported results.
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Affiliation(s)
- Sahar Allouch
- Univ Rennes, INSERM, LTSI - UMR 1099, Rennes F-35000, France; Azm Center for Research in Biotechnology and Its Applications, EDST, Tripoli, Lebanon.
| | - Aya Kabbara
- MINDIG, Rennes F-35000, France; LASeR - Lebanese Association for Scientific Research, Tripoli, Lebanon
| | - Joan Duprez
- Univ Rennes, INSERM, LTSI - UMR 1099, Rennes F-35000, France
| | - Mohamad Khalil
- Azm Center for Research in Biotechnology and Its Applications, EDST, Tripoli, Lebanon; CRSI research center, Faculty of Engineering, Lebanese University, Beirut, Lebanon
| | - Julien Modolo
- Univ Rennes, INSERM, LTSI - UMR 1099, Rennes F-35000, France
| | - Mahmoud Hassan
- MINDIG, Rennes F-35000, France; School of Science and Engineering, Reykjavik University, Reykjavik, Iceland
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Arutiunian V, Arcara G, Buyanova I, Davydova E, Pereverzeva D, Sorokin A, Tyushkevich S, Mamokhina U, Danilina K, Dragoy O. Neuromagnetic 40 Hz Auditory Steady-State Response in the left auditory cortex is related to language comprehension in children with Autism Spectrum Disorder. Prog Neuropsychopharmacol Biol Psychiatry 2023; 122:110690. [PMID: 36470421 DOI: 10.1016/j.pnpbp.2022.110690] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 11/06/2022] [Accepted: 11/29/2022] [Indexed: 12/08/2022]
Abstract
Language impairment is comorbid in most children with Autism Spectrum Disorder (ASD), but its neural mechanisms are still poorly understood. Some studies hypothesize that the atypical low-level sensory perception in the auditory cortex accounts for the abnormal language development in these children. One of the potential non-invasive measures of such low-level perception can be the cortical gamma-band oscillations registered with magnetoencephalography (MEG), and 40 Hz Auditory Steady-State Response (40 Hz ASSR) is a reliable paradigm for eliciting auditory gamma response. Although there is research in children with and without ASD using 40 Hz ASSR, nothing is known about the relationship between this auditory response in children with ASD and their language abilities measured directly in formal assessment. In the present study, we used MEG and individual brain models to investigate 40 Hz ASSR in primary-school-aged children with and without ASD. It was also used to assess how the strength of the auditory response is related to language abilities of children with ASD, their non-verbal IQ, and social functioning. A total of 40 children were included in the study. The results demonstrated that 40 Hz ASSR was reduced in the right auditory cortex in children with ASD when comparing them to typically developing controls. Importantly, our study provides the first evidence of the association between 40 Hz ASSR in the language-dominant left auditory cortex and language comprehension in children with ASD. This link was domain-specific because the other brain-behavior correlations were non-significant.
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Affiliation(s)
| | | | - Irina Buyanova
- Center for Language and Brain, HSE University, Moscow, Russia
| | - Elizaveta Davydova
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Moscow, Russia; Chair of Differential Psychology and Psychophysiology, Moscow State University of Psychology and Education, Moscow, Russia
| | - Darya Pereverzeva
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Moscow, Russia
| | - Alexander Sorokin
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Moscow, Russia; Haskins Laboratories, New Haven, CT, United States of America
| | - Svetlana Tyushkevich
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Moscow, Russia
| | - Uliana Mamokhina
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Moscow, Russia
| | - Kamilla Danilina
- Federal Resource Center for ASD, Moscow State University of Psychology and Education, Moscow, Russia
| | - Olga Dragoy
- Center for Language and Brain, HSE University, Moscow, Russia; Institute of Linguistics, Russian Academy of Sciences, Moscow, Russia
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Hatlestad-Hall C, Bruña R, Liljeström M, Renvall H, Heuser K, Taubøll E, Maestú F, Haraldsen IH. Reliable evaluation of functional connectivity and graph theory measures in source-level EEG: How many electrodes are enough? Clin Neurophysiol 2023; 150:1-16. [PMID: 36972647 DOI: 10.1016/j.clinph.2023.03.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 02/03/2023] [Accepted: 03/01/2023] [Indexed: 03/18/2023]
Abstract
OBJECTIVE Using EEG to characterise functional brain networks through graph theory has gained significant interest in clinical and basic research. However, the minimal requirements for reliable measures remain largely unaddressed. Here, we examined functional connectivity estimates and graph theory metrics obtained from EEG with varying electrode densities. METHODS EEG was recorded with 128 electrodes in 33 participants. The high-density EEG data were subsequently subsampled into three sparser montages (64, 32, and 19 electrodes). Four inverse solutions, four measures of functional connectivity, and five graph theory metrics were tested. RESULTS The correlation between the results obtained with 128-electrode and the subsampled montages decreased as a function of the number of electrodes. As a result of decreased electrode density, the network metrics became skewed: mean network strength and clustering coefficient were overestimated, while characteristic path length was underestimated. CONCLUSIONS Several graph theory metrics were altered when electrode density was reduced. Our results suggest that, for optimal balance between resource demand and result precision, a minimum of 64 electrodes should be utilised when graph theory metrics are used to characterise functional brain networks in source-reconstructed EEG data. SIGNIFICANCE Characterisation of functional brain networks derived from low-density EEG warrants careful consideration.
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Affiliation(s)
| | - Ricardo Bruña
- Centre for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain; Department of Radiology, Universidad Complutense de Madrid, Madrid, Spain
| | - Mia Liljeström
- Department of Neuroscience and Biomedical Engineering, Aalto University, Helsinki, Finland; BioMag Laboratory, HUS Medical Imaging Centre, Helsinki University Hospital, Helsinki, Finland
| | - Hanna Renvall
- Department of Neuroscience and Biomedical Engineering, Aalto University, Helsinki, Finland; BioMag Laboratory, HUS Medical Imaging Centre, Helsinki University Hospital, Helsinki, Finland
| | - Kjell Heuser
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Erik Taubøll
- Department of Neurology, Oslo University Hospital, Oslo, Norway; Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Fernando Maestú
- Centre for Cognitive and Computational Neuroscience, Universidad Complutense de Madrid, Madrid, Spain; Department of Experimental Psychology, Universidad Complutense de Madrid, Pozuelo de Alarcón, Spain
| | - Ira H Haraldsen
- Department of Neurology, Oslo University Hospital, Oslo, Norway; BrainSymph AS, Oslo, Norway
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Huels ER, Kafashan M, Hickman LB, Ching S, Lin N, Lenze EJ, Farber NB, Avidan MS, Hogan RE, Palanca BJA. Central-positive complexes in ECT-induced seizures: Possible evidence for thalamocortical mechanisms. Clin Neurophysiol 2023; 146:77-86. [PMID: 36549264 PMCID: PMC10273093 DOI: 10.1016/j.clinph.2022.11.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 10/20/2022] [Accepted: 11/27/2022] [Indexed: 12/13/2022]
Abstract
OBJECTIVE Central-positive complexes (CPCs) are elicited during electroconvulsive therapy (ECT) as generalized high-amplitude waveforms with maximum positive voltage over the vertex. While these complexes have been qualitatively assessed in previous literature, quantitative analyses are lacking. This study aims to characterize CPCs across temporal, spatial, and spectral domains. METHODS High-density 64-electrode electroencephalogram (EEG) recordings during 50 seizures acquired from 11 patients undergoing right unilateral ECT allowed for evaluation of spatiotemporal characteristics of CPCs via source localization and spectral analysis. RESULTS Peak-amplitude CPC scalp topology was consistent across seizures, showing maximal positive polarity over the midline fronto-central region and maximal negative polarity over the suborbital regions. The sources of these peak potentials were localized to the bilateral medial thalamus and cingulate cortical regions. Delta, beta, and gamma oscillations were correlated with the peak amplitude of CPCs during seizures induced during ketamine, whereas delta and gamma oscillations were associated with CPC peaks during etomidate anesthesia (excluding the dose-charge titration). CONCLUSIONS Our findings demonstrate the consistency of CPC presence across participant, stimulus charge, time, and anesthetic agent, with peaks localized to bilateral medial thalamus and cingulate cortical regions and associated with delta, beta, and gamma band oscillations (depending on the anesthetic condition). SIGNIFICANCE The consistency and reproducibility of CPCs offers ECT as a new avenue for studying the dynamics of generalized seizure activity and thalamocortical networks.
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Affiliation(s)
- Emma R Huels
- Department of Anesthesiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA; Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI, USA; Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA; Center for Consciousness Science, University of Michigan, Ann Arbor, MI, USA
| | - MohammadMehdi Kafashan
- Department of Anesthesiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA; Center on Biological Rhythms and Sleep, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - L Brian Hickman
- Department of Anesthesiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA; Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - ShiNung Ching
- Department of Electrical & Systems Engineering, Washington University in St. Louis, St. Louis, MO, USA; Division of Biology and Biomedical Sciences, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Nan Lin
- Department of Mathematics and Statistics, Washington University in St. Louis, St. Louis, MO, USA
| | - Eric J Lenze
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Nuri B Farber
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Michael S Avidan
- Department of Anesthesiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA; Division of Biology and Biomedical Sciences, Washington University School of Medicine in St. Louis, St. Louis, MO, USA; Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - R Edward Hogan
- Department of Neurology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Ben Julian A Palanca
- Department of Anesthesiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA; Center on Biological Rhythms and Sleep, Washington University School of Medicine in St. Louis, St. Louis, MO, USA; Division of Biology and Biomedical Sciences, Washington University School of Medicine in St. Louis, St. Louis, MO, USA; Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO, USA; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA; Neuroimaging Labs Research Center, Washington University School of Medicine in St. Louis, St. Louis, MO, USA.
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50
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Alho J, Khan S, Mamashli F, Perrachione TK, Losh A, McGuiggan NM, Graham S, Nayal Z, Joseph RM, Hämäläinen MS, Bharadwaj H, Kenet T. Atypical cortical processing of bottom-up speech binding cues in children with autism spectrum disorders. Neuroimage Clin 2023; 37:103336. [PMID: 36724734 PMCID: PMC9898310 DOI: 10.1016/j.nicl.2023.103336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 01/10/2023] [Accepted: 01/20/2023] [Indexed: 01/23/2023]
Abstract
Individuals with autism spectrum disorder (ASD) commonly display speech processing abnormalities. Binding of acoustic features of speech distributed across different frequencies into coherent speech objects is fundamental in speech perception. Here, we tested the hypothesis that the cortical processing of bottom-up acoustic cues for speech binding may be anomalous in ASD. We recorded magnetoencephalography while ASD children (ages 7-17) and typically developing peers heard sentences of sine-wave speech (SWS) and modulated SWS (MSS) where binding cues were restored through increased temporal coherence of the acoustic components and the introduction of harmonicity. The ASD group showed increased long-range feedforward functional connectivity from left auditory to parietal cortex with concurrent decreased local functional connectivity within the parietal region during MSS relative to SWS. As the parietal region has been implicated in auditory object binding, our findings support our hypothesis of atypical bottom-up speech binding in ASD. Furthermore, the long-range functional connectivity correlated with behaviorally measured auditory processing abnormalities, confirming the relevance of these atypical cortical signatures to the ASD phenotype. Lastly, the group difference in the local functional connectivity was driven by the youngest participants, suggesting that impaired speech binding in ASD might be ameliorated upon entering adolescence.
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Affiliation(s)
- Jussi Alho
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Boston, MA 02129, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Boston, MA 02129, USA.
| | - Sheraz Khan
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Boston, MA 02129, USA; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Boston, MA 02129, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Boston, MA 02129, USA
| | - Fahimeh Mamashli
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Boston, MA 02129, USA; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Boston, MA 02129, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Boston, MA 02129, USA
| | - Tyler K Perrachione
- Department of Speech, Language, and Hearing Sciences, Boston University, 635 Commonwealth Ave, Boston, MA 02215, USA
| | - Ainsley Losh
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Boston, MA 02129, USA
| | - Nicole M McGuiggan
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Boston, MA 02129, USA
| | - Steven Graham
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Boston, MA 02129, USA
| | - Zein Nayal
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Boston, MA 02129, USA
| | - Robert M Joseph
- Department of Anatomy and Neurobiology, Boston University School of Medicine, 72 East Concord St, Boston, MA 02118, USA
| | - Matti S Hämäläinen
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Boston, MA 02129, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Boston, MA 02129, USA
| | - Hari Bharadwaj
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Boston, MA 02129, USA; Department of Speech, Language, and Hearing Sciences, and Weldon School of Biomedical Engineering, Purdue University, 715 Clinic Drive, West Lafayette, IN 47907, USA
| | - Tal Kenet
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Boston, MA 02129, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, 149 13th St, Boston, MA 02129, USA.
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