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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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Gilbreath D, Hagood D, Larson-Prior L. A Systematic Review over the Effect of Early Infant Diet on Neurodevelopment: Insights from Neuroimaging. Nutrients 2024; 16:1703. [PMID: 38892636 PMCID: PMC11174660 DOI: 10.3390/nu16111703] [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: 03/20/2024] [Revised: 04/29/2024] [Accepted: 05/23/2024] [Indexed: 06/21/2024] Open
Abstract
The optimization of infant neuronal development through nutrition is an increasingly studied area. While human milk consumption during infancy is thought to give a slight cognitive advantage throughout early childhood in comparison to commercial formula, the biological underpinnings of this process are less well-known and debated in the literature. This systematic review seeks to quantitatively analyze whether early diet affects infant neurodevelopment as measured by various neuroimaging modalities and techniques. Results presented suggest that human milk does have a slight positive impact on the structural development of the infant brain-and that this impact is larger in preterm infants. Other diets with distinct macronutrient compositions were also considered, although these had more conflicting results.
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Affiliation(s)
- Dylan Gilbreath
- Department of Neurobiology and Developmental Sciences, University of Arkansas for Medical Science, Little Rock, AR 72207, USA;
- Arkansas Children’s Nutrition Center, Little Rock, AR 72202, USA;
| | - Darcy Hagood
- Arkansas Children’s Nutrition Center, Little Rock, AR 72202, USA;
| | - Linda Larson-Prior
- Department of Neurobiology and Developmental Sciences, University of Arkansas for Medical Science, Little Rock, AR 72207, USA;
- Arkansas Children’s Nutrition Center, Little Rock, AR 72202, USA;
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3
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Turk-Browne NB, Aslin RN. Infant neuroscience: how to measure brain activity in the youngest minds. Trends Neurosci 2024; 47:338-354. [PMID: 38570212 DOI: 10.1016/j.tins.2024.02.003] [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: 06/30/2023] [Revised: 01/08/2024] [Accepted: 02/09/2024] [Indexed: 04/05/2024]
Abstract
The functional properties of the infant brain are poorly understood. Recent advances in cognitive neuroscience are opening new avenues for measuring brain activity in human infants. These include novel uses of existing technologies such as electroencephalography (EEG) and magnetoencephalography (MEG), the availability of newer technologies including functional near-infrared spectroscopy (fNIRS) and optically pumped magnetometry (OPM), and innovative applications of functional magnetic resonance imaging (fMRI) in awake infants during cognitive tasks. In this review article we catalog these available non-invasive methods, discuss the challenges and opportunities encountered when applying them to human infants, and highlight the potential they may ultimately hold for advancing our understanding of the youngest minds.
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Affiliation(s)
- Nicholas B Turk-Browne
- Department of Psychology, Yale University, New Haven, CT 06520, USA; Wu Tsai Institute, Yale University, New Haven, CT 06510, USA.
| | - Richard N Aslin
- Department of Psychology, Yale University, New Haven, CT 06520, USA; Child Study Center, Yale School of Medicine, New Haven, CT 06520, USA
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4
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Sano M, Hirosawa T, Yoshimura Y, Hasegawa C, An KM, Tanaka S, Yaoi K, Naitou N, Kikuchi M. Neural responses to syllable-induced P1m and social impairment in children with autism spectrum disorder and typically developing Peers. PLoS One 2024; 19:e0298020. [PMID: 38457397 PMCID: PMC10923473 DOI: 10.1371/journal.pone.0298020] [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: 07/16/2023] [Accepted: 01/17/2024] [Indexed: 03/10/2024] Open
Abstract
In previous magnetoencephalography (MEG) studies, children with autism spectrum disorder (ASD) have been shown to respond differently to speech stimuli than typically developing (TD) children. Quantitative evaluation of this difference in responsiveness may support early diagnosis and intervention for ASD. The objective of this research is to investigate the relationship between syllable-induced P1m and social impairment in children with ASD and TD children. We analyzed 49 children with ASD aged 40-92 months and age-matched 26 TD children. We evaluated their social impairment by means of the Social Responsiveness Scale (SRS) and their intelligence ability using the Kaufman Assessment Battery for Children (K-ABC). Multiple regression analysis with SRS score as the dependent variable and syllable-induced P1m latency or intensity and intelligence ability as explanatory variables revealed that SRS score was associated with syllable-induced P1m latency in the left hemisphere only in the TD group and not in the ASD group. A second finding was that increased leftward-lateralization of intensity was correlated with higher SRS scores only in the ASD group. These results provide valuable insights but also highlight the intricate nature of neural mechanisms and their relationship with autistic traits.
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Affiliation(s)
- Masuhiko Sano
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
| | - Tetsu Hirosawa
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Yuko Yoshimura
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
- Faculty of Education, Institute of Human and Social Sciences, Kanazawa University, Kanazawa, Japan
| | - Chiaki Hasegawa
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Kyung-Min An
- School of Psychology, University of Birmingham, Birmingham, United Kingdom
| | - Sanae Tanaka
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Ken Yaoi
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Nobushige Naitou
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
| | - Mitsuru Kikuchi
- Department of Psychiatry and Neurobiology, Graduate School of Medical Science, Kanazawa University, Kanazawa, Japan
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
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5
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Green HL, Shen G, Franzen RE, Mcnamee M, Berman JI, Mowad TG, Ku M, Bloy L, Liu S, Chen YH, Airey M, McBride E, Goldin S, Dipiero MA, Blaskey L, Kuschner ES, Kim M, Konka K, Roberts TPL, Edgar JC. Differential Maturation of Auditory Cortex Activity in Young Children with Autism and Typical Development. J Autism Dev Disord 2023; 53:4076-4089. [PMID: 35960416 PMCID: PMC9372967 DOI: 10.1007/s10803-022-05696-8] [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] [Accepted: 07/22/2022] [Indexed: 11/20/2022]
Abstract
Maturation of auditory cortex neural encoding processes was assessed in children with typical development (TD) and autism. Children 6-9 years old were enrolled at Time 1 (T1), with follow-up data obtained ~ 18 months later at Time 2 (T2), and ~ 36 months later at Time 3 (T3). Findings suggested an initial period of rapid auditory cortex maturation in autism, earlier than TD (prior to and surrounding the T1 exam), followed by a period of faster maturation in TD than autism (T1-T3). As a result of group maturation differences, post-stimulus group differences were observed at T1 but not T3. In contrast, stronger pre-stimulus activity in autism than TD was found at all time points, indicating this brain measure is stable across time.
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Affiliation(s)
- Heather L Green
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
| | - Guannan Shen
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Rose E Franzen
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Marybeth Mcnamee
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Jeffrey I Berman
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Theresa G Mowad
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew Ku
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Luke Bloy
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Song Liu
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Yu-Han Chen
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Megan Airey
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Emma McBride
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Sophia Goldin
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Marissa A Dipiero
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Lisa Blaskey
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Autism Research, Department of Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Emily S Kuschner
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Center for Autism Research, Department of Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Mina Kim
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Kimberly Konka
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Timothy P L Roberts
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - J Christopher Edgar
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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6
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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 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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7
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Edgar JC, Franzen RE, McNamee M, Green HL, Shen G, DiPiero M, Liu S, Airey M, Goldin S, Blaskey L, Kuschner ES, Kim M, Konka K, Roberts TP, Chen Y. A comparison of resting-state eyes-closed and dark-room alpha-band activity in children. Psychophysiology 2023; 60:e14285. [PMID: 36929476 PMCID: PMC11097109 DOI: 10.1111/psyp.14285] [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: 05/03/2022] [Revised: 02/14/2023] [Accepted: 02/16/2023] [Indexed: 03/18/2023]
Abstract
In a relaxed and awake state with the eyes closed, 8-12 Hz neural oscillations are the dominant rhythm, most prominent in parietal-occipital regions. Resting-state (RS) alpha is associated with processing speed and is also thought to be central to how networks process information. Unfortunately, the RS eyes-closed (EC) exam can only be used with individuals who can remain awake with their eyes closed for an extended period. As such, infants, toddlers, and individuals with intellectual disabilities are usually excluded from RS alpha studies. Previous research suggests obtaining RS alpha measures in a dark room with the eyes open as a viable alternative to the traditional RS EC exam. To further explore this, RS EC and RS dark room (DR) eyes-open alpha activity was recorded using magnetoencephalography in children with typical development (TD; N = 37) and children with autism spectrum disorder (ASD; N = 30) 6.9-12.6 years old. Findings showed good reliability for the RS EC and DR peak alpha frequency (frequency with strongest alpha power; interclass correlation (ICC) = 0.83). ICCs for posterior alpha power were slightly lower (ICCs in the 0.70 s), with an ~ 5% reduction in posterior alpha power in the DR than EC condition. No differences in the EC and DR associations were observed between the TD and ASD groups. Finally, age was associated with both EC and DR peak alpha frequency. Findings thus indicate the DR exam as a viable way to obtain RS alpha measures in populations frequently excluded from electrophysiology RS studies.
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Affiliation(s)
- J. Christopher Edgar
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania
| | - Rose E. Franzen
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Marybeth McNamee
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Heather L. Green
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Guannan Shen
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Marissa DiPiero
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Song Liu
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Megan Airey
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Sophia Goldin
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Lisa Blaskey
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania
- Center for Autism Research, Department of Pediatrics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Emily S. Kuschner
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Center for Autism Research, Department of Pediatrics, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Mina Kim
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Kimberly Konka
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
| | - Timothy P.L. Roberts
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania
| | - Yuhan Chen
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA
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Chen Y, Allison O, Green HL, Kuschner ES, Liu S, Kim M, Slinger M, Mol K, Chiang T, Bloy L, Roberts TPL, Edgar JC. Maturational trajectory of fusiform gyrus neural activity when viewing faces: From 4 months to 4 years old. Front Hum Neurosci 2022; 16:917851. [PMID: 36034116 PMCID: PMC9411513 DOI: 10.3389/fnhum.2022.917851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 07/20/2022] [Indexed: 11/26/2022] Open
Abstract
Infant and young child electrophysiology studies have provided information regarding the maturation of face-encoding neural processes. A limitation of previous research is that very few studies have examined face-encoding processes in children 12-48 months of age, a developmental period characterized by rapid changes in the ability to encode facial information. The present study sought to fill this gap in the literature via a longitudinal study examining the maturation of a primary node in the face-encoding network-the left and right fusiform gyrus (FFG). Whole-brain magnetoencephalography (MEG) data were obtained from 25 infants with typical development at 4-12 months, and with follow-up MEG exams every ∼12 months until 3-4 years old. Children were presented with color images of Face stimuli and visual noise images (matched on spatial frequency, color distribution, and outer contour) that served as Non-Face stimuli. Using distributed source modeling, left and right face-sensitive FFG evoked waveforms were obtained from each child at each visit, with face-sensitive activity identified via examining the difference between the Non-Face and Face FFG timecourses. Before 24 months of age (Visits 1 and 2) the face-sensitive FFG M290 response was the dominant response, observed in the left and right FFG ∼250-450 ms post-stimulus. By 3-4 years old (Visit 4), the left and right face-sensitive FFG response occurred at a latency consistent with a face-sensitive M170 response ∼100-250 ms post-stimulus. Face-sensitive left and right FFG peak latencies decreased as a function of age (with age explaining greater than 70% of the variance in face-sensitive FFG latency), and with an adult-like FFG latency observed at 3-4 years old. Study findings thus showed face-sensitive FFG maturational changes across the first 4 years of life. Whereas a face-sensitive M290 response was observed under 2 years of age, by 3-4 years old, an adult-like face-sensitive M170 response was observed bilaterally. Future studies evaluating the maturation of face-sensitive FFG activity in infants at risk for neurodevelopmental disorders are of interest, with the present findings suggesting age-specific face-sensitive neural markers of a priori interest.
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Affiliation(s)
- Yuhan Chen
- Lurie Family Foundations MEG Imaging Center, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
| | - Olivia Allison
- Lurie Family Foundations MEG Imaging Center, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
| | - Heather L. Green
- Lurie Family Foundations MEG Imaging Center, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
| | - Emily S. Kuschner
- Lurie Family Foundations MEG Imaging Center, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Song Liu
- Lurie Family Foundations MEG Imaging Center, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
| | - Mina Kim
- Lurie Family Foundations MEG Imaging Center, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
| | - Michelle Slinger
- Lurie Family Foundations MEG Imaging Center, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
| | - Kylie Mol
- Lurie Family Foundations MEG Imaging Center, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
| | - Taylor Chiang
- Lurie Family Foundations MEG Imaging Center, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
| | - Luke Bloy
- Lurie Family Foundations MEG Imaging Center, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
| | - Timothy P. L. Roberts
- Lurie Family Foundations MEG Imaging Center, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - J. Christopher Edgar
- Lurie Family Foundations MEG Imaging Center, Children’s Hospital of Philadelphia, Philadelphia, PA, United States
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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9
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Brookes MJ, Leggett J, Rea M, Hill RM, Holmes N, Boto E, Bowtell R. Magnetoencephalography with optically pumped magnetometers (OPM-MEG): the next generation of functional neuroimaging. Trends Neurosci 2022; 45:621-634. [PMID: 35779970 PMCID: PMC10465236 DOI: 10.1016/j.tins.2022.05.008] [Citation(s) in RCA: 48] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 05/06/2022] [Accepted: 05/24/2022] [Indexed: 10/17/2022]
Abstract
Magnetoencephalography (MEG) measures human brain function via assessment of the magnetic fields generated by electrical activity in neurons. Despite providing high-quality spatiotemporal maps of electrophysiological activity, current MEG instrumentation is limited by cumbersome field sensing technologies, resulting in major barriers to utility. Here, we review a new generation of MEG technology that is beginning to lift many of these barriers. By exploiting quantum sensors, known as optically pumped magnetometers (OPMs), 'OPM-MEG' has the potential to dramatically outperform the current state of the art, promising enhanced data quality (better sensitivity and spatial resolution), adaptability to any head size/shape (from babies to adults), motion robustness (participants can move freely during scanning), and a less complex imaging platform (without reliance on cryogenics). We discuss the current state of this emerging technique and describe its far-reaching implications for neuroscience.
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Affiliation(s)
- Matthew J Brookes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK.
| | - James Leggett
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Molly Rea
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Ryan M Hill
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Niall Holmes
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Elena Boto
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Richard Bowtell
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
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10
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Research on the Correlation between Multisource Big Data Virtual Assisted Preschool Education and the Development of Children’s Innovative Ability. Occup Ther Int 2022; 2022:3880201. [PMID: 35572165 PMCID: PMC9068341 DOI: 10.1155/2022/3880201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Revised: 04/02/2022] [Accepted: 04/06/2022] [Indexed: 11/17/2022] Open
Abstract
Objective. Innovation ability is an important part of children’s core literacy and the core goal of science curriculum. As one of the important contents of scientific literacy, innovation ability is the key ability of young children to make informed decisions when facing scientific problems in social and personal life. In order to adapt to the future life, it is very important for children to have the ability to innovate. This research will provide a reference for the cultivation of children’s innovative ability. Method. In the process of database design, certain design principles need to be followed. In this paper, the system and user experience are greatly optimized by reasonably constructing table structure, allocating storage space, and establishing indexes. In this system, the MySQL database is used to store system data, such as user registration information, subscription information, and system-provided services, and the data uploaded by users that needs to be processed is stored in Hive. Although the GFP algorithm can solve the problem of load balancing, when the largest conditional pattern base of a frequent item is projected to other nodes, a large amount of data transmission will occur, resulting in increased communication between nodes. In order to solve this problem, the FP-growth parallel algorithm based on traffic optimization gives priority to assigning each frequent item to the node that needs the least traffic when grouping it. Results/Discussion. Experiments show that the TFP algorithm not only satisfies the load balance of nodes but also ensures a small amount of communication between nodes, which is more efficient than the traditional FP-growth parallel algorithm. The survey results of the influencing factors of children’s innovation ability match the theoretical hypothesis, and different influencing factors have different effects on each dimension of children’s innovation ability. Through the basic fit index of the model, the evaluation of the external quality of the model and the test of the internal quality of the model, it is shown that the survey results of the influencing factors of children’s innovation ability match the theoretical hypothesis. The three influencing factors of family participation and investment, teacher teaching, and peer collaboration and communication have a positive role in promoting children’s innovation ability.
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11
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Clarke MD, Bosseler AN, Mizrahi JC, Peterson ER, Larson E, Meltzoff AN, Kuhl PK, Taulu S. Infant brain imaging using magnetoencephalography: Challenges, solutions, and best practices. Hum Brain Mapp 2022; 43:3609-3619. [PMID: 35429095 PMCID: PMC9294291 DOI: 10.1002/hbm.25871] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 02/24/2022] [Accepted: 03/17/2022] [Indexed: 11/18/2022] Open
Abstract
The excellent temporal resolution and advanced spatial resolution of magnetoencephalography (MEG) makes it an excellent tool to study the neural dynamics underlying cognitive processes in the developing brain. Nonetheless, a number of challenges exist when using MEG to image infant populations. There is a persistent belief that collecting MEG data with infants presents a number of limitations and challenges that are difficult to overcome. Due to this notion, many researchers either avoid conducting infant MEG research or believe that, in order to collect high-quality data, they must impose limiting restrictions on the infant or the experimental paradigm. In this article, we discuss the various challenges unique to imaging awake infants and young children with MEG, and share general best-practice guidelines and recommendations for data collection, acquisition, preprocessing, and analysis. The current article is focused on methodology that allows investigators to test the sensory, perceptual, and cognitive capacities of awake and moving infants. We believe that such methodology opens the pathway for using MEG to provide mechanistic explanations for the complex behavior observed in awake, sentient, and dynamically interacting infants, thus addressing core topics in developmental cognitive neuroscience.
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Affiliation(s)
- Maggie D. Clarke
- Institute for Learning & Brain SciencesUniversity of WashingtonSeattleWashingtonUSA
| | - Alexis N. Bosseler
- Institute for Learning & Brain SciencesUniversity of WashingtonSeattleWashingtonUSA
| | - Julia C. Mizrahi
- Institute for Learning & Brain SciencesUniversity of WashingtonSeattleWashingtonUSA
| | - Erica R. Peterson
- Institute for Learning & Brain SciencesUniversity of WashingtonSeattleWashingtonUSA
| | - Eric Larson
- Institute for Learning & Brain SciencesUniversity of WashingtonSeattleWashingtonUSA
| | - Andrew N. Meltzoff
- Institute for Learning & Brain SciencesUniversity of WashingtonSeattleWashingtonUSA,Department of PsychologyUniversity of WashingtonSeattleWashingtonUSA
| | - Patricia K. Kuhl
- Institute for Learning & Brain SciencesUniversity of WashingtonSeattleWashingtonUSA,Department of Speech and Hearing SciencesUniversity of WashingtonSeattleWashingtonUSA
| | - Samu Taulu
- Institute for Learning & Brain SciencesUniversity of WashingtonSeattleWashingtonUSA,Department of PhysicsUniversity of WashingtonSeattleWashingtonUSA
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12
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Vo Van P, Alison M, Morel B, Beck J, Bednarek N, Hertz-Pannier L, Loron G. Advanced Brain Imaging in Preterm Infants: A Narrative Review of Microstructural and Connectomic Disruption. CHILDREN (BASEL, SWITZERLAND) 2022; 9:children9030356. [PMID: 35327728 PMCID: PMC8947160 DOI: 10.3390/children9030356] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Revised: 02/21/2022] [Accepted: 03/02/2022] [Indexed: 11/16/2022]
Abstract
Preterm birth disrupts the in utero environment, preventing the brain from fully developing, thereby causing later cognitive and behavioral disorders. Such cerebral alteration occurs beneath an anatomical scale, and is therefore undetectable by conventional imagery. Prematurity impairs the microstructure and thus the histological process responsible for the maturation, including the myelination. Cerebral MRI diffusion tensor imaging sequences, based on water’s motion into the brain, allows a representation of this maturation process. Similarly, the brain’s connections become disorganized. The connectome gathers structural and anatomical white matter fibers, as well as functional networks referring to remote brain regions connected one over another. Structural and functional connectivity is illustrated by tractography and functional MRI, respectively. Their organizations consist of core nodes connected by edges. This basic distribution is already established in the fetal brain. It evolves greatly over time but is compromised by prematurity. Finally, cerebral plasticity is nurtured by a lifetime experience at microstructural and macrostructural scales. A preterm birth causes a negative and early disruption, though it can be partly mitigated by positive stimuli based on developmental neonatal care.
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Affiliation(s)
- Philippe Vo Van
- Department of Neonatology, Hospices Civils de Lyon, Femme Mère Enfant Hospital, 59 Boulevard Pinel, 69500 Bron, France
- Correspondence:
| | - Marianne Alison
- Service d’Imagerie Pédiatrique, Hôpital Robert Debré, APHP, 75019 Paris, France;
- U1141 Neurodiderot, Équipe 5 inDev, Inserm, CEA, Université de Paris, 75019 Paris, France;
| | - Baptiste Morel
- Pediatric Radiology Department, Clocheville Hospital, CHRU of Tours, 37000 Tours, France;
- UMR 1253, iB-Rain, Université de Tours, Inserm, 37000 Tours, France
| | - Jonathan Beck
- Department of Neonatology, Reims University Hospital Alix de Champagne, 51100 Reims, France; (J.B.); (N.B.); (G.L.)
- CReSTIC EA 3804, Université de Reims Champagne Ardenne, 51100 Reims, France
| | - Nathalie Bednarek
- Department of Neonatology, Reims University Hospital Alix de Champagne, 51100 Reims, France; (J.B.); (N.B.); (G.L.)
- CReSTIC EA 3804, Université de Reims Champagne Ardenne, 51100 Reims, France
| | - Lucie Hertz-Pannier
- U1141 Neurodiderot, Équipe 5 inDev, Inserm, CEA, Université de Paris, 75019 Paris, France;
- NeuroSpin, CEA-Saclay, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
| | - Gauthier Loron
- Department of Neonatology, Reims University Hospital Alix de Champagne, 51100 Reims, France; (J.B.); (N.B.); (G.L.)
- CReSTIC EA 3804, Université de Reims Champagne Ardenne, 51100 Reims, France
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Functional Hyperconnectivity during a Stories Listening Task in Magnetoencephalography Is Associated with Language Gains for Children Born Extremely Preterm. Brain Sci 2021; 11:brainsci11101271. [PMID: 34679336 PMCID: PMC8534020 DOI: 10.3390/brainsci11101271] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 09/17/2021] [Accepted: 09/20/2021] [Indexed: 01/25/2023] Open
Abstract
Extreme prematurity (EPT, <28 weeks gestation) is associated with language problems. We previously reported hyperconnectivity in EPT children versus term children (TC) using magnetoencephalography (MEG). Here, we aim to ascertain whether functional hyperconnectivity is a marker of language resiliency for EPT children, validating our earlier work with a distinct sample of contemporary well-performing EPT and preterm children with history of language delay (EPT-HLD). A total of 58 children (17 EPT, 9 EPT-HLD, and 32 TC) participated in stories listening during MEG and functional magnetic resonance imaging (fMRI) at 4–6 years. We compared connectivity in EPT and EPT-HLD, investigating relationships with language over time. We measured fMRI activation during stories listening and parcellated the activation map to obtain “nodes” for MEG connectivity analysis. There were no significant group differences in age, sex, race, ethnicity, parental education, income, language scores, or language representation on fMRI. MEG functional connectivity (weighted phase lag index) was significantly different between groups. Preterm children had increased connectivity, replicating our earlier work. EPT and EPT-HLD had hyperconnectivity versus TC at 24–26 Hz, with EPT-HLD exhibiting greatest connectivity. Network strength correlated with change in standardized scores from 2 years to 4–6 years of age, suggesting hyperconnectivity is a marker of advancing language development.
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14
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Edgar JC. Pediatric brain imaging research: Brain maturation constrains study design and clinical interpretation. Psychiatry Clin Neurosci 2021; 75:267-269. [PMID: 34121272 DOI: 10.1111/pcn.13278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 05/03/2021] [Accepted: 05/17/2021] [Indexed: 11/28/2022]
Affiliation(s)
- J Christopher Edgar
- Department of Radiology, Lurie Family Foundations MEG Imaging Center, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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15
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Shi LJ, Wei BX, Xu L, Lin YC, Wang YP, Zhang JC. Magnetoencephalography for epileptic focus localization based on Tucker decomposition with ripple window. CNS Neurosci Ther 2021; 27:820-830. [PMID: 33942534 PMCID: PMC8193700 DOI: 10.1111/cns.13643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 03/24/2021] [Indexed: 11/30/2022] Open
Abstract
AIMS To improve the Magnetoencephalography (MEG) spatial localization precision of focal epileptic. METHODS 306-channel simulated or real clinical MEG is estimated as a lower-dimensional tensor by Tucker decomposition based on Higher-order orthogonal iteration (HOOI) before the inverse problem using linearly constraint minimum variance (LCMV). For simulated MEG data, the proposed method is compared with dynamic imaging of coherent sources (DICS), multiple signal classification (MUSIC), and LCMV. For clinical real MEG of 31 epileptic patients, the ripples (80-250 Hz) were detected to compare the source location precision with spikes using the proposed method or the dipole-fitting method. RESULTS The experimental results showed that the positional accuracy of the proposed method was higher than that of LCMV, DICS, and MUSIC for simulation data. For clinical real MEG data, the positional accuracy of the proposed method was higher than that of dipole-fitting regardless of whether the time window was ripple window or spike window. Also, the positional accuracy of the ripple window was higher than that of the spike window regardless of whether the source location method was the proposed method or the dipole-fitting method. For both shallow and deep sources, the proposed method provided effective performance. CONCLUSION Tucker estimation of MEG for source imaging by ripple window is a promising approach toward the presurgical evaluation of epileptics.
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Affiliation(s)
- Li-Juan Shi
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China.,Beijing Advanced Innovation Centre for Big Data-Based Precision Medicine, Beihang University, Beijing, China.,Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, China
| | - Bo-Xuan Wei
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China.,Beijing Advanced Innovation Centre for Big Data-Based Precision Medicine, Beihang University, Beijing, China.,Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, China.,Hefei Innovation Research Institute, Beihang University, Hefei, Anhui, China
| | - Lu Xu
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China.,Beijing Advanced Innovation Centre for Big Data-Based Precision Medicine, Beihang University, Beijing, China.,Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, China
| | - Yi-Cong Lin
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Brain Functional Disease and Neuromodulation of Beijing Key Laboratory, Beijing, China
| | - Yu-Ping Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.,Brain Functional Disease and Neuromodulation of Beijing Key Laboratory, Beijing, China
| | - Ji-Cong Zhang
- School of Biological Science and Medical Engineering, Beihang University, Beijing, China.,Beijing Advanced Innovation Centre for Big Data-Based Precision Medicine, Beihang University, Beijing, China.,Beijing Advanced Innovation Centre for Biomedical Engineering, Beihang University, Beijing, China.,Hefei Innovation Research Institute, Beihang University, Hefei, Anhui, China
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16
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Kuschner ES, Kim M, Bloy L, Dipiero M, Edgar JC, Roberts TPL. MEG-PLAN: a clinical and technical protocol for obtaining magnetoencephalography data in minimally verbal or nonverbal children who have autism spectrum disorder. J Neurodev Disord 2021; 13:8. [PMID: 33485311 PMCID: PMC7827989 DOI: 10.1186/s11689-020-09350-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 12/10/2020] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Neuroimaging research on individuals who have autism spectrum disorder (ASD) has historically been limited primarily to those with age-appropriate cognitive and language performance. Children with limited abilities are frequently excluded from such neuroscience research given anticipated barriers like tolerating the loud sounds associated with magnetic resonance imaging and remaining still during data collection. To better understand brain function across the full range of ASD there is a need to (1) include individuals with limited cognitive and language performance in neuroimaging research (non-sedated, awake) and (2) improve data quality across the performance range. The purpose of this study was to develop, implement, and test the feasibility of a clinical/behavioral and technical protocol for obtaining magnetoencephalography (MEG) data. Participants were 38 children with ASD (8-12 years) meeting the study definition of minimally verbal/nonverbal language. MEG data were obtained during a passive pure-tone auditory task. RESULTS Based on stakeholder feedback, the MEG Protocol for Low-language/cognitive Ability Neuroimaging (MEG-PLAN) was developed, integrating clinical/behavioral and technical components to be implemented by an interdisciplinary team (clinicians, behavior specialists, scientists, and technologists). Using MEG-PLAN, a 74% success rate was achieved for acquiring MEG data, with a 71% success rate for evaluable and analyzable data. Exploratory analyses suggested nonverbal IQ and adaptive skills were related to reaching the point of acquirable data. No differences in group characteristics were observed between those with acquirable versus evaluable/analyzable data. Examination of data quality (evaluable trial count) was acceptable. Moreover, results were reproducible, with high intraclass correlation coefficients for pure-tone auditory latency. CONCLUSIONS Children who have ASD who are minimally verbal/nonverbal, and often have co-occurring cognitive impairments, can be effectively and comfortably supported to complete an electrophysiological exam that yields valid and reproducible results. MEG-PLAN is a protocol that can be disseminated and implemented across research teams and adapted across technologies and neurodevelopmental disorders to collect electrophysiology and neuroimaging data in previously understudied groups of individuals.
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Affiliation(s)
- Emily S Kuschner
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, 2716 South Street, 5th Floor, Room 5251, Philadelphia, PA, 19146, USA. .,Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| | - Mina Kim
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, 2716 South Street, 5th Floor, Room 5251, Philadelphia, PA, 19146, USA
| | - Luke Bloy
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, 2716 South Street, 5th Floor, Room 5251, Philadelphia, PA, 19146, USA
| | - Marissa Dipiero
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, 2716 South Street, 5th Floor, Room 5251, Philadelphia, PA, 19146, USA
| | - J Christopher Edgar
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, 2716 South Street, 5th Floor, Room 5251, Philadelphia, PA, 19146, USA
| | - Timothy P L Roberts
- Lurie Family Foundations MEG Imaging Center, Department of Radiology, The Children's Hospital of Philadelphia, 2716 South Street, 5th Floor, Room 5251, Philadelphia, PA, 19146, USA
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17
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Chen Y, Slinger M, Edgar JC, Bloy L, Kuschner ES, Kim M, Green HL, Chiang T, Yount T, Liu S, Lebus J, Lam S, Stephen JM, Huang H, Roberts TPL. Maturation of hemispheric specialization for face encoding during infancy and toddlerhood. Dev Cogn Neurosci 2021; 48:100918. [PMID: 33571846 PMCID: PMC7876542 DOI: 10.1016/j.dcn.2021.100918] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Revised: 12/28/2020] [Accepted: 01/08/2021] [Indexed: 11/30/2022] Open
Abstract
Using infant magnetoencephalography (MEG), study findings show maturational changes to fusiform gyrus (FFG) activity when viewing faces. Earlier right FFG activity to face stimuli is associated with better social and cognitive ability. Stronger right- than left-hemisphere FFG responses to face stimuli are most evident after 1 year of age.
Little is known about the neural processes associated with attending to social stimuli during infancy and toddlerhood. Using infant magnetoencephalography (MEG), fusiform gyrus (FFG) activity while processing Face and Non-Face stimuli was examined in 46 typically developing infants 3 to 24 months old (28 males). Several findings indicated FFG maturation throughout the first two years of life. First, right FFG responses to Face stimuli decreased as a function of age. Second, hemispheric specialization to the face stimuli developed somewhat slowly, with earlier right than left FFG peak activity most evident after 1 year of age. Right FFG activity to Face stimuli was of clinical interest, with an earlier right FFG response associated with better performance on tests assessing social and cognitive ability. Building on the above, clinical studies examining maturational change in FFG activity (e.g., lateralization and speed) in infants at-risk for childhood disorders associated with social deficits are of interest to identify atypical FFG maturation before a formal diagnosis is possible.
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Affiliation(s)
- Yuhan Chen
- Lurie Family Foundations MEG Imaging Center, Dept. of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA.
| | - Michelle Slinger
- Lurie Family Foundations MEG Imaging Center, Dept. of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - J Christopher Edgar
- Lurie Family Foundations MEG Imaging Center, Dept. 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
| | - Luke Bloy
- Lurie Family Foundations MEG Imaging Center, Dept. of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Emily S Kuschner
- Lurie Family Foundations MEG Imaging Center, Dept. 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, Dept. of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Heather L Green
- Lurie Family Foundations MEG Imaging Center, Dept. of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Taylor Chiang
- Lurie Family Foundations MEG Imaging Center, Dept. of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Tess Yount
- Lurie Family Foundations MEG Imaging Center, Dept. of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Song Liu
- Lurie Family Foundations MEG Imaging Center, Dept. of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Jill Lebus
- Lurie Family Foundations MEG Imaging Center, Dept. of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Samantha Lam
- Lurie Family Foundations MEG Imaging Center, Dept. of Radiology, Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Julia M Stephen
- The Mind Research Network and Lovelace Biomedical and Environmental Research Institute, Albuquerque, NM, 87106, USA
| | - Hao Huang
- Lurie Family Foundations MEG Imaging Center, Dept. 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
| | - Timothy P L Roberts
- Lurie Family Foundations MEG Imaging Center, Dept. 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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18
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Eswaran H, Lau C, Murphy P, Siegel ER, Preissl H, Lowery C. Tracking evoked responses to auditory and visual stimuli in fetuses exposed to maternal high-risk conditions. Dev Psychobiol 2020; 63:5-15. [PMID: 32654120 DOI: 10.1002/dev.22008] [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: 06/21/2019] [Revised: 04/08/2020] [Accepted: 06/01/2020] [Indexed: 11/05/2022]
Abstract
Magnetoencephalography (MEG) has been successfully applied to record fetal auditory (auditory evoked response [AER]) and visual evoked responses (VER). In this study, we report the AER and VER development trajectory by tracking the evoked response detectability and latency from recordings starting at 27 weeks of gestation in pregnancies classified as high risk. Fetal MEG and ultrasound recordings were performed on 158 pregnant women, and the total number of fetal auditory and visual tests conducted was 321 and 237, respectively. The overall evoked response analysis showed 237 AER (73.8%) and 164 VER detections (69.2%). The mean AER latency was 290.7 (SD 125.5) ms and the mean VER latency was 293.7 (SD 114.5) ms. The rate of decrease (95% confidence limits) in average AER and VER first-peak latency between 100-350 ms was 1.97 (-1.86, +5.81) ms/week and 1.35 (-3.83, +6.53) ms/week, respectively. This trend in high-risk fetuses conforms to the general trajectory of decrease in latency with gestational age progression, even though this decrease was non-significant, as reported in the case of normal growing fetuses. Although there was a significant difference in detection rates between male and female fetuses, this was not reflected in either latency values or the sensory modality applied. Furthermore, the main factors that had the most significant effect on response detectability included the presence of intervening layers of adipose tissue between the fetal head and stimulus source and an increase in the maternal body mass index.
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Affiliation(s)
- Hari Eswaran
- Department of Obstetrics and Gynecology, SARA Fetal MEG Research Center, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Chrystal Lau
- Department of Obstetrics and Gynecology, SARA Fetal MEG Research Center, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Pam Murphy
- Department of Obstetrics and Gynecology, SARA Fetal MEG Research Center, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Eric R Siegel
- Department of Biostatistics, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Hubert Preissl
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich at the University of Tübingen, Tübingen, Germany
| | - Curtis Lowery
- Department of Obstetrics and Gynecology, SARA Fetal MEG Research Center, University of Arkansas for Medical Sciences, Little Rock, AR, USA
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Abstract
Magnetoencephalography (MEG) is a noninvasive neuroimaging technique that measures the electromagnetic fields generated by the human brain. This article highlights the benefits that pediatric MEG has to offer to clinical practice and pediatric research, particularly for infants and young children; reviews the existing literature on adult MEG systems for pediatric use; briefly describes the few pediatric MEG systems currently extant; and draws attention to future directions of research, with focus on the clinical use of MEG for patients with drug-resistant epilepsy.
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20
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Edgar JC. Identifying electrophysiological markers of autism spectrum disorder and schizophrenia against a backdrop of normal brain development. Psychiatry Clin Neurosci 2020; 74:1-11. [PMID: 31472015 PMCID: PMC10150852 DOI: 10.1111/pcn.12927] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Revised: 08/26/2019] [Accepted: 08/27/2019] [Indexed: 01/25/2023]
Abstract
An examination of electroencephalographic and magnetoencephalographic studies demonstrates how age-related changes in brain neural function temporally constrain their use as diagnostic markers. A first example shows that, given maturational changes in the resting-state peak alpha frequency in typically developing children but not in children who have autism spectrum disorder (ASD), group differences in alpha-band activity characterize only a subset of children who have ASD. A second example, auditory encoding processes in schizophrenia, shows that the complication of normal age-related brain changes on detecting and interpreting group differences in neural activity is not specific to children. MRI studies reporting group differences in the rate of brain maturation demonstrate that a group difference in brain maturation may be a concern for all diagnostic brain markers. Attention to brain maturation is needed whether one takes a DSM-5 or a Research Domain Criteria approach to research. For example, although there is interest in cross-diagnostic studies comparing brain measures in ASD and schizophrenia, such studies are difficult given that measures are obtained in one group well after and in the other much closer to the onset of symptoms. In addition, given differences in brain activity among infants, toddlers, children, adolescents, and younger and older adults, creating tasks and research designs that produce interpretable findings across the life span and yet allow for development is difficult at best. To conclude, brain imaging findings show an effect of brain maturation on diagnostic markers separate from (and potentially difficult to distinguish from) effects of disease processes. Available research with large samples already provides direction about the age range(s) when diagnostic markers are most robust and informative.
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Affiliation(s)
- J Christopher Edgar
- Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, USA
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21
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Edgar JC, Blaskey L, Green HL, Konka K, Shen G, Dipiero MA, Berman JI, Bloy L, Liu S, McBride E, Ku M, Kuschner ES, Airey M, Kim M, Franzen RE, Miller GA, Roberts TPL. Maturation of Auditory Cortex Neural Activity in Children and Implications for Auditory Clinical Markers in Diagnosis. Front Psychiatry 2020; 11:584557. [PMID: 33329127 PMCID: PMC7717950 DOI: 10.3389/fpsyt.2020.584557] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 10/15/2020] [Indexed: 01/14/2023] Open
Abstract
Functional brain markers that can inform research on brain abnormalities, and especially those ready to facilitate clinical work on such abnormalities, will need to show not only considerable sensitivity and specificity but enough consistency with respect to developmental course that their validity in individual cases can be trusted. A challenge to establishing such markers may be individual differences in developmental course. The present study examined auditory cortex activity in children at an age when developmental changes to the auditory cortex 50 ms (M50) and 100 ms (M100) components are prominent to better understand the use of auditory markers in pediatric clinical research. MEG auditory encoding measures (auditory evoked fields in response to pure tone stimuli) were obtained from 15 typically developing children 6-8 years old, with measures repeated 18 and 36 months after the initial exam. MEG analyses were conducted in source space (i.e., brain location), with M50 and M100 sources identified in left and right primary/secondary auditory cortex (Heschl's gyrus). A left and right M50 response was observed at all times (Time 1, Time 2, Time 3), with M50 latency (collapsing across hemisphere) at Time 3 (77 ms) 10 ms earlier than Time 1 (87 ms; p < 0.001) and with M50 responses on average (collapsing across time) 5 ms earlier in the right (80 ms) than left hemisphere (85 ms; p < 0.05). In the majority of children, however, M50 latency changes were not constant across the three-year period; for example, whereas in some children a ~10 ms latency reduction was observed from Time 1 to Time 2, in other children a ~10 ms latency reduction was observed from Time 2 to Time 3. M100 responses were defined by a significant "peak" of detected power with magnetic field topography opposite M50 and occurring 50-100 ms later than the M50. Although M100s were observed in a few children at Time 1 and Time 2 (and more often in the right than left hemisphere), M100s were not observed in the majority of children except in the right hemisphere at Time 3. In sum, longitudinal findings showed large between- and within-subject variability in rate of change as well as time to reach neural developmental milestones (e.g., presence of a detectable M100 response). Findings also demonstrated the need to examine whole-brain activity, given hemisphere differences in the rate of auditory cortex maturation. Pediatric research will need to take such normal variability into account when seeking clinical auditory markers.
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Affiliation(s)
- J Christopher Edgar
- Department of Radiology, Lurie Family Foundations Magnetoencephalography Imaging Center, The Children's Hospital of Philadelphia, Philadelphia, PA, United States.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Lisa Blaskey
- Department of Radiology, Lurie Family Foundations Magnetoencephalography Imaging Center, The Children's Hospital of Philadelphia, Philadelphia, PA, United States.,Department of Pediatrics, Center for Autism Research, The Children's Hospital of Philadelphia, Philadelphia, PA, United States.,Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Heather L Green
- Department of Radiology, Lurie Family Foundations Magnetoencephalography Imaging Center, The Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Kimberly Konka
- Department of Radiology, Lurie Family Foundations Magnetoencephalography Imaging Center, The Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Guannan Shen
- Department of Radiology, Lurie Family Foundations Magnetoencephalography Imaging Center, The Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Marissa A Dipiero
- Department of Radiology, Lurie Family Foundations Magnetoencephalography Imaging Center, The Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Jeffrey I Berman
- Department of Radiology, Lurie Family Foundations Magnetoencephalography Imaging Center, The Children's Hospital of Philadelphia, Philadelphia, PA, United States.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Luke Bloy
- Department of Radiology, Lurie Family Foundations Magnetoencephalography Imaging Center, The Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Song Liu
- Department of Radiology, Lurie Family Foundations Magnetoencephalography Imaging Center, The Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Emma McBride
- Department of Radiology, Lurie Family Foundations Magnetoencephalography Imaging Center, The Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Matt Ku
- Department of Radiology, Lurie Family Foundations Magnetoencephalography Imaging Center, The Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Emily S Kuschner
- Department of Radiology, Lurie Family Foundations Magnetoencephalography Imaging Center, The Children's Hospital of Philadelphia, Philadelphia, PA, United States.,Department of Pediatrics, Center for Autism Research, The Children's Hospital of Philadelphia, Philadelphia, PA, United States.,Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Megan Airey
- Department of Radiology, Lurie Family Foundations Magnetoencephalography Imaging Center, The Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Mina Kim
- Department of Radiology, Lurie Family Foundations Magnetoencephalography Imaging Center, The Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Rose E Franzen
- Department of Radiology, Lurie Family Foundations Magnetoencephalography Imaging Center, The Children's Hospital of Philadelphia, Philadelphia, PA, United States
| | - Gregory A Miller
- Department of Psychology, University of California, Los Angeles, Los Angeles, CA, United States.,Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, United States
| | - Timothy P L Roberts
- Department of Radiology, Lurie Family Foundations Magnetoencephalography Imaging Center, The Children's Hospital of Philadelphia, Philadelphia, PA, United States.,Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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Nguyen T, Bánki A, Markova G, Hoehl S. Studying parent-child interaction with hyperscanning. PROGRESS IN BRAIN RESEARCH 2020; 254:1-24. [DOI: 10.1016/bs.pbr.2020.05.003] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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Hironaga N, Takei Y, Mitsudo T, Kimura T, Hirano Y. Prospects for Future Methodological Development and Application of Magnetoencephalography Devices in Psychiatry. Front Psychiatry 2020; 11:863. [PMID: 32973591 PMCID: PMC7472776 DOI: 10.3389/fpsyt.2020.00863] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 08/07/2020] [Indexed: 12/18/2022] Open
Abstract
Magnetoencephalography (MEG) is a functional neuroimaging tool that can record activity from the entire cortex on the order of milliseconds. MEG has been used to investigate numerous psychiatric disorders, such as schizophrenia, bipolar disorder, major depression, dementia, and autism spectrum disorder. Although several review papers on the subject have been published, perspectives and opinions regarding the use of MEG in psychiatric research have primarily been discussed from a psychiatric research point of view. Owing to a newly developed MEG sensor, the use of MEG devices will soon enter a critical period, and now is a good time to discuss the future of MEG use in psychiatric research. In this paper, we will discuss MEG devices from a methodological point of view. We will first introduce the utilization of MEG in psychiatric research and the development of its technology. Then, we will describe the principle theory of MEG and common algorithms, which are useful for applying MEG tools to psychiatric research. Next, we will consider three topics-child psychiatry, resting-state networks, and cortico-subcortical networks-and address the future use of MEG in psychiatry from a broader perspective. Finally, we will introduce the newly developed device, the optically-pumped magnetometer, and discuss its future use in MEG systems in psychiatric research from a methodological point of view. We believe that state-of-the-art electrophysiological tools, such as this new MEG system, will further contribute to our understanding of the core pathology in various psychiatric disorders and translational research.
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Affiliation(s)
- Naruhito Hironaga
- Brain Center, Faculty of Medicine, Kyushu University, Fukuoka, Japan
| | - Yuichi Takei
- Department of Psychiatry and Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Takako Mitsudo
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Takahiro Kimura
- Institute of Liberal Arts and Science, Kanazawa University, Kanazawa, Japan
| | - Yoji Hirano
- Department of Neuropsychiatry, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
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24
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A decade of infant neuroimaging research: What have we learned and where are we going? Infant Behav Dev 2019; 58:101389. [PMID: 31778859 DOI: 10.1016/j.infbeh.2019.101389] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Revised: 10/10/2019] [Accepted: 10/10/2019] [Indexed: 12/15/2022]
Abstract
The past decade has seen the emergence of neuroimaging studies of infant populations. Incorporating imaging has resulted in invaluable insights about neurodevelopment at the start of life. However, little has been enquired of the experimental specifications and study characteristics of typical findings. This review systematically screened empirical studies that used electroencephalography (EEG), magnetoencephalography (MEG), functional near-infrared spectroscopy (fNIRS), and functional magnetic resonance imaging (fMRI) on infants (max. age of 24 months). From more than 21,000 publications, a total of 710 records were included for analyses. With the exception of EEG studies, infant studies with MEG, fNIRS, and fMRI were most often conducted around birth and at 12 months. The vast majority of infant studies came from North America, with very few studies conducted in Africa, certain parts of South America, and Southeast Asia. Finally, longitudinal neuroimaging studies were inclined to adopt EEG, followed by fMRI, fNIRS, and MEG. These results show that there is compelling need for studies with larger sample sizes, studies investigating a broader range of infant developmental periods, and studies from under- and less-developed regions in the world. Addressing these shortcomings in the future will provide a more representative and accurate understanding of neurodevelopment in infancy.
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26
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Magnetic Source Imaging and Infant MEG: Current Trends and Technical Advances. Brain Sci 2019; 9:brainsci9080181. [PMID: 31357668 PMCID: PMC6721320 DOI: 10.3390/brainsci9080181] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Revised: 07/23/2019] [Accepted: 07/26/2019] [Indexed: 12/25/2022] Open
Abstract
Magnetoencephalography (MEG) is known for its temporal precision and good spatial resolution in cognitive brain research. Nonetheless, it is still rarely used in developmental research, and its role in developmental cognitive neuroscience is not adequately addressed. The current review focuses on the source analysis of MEG measurement and its potential to answer critical questions on neural activation origins and patterns underlying infants’ early cognitive experience. The advantages of MEG source localization are discussed in comparison with functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS), two leading imaging tools for studying cognition across age. Challenges of the current MEG experimental protocols are highlighted, including measurement and data processing, which could potentially be resolved by developing and improving both software and hardware. A selection of infant MEG research in auditory, speech, vision, motor, sleep, cross-modality, and clinical application is then summarized and discussed with a focus on the source localization analyses. Based on the literature review and the advancements of the infant MEG systems and source analysis software, typical practices of infant MEG data collection and analysis are summarized as the basis for future developmental cognitive research.
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