1
|
Bagdasarov A, Brunet D, Michel CM, Gaffrey MS. Microstate Analysis of Continuous Infant EEG: Tutorial and Reliability. Brain Topogr 2024; 37:496-513. [PMID: 38430283 PMCID: PMC11199263 DOI: 10.1007/s10548-024-01043-5] [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: 07/12/2023] [Accepted: 02/16/2024] [Indexed: 03/03/2024]
Abstract
Microstate analysis of resting-state EEG is a unique data-driven method for identifying patterns of scalp potential topographies, or microstates, that reflect stable but transient periods of synchronized neural activity evolving dynamically over time. During infancy - a critical period of rapid brain development and plasticity - microstate analysis offers a unique opportunity for characterizing the spatial and temporal dynamics of brain activity. However, whether measurements derived from this approach (e.g., temporal properties, transition probabilities, neural sources) show strong psychometric properties (i.e., reliability) during infancy is unknown and key information for advancing our understanding of how microstates are shaped by early life experiences and whether they relate to individual differences in infant abilities. A lack of methodological resources for performing microstate analysis of infant EEG has further hindered adoption of this cutting-edge approach by infant researchers. As a result, in the current study, we systematically addressed these knowledge gaps and report that most microstate-based measurements of brain organization and functioning except for transition probabilities were stable with four minutes of video-watching resting-state data and highly internally consistent with just one minute. In addition to these results, we provide a step-by-step tutorial, accompanying website, and open-access data for performing microstate analysis using a free, user-friendly software called Cartool. Taken together, the current study supports the reliability and feasibility of using EEG microstate analysis to study infant brain development and increases the accessibility of this approach for the field of developmental neuroscience.
Collapse
Affiliation(s)
- Armen Bagdasarov
- Department of Psychology & Neuroscience, Duke University, Reuben-Cooke Building, 417 Chapel Drive, Durham, NC, 27708, USA.
| | - Denis Brunet
- Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, Geneva, 1202, Switzerland
- Center for Biomedical Imaging (CIBM) Lausanne, EPFL AVP CP CIBM Station 6, Lausanne, 1015, Switzerland
| | - Christoph M Michel
- Department of Basic Neurosciences, University of Geneva, Campus Biotech, 9 Chemin des Mines, Geneva, 1202, Switzerland
- Center for Biomedical Imaging (CIBM) Lausanne, EPFL AVP CP CIBM Station 6, Lausanne, 1015, Switzerland
| | - Michael S Gaffrey
- Department of Psychology & Neuroscience, Duke University, Reuben-Cooke Building, 417 Chapel Drive, Durham, NC, 27708, USA
- Children's Wisconsin, 9000 W. Wisconsin Avenue, Milwaukee, WI, 53226, USA
- Medical College of Wisconsin, Division of Pediatric Psychology and Developmental Medicine, Department of Pediatrics, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA
| |
Collapse
|
2
|
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.
Collapse
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
| |
Collapse
|
3
|
Conte S, Richards JE, Fox NA, Valadez EA, McSweeney M, Tan E, Pine DS, Winkler AM, Liuzzi L, Cardinale EM, White LK, Buzzell GA. Multimodal study of the neural sources of error monitoring in adolescents and adults. Psychophysiology 2023; 60:e14336. [PMID: 37212619 PMCID: PMC10524909 DOI: 10.1111/psyp.14336] [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: 10/03/2022] [Revised: 04/16/2023] [Accepted: 05/01/2023] [Indexed: 05/23/2023]
Abstract
The ability to monitor performance during a goal-directed behavior differs among children and adults in ways that can be measured with several tasks and techniques. As well, recent work has shown that individual differences in error monitoring moderate temperamental risk for anxiety and that this moderation changes with age. We investigated age differences in neural responses linked to performance monitoring using a multimodal approach. The approach combined functional MRI and source localization of event-related potentials (ERPs) in 12-year-old, 15-year-old, and adult participants. Neural generators of two components related to performance and error monitoring, the N2 and ERN, lay within specific areas of fMRI clusters. Whereas correlates of the N2 component appeared similar across age groups, age-related differences manifested in the location of the generators of the ERN component. The dorsal anterior cingulate cortex (dACC) was the predominant source location for the 12-year-old group; this area manifested posteriorly for the 15-year-old and adult groups. A fMRI-based ROI analysis confirmed this pattern of activity. These results suggest that changes in the underlying neural mechanisms are related to developmental changes in performance monitoring.
Collapse
Affiliation(s)
- Stefania Conte
- Department of Psychology, University of South Carolina, Columbia, South Carolina, USA
| | - John E Richards
- Department of Psychology, University of South Carolina, Columbia, South Carolina, USA
| | - Nathan A Fox
- Department of Human Development and Quantitative Methodology, University of Maryland, College Park, Maryland, USA
| | - Emilio A Valadez
- Department of Human Development and Quantitative Methodology, University of Maryland, College Park, Maryland, USA
| | - Marco McSweeney
- Department of Human Development and Quantitative Methodology, University of Maryland, College Park, Maryland, USA
| | - Enda Tan
- Department of Human Development and Quantitative Methodology, University of Maryland, College Park, Maryland, USA
| | - Daniel S Pine
- National Institute of Mental Health, Emotion and Development Branch, Bethesda, Maryland, USA
| | - Anderson M Winkler
- National Institute of Mental Health, Emotion and Development Branch, Bethesda, Maryland, USA
| | - Lucrezia Liuzzi
- National Institute of Mental Health, Emotion and Development Branch, Bethesda, Maryland, USA
| | - Elise M Cardinale
- National Institute of Mental Health, Emotion and Development Branch, Bethesda, Maryland, USA
| | - Lauren K White
- Lifespan Brain Institute of the Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, Pennsylvania, USA
| | - George A Buzzell
- Florida International University and the Center for Children and Families, Miami, Florida, USA
| |
Collapse
|
4
|
Polver S, Háden GP, Bulf H, Winkler I, Tóth B. Early maturation of sound duration processing in the infant's brain. Sci Rep 2023; 13:10287. [PMID: 37355709 PMCID: PMC10290631 DOI: 10.1038/s41598-023-36794-x] [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: 06/23/2022] [Accepted: 06/12/2023] [Indexed: 06/26/2023] Open
Abstract
The ability to process sound duration is crucial already at a very early age for laying the foundation for the main functions of auditory perception, such as object perception and music and language acquisition. With the availability of age-appropriate structural anatomical templates, we can reconstruct EEG source activity with much-improved reliability. The current study capitalized on this possibility by reconstructing the sources of event-related potential (ERP) waveforms sensitive to sound duration in 4- and 9-month-old infants. Infants were presented with short (200 ms) and long (300 ms) sounds equiprobable delivered in random order. Two temporally separate ERP waveforms were found to be modulated by sound duration. Generators of these waveforms were mainly located in the primary and secondary auditory areas and other language-related regions. The results show marked developmental changes between 4 and 9 months, partly reflected by scalp-recorded ERPs, but appearing in the underlying generators in a far more nuanced way. The results also confirm the feasibility of the application of anatomical templates in developmental populations.
Collapse
Affiliation(s)
- Silvia Polver
- Department of Psychology, University of Milano-Bicocca, Milan, Italy
| | - Gábor P Háden
- Institute of Cognitive Neuroscience and Psychology, Research Center for Natural Sciences, Budapest, Hungary
- Department of Telecommunications and Media Informatics, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, Budapest, Hungary
| | - Hermann Bulf
- Department of Psychology, University of Milano-Bicocca, Milan, Italy
- NeuroMI, Milan Center for Neuroscience, University of Milano-Bicocca, Milan, Italy
| | - István Winkler
- Institute of Cognitive Neuroscience and Psychology, Research Center for Natural Sciences, Budapest, Hungary
| | - Brigitta Tóth
- Institute of Cognitive Neuroscience and Psychology, Research Center for Natural Sciences, Budapest, Hungary.
| |
Collapse
|
5
|
Buzzell GA, Morales S, Valadez EA, Hunnius S, Fox NA. Maximizing the potential of EEG as a developmental neuroscience tool. Dev Cogn Neurosci 2023; 60:101201. [PMID: 36732112 PMCID: PMC10150174 DOI: 10.1016/j.dcn.2023.101201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/28/2023] Open
Affiliation(s)
- George A Buzzell
- Department of Psychology, Florida International University, USA; Center for Children and Families, Florida International University, USA.
| | - Santiago Morales
- Department of Psychology, University of Southern California, USA
| | - Emilio A Valadez
- Department of Human Development and Quantitative Methodology, University of Maryland - College Park, USA
| | - Sabine Hunnius
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, the Netherlands
| | - Nathan A Fox
- Department of Human Development and Quantitative Methodology, University of Maryland - College Park, USA
| |
Collapse
|
6
|
Guy MW, Richards JE, Roberts JE. Cortical Source Analysis of the Face Sensitive N290 ERP Component in Infants at High Risk for Autism. Brain Sci 2022; 12:1129. [PMID: 36138866 PMCID: PMC9497227 DOI: 10.3390/brainsci12091129] [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: 07/13/2022] [Revised: 08/15/2022] [Accepted: 08/22/2022] [Indexed: 11/17/2022] Open
Abstract
Appropriate head models for cortical source analysis were investigated and applied to source analyses examining the neural bases of the face-sensitive N290 event-related potential (ERP) component in infants at high risk for autism spectrum disorder (ASD). This included infant siblings of children with ASD (ASIBs) and infants with fragile X syndrome (FXS). First, alternative head models for use with ASIBs and FXS were investigated. Head models created from the infant's own MRI were examined in relation to five head models based on average MRI templates. The results of the head model comparison identified group-specific (i.e., ASIB or FXS) head models created from a large collection of structural MRIs as the best substitution for the head model created from the participant's own structural MRI. Second, the cortical source analysis was completed on N290 data collected from a previous study to investigate brain areas associated with face sensitive ERP responses. Participants' own MRIs were used for head models when available, and the group-specific head model was used when the participants' own MRIs were not available. The results provide evidence for unique patterns of neural activation during face processing across infants at high and low risk for ASD and across etiologically distinct high-risk groups. All infants demonstrated greater activation to faces than toys in brain areas most associated with specialized face processing. Infants with FXS displayed higher levels of activation to faces across all areas analyzed, while ASIBs show more muted levels of activation. Overall, the results of the current study demonstrate the importance of group-specific head models for accurate cortical source analysis in infants at high risk for ASD. This also allows for further research on early distinctions in brain function based on risk status.
Collapse
Affiliation(s)
- Maggie W. Guy
- Department of Psychology, Loyola University Chicago, Chicago, IL 60660, USA
| | - John E. Richards
- Department of Psychology, University of South Carolina, Columbia, SC 29208, USA
| | - Jane E. Roberts
- Department of Psychology, University of South Carolina, Columbia, SC 29208, USA
| |
Collapse
|
7
|
Fu X, Richards JE. Evaluating Head Models for Cortical Source Localization of the Face-Sensitive N290 Component in Infants. Brain Topogr 2022; 35:398-415. [PMID: 35543889 DOI: 10.1007/s10548-022-00899-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 04/09/2022] [Indexed: 11/28/2022]
Abstract
Accurate cortical source localization of event-related potentials (ERPs) requires using realistic head models constructed from the participant's structural magnetic resonance imaging (MRI). A challenge in developmental studies is the limited accessibility of participant-specific MRIs. The present study compared source localization of infants' N290 ERP activities estimated using participant-specific head models with a series of substitute head models. The N290 responses to faces relative to toys were measured in 36 infants aged at 4.5, 7.5, 9, and 12 months. The substitutes were individual-based head models constructed from age-matched MRIs with closely matched ("close") or different ("far") head measures with the participants, age-appropriate average template, and age-inappropriate average templates. The greater source responses to faces than toys at the middle fusiform gyrus (mFG) estimated using participant-specific head models were preserved in individual-based head models, but not average templates. The "close" head models yielded the best fit with the participant-specific head models in source activities at the mFG and across face-processing-related regions of interest (ROIs). The age-appropriate average template showed mixed results, not supporting the stimulus effect but showed topographical distributions across the ROIs like the participant-specific head models. The "close" head models are the most optimal substitute for participant-specific MRIs.
Collapse
Affiliation(s)
- Xiaoxue Fu
- Department of Psychology, University of South Carolina, Columbia, USA.
| | - John E Richards
- Department of Psychology, University of South Carolina, Columbia, USA
| |
Collapse
|