Single‐subject electroencephalography measurement of interhemispheric transfer time for the in‐vivo estimation of axonal morphology
Assessing axonal morphology in vivo opens new avenues for the combined study of brain structure and function. A novel approach has recently been introduced to estimate the morphology of axonal fibers from the combination of magnetic resonance imaging (MRI) data and electroencephalography (EEG) measu...
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| Published in | Human brain mapping Vol. 44; no. 14; pp. 4859 - 4874 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
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Hoboken, USA
John Wiley & Sons, Inc
01.10.2023
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| Abstract | Assessing axonal morphology in vivo opens new avenues for the combined study of brain structure and function. A novel approach has recently been introduced to estimate the morphology of axonal fibers from the combination of magnetic resonance imaging (MRI) data and electroencephalography (EEG) measures of the interhemispheric transfer time (IHTT). In the original study, the IHTT measures were computed from EEG data averaged across a group, leading to bias of the axonal morphology estimates. Here, we seek to estimate axonal morphology from individual measures of IHTT, obtained from EEG data acquired in a visual evoked potential experiment. Subject‐specific IHTTs are computed in a data‐driven framework with minimal a priori constraints, based on the maximal peak of neural responses to visual stimuli within periods of statistically significant evoked activity in the inverse solution space. The subject‐specific IHTT estimates ranged from 8 to 29 ms except for one participant and the between‐session variability was comparable to between‐subject variability. The mean radius of the axonal radius distribution, computed from the IHTT estimates and the MRI data, ranged from 0 to 1.09 μm across subjects. The change in axonal g‐ratio with axonal radius ranged from 0.62 to 0.81 μm−α. The single‐subject measurement of the IHTT yields estimates of axonal morphology that are consistent with histological values. However, improvement of the repeatability of the IHTT estimates is required to improve the specificity of the single‐subject axonal morphology estimates.
Subject‐specific interhemispheric transfer time (IHTT) was estimated from electroencephalography, based on the maximal peak of neural response to visual stimuli within periods of statistically significant evoked activity. Subject‐specific axonal morphology was estimated from the combination of the estimated IHTT and magnetic resonance imaging data. IHTT and axonal morphology estimates were consistent with histological values. |
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| AbstractList | Assessing axonal morphology in vivo opens new avenues for the combined study of brain structure and function. A novel approach has recently been introduced to estimate the morphology of axonal fibers from the combination of magnetic resonance imaging (MRI) data and electroencephalography (EEG) measures of the interhemispheric transfer time (IHTT). In the original study, the IHTT measures were computed from EEG data averaged across a group, leading to bias of the axonal morphology estimates. Here, we seek to estimate axonal morphology from individual measures of IHTT, obtained from EEG data acquired in a visual evoked potential experiment. Subject‐specific IHTTs are computed in a data‐driven framework with minimal a priori constraints, based on the maximal peak of neural responses to visual stimuli within periods of statistically significant evoked activity in the inverse solution space. The subject‐specific IHTT estimates ranged from 8 to 29 ms except for one participant and the between‐session variability was comparable to between‐subject variability. The mean radius of the axonal radius distribution, computed from the IHTT estimates and the MRI data, ranged from 0 to 1.09 μm across subjects. The change in axonal g‐ratio with axonal radius ranged from 0.62 to 0.81 μm
−
α
. The single‐subject measurement of the IHTT yields estimates of axonal morphology that are consistent with histological values. However, improvement of the repeatability of the IHTT estimates is required to improve the specificity of the single‐subject axonal morphology estimates. Assessing axonal morphology in vivo opens new avenues for the combined study of brain structure and function. A novel approach has recently been introduced to estimate the morphology of axonal fibers from the combination of magnetic resonance imaging (MRI) data and electroencephalography (EEG) measures of the interhemispheric transfer time (IHTT). In the original study, the IHTT measures were computed from EEG data averaged across a group, leading to bias of the axonal morphology estimates. Here, we seek to estimate axonal morphology from individual measures of IHTT, obtained from EEG data acquired in a visual evoked potential experiment. Subject‐specific IHTTs are computed in a data‐driven framework with minimal a priori constraints, based on the maximal peak of neural responses to visual stimuli within periods of statistically significant evoked activity in the inverse solution space. The subject‐specific IHTT estimates ranged from 8 to 29 ms except for one participant and the between‐session variability was comparable to between‐subject variability. The mean radius of the axonal radius distribution, computed from the IHTT estimates and the MRI data, ranged from 0 to 1.09 μm across subjects. The change in axonal g‐ratio with axonal radius ranged from 0.62 to 0.81 μm−α. The single‐subject measurement of the IHTT yields estimates of axonal morphology that are consistent with histological values. However, improvement of the repeatability of the IHTT estimates is required to improve the specificity of the single‐subject axonal morphology estimates. Subject‐specific interhemispheric transfer time (IHTT) was estimated from electroencephalography, based on the maximal peak of neural response to visual stimuli within periods of statistically significant evoked activity. Subject‐specific axonal morphology was estimated from the combination of the estimated IHTT and magnetic resonance imaging data. IHTT and axonal morphology estimates were consistent with histological values. Assessing axonal morphology in vivo opens new avenues for the combined study of brain structure and function. A novel approach has recently been introduced to estimate the morphology of axonal fibers from the combination of magnetic resonance imaging (MRI) data and electroencephalography (EEG) measures of the interhemispheric transfer time (IHTT). In the original study, the IHTT measures were computed from EEG data averaged across a group, leading to bias of the axonal morphology estimates. Here, we seek to estimate axonal morphology from individual measures of IHTT, obtained from EEG data acquired in a visual evoked potential experiment. Subject‐specific IHTTs are computed in a data‐driven framework with minimal a priori constraints, based on the maximal peak of neural responses to visual stimuli within periods of statistically significant evoked activity in the inverse solution space. The subject‐specific IHTT estimates ranged from 8 to 29 ms except for one participant and the between‐session variability was comparable to between‐subject variability. The mean radius of the axonal radius distribution, computed from the IHTT estimates and the MRI data, ranged from 0 to 1.09 μm across subjects. The change in axonal g‐ratio with axonal radius ranged from 0.62 to 0.81 μm − α . The single‐subject measurement of the IHTT yields estimates of axonal morphology that are consistent with histological values. However, improvement of the repeatability of the IHTT estimates is required to improve the specificity of the single‐subject axonal morphology estimates. Subject‐specific interhemispheric transfer time (IHTT) was estimated from electroencephalography, based on the maximal peak of neural response to visual stimuli within periods of statistically significant evoked activity. Subject‐specific axonal morphology was estimated from the combination of the estimated IHTT and magnetic resonance imaging data. IHTT and axonal morphology estimates were consistent with histological values. Assessing axonal morphology in vivo opens new avenues for the combined study of brain structure and function. A novel approach has recently been introduced to estimate the morphology of axonal fibers from the combination of magnetic resonance imaging (MRI) data and electroencephalography (EEG) measures of the interhemispheric transfer time (IHTT). In the original study, the IHTT measures were computed from EEG data averaged across a group, leading to bias of the axonal morphology estimates. Here, we seek to estimate axonal morphology from individual measures of IHTT, obtained from EEG data acquired in a visual evoked potential experiment. Subject‐specific IHTTs are computed in a data‐driven framework with minimal a priori constraints, based on the maximal peak of neural responses to visual stimuli within periods of statistically significant evoked activity in the inverse solution space. The subject‐specific IHTT estimates ranged from 8 to 29 ms except for one participant and the between‐session variability was comparable to between‐subject variability. The mean radius of the axonal radius distribution, computed from the IHTT estimates and the MRI data, ranged from 0 to 1.09 μm across subjects. The change in axonal g‐ratio with axonal radius ranged from 0.62 to 0.81 μm−α. The single‐subject measurement of the IHTT yields estimates of axonal morphology that are consistent with histological values. However, improvement of the repeatability of the IHTT estimates is required to improve the specificity of the single‐subject axonal morphology estimates. Assessing axonal morphology in vivo opens new avenues for the combined study of brain structure and function. A novel approach has recently been introduced to estimate the morphology of axonal fibers from the combination of magnetic resonance imaging (MRI) data and electroencephalography (EEG) measures of the interhemispheric transfer time (IHTT). In the original study, the IHTT measures were computed from EEG data averaged across a group, leading to bias of the axonal morphology estimates. Here, we seek to estimate axonal morphology from individual measures of IHTT, obtained from EEG data acquired in a visual evoked potential experiment. Subject-specific IHTTs are computed in a data-driven framework with minimal a priori constraints, based on the maximal peak of neural responses to visual stimuli within periods of statistically significant evoked activity in the inverse solution space. The subject-specific IHTT estimates ranged from 8 to 29 ms except for one participant and the between-session variability was comparable to between-subject variability. The mean radius of the axonal radius distribution, computed from the IHTT estimates and the MRI data, ranged from 0 to 1.09 μm across subjects. The change in axonal g-ratio with axonal radius ranged from 0.62 to 0.81 μm-α . The single-subject measurement of the IHTT yields estimates of axonal morphology that are consistent with histological values. However, improvement of the repeatability of the IHTT estimates is required to improve the specificity of the single-subject axonal morphology estimates.Assessing axonal morphology in vivo opens new avenues for the combined study of brain structure and function. A novel approach has recently been introduced to estimate the morphology of axonal fibers from the combination of magnetic resonance imaging (MRI) data and electroencephalography (EEG) measures of the interhemispheric transfer time (IHTT). In the original study, the IHTT measures were computed from EEG data averaged across a group, leading to bias of the axonal morphology estimates. Here, we seek to estimate axonal morphology from individual measures of IHTT, obtained from EEG data acquired in a visual evoked potential experiment. Subject-specific IHTTs are computed in a data-driven framework with minimal a priori constraints, based on the maximal peak of neural responses to visual stimuli within periods of statistically significant evoked activity in the inverse solution space. The subject-specific IHTT estimates ranged from 8 to 29 ms except for one participant and the between-session variability was comparable to between-subject variability. The mean radius of the axonal radius distribution, computed from the IHTT estimates and the MRI data, ranged from 0 to 1.09 μm across subjects. The change in axonal g-ratio with axonal radius ranged from 0.62 to 0.81 μm-α . The single-subject measurement of the IHTT yields estimates of axonal morphology that are consistent with histological values. However, improvement of the repeatability of the IHTT estimates is required to improve the specificity of the single-subject axonal morphology estimates. Assessing axonal morphology in vivo opens new avenues for the combined study of brain structure and function. A novel approach has recently been introduced to estimate the morphology of axonal fibers from the combination of magnetic resonance imaging (MRI) data and electroencephalography (EEG) measures of the interhemispheric transfer time (IHTT). In the original study, the IHTT measures were computed from EEG data averaged across a group, leading to bias of the axonal morphology estimates. Here, we seek to estimate axonal morphology from individual measures of IHTT, obtained from EEG data acquired in a visual evoked potential experiment. Subject-specific IHTTs are computed in a data-driven framework with minimal a priori constraints, based on the maximal peak of neural responses to visual stimuli within periods of statistically significant evoked activity in the inverse solution space. The subject-specific IHTT estimates ranged from 8 to 29 ms except for one participant and the between-session variability was comparable to between-subject variability. The mean radius of the axonal radius distribution, computed from the IHTT estimates and the MRI data, ranged from 0 to 1.09 μm across subjects. The change in axonal g-ratio with axonal radius ranged from 0.62 to 0.81 μm . The single-subject measurement of the IHTT yields estimates of axonal morphology that are consistent with histological values. However, improvement of the repeatability of the IHTT estimates is required to improve the specificity of the single-subject axonal morphology estimates. |
| Author | De Lucia, Marzia Lutti, Antoine Oliveira, Rita |
| AuthorAffiliation | 1 Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience Lausanne University Hospital and University of Lausanne Lausanne Switzerland |
| AuthorAffiliation_xml | – name: 1 Laboratory for Research in Neuroimaging, Department of Clinical Neuroscience Lausanne University Hospital and University of Lausanne Lausanne Switzerland |
| Author_xml | – sequence: 1 givenname: Rita orcidid: 0000-0002-7597-6919 surname: Oliveira fullname: Oliveira, Rita email: ana.veiga-de-oliveira@chuv.ch organization: Lausanne University Hospital and University of Lausanne – sequence: 2 givenname: Marzia orcidid: 0000-0001-8792-7885 surname: De Lucia fullname: De Lucia, Marzia organization: Lausanne University Hospital and University of Lausanne – sequence: 3 givenname: Antoine orcidid: 0000-0003-3281-5477 surname: Lutti fullname: Lutti, Antoine organization: Lausanne University Hospital and University of Lausanne |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/37470446$$D View this record in MEDLINE/PubMed |
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| Keywords | conduction velocity myelination tractography MRI g-ratio EEG |
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| Snippet | Assessing axonal morphology in vivo opens new avenues for the combined study of brain structure and function. A novel approach has recently been introduced to... |
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| SubjectTerms | Biomarkers Cerebral hemispheres Computation conduction velocity Data acquisition EEG Electrodes Electroencephalography Estimates Functional anatomy g‐ratio In vivo methods and tests Interhemispheric transfer Magnetic resonance imaging Morphology MRI myelination Neuroimaging Solution space Statistical analysis Structure-function relationships tractography Variability Visual evoked potentials Visual stimuli |
| Title | Single‐subject electroencephalography measurement of interhemispheric transfer time for the in‐vivo estimation of axonal morphology |
| URI | https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fhbm.26420 https://www.ncbi.nlm.nih.gov/pubmed/37470446 https://www.proquest.com/docview/2859571517 https://www.proquest.com/docview/2840244283 https://pubmed.ncbi.nlm.nih.gov/PMC10472916 |
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