1
|
Khazaei M, Raeisi K, Vanhatalo S, Zappasodi F, Comani S, Tokariev A. Neonatal cortical activity organizes into transient network states that are affected by vigilance states and brain injury. Neuroimage 2023; 279:120342. [PMID: 37619792 DOI: 10.1016/j.neuroimage.2023.120342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 08/11/2023] [Accepted: 08/21/2023] [Indexed: 08/26/2023] Open
Abstract
Early neurodevelopment is critically dependent on the structure and dynamics of spontaneous neuronal activity; however, the natural organization of newborn cortical networks is poorly understood. Recent adult studies suggest that spontaneous cortical activity exhibits discrete network states with physiological correlates. Here, we studied newborn cortical activity during sleep using hidden Markov modeling to determine the presence of such discrete neonatal cortical states (NCS) in 107 newborn infants, with 47 of them presenting with a perinatal brain injury. Our results show that neonatal cortical activity organizes into four discrete NCSs that are present in both cardinal sleep states of a newborn infant, active and quiet sleep, respectively. These NCSs exhibit state-specific spectral and functional network characteristics. The sleep states exhibit different NCS dynamics, with quiet sleep presenting higher fronto-temporal activity and a stronger brain-wide neuronal coupling. Brain injury was associated with prolonged lifetimes of the transient NCSs, suggesting lowered dynamics, or flexibility, in the cortical networks. Taken together, the findings suggest that spontaneously occurring transient network states are already present at birth, with significant physiological and pathological correlates; this NCS analysis framework can be fully automatized, and it holds promise for offering an objective, global level measure of early brain function for benchmarking neurodevelopmental or clinical research.
Collapse
Affiliation(s)
- Mohammad Khazaei
- Department of Neurosciences, Imaging and Clinical Sciences, University "Gabriele d'Annunzio" of Chieti-Pescara, ITAB building, 3rd floor, room 314, Chieti, Via dei Vestini, Italy.
| | - Khadijeh Raeisi
- Department of Neurosciences, Imaging and Clinical Sciences, University "Gabriele d'Annunzio" of Chieti-Pescara, ITAB building, 3rd floor, room 314, Chieti, Via dei Vestini, Italy
| | - Sampsa Vanhatalo
- BABA center, Pediatric Research Center, Departments of Clinical Neurophysiology and Physiology, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Filippo Zappasodi
- Department of Neurosciences, Imaging and Clinical Sciences, University "Gabriele d'Annunzio" of Chieti-Pescara, ITAB building, 3rd floor, room 314, Chieti, Via dei Vestini, Italy; Institute for Advanced Biomedical Technologies, University "Gabriele d'Annunzio" of Chieti-Pescara, Chieti, Italy
| | - Silvia Comani
- Department of Neurosciences, Imaging and Clinical Sciences, University "Gabriele d'Annunzio" of Chieti-Pescara, ITAB building, 3rd floor, room 314, Chieti, Via dei Vestini, Italy; Behavioral Imaging and Neural Dynamics Center, University "Gabriele d'Annunzio" of Chieti-Pescara, Chieti, Italy
| | - Anton Tokariev
- BABA center, Pediatric Research Center, Departments of Clinical Neurophysiology and Physiology, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| |
Collapse
|
2
|
Azizollahi H, Aarabi A, Kazemi K, Wallois F. Assessing the effects of head modelling errors and measurement noise on EEG source localization accuracy in preterm newborns: A single-subject study. Eur J Neurosci 2023; 58:2746-2765. [PMID: 37448164 DOI: 10.1111/ejn.16060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 05/22/2023] [Accepted: 05/27/2023] [Indexed: 07/15/2023]
Abstract
The accuracy of electroencephalogram (EEG) source localization is compromised because of head modelling errors. In this study, we investigated the effect of inaccuracy in the conductivity of head tissues and head model structural deficiencies on the accuracy of EEG source analysis in premature neonates. A series of EEG forward and inverse simulations was performed by introducing structural deficiencies into the reference head models to generate test models, which were then used to investigate head modelling errors caused by cerebrospinal fluid (CSF) exclusion, lack of grey matter (GM)-white matter (WM) distinction, fontanel exclusion and inaccuracy in skull conductivity. The modelling errors were computed between forward and inverse solutions obtained using the reference and test models generated for each deficiency. Our results showed that the exclusion of CSF from the head model had a strong widespread effect on the accuracy of the EEG source localization with position errors lower than 4.17 mm. The GM and WM distinction also caused strong localization errors (up to 3.5 mm). The exclusion of fontanels from the head model also strongly affected the accuracy of the EEG source localization for sources located beneath the fontanels with a maximum localization error of 4.37 mm. Similarly, inaccuracies in the skull conductivity caused errors in EEG forward and inverse modelling in sources beneath cranial bones. Our results indicate that the accuracy of EEG source imaging in premature neonates can be largely improved by using head models, which include not only the brain, skull and scalp but also the CSF, GM, WM and fontanels.
Collapse
Affiliation(s)
- Hamed Azizollahi
- GRAMFC, Inserm U1105, University Research Center (CURS), CHU AMIENS-SITE SUD, Amiens, France
| | - Ardalan Aarabi
- Laboratory of Functional Neuroscience and Pathologies (LNFP UR 4559), University Research Center, University Hospital, Amiens, France
- Faculty of Medicine, University of Picardy Jules Verne, Amiens, France
| | - Kamran Kazemi
- Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz, Iran
| | - Fabrice Wallois
- GRAMFC, Inserm U1105, University Research Center (CURS), CHU AMIENS-SITE SUD, Amiens, France
- EFSN Pediatric (Pediatric Nervous System Functional Investigation Unit), Department of Pediatrics, CHU AMIENS-SITE SUD, Amiens, France
| |
Collapse
|
3
|
Perakis E. On Modelling Electrical Conductivity of the Cerebral White Matter. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2023; 1424:81-89. [PMID: 37486482 DOI: 10.1007/978-3-031-31982-2_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
The conductivity, in general, of the brain tissues is a characteristic key of functional cerebral changes. White matter electric conductivity appears to be extremely anisotropic, so a tensor (matrix) is needed to describe it. Traditional methods of imaging brain electrical properties fail to capture it and required the interpolation of the diffusion matrix. The electrochemical model is suitable for analysis, while, on the other hand, the volume fraction model is suitable for studying the effect of white matter structural changes in relation to electrical conductivity. It adopts a relevant algorithm, based upon a linear conductivity-to-diffusivity relationship and a volume constraint, respectively. It incorporates the effects of the partial volume of the cerebrospinal fluid and the structure of the neuronal fiber crossing, which was not achieved by the existing algorithms, accomplishing a more accurate estimation of the anisotropic conductivity of the white matter. Diffusion matrix imaging is a powerful noninvasive method for characterizing neuronal tissue in the human brain. The ultimate goal is to study and draw appropriate conclusions, regarding the molecule diffusion in the brain under normal physiological conditions and the changes that occur in development, diseases, and aging. The ability to measure the electrical conductivity of brain tissues in a noninvasive way also helps in characterizing endogenous currents by measuring the associated electromagnetic fields.
Collapse
|
4
|
Xie W, Toll RT, Nelson CA. EEG functional connectivity analysis in the source space. Dev Cogn Neurosci 2022; 56:101119. [PMID: 35716637 PMCID: PMC9204388 DOI: 10.1016/j.dcn.2022.101119] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 05/15/2022] [Accepted: 06/06/2022] [Indexed: 11/18/2022] Open
Abstract
There is a growing interest in using electroencephalography (EEG) and source modeling to investigate functional interactions among cortical processes, particularly when dealing with pediatric populations. This paper introduces two pipelines that have been recently used to conduct EEG FC analysis in the cortical source space. The analytic streams of these pipelines can be summarized into the following steps: 1) cortical source reconstruction of high-density EEG data using realistic magnetic resonance imaging (MRI) models created with age-appropriate MRI templates; 2) segmentation of reconstructed source activities into brain regions of interest; and 3) estimation of FC in age-related frequency bands using robust EEG FC measures, such as weighted phase lag index and orthogonalized power envelope correlation. In this paper we demonstrate the two pipelines with resting-state EEG data collected from children at 12 and 36 months of age. We also discuss the advantages and limitations of the methods/techniques integrated into the pipelines. Given there is a need in the research community for open-access analytic toolkits that can be used for pediatric EEG data, programs and codes used for the current analysis are made available to the public.
Collapse
Affiliation(s)
- Wanze Xie
- School of Psychological and Cognitive Sciences, Peking University, China; PKU-IDG/McGovern Institute for Brain Research, Peking University, China; Beijing Key Laboratory of Behavior and Mental Health, Peking University, China.
| | - Russell T Toll
- Department of Psychiatry, University of Texas Southwestern Medical Centre at Dallas, USA
| | - Charles A Nelson
- Boston Children's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard Graduate School of Education, Cambridge, MA, USA
| |
Collapse
|
5
|
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
|
6
|
van 't Westende C, Geraedts VJ, van Ramesdonk T, Dudink J, Schoonmade LJ, van der Knaap MS, Stam CJ, van de Pol LA. Neonatal quantitative electroencephalography and long-term outcomes: a systematic review. Dev Med Child Neurol 2022; 64:413-420. [PMID: 34932822 DOI: 10.1111/dmcn.15133] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 10/22/2021] [Accepted: 11/08/2021] [Indexed: 11/29/2022]
Abstract
AIM To evaluate quantitative electroencephalogram (EEG) measures as predictors of long-term neurodevelopmental outcome in infants with a postconceptional age below 46 weeks, including typically developing infants born at term, infants with heterogeneous underlying pathologies, and infants born preterm. METHOD A comprehensive search was performed using PubMed, Embase, and Web of Science from study inception up to 8th January 2021. Studies that examined associations between neonatal quantitative EEG measures, based on conventional and amplitude-integrated EEG, and standardized neurodevelopmental outcomes at 2 years of age or older were reviewed. Significant associations between neonatal quantitative EEG and long-term outcome measures were grouped into one or more of the following categories: cognitive outcome; motor outcome; composite scores; and other standardized outcome assessments. RESULTS Twenty-four out of 1740 studies were included. Multiple studies showed that conventional EEG-based absolute power in the delta, theta, alpha, and beta frequency bands and conventional and amplitude-integrated EEG-related amplitudes were positively associated with favourable long-term outcome across several domains, including cognition and motor performance. Furthermore, a lower presence of discontinuous background pattern was also associated with favourable outcomes. However, interpretation of the results is limited by heterogeneity in study design and populations. INTERPRETATION Neonatal quantitative EEG measures may be used as prognostic biomarkers to identify those infants who will develop long-term difficulties and who might benefit from early interventions.
Collapse
Affiliation(s)
- Charlotte van 't Westende
- Department of Child Neurology, Emma Children's Hospital, Amsterdam University Medical Centers, Amsterdam, The Netherlands.,Department of Clinical Neurophysiology, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Victor J Geraedts
- Departments of Neurology and Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Tino van Ramesdonk
- Department of Child Neurology, Emma Children's Hospital, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Jeroen Dudink
- Department of Neonatology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, The Netherlands
| | | | - Marjo S van der Knaap
- Department of Child Neurology, Emma Children's Hospital, Amsterdam University Medical Centers, Amsterdam, The Netherlands.,Department of Functional Genomics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, the Netherlands
| | - Cornelis J Stam
- Department of Clinical Neurophysiology, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| | - Laura A van de Pol
- Department of Child Neurology, Emma Children's Hospital, Amsterdam University Medical Centers, Amsterdam, The Netherlands
| |
Collapse
|
7
|
Tokariev A, Oberlander VC, Videman M, Vanhatalo S. Cortical Cross-Frequency Coupling Is Affected by in utero Exposure to Antidepressant Medication. Front Neurosci 2022; 16:803708. [PMID: 35310093 PMCID: PMC8927083 DOI: 10.3389/fnins.2022.803708] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 01/27/2022] [Indexed: 11/24/2022] Open
Abstract
Up to five percent of human infants are exposed to maternal antidepressant medication by serotonin reuptake inhibitors (SRI) during pregnancy, yet the SRI effects on infants’ early neurodevelopment are not fully understood. Here, we studied how maternal SRI medication affects cortical frequency-specific and cross-frequency interactions estimated, respectively, by phase-phase correlations (PPC) and phase-amplitude coupling (PAC) in electroencephalographic (EEG) recordings. We examined the cortical activity in infants after fetal exposure to SRIs relative to a control group of infants without medical history of any kind. Our findings show that the sleep-related dynamics of PPC networks are selectively affected by in utero SRI exposure, however, those alterations do not correlate to later neurocognitive development as tested by neuropsychological evaluation at two years of age. In turn, phase-amplitude coupling was found to be suppressed in SRI infants across multiple distributed cortical regions and these effects were linked to their neurocognitive outcomes. Our results are compatible with the overall notion that in utero drug exposures may cause subtle, yet measurable changes in the brain structure and function. Our present findings are based on the measures of local and inter-areal neuronal interactions in the cortex which can be readily used across species, as well as between different scales of inspection: from the whole animals to in vitro preparations. Therefore, this work opens a framework to explore the cellular and molecular mechanisms underlying neurodevelopmental SRI effects at all translational levels.
Collapse
Affiliation(s)
- Anton Tokariev
- Department of Clinical Neurophysiology, BABA Center, New Children’s Hospital, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- *Correspondence: Anton Tokariev,
| | - Victoria C. Oberlander
- Department of Clinical Neurophysiology, BABA Center, New Children’s Hospital, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
- Department of Computer Science, Aalto University, Espoo, Finland
| | - Mari Videman
- Department of Clinical Neurophysiology, BABA Center, New Children’s Hospital, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
- Department of Pediatric Neurology, New Children’s Hospital, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Sampsa Vanhatalo
- Department of Clinical Neurophysiology, BABA Center, New Children’s Hospital, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Department of Physiology, University of Helsinki, Helsinki, Finland
- Sampsa Vanhatalo,
| |
Collapse
|
8
|
Kumaravel VP, Farella E, Parise E, Buiatti M. NEAR: An artifact removal pipeline for human newborn EEG data. Dev Cogn Neurosci 2022; 54:101068. [PMID: 35085870 PMCID: PMC8800139 DOI: 10.1016/j.dcn.2022.101068] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 11/15/2021] [Accepted: 01/13/2022] [Indexed: 12/17/2022] Open
Abstract
Electroencephalography (EEG) is arising as a valuable method to investigate neurocognitive functions shortly after birth. However, obtaining high-quality EEG data from human newborn recordings is challenging. Compared to adults and older infants, datasets are typically much shorter due to newborns’ limited attentional span and much noisier due to non-stereotyped artifacts mainly caused by uncontrollable movements. We propose Newborn EEG Artifact Removal (NEAR), a pipeline for EEG artifact removal designed explicitly for human newborns. NEAR is based on two key steps: 1) A novel bad channel detection tool based on the Local Outlier Factor (LOF), a robust outlier detection algorithm; 2) A parameter calibration procedure for adapting to newborn EEG data the algorithm Artifacts Subspace Reconstruction (ASR), developed for artifact removal in mobile adult EEG. Tests on simulated data showed that NEAR outperforms existing methods in removing representative newborn non-stereotypical artifacts. NEAR was validated on two developmental populations (newborns and 9-month-old infants) recorded with two different experimental designs (frequency-tagging and ERP). Results show that NEAR artifact removal successfully reproduces established EEG responses from noisy datasets, with a higher statistical significance than the one obtained by existing artifact removal methods. The EEGLAB-based NEAR pipeline is freely available at https://github.com/vpKumaravel/NEAR.
Collapse
|
9
|
Yrjölä P, Stjerna S, Palva JM, Vanhatalo S, Tokariev A. Phase-Based Cortical Synchrony Is Affected by Prematurity. Cereb Cortex 2021; 32:2265-2276. [PMID: 34668522 PMCID: PMC9113310 DOI: 10.1093/cercor/bhab357] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 08/26/2021] [Accepted: 08/30/2021] [Indexed: 11/22/2022] Open
Abstract
Inter-areal synchronization by phase–phase correlations (PPCs) of cortical oscillations mediates many higher neurocognitive functions, which are often affected by prematurity, a globally prominent neurodevelopmental risk factor. Here, we used electroencephalography to examine brain-wide cortical PPC networks at term-equivalent age, comparing human infants after early prematurity to a cohort of healthy controls. We found that prematurity affected these networks in a sleep state-specific manner, and the differences between groups were also frequency-selective, involving brain-wide connections. The strength of synchronization in these networks was predictive of clinical outcomes in the preterm infants. These findings show that prematurity affects PPC networks in a clinically significant manner, suggesting early functional biomarkers of later neurodevelopmental compromise that may be used in clinical or translational studies after early neonatal adversity.
Collapse
Affiliation(s)
- Pauliina Yrjölä
- Department of Clinical Neurophysiology, BABA Center, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, 00029 HUS, Finland.,Department of Neuroscience and Biomedical Engineering, Aalto University, Helsinki, 00076 AALTO, Finland.,Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, 00014 Helsinki, Finland
| | - Susanna Stjerna
- Department of Clinical Neurophysiology, BABA Center, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, 00029 HUS, Finland.,Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, 00014 Helsinki, Finland.,Division of Neuropsychology, HUS Neurocenter, Helsinki University Hospital and University of Helsinki, PL 340, 00029 HUS, Finland
| | - J Matias Palva
- Department of Neuroscience and Biomedical Engineering, Aalto University, Helsinki, 00076 AALTO, Finland.,Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, 00014 Helsinki, Finland.,Centre for Cognitive Neuroimaging, Institute of Neuroscience and Psychology, University of Glasgow, Glasgow G12 8QB, UK
| | - Sampsa Vanhatalo
- Department of Clinical Neurophysiology, BABA Center, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, 00029 HUS, Finland.,Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, 00014 Helsinki, Finland
| | - Anton Tokariev
- Department of Clinical Neurophysiology, BABA Center, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, 00029 HUS, Finland.,Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, 00014 Helsinki, Finland
| |
Collapse
|
10
|
Tokariev A, Breakspear M, Videman M, Stjerna S, Scholtens LH, van den Heuvel MP, Cocchi L, Vanhatalo S. Impact of In Utero Exposure to Antiepileptic Drugs on Neonatal Brain Function. Cereb Cortex 2021; 32:2385-2397. [PMID: 34585721 PMCID: PMC9157298 DOI: 10.1093/cercor/bhab338] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 08/18/2021] [Accepted: 08/22/2021] [Indexed: 12/27/2022] Open
Abstract
In utero brain development underpins brain health across the lifespan but is vulnerable to physiological and pharmacological perturbation. Here, we show that antiepileptic medication during pregnancy impacts on cortical activity during neonatal sleep, a potent indicator of newborn brain health. These effects are evident in frequency-specific functional brain networks and carry prognostic information for later neurodevelopment. Notably, such effects differ between different antiepileptic drugs that suggest neurodevelopmental adversity from exposure to antiepileptic drugs and not maternal epilepsy per se. This work provides translatable bedside metrics of brain health that are sensitive to the effects of antiepileptic drugs on postnatal neurodevelopment and carry direct prognostic value.
Collapse
Affiliation(s)
- Anton Tokariev
- Baby Brain Activity Center (BABA), Department of Clinical Neurophysiology, New Children's Hospital, HUS Imaging, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.,Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Michael Breakspear
- School of Psychology, College of Engineering, Science and the Environment, University of Newcastle, Callaghan, New South Wales, Australia.,School of Medicine and Public Health, College of Health and Medicine, University of Newcastle, Callaghan, New South Wales, Australia
| | - Mari Videman
- Baby Brain Activity Center (BABA), Department of Clinical Neurophysiology, New Children's Hospital, HUS Imaging, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.,Department of Pediatric Neurology, New Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Susanna Stjerna
- Baby Brain Activity Center (BABA), Department of Clinical Neurophysiology, New Children's Hospital, HUS Imaging, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.,Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Lianne H Scholtens
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Martijn P van den Heuvel
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, the Netherlands.,Department of Child Psychiatry, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Luca Cocchi
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Sampsa Vanhatalo
- Baby Brain Activity Center (BABA), Department of Clinical Neurophysiology, New Children's Hospital, HUS Imaging, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.,Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| |
Collapse
|
11
|
McCann H, Beltrachini L. Does participant's age impact on tDCS induced fields? Insights from computational simulations. Biomed Phys Eng Express 2021; 7. [PMID: 34038881 DOI: 10.1088/2057-1976/ac0547] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 05/26/2021] [Indexed: 12/20/2022]
Abstract
Objective: Understanding the induced current flow from transcranial direct current stimulation (tDCS) is essential for determining the optimal dose and treatment. Head tissue conductivities play a key role in the resulting electromagnetic fields. However, there exists a complicated relationship between skull conductivity and participant age, that remains unclear. We explored how variations in skull electrical conductivities, particularly as a suggested function of age, affected tDCS induced electric fields.Approach: Simulations were employed to compare tDCS outcomes for different intensities across head atlases of varying age. Three databases were chosen to demonstrate differing variability in skull conductivity with age and how this may affect induced fields. Differences in tDCS electric fields due to proposed age-dependent skull conductivity variation, as well as deviations in grey matter, white matter and scalp, were compared and the most influential tissues determined.Main results: tDCS induced peak electric fields significantly negatively correlated with age, exacerbated by employing proposed age-appropriate skull conductivity (according to all three datasets). Uncertainty in skull conductivity was the most sensitive to changes in peak fields with increasing age. These results were revealed to be directly due to changing skull conductivity, rather than head geometry alone. There was no correlation between tDCS focality and age.Significance: Accurate and individualised head anatomy andin vivoskull conductivity measurements are essential for modelling tDCS induced fields. In particular, age should be taken into account when considering stimulation dose to precisely predict outcomes.
Collapse
Affiliation(s)
- Hannah McCann
- School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom.,Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff, United Kingdom
| | - Leandro Beltrachini
- School of Physics and Astronomy, Cardiff University, Cardiff, United Kingdom.,Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff, United Kingdom
| |
Collapse
|
12
|
Mariscal MG, Levin AR, Gabard-Durnam LJ, Xie W, Tager-Flusberg H, Nelson CA. EEG Phase-Amplitude Coupling Strength and Phase Preference: Association with Age over the First Three Years after Birth. eNeuro 2021; 8:ENEURO.0264-20.2021. [PMID: 34049989 PMCID: PMC8225408 DOI: 10.1523/eneuro.0264-20.2021] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 04/26/2021] [Accepted: 05/10/2021] [Indexed: 01/11/2023] Open
Abstract
Phase-amplitude coupling (PAC), the coupling of the phase of slower electrophysiological oscillations with the amplitude of faster oscillations, is thought to facilitate dynamic integration of neural activity in the brain. Although the brain undergoes dramatic change and development during the first few years of life, how PAC changes through this developmental period has not been extensively studied. Here, we examined PAC through electroencephalography (EEG) data collected during an awake, eyes-open EEG collection paradigm in 98 children between the ages of three months and three years. We employed non-parametric clustering methods to identify areas of significant PAC across a range of frequency pairs and electrode locations, and examined how PAC strength and phase preference develops in these areas. We found that PAC, primarily between the α-β and γ frequencies, was positively correlated with age from early infancy to early childhood (p = 2.035 × 10-6). Additionally, we found γ over anterior electrodes coupled with the rising phase of the α-β waveform, while γ over posterior electrodes coupled with the falling phase of the α-β waveform; this regionalized phase preference became more prominent with age. This opposing trend may reflect each region's specialization toward feedback or feedforward processing, respectively, suggesting opportunities for back translation in future studies.
Collapse
Affiliation(s)
- Michael G Mariscal
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115
| | - April R Levin
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115
| | - Laurel J Gabard-Durnam
- Division of Developmental Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02215
| | - Wanze Xie
- Division of Developmental Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02215
| | - Helen Tager-Flusberg
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215
| | - Charles A Nelson
- Division of Developmental Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA 02215
- Harvard Graduate School of Education, Cambridge, MA 02138
| |
Collapse
|
13
|
Kuchenbuch M, Nabbout R, Yochum M, Sauleau P, Modolo J, Wendling F, Benquet P. In silico model reveals the key role of GABA in KCNT1-epilepsy in infancy with migrating focal seizures. Epilepsia 2021; 62:683-697. [PMID: 33617692 DOI: 10.1111/epi.16834] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 12/08/2020] [Accepted: 01/18/2021] [Indexed: 02/06/2023]
Abstract
OBJECTIVE This study was undertaken to investigate how gain of function (GOF) of slack channel due to a KCNT1 pathogenic variant induces abnormal neuronal cortical network activity and generates specific electroencephalographic (EEG) patterns of epilepsy in infancy with migrating focal seizures. METHODS We used detailed microscopic computational models of neurons to explore the impact of GOF of slack channel (explicitly coded) on each subtype of neurons and on a cortical micronetwork. Then, we adapted a thalamocortical macroscopic model considering results obtained in detailed models and immature properties related to epileptic brain in infancy. Finally, we compared simulated EEGs resulting from the macroscopic model with interictal and ictal patterns of affected individuals using our previously reported EEG markers. RESULTS The pathogenic variants of KCNT1 strongly decreased the firing rate properties of γ-aminobutyric acidergic (GABAergic) interneurons and, to a lesser extent, those of pyramidal cells. This change led to hyperexcitability with increased synchronization in a cortical micronetwork. At the macroscopic scale, introducing slack GOF effect resulted in epilepsy of infancy with migrating focal seizures (EIMFS) EEG interictal patterns. Increased excitation-to-inhibition ratio triggered seizure, but we had to add dynamic depolarizing GABA between somatostatin-positive interneurons and pyramidal cells to obtain migrating seizure. The simulated migrating seizures were close to EIMFS seizures, with similar values regarding the delay between the different ictal activities (one of the specific EEG markers of migrating focal seizures due to KCNT1 pathogenic variants). SIGNIFICANCE This study illustrates the interest of biomathematical models to explore pathophysiological mechanisms bridging the gap between the functional effect of gene pathogenic variants and specific EEG phenotype. Such models can be complementary to in vitro cellular and animal models. This multiscale approach provides an in silico framework that can be further used to identify candidate innovative therapies.
Collapse
Affiliation(s)
- Mathieu Kuchenbuch
- LTSI-U1099, Université de Rennes 1, INSERM, Rennes, France.,Department of Pediatric Neurology, Reference Center for Rare Epilepsies, Hôpital Necker-Enfants malades, member of European Network EPICARE, Paris, France.,Laboratory of Translational Research for Neurological Disorders (UMR 1163), IHU Imagine Institute of Genetic Diseases, INSERM, University of Paris, Paris, France
| | - Rima Nabbout
- Department of Pediatric Neurology, Reference Center for Rare Epilepsies, Hôpital Necker-Enfants malades, member of European Network EPICARE, Paris, France.,Laboratory of Translational Research for Neurological Disorders (UMR 1163), IHU Imagine Institute of Genetic Diseases, INSERM, University of Paris, Paris, France
| | - Maxime Yochum
- LTSI-U1099, Université de Rennes 1, INSERM, Rennes, France
| | - Paul Sauleau
- CHU de Rennes (Department of Neurophysiology), "Behavior and Basal Ganglia" Research Unit (EA4712), University of Rennes, Rennes, France
| | - Julien Modolo
- LTSI-U1099, Université de Rennes 1, INSERM, Rennes, France
| | | | - Pascal Benquet
- LTSI-U1099, Université de Rennes 1, INSERM, Rennes, France
| |
Collapse
|
14
|
Antonakakis M, Schrader S, Aydin Ü, Khan A, Gross J, Zervakis M, Rampp S, Wolters CH. Inter-Subject Variability of Skull Conductivity and Thickness in Calibrated Realistic Head Models. Neuroimage 2020; 223:117353. [DOI: 10.1016/j.neuroimage.2020.117353] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 08/19/2020] [Accepted: 09/05/2020] [Indexed: 01/11/2023] Open
|
15
|
Ahtola E, Stjerna S, Tokariev A, Vanhatalo S. Use of complex visual stimuli allows controlled recruitment of cortical networks in infants. Clin Neurophysiol 2020; 131:2032-2040. [PMID: 32461100 DOI: 10.1016/j.clinph.2020.03.034] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 02/25/2020] [Accepted: 03/16/2020] [Indexed: 01/23/2023]
Abstract
OBJECTIVE To characterize cortical networks activated by patterned visual stimuli in infants, and to evaluate their potential for assessment of visual processing and their associations with neurocognitive development. METHODS Three visual stimuli, orientation reversal (OR), global form (GF), and global motion (GM), were presented to cohort of five-month-old infants (N = 26). Eye tracker was used to guide the stimulation and to choose epochs for analysis. Visual responses were recorded with electroencephalography and analysed in source space using weighted phase lag index as the connectivity measure. The networks were quantified using several metrics that were compared between stimuli and correlated to cognitive outcomes. RESULTS Responses to OR/GF/GM stimuli were observed in nearly all (96/100/100%) recordings. All stimuli recruited cortical networks that were partly condition-specific in their characteristics. The more complex GF and GM conditions recruited wider global networks than OR. Additionally, strength of the GF network showed positive association with later cognitive performance. CONCLUSIONS Network analysis suggests that visual stimulation recruits large-scale cortical networks that extend far beyond the conventional visual streams and that differ between stimulation conditions. SIGNIFICANCE The method allows controlled recruitment of wide cortical networks, which holds promise for the early assessment of visual processing and its related higher-order cognitive processes.
Collapse
Affiliation(s)
- Eero Ahtola
- BABA Center and Department of Clinical Neurophysiology, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland; Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland.
| | - Susanna Stjerna
- BABA Center and Department of Clinical Neurophysiology, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Anton Tokariev
- BABA Center and Department of Clinical Neurophysiology, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland; Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Sampsa Vanhatalo
- BABA Center and Department of Clinical Neurophysiology, Children's Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland; Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| |
Collapse
|
16
|
14 challenges and their solutions for conducting social neuroscience and longitudinal EEG research with infants. Infant Behav Dev 2019; 58:101393. [PMID: 31830682 DOI: 10.1016/j.infbeh.2019.101393] [Citation(s) in RCA: 44] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2019] [Revised: 11/14/2019] [Accepted: 11/15/2019] [Indexed: 12/11/2022]
Abstract
The use of electroencephalography (EEG) to study infant brain development is a growing trend. In addition to classical longitudinal designs that study the development of neural, cognitive and behavioural functions, new areas of EEG application are emerging, such as novel social neuroscience paradigms using dual infant-adult EEG recordings. However, most of the experimental designs, analysis methods, as well as EEG hardware were originally developed for single-person adult research. When applied to study infant development, adult-based solutions often pose unique problems that may go unrecognised. Here, we identify 14 challenges that infant EEG researchers may encounter when designing new experiments, collecting data, and conducting data analysis. Challenges related to the experimental design are: (1) small sample size and data attrition, and (2) varying arousal in younger infants. Challenges related to data acquisition are: (3) determining the optimal location for reference and ground electrodes, (4) control of impedance when testing with the high-density sponge electrode nets, (5) poor fit of standard EEG caps to the varying infant head shapes, and (6) ensuring a high degree of temporal synchronisation between amplifiers and recording devices during dual-EEG acquisition. Challenges related to the analysis of longitudinal and social neuroscience datasets are: (7) developmental changes in head anatomy, (8) prevalence and diversity of infant myogenic artefacts, (9) a lack of stereotypical topography of eye movements needed for the ICA-based data cleaning, (10) and relatively high inter-individual variability of EEG responses in younger cohorts. Additional challenges for the analysis of dual EEG data are: (11) developmental shifts in canonical EEG rhythms and difficulties in differentiating true inter-personal synchrony from spurious synchrony due to (12) common intrinsic properties of the signal and (13) shared external perturbation. Finally, (14) there is a lack of test-retest reliability studies of infant EEG. We describe each of these challenges and suggest possible solutions. While we focus specifically on the social neuroscience and longitudinal research, many of the issues we raise are relevant for all fields of infant EEG research.
Collapse
|
17
|
Leikos S, Tokariev A, Koolen N, Nevalainen P, Vanhatalo S. Cortical responses to tactile stimuli in preterm infants. Eur J Neurosci 2019; 51:1059-1073. [PMID: 31679163 DOI: 10.1111/ejn.14613] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Revised: 10/07/2019] [Accepted: 10/22/2019] [Indexed: 12/22/2022]
Abstract
The conventional assessment of preterm somatosensory functions using averaged cortical responses to electrical stimulation ignores the characteristic components of preterm somatosensory evoked responses (SERs). Our study aimed to systematically evaluate the occurrence and development of SERs after tactile stimulus in preterm infants. We analysed SERs performed during 45 electroencephalograms (EEGs) from 29 infants at the mean post-menstrual age of 30.7 weeks. Altogether 2,087 SERs were identified visually at single-trial level from unfiltered signals capturing also their slowest components. We observed salient SERs with a high-amplitude slow component at a high success rate after hand (95%) and foot (83%) stimuli. There was a clear developmental change in both the slow wave and the higher-frequency components of the SERs. Infants with intraventricular haemorrhage (IVH; eleven infants) had initially normal SERs, but those with bilateral IVH later showed a developmental decrease in the ipsilateral SER occurrence after 30 weeks of post-menstrual age. Our study shows that tactile stimulus applied at bedside elicits salient SERs with a large slow component and an overriding fast oscillation, which are specific to the preterm period. Prior experimental research indicates that such SERs allow studying both subplate and cortical functions. Our present findings further suggest that they might offer a window to the emergence of neurodevelopmental sequelae after major structural brain lesions and, hence, an additional tool for both research and clinical neurophysiological evaluation of infants before term age.
Collapse
Affiliation(s)
- Susanna Leikos
- Children's Clinical Neurophysiology, BABA Center, Children's Hospital, HUS Medical Imaging Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Anton Tokariev
- Children's Clinical Neurophysiology, BABA Center, Children's Hospital, HUS Medical Imaging Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Ninah Koolen
- Children's Clinical Neurophysiology, BABA Center, Children's Hospital, HUS Medical Imaging Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Päivi Nevalainen
- Children's Clinical Neurophysiology, BABA Center, Children's Hospital, HUS Medical Imaging Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Sampsa Vanhatalo
- Children's Clinical Neurophysiology, BABA Center, Children's Hospital, HUS Medical Imaging Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| |
Collapse
|
18
|
Tokariev A, Roberts JA, Zalesky A, Zhao X, Vanhatalo S, Breakspear M, Cocchi L. Large-scale brain modes reorganize between infant sleep states and carry prognostic information for preterms. Nat Commun 2019; 10:2619. [PMID: 31197175 PMCID: PMC6565810 DOI: 10.1038/s41467-019-10467-8] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 05/06/2019] [Indexed: 12/18/2022] Open
Abstract
Sleep architecture carries vital information about brain health across the lifespan. In particular, the ability to express distinct vigilance states is a key physiological marker of neurological wellbeing in the newborn infant although systems-level mechanisms remain elusive. Here, we demonstrate that the transition from quiet to active sleep in newborn infants is marked by a substantial reorganization of large-scale cortical activity and functional brain networks. This reorganization is attenuated in preterm infants and predicts visual performance at two years. We find a striking match between these empirical effects and a computational model of large-scale brain states which uncovers fundamental biophysical mechanisms not evident from inspection of the data. Active sleep is defined by reduced energy in a uniform mode of neural activity and increased energy in two more complex anteroposterior modes. Preterm-born infants show a deficit in this sleep-related reorganization of modal energy that carries novel prognostic information.
Collapse
Affiliation(s)
- Anton Tokariev
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, 4006, Australia. .,Department of Clinical Neurophysiology, Clinicum, University of Helsinki, 00014, Helsinki, Finland. .,BABA center, Pediatric Research Center, Clinical Neurophysiology, Children's Hospital, Helsinki University Central Hospital, 00029, Helsinki, Finland.
| | - James A Roberts
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, 4006, Australia
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, VIC, 3053, Australia.,Department of Biomedical Engineering, University of Melbourne, Melbourne, VIC, 3010, Australia
| | - Xuelong Zhao
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Sampsa Vanhatalo
- Department of Clinical Neurophysiology, Clinicum, University of Helsinki, 00014, Helsinki, Finland.,BABA center, Pediatric Research Center, Clinical Neurophysiology, Children's Hospital, Helsinki University Central Hospital, 00029, Helsinki, Finland
| | - Michael Breakspear
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, 4006, Australia.,Hunter Medical Research Institute, University of Newcastle, Newcastle, NSW, 2305, Australia
| | - Luca Cocchi
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, 4006, Australia. .,School of Medicine, University of Queensland, Brisbane, QLD, 4006, Australia.
| |
Collapse
|
19
|
Stevenson NJ, Tapani K, Lauronen L, Vanhatalo S. A dataset of neonatal EEG recordings with seizure annotations. Sci Data 2019; 6:190039. [PMID: 30835259 PMCID: PMC6400100 DOI: 10.1038/sdata.2019.39] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Accepted: 01/31/2019] [Indexed: 01/27/2023] Open
Abstract
Neonatal seizures are a common emergency in the neonatal intensive care unit (NICU). There are many questions yet to be answered regarding the temporal/spatial characteristics of seizures from different pathologies, response to medication, effects on neurodevelopment and optimal detection. The dataset presented in this descriptor contains EEG recordings from human neonates, the visual interpretation of the EEG by the human experts, supporting clinical data and codes to assist access. Multi-channel EEG was recorded from 79 term neonates admitted to the NICU at the Helsinki University Hospital. The median recording duration was 74 min (IQR: 64 to 96 min). The presence of seizures in the EEGs was annotated independently by three experts. An average of 460 seizures were annotated per expert in the dataset; 39 neonates had seizures and 22 were seizure free, by consensus. The dataset can be used as a reference set of neonatal seizures, in studies of inter-observer agreement and for the development of automated methods of seizure detection and other EEG analyses.
Collapse
Affiliation(s)
- N. J. Stevenson
- BABA Center, Children’s Hospital, HUS Medical Imaging Center, Department of Clinical Neurophysiology, Helsinki University Hospital, Helsinki, Finland
- Clinicum, University of Helsinki, Helsinki, Finland
- Brain Modelling Group, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - K. Tapani
- BABA Center, Children’s Hospital, HUS Medical Imaging Center, Department of Clinical Neurophysiology, Helsinki University Hospital, Helsinki, Finland
| | - L. Lauronen
- BABA Center, Children’s Hospital, HUS Medical Imaging Center, Department of Clinical Neurophysiology, Helsinki University Hospital, Helsinki, Finland
- Clinicum, University of Helsinki, Helsinki, Finland
| | - S. Vanhatalo
- BABA Center, Children’s Hospital, HUS Medical Imaging Center, Department of Clinical Neurophysiology, Helsinki University Hospital, Helsinki, Finland
- Clinicum, University of Helsinki, Helsinki, Finland
| |
Collapse
|
20
|
Abstract
Humans are endowed with an exceptional ability for detecting faces, a competence that, in adults, is supported by a set of face-specific cortical patches. Human newborns, already shortly after birth, preferentially orient to faces, even when they are presented in the form of highly schematic geometrical patterns vs. perceptually equivalent nonfacelike stimuli. The neural substrates underlying this early preference are still largely unexplored. Is the adult face-specific cortical circuit already active at birth, or does its specialization develop slowly as a function of experience and/or maturation? We measured EEG responses in 1- to 4-day-old awake, attentive human newborns to schematic facelike patterns and nonfacelike control stimuli, visually presented with slow oscillatory "peekaboo" dynamics (0.8 Hz) in a frequency-tagging design. Despite the limited duration of newborns' attention, reliable frequency-tagged responses could be estimated for each stimulus from the peak of the EEG power spectrum at the stimulation frequency. Upright facelike stimuli elicited a significantly stronger frequency-tagged response than inverted facelike controls in a large set of electrodes. Source reconstruction of the underlying cortical activity revealed the recruitment of a partially right-lateralized network comprising lateral occipitotemporal and medial parietal areas overlapping with the adult face-processing circuit. This result suggests that the cortical route specialized in face processing is already functional at birth.
Collapse
|
21
|
|
22
|
Abstract
EEG changes during the perinatal period, infancy, childhood, and adolescence are concomitant with brain growth, myelination, expanding connectivity, and overall maturation, which are particularly fast during the first year of life. EEG aspects of early brain development are accessible in preterm during the third trimester of gestational age, and they evolve to full-term, infancy, and childhood EEG patterns. Each of these age periods shares specific EEG features that reach gross adult outlines in the first year. Interpreting EEG needs therefore a deep knowledge of pathological and normal EEG patterns with their variants belonging to each age range. Recording EEG during these periods also requires adapting the recording techniques to the specific age in order to obtain interpretable records. This chapter describes normal EEG features and variants, characteristic patterns of development, and some patterns that are unusual for age, from the neonatal period to adolescence.
Collapse
Affiliation(s)
- A Kaminska
- Department of Clinical Neurophysiology, Necker-Enfants Malades Hospital, APHP, Paris, France.
| | - M Eisermann
- Department of Clinical Neurophysiology, Necker-Enfants Malades Hospital, APHP, Paris, France
| | - P Plouin
- Department of Clinical Neurophysiology, Necker-Enfants Malades Hospital, APHP, Paris, France
| |
Collapse
|
23
|
Rimpiläinen V, Koulouri A, Lucka F, Kaipio JP, Wolters CH. Improved EEG source localization with Bayesian uncertainty modelling of unknown skull conductivity. Neuroimage 2018; 188:252-260. [PMID: 30529398 DOI: 10.1016/j.neuroimage.2018.11.058] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Accepted: 11/30/2018] [Indexed: 10/27/2022] Open
Abstract
Electroencephalography (EEG) source imaging is an ill-posed inverse problem that requires accurate conductivity modelling of the head tissues, especially the skull. Unfortunately, the conductivity values are difficult to determine in vivo. In this paper, we show that the exact knowledge of the skull conductivity is not always necessary when the Bayesian approximation error (BAE) approach is exploited. In BAE, we first postulate a probability distribution for the skull conductivity that describes our (lack of) knowledge on its value, and model the effects of this uncertainty on EEG recordings with the help of an additive error term in the observation model. Before the Bayesian inference, the likelihood is marginalized over this error term. Thus, in the inversion we estimate only our primary unknown, the source distribution. We quantified the improvements in the source localization when the proposed Bayesian modelling was used in the presence of different skull conductivity errors and levels of measurement noise. Based on the results, BAE was able to improve the source localization accuracy, particularly when the unknown (true) skull conductivity was much lower than the expected standard conductivity value. The source locations that gained the highest improvements were shallow and originally exhibited the largest localization errors. In our case study, the benefits of BAE became negligible when the signal-to-noise ratio dropped to 20 dB.
Collapse
Affiliation(s)
- Ville Rimpiläinen
- Department of Physics, University of Bath, Claverton Down, Bath, BA2 7AY, United Kingdom; Institute for Biomagnetism and Biosignalanalysis, University of Münster, Malmedyweg 15, D-48149, Münster, Germany.
| | - Alexandra Koulouri
- Laboratory of Mathematics, Tampere University of Technology, P. O. Box 692, 33101, Tampere, Finland; Department of Physics, Aristotle University of Thessaloniki, Thessaloniki, 541 24, Greece
| | - Felix Lucka
- Computational Imaging, Centrum Wiskunde & Informatica, Science Park 123, 1098 XG, Amsterdam, the Netherlands; Centre for Medical Image Computing, University College London, Gower Street, London, WC1E 6BT, United Kingdom
| | - Jari P Kaipio
- Department of Mathematics, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand; Department of Applied Physics, University of Eastern Finland, FI-90211, Kuopio, Finland
| | - Carsten H Wolters
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Malmedyweg 15, D-48149, Münster, Germany
| |
Collapse
|
24
|
Skull Modeling Effects in Conductivity Estimates Using Parametric Electrical Impedance Tomography. IEEE Trans Biomed Eng 2018; 65:1785-1797. [DOI: 10.1109/tbme.2017.2777143] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
25
|
A review of anisotropic conductivity models of brain white matter based on diffusion tensor imaging. Med Biol Eng Comput 2018; 56:1325-1332. [DOI: 10.1007/s11517-018-1845-9] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2016] [Accepted: 05/08/2018] [Indexed: 10/14/2022]
|
26
|
Tokariev A, Stjerna S, Lano A, Metsäranta M, Palva JM, Vanhatalo S. Preterm Birth Changes Networks of Newborn Cortical Activity. Cereb Cortex 2018; 29:814-826. [DOI: 10.1093/cercor/bhy012] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2017] [Accepted: 01/07/2018] [Indexed: 12/31/2022] Open
Affiliation(s)
- Anton Tokariev
- Department of Clinical Neurophysiology, University of Helsinki, HUS, Helsinki, Finland
| | - Susanna Stjerna
- Department of Clinical Neurophysiology, University of Helsinki, HUS, Helsinki, Finland
| | - Aulikki Lano
- Department of Child Neurology, Children’s Hospital, University of Helsinki and HUH, Helsinki, Finland
| | - Marjo Metsäranta
- Department of Neonatology, Children’s Hospital, University of Helsinki and HUH, Helsinki, Finland
| | - J Matias Palva
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Sampsa Vanhatalo
- Department of Clinical Neurophysiology, University of Helsinki, HUS, Helsinki, Finland
| |
Collapse
|
27
|
de Camp NV, Hense F, Lecher B, Scheu H, Bergeler J. Models for Preterm Cortical Development Using Non Invasive Clinical EEG. Transl Neurosci 2018; 8:211-224. [PMID: 29445543 PMCID: PMC5811640 DOI: 10.1515/tnsci-2017-0029] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2017] [Accepted: 09/20/2017] [Indexed: 01/14/2023] Open
Abstract
The objective of this study was to evaluate the piglet and the mouse as model systems for preterm cortical development. According to the clinical context, we used non invasive EEG recordings. As a prerequisite, we developed miniaturized Ag/AgCl electrodes for full band EEG recordings in mice and verified that Urethane had no effect on EEG band power. Since mice are born with a “preterm” brain, we evaluated three age groups: P0/P1, P3/P4 and P13/P14. Our aim was to identify EEG patterns in the somatosensory cortex which are distinguishable between developmental stages and represent a physiologic brain development. In mice, we were able to find clear differences between age groups with a simple power analysis of EEG bands and also for phase locking and power spectral density. Interhemispheric coherence between corresponding regions can only be seen in two week old mice. The canolty maps for piglets as well as for mice show a clear PAC (phase amplitude coupling) pattern during development. From our data it can be concluded that analytic tools relying on network activity, as for example PAC (phase amplitude coupling) are best suited to extract basic EEG patterns of cortical development across species.
Collapse
Affiliation(s)
- Nora Vanessa de Camp
- Medical Center of the Johannes Gutenberg, University Mainz, Mainz, Germany.,Free University Berlin, Berlin, Germany.,Humboldt University Berlin, Berlin, Germany
| | - Florian Hense
- Medical Center of the Johannes Gutenberg, University Mainz, Mainz, Germany
| | | | - Helmut Scheu
- Lehr- und Versuchstieranstalt Hofgut Neumühle, Neumühle, Germany
| | - Jürgen Bergeler
- Medical Center of the Johannes Gutenberg, University Mainz, Mainz, Germany.,Free University Berlin, Berlin, Germany
| |
Collapse
|
28
|
Kaminska A, Delattre V, Laschet J, Dubois J, Labidurie M, Duval A, Manresa A, Magny JF, Hovhannisyan S, Mokhtari M, Ouss L, Boissel A, Hertz-Pannier L, Sintsov M, Minlebaev M, Khazipov R, Chiron C. Cortical Auditory-Evoked Responses in Preterm Neonates: Revisited by Spectral and Temporal Analyses. Cereb Cortex 2017; 28:3429-3444. [DOI: 10.1093/cercor/bhx206] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Indexed: 11/12/2022] Open
Affiliation(s)
- A Kaminska
- INSERM U1129, Paris, France
- Paris Descartes University, Sorbonne Paris Cité, Paris, France
- CEA, 91191 Gif sur Yvette, France
- Department of Clinical Neurophysiology, AP-HP, Necker-Enfants Malades Hospital, Paris, France
| | - V Delattre
- INSERM U1129, Paris, France
- Paris Descartes University, Sorbonne Paris Cité, Paris, France
- CEA, 91191 Gif sur Yvette, France
- Neurospin, UNIACT, CEA, Gif sur Yvette, France
| | - J Laschet
- INSERM U1129, Paris, France
- Paris Descartes University, Sorbonne Paris Cité, Paris, France
- CEA, 91191 Gif sur Yvette, France
| | - J Dubois
- INSERM U992, CEA/DRF/I2BM/Neurospin/UNICOG, Gif-sur-Yvette, France
- Paris Saclay University, Paris-Sud University, Gif-sur-Yvette, France
| | - M Labidurie
- INSERM U1129, Paris, France
- Paris Descartes University, Sorbonne Paris Cité, Paris, France
- CEA, 91191 Gif sur Yvette, France
| | - A Duval
- INSERM U1129, Paris, France
- Paris Descartes University, Sorbonne Paris Cité, Paris, France
- CEA, 91191 Gif sur Yvette, France
- Neurospin, UNIACT, CEA, Gif sur Yvette, France
| | - A Manresa
- Laboratory of Psychology and Neurosciences (LPN) (EA 47000), Rouen University, Rouen, France
| | - J -F Magny
- Neonatal Intensive Care Unit, AP-HP, Necker-Enfants Malades Hospital, Paris, France
| | - S Hovhannisyan
- Neonatal Intensive Care Unit, AP-HP, Necker-Enfants Malades Hospital, Paris, France
| | - M Mokhtari
- Neonatal Intensive Care Unit, AP-HP, Bicetre Hospital, Kremlin-Bicetre, France
| | - L Ouss
- Department of Pediatric Neurology, AP-HP, Necker-Enfants Malades Hospital, Paris, France
| | - A Boissel
- Laboratory of Psychology and Neurosciences (LPN) (EA 47000), Rouen University, Rouen, France
| | - L Hertz-Pannier
- INSERM U1129, Paris, France
- Paris Descartes University, Sorbonne Paris Cité, Paris, France
- CEA, 91191 Gif sur Yvette, France
- Neurospin, UNIACT, CEA, Gif sur Yvette, France
| | - M Sintsov
- Laboratory of Neurobiology, Kazan Federal University, Kazan, Russia
| | - M Minlebaev
- Laboratory of Neurobiology, Kazan Federal University, Kazan, Russia
- INSERM U901/ INMED, Aix-Marseille University, Marseille, France
| | - R Khazipov
- Laboratory of Neurobiology, Kazan Federal University, Kazan, Russia
- INSERM U901/ INMED, Aix-Marseille University, Marseille, France
| | - C Chiron
- INSERM U1129, Paris, France
- Paris Descartes University, Sorbonne Paris Cité, Paris, France
- CEA, 91191 Gif sur Yvette, France
| |
Collapse
|
29
|
Ahtola E, Stjerna S, Stevenson N, Vanhatalo S. Use of eye tracking improves the detection of evoked responses to complex visual stimuli during EEG in infants. Clin Neurophysiol Pract 2017; 2:81-90. [PMID: 30214977 PMCID: PMC6123848 DOI: 10.1016/j.cnp.2017.03.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2016] [Revised: 01/04/2017] [Accepted: 03/03/2017] [Indexed: 12/17/2022] Open
Abstract
OBJECTIVE To improve the reliability of detecting EEG responses evoked by complex visual stimuli to the level required for clinical use by integrating an eye tracker to the EEG setup and optimizing the analysis protocol. METHODS Infants were presented with continuous orientation reversal (OR), global form (GF), and global motion (GM) stimuli. Eye tracking was used to control stimulus presentation and exclude epochs with disoriented gaze. The spectral responses were estimated from 13 postcentral EEG channels using a circular variant of Hotelling's T2 test statistic. RESULTS Among 39 healthy infants, statistically significant (p < 0.01) responses to OR/GF/GM stimuli were found from 92%/100%/95% recordings, respectively. The specificity test of the detection algorithm, using non-stimulated baseline EEG, did not yield any false-positive findings. Taken together, this yields 15% improvement on average in the detection performance compared to that in the current literature. CONCLUSIONS Changes to the test protocol and incorporation of the eye tracking information improves the detection of responses to complex visual stimuli in infants. SIGNIFICANCE This work presents a test protocol suitable for use in a clinical environment at a level of reliability that allows individual diagnostics.
Collapse
Key Words
- AUC, area under receiver operating characteristic
- Assessment of cortical visual functions
- EEG
- ERVS, EEG response to visual stimulus
- Evoked visual response
- Eye tracking
- FDR, false discovery rate (correction)
- FPR, false-positive detection rate
- GF, global form
- GM, global motion
- IQR, interquartile range
- Infant
- OR, orientation reversal
- TNR, true-negative detection rate
- TPR, true-positive detection rate
- Visual stimulation
Collapse
Affiliation(s)
- Eero Ahtola
- Department of Children’s Clinical Neurophysiology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
- Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
| | - Susanna Stjerna
- Department of Children’s Clinical Neurophysiology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Nathan Stevenson
- Department of Children’s Clinical Neurophysiology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| | - Sampsa Vanhatalo
- Department of Children’s Clinical Neurophysiology, Helsinki University Hospital and University of Helsinki, Helsinki, Finland
| |
Collapse
|
30
|
Xie W, Richards JE. The Relation between Infant Covert Orienting, Sustained Attention and Brain Activity. Brain Topogr 2017; 30:198-219. [PMID: 27416932 PMCID: PMC5237418 DOI: 10.1007/s10548-016-0505-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2016] [Accepted: 06/29/2016] [Indexed: 02/07/2023]
Abstract
This study used measures of event-related potentials (ERPs) and cortical source analysis to examine the effect of covert orienting and sustained attention on 3- and 4.5-month-old infants' brain activity in a spatial cueing paradigm. Cortical source analysis was conducted with current density reconstruction using realistic head models created from age-appropriate infant MRIs. The validity effect was found in the P1 ERP component that was greater for valid than neutral trials in the electrodes contralateral to the visual targets when the stimulus onset asynchrony (SOA) was short. Cortical source analysis revealed greater current density amplitude around the P1 peak latency in the contralateral inferior occipital and ventral temporal regions for valid than neutral and invalid trials. The processing cost effect was found in the N1 ERP component that was greater for neutral than invalid trials in the short SOA condition. This processing cost effect was also shown in the current density amplitude around the N1 peak latency in the contralateral inferior and middle occipital and middle and superior temporal regions. Infant sustained attention was found to modulate infants' brain responses in covert orienting by enhancing the P1 ERP responses and current density amplitude in their cortical sources during sustained attention. These findings suggest that the neural mechanisms that underpin covert orienting already exist in 3- to 4.5-month-old, and they could be facilitated by infant sustained attention.
Collapse
Affiliation(s)
- Wanze Xie
- Department of Psychology, and Institute for Mind and Brain, University of South Carolina, Columbia, SC, 29208, USA.
| | - John E Richards
- Department of Psychology, and Institute for Mind and Brain, University of South Carolina, Columbia, SC, 29208, USA
| |
Collapse
|
31
|
Pursiainen S, Lew S, Wolters CH. Forward and inverse effects of the complete electrode model in neonatal EEG. J Neurophysiol 2016; 117:876-884. [PMID: 27852731 PMCID: PMC5338621 DOI: 10.1152/jn.00427.2016] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2016] [Accepted: 11/10/2016] [Indexed: 11/24/2022] Open
Abstract
The effect of the complete electrode model on electroencephalography forward and inverse computations is explored. A realistic neonatal head model, including a skull structure with fontanels and sutures, is used. The electrode and skull modeling differences are analyzed and compared with each other. The results suggest that the complete electrode model can be considered as an integral part of the outer head model. To achieve optimal source localization results, accurate electrode modeling might be necessary. This paper investigates finite element method-based modeling in the context of neonatal electroencephalography (EEG). In particular, the focus lies on electrode boundary conditions. We compare the complete electrode model (CEM) with the point electrode model (PEM), which is the current standard in EEG. In the CEM, the voltage experienced by an electrode is modeled more realistically as the integral average of the potential distribution over its contact surface, whereas the PEM relies on a point value. Consequently, the CEM takes into account the subelectrode shunting currents, which are absent in the PEM. In this study, we aim to find out how the electrode voltage predicted by these two models differ, if standard size electrodes are attached to a head of a neonate. Additionally, we study voltages and voltage variation on electrode surfaces with two source locations: 1) next to the C6 electrode and 2) directly under the Fz electrode and the frontal fontanel. A realistic model of a neonatal head, including a skull with fontanels and sutures, is used. Based on the results, the forward simulation differences between CEM and PEM are in general small, but significant outliers can occur in the vicinity of the electrodes. The CEM can be considered as an integral part of the outer head model. The outcome of this study helps understanding volume conduction of neonatal EEG, since it enlightens the role of advanced skull and electrode modeling in forward and inverse computations. NEW & NOTEWORTHY The effect of the complete electrode model on electroencephalography forward and inverse computations is explored. A realistic neonatal head model, including a skull structure with fontanels and sutures, is used. The electrode and skull modeling differences are analyzed and compared with each other. The results suggest that the complete electrode model can be considered as an integral part of the outer head model. To achieve optimal source localization results, accurate electrode modeling might be necessary.
Collapse
Affiliation(s)
- S Pursiainen
- Department of Mathematics, Tampere University of Technology, Tampere, Finland;
| | - S Lew
- Newborn Medicine in the Boston Children's Hospital, Boston, Massachusetts.,Department of Engineering, Olivet Nazarene University, Bourbonnais, Illinois; and
| | - C H Wolters
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
| |
Collapse
|
32
|
Azizollahi H, Aarabi A, Wallois F. Effects of uncertainty in head tissue conductivity and complexity on EEG forward modeling in neonates. Hum Brain Mapp 2016; 37:3604-22. [PMID: 27238749 DOI: 10.1002/hbm.23263] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2016] [Revised: 05/04/2016] [Accepted: 05/09/2016] [Indexed: 11/09/2022] Open
Abstract
In this study, we investigated the impact of uncertainty in head tissue conductivities and inherent geometrical complexities including fontanels in neonates. Based on MR and CT coregistered images, we created a realistic neonatal head model consisting of scalp, skull, fontanels, cerebrospinal fluid (CSF), gray matter (GM), and white matter (WM). Using computer simulations, we investigated the effects of exclusion of CSF and fontanels, discrimination between GM and WM, and uncertainty in conductivity of neonatal head tissues on EEG forward modeling. We found that exclusion of CSF from the head model induced the strongest widespread effect on the EEG forward solution. Discrimination between GM and white matter also induced a strong widespread effect, but which was less intense than that of CSF exclusion. The results also showed that exclusion of the fontanels from the neonatal head model locally affected areas beneath the fontanels, but this effect was much less pronounced than those of exclusion of CSF and GM/WM discrimination. Changes in GM/WM conductivities by 25% with respect to reference values induced considerable effects in EEG forward solution, but this effect was more pronounced for GM conductivity. Similarly, changes in skull conductivity induced effects in the EEG forward modeling in areas covered by the cranial bones. The least intense effect on EEG was caused by changes in conductivity of the fontanels. Our findings clearly emphasize the impact of uncertainty in conductivity and deficiencies in head tissue compartments on modeling research and localization of brain electrical activity in neonates. Hum Brain Mapp 37:3604-3622, 2016. © 2016 Wiley Periodicals, Inc.
Collapse
Affiliation(s)
- Hamed Azizollahi
- GRAMFC, Inserm U1105, University Research Center, Department of Medicine, Amiens University Hospital, Amiens, France
| | - Ardalan Aarabi
- GRAMFC, Inserm U1105, University Research Center, Department of Medicine, Amiens University Hospital, Amiens, France
| | - Fabrice Wallois
- GRAMFC, Inserm U1105, University Research Center, Department of Medicine, Amiens University Hospital, Amiens, France.,EFSN Pediatric (Pediatric Nervous System Functional Investigation Unit), Department of Pediatrics, CHU AMIENS-SITE SUD, Amiens, France
| |
Collapse
|
33
|
Koolen N, Dereymaeker A, Räsänen O, Jansen K, Vervisch J, Matic V, Naulaers G, De Vos M, Van Huffel S, Vanhatalo S. Early development of synchrony in cortical activations in the human. Neuroscience 2016; 322:298-307. [PMID: 26876605 PMCID: PMC4819727 DOI: 10.1016/j.neuroscience.2016.02.017] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2015] [Revised: 02/05/2016] [Accepted: 02/08/2016] [Indexed: 11/26/2022]
Abstract
We study the early development of cortical activations synchrony index (ASI). Cortical activations become increasingly synchronized during the last trimester. Interhemispheric synchrony increases more than intrahemispheric synchrony. Our EEG metric ASI can be directly translated to experimental animal studies. ASI holds promise as an early functional biomarker of brain networks.
Early intermittent cortical activity is thought to play a crucial role in the growth of neuronal network development, and large scale brain networks are known to provide the basis for higher brain functions. Yet, the early development of the large scale synchrony in cortical activations is unknown. Here, we tested the hypothesis that the early intermittent cortical activations seen in the human scalp EEG show a clear developmental course during the last trimester of pregnancy, the period of intensive growth of cortico-cortical connections. We recorded scalp EEG from altogether 22 premature infants at post-menstrual age between 30 and 44 weeks, and the early cortical synchrony was quantified using recently introduced activation synchrony index (ASI). The developmental correlations of ASI were computed for individual EEG signals as well as anatomically and mathematically defined spatial subgroups. We report two main findings. First, we observed a robust and statistically significant increase in ASI in all cortical areas. Second, there were significant spatial gradients in the synchrony in fronto-occipital and left-to-right directions. These findings provide evidence that early cortical activity is increasingly synchronized across the neocortex. The ASI-based metrics introduced in our work allow direct translational comparison to in vivo animal models, as well as hold promise for implementation as a functional developmental biomarker in future research on human neonates.
Collapse
Affiliation(s)
- N Koolen
- Division STADIUS, Department of Electrical Engineering (ESAT), University of Leuven, Leuven, Belgium; iMinds-KU Leuven Medical IT Department, Leuven, Belgium.
| | - A Dereymaeker
- Department of Development and Regeneration, Neonatology, University of Leuven, Leuven, Belgium
| | - O Räsänen
- Department of Signal Processing and Acoustics, Aalto University, Espoo, Finland
| | - K Jansen
- Department of Development and Regeneration, Neonatology, University of Leuven, Leuven, Belgium
| | - J Vervisch
- Department of Development and Regeneration, Neonatology, University of Leuven, Leuven, Belgium
| | - V Matic
- Division STADIUS, Department of Electrical Engineering (ESAT), University of Leuven, Leuven, Belgium; iMinds-KU Leuven Medical IT Department, Leuven, Belgium
| | - G Naulaers
- Department of Development and Regeneration, Neonatology, University of Leuven, Leuven, Belgium
| | - M De Vos
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK
| | - S Van Huffel
- Division STADIUS, Department of Electrical Engineering (ESAT), University of Leuven, Leuven, Belgium; iMinds-KU Leuven Medical IT Department, Leuven, Belgium
| | - S Vanhatalo
- Department of Children's Clinical Neurophysiology, HUS Medical Imaging Center and Children's Hospital, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland
| |
Collapse
|
34
|
Vanhatalo S, Fransson P. Advanced EEG and MRI Measurements to Study the Functional Development of the Newborn Brain. ACTA ACUST UNITED AC 2016. [DOI: 10.1007/978-1-4939-3014-2_4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
|
35
|
Tokariev A, Vanhatalo S, Palva JM. Analysis of infant cortical synchrony is constrained by the number of recording electrodes and the recording montage. Clin Neurophysiol 2016; 127:310-323. [DOI: 10.1016/j.clinph.2015.04.291] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2014] [Revised: 03/18/2015] [Accepted: 04/24/2015] [Indexed: 12/11/2022]
|
36
|
Cruz-Garza JG, Hernandez ZR, Tse T, Caducoy E, Abibullaev B, Contreras-Vidal JL. A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants. J Vis Exp 2015. [PMID: 26485409 PMCID: PMC4692634 DOI: 10.3791/53406] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Understanding typical and atypical development remains one of the fundamental questions in developmental human neuroscience. Traditionally, experimental paradigms and analysis tools have been limited to constrained laboratory tasks and contexts due to technical limitations imposed by the available set of measuring and analysis techniques and the age of the subjects. These limitations severely limit the study of developmental neural dynamics and associated neural networks engaged in cognition, perception and action in infants performing “in action and in context”. This protocol presents a novel approach to study infants and young children as they freely organize their own behavior, and its consequences in a complex, partly unpredictable and highly dynamic environment. The proposed methodology integrates synchronized high-density active scalp electroencephalography (EEG), inertial measurement units (IMUs), video recording and behavioral analysis to capture brain activity and movement non-invasively in freely-behaving infants. This setup allows for the study of neural network dynamics in the developing brain, in action and context, as these networks are recruited during goal-oriented, exploration and social interaction tasks.
Collapse
Affiliation(s)
- Jesus G Cruz-Garza
- Laboratory for Noninvasive Brain-Machine Interface Systems, Department of Electrical and Computer Engineering, University of Houston;
| | - Zachery R Hernandez
- Laboratory for Noninvasive Brain-Machine Interface Systems, Department of Electrical and Computer Engineering, University of Houston
| | - Teresa Tse
- Laboratory for Noninvasive Brain-Machine Interface Systems, Department of Electrical and Computer Engineering, University of Houston; Department of Biomedical Engineering, University of Houston; Department of Biology and Biochemistry, University of Houston
| | - Eunice Caducoy
- Laboratory for Noninvasive Brain-Machine Interface Systems, Department of Electrical and Computer Engineering, University of Houston; Department of Biology and Biochemistry, University of Houston
| | - Berdakh Abibullaev
- Laboratory for Noninvasive Brain-Machine Interface Systems, Department of Electrical and Computer Engineering, University of Houston
| | - Jose L Contreras-Vidal
- Laboratory for Noninvasive Brain-Machine Interface Systems, Department of Electrical and Computer Engineering, University of Houston; Department of Biomedical Engineering, University of Houston
| |
Collapse
|
37
|
Tokariev A, Videman M, Palva JM, Vanhatalo S. Functional Brain Connectivity Develops Rapidly Around Term Age and Changes Between Vigilance States in the Human Newborn. Cereb Cortex 2015; 26:4540-4550. [DOI: 10.1093/cercor/bhv219] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
|
38
|
Gargiulo P, Belfiore P, Friðgeirsson E, Vanhatalo S, Ramon C. The effect of fontanel on scalp EEG potentials in the neonate. Clin Neurophysiol 2015; 126:1703-10. [DOI: 10.1016/j.clinph.2014.12.002] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2014] [Revised: 11/05/2014] [Accepted: 12/04/2014] [Indexed: 10/24/2022]
|
39
|
Structural damage in early preterm brain changes the electric resting state networks. Neuroimage 2015; 120:266-73. [PMID: 26163804 DOI: 10.1016/j.neuroimage.2015.06.091] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2014] [Revised: 04/22/2015] [Accepted: 06/30/2015] [Indexed: 01/24/2023] Open
Abstract
A robust functional bimodality is found in the long-range spatial correlations of newborn cortical activity, and it likely provides the developmentally crucial functional coordination during the initial growth of brain networks. This study searched for possible acute effects on this large scale cortical coordination after acute structural brain lesion in early preterm infants. EEG recordings were obtained from preterm infants without (n=11) and with (n=6) haemorrhagic brain lesion detected in their routine ultrasound exam. The spatial cortical correlations in band-specific amplitudes were examined within two amplitude regimes, high and low amplitude periods, respectively. Technical validation of our analytical approach showed that bimodality of this kind is a genuine physiological characteristic of each brain network. It was not observed in datasets created from uniform noise, neither is it found between randomly paired signals. Hence, the observed bimodality arises from specific interactions between cortical regions. We found that significant long-range amplitude correlations are found in most signal pairs in both groups at high amplitudes, but the correlations are generally weaker in newborns with brain lesions. The group difference is larger during high mode, however the difference did not have any statistically apparent topology. Graph theoretical analysis confirmed a significantly larger weight dispersion in the newborns with brain lesion. Comparison of graph measures to a child's performance at two years showed that lower clustering coefficient and weight dispersion were both correlated to better neurodevelopmental outcomes. Our findings suggest that the common preterm brain haemorrhage causes diffuse changes in the functional long-range cortical correlations. It has been recently recognized that the high mode network activity is crucial for early brain development. The present observations may hence offer a mechanistic link between early lesion and the later emergence of complex neurocognitive sequelae.
Collapse
|