Le travail realise au cours de cette these a porte sur l'etude de la connectivite cerebrale f... more Le travail realise au cours de cette these a porte sur l'etude de la connectivite cerebrale fonctionnelle des reseaux epileptiques chez des enfants presentant des epilepsies avec pointes centro temporales (EPCT), et sur l'organisation fonctionnelle des reseaux de repos chez des nouveaux-nes sains et des prematures. Les patients epileptiques presentent une desorganisation fonctionnelle cerebrale qui participe a une alteration des reseaux de repos selon la gamme de frequence des activites cerebrales. Cette desorganisation fonctionnelle bien que plus importante durant les periodes de pointes epileptiques intercritiques est aussi observee dans les periodes sans pointes intercritiques. Les regions impliquees dans la genese et la propagation des pointes intercritiques englobent la region centrale (zone epileptiques), la region rolandique et l'aire premotrice. Chez le nouveau-ne et le premature la connectivite fonctionnelle est majeure dans les regions frontales et posterieures. Les activites endogenes theta temporales du premature presentent une connectivite restreinte aux seules regions temporales. Chez le nouveau-ne a terme l'organisation fonctionnelle est similaire avec une forte connectivite dans les regions frontales temporales et posterieures dans le sommeil calme et le sommeil agite
ABSTRACT Background / Purpose: Benign childhood epilepsy with centrotemporal spikes (BCECTS) is t... more ABSTRACT Background / Purpose: Benign childhood epilepsy with centrotemporal spikes (BCECTS) is the most common idiopathic epileptic syndrome with prevalence of approximately 15% in children with seizures. Cognitive impairments in memory and language are often associated with BCECTS. Functional connectivity analysis may provide key information to better understand the functional interactions of neural dynamics in patients with BCECTS. Main conclusion: BCECTS patients were characterized with altered resting state brain dynamics and impaired functional connectivity.
bioRxiv (Cold Spring Harbor Laboratory), Apr 14, 2022
To better understand complex human phenotypes, large-scale studies have increasingly collected mu... more To better understand complex human phenotypes, large-scale studies have increasingly collected multiple data modalities across domains such as imaging, mobile health, and physical activity. The properties of each data type often differ substantially and require either separate analyses or extensive processing to obtain comparable features for a combined analysis. Multimodal data fusion enables certain analyses on matrix-valued and vector-valued data, but it generally cannot integrate modalities of different dimensions and data structures. For a single data modality, multivariate distance matrix regression provides a distance-based framework for regression accommodating a wide range of data types. However, no distancebased method exists to handle multiple complementary types of data. We propose a novel distance-based regression model, which we refer to as Similarity-based Multimodal Regression (SiMMR), that enables simultaneous regression of multiple modalities through their distance profiles. We demonstrate through simulation, imaging studies, and longitudinal mobile health analyses that our proposed method can detect associations in multimodal data of differing properties and dimensionalities, even with modest sample sizes. We perform experiments to evaluate several different test statistics and provide recommendations for applying our method across a broad range of scenarios.
bioRxiv (Cold Spring Harbor Laboratory), Sep 11, 2020
Many key findings in neuroimaging studies involve similarities between brain maps, but statistica... more Many key findings in neuroimaging studies involve similarities between brain maps, but statistical methods used to measure these findings have varied. Current state-of-the-art methods involve comparing observed group-level brain maps (after averaging intensities at each image location across multiple subjects) against spatial null models of these group-level maps. However, these methods typically make strong and potentially unrealistic statistical assumptions, such as covariance stationarity. To address these issues, in this paper we propose using subject-level data and a classical permutation testing framework to test and assess similarities between brain maps. Our method is comparable to traditional permutation tests in that it involves randomly permuting subjects to generate a null distribution of intermodal correspondence statistics, which we compare to an observed statistic to estimate a p-value. We apply and compare our method in simulated and real neuroimaging data from the Philadelphia Neurodevelopmental Cohort. We show that our method performs well for detecting relationships between modalities known to be strongly related (cortical thickness and sulcal depth), and it is conservative when an association would not be expected (cortical thickness and activation on the n-back working memory task). Notably, our method is the most flexible and reliable for localizing intermodal relationships within subregions of the brain and allows for generalizable statistical inference.
bioRxiv (Cold Spring Harbor Laboratory), Aug 15, 2022
Animal studies of neurodevelopmental plasticity have shown that intrinsic brain activity evolves ... more Animal studies of neurodevelopmental plasticity have shown that intrinsic brain activity evolves from high amplitude and globally synchronized to suppressed and sparse as plasticity declines and the cortex matures. Leveraging resting-state functional MRI data from 1033 individuals (8-23 years), we reveal that this stereotyped refinement of intrinsic activity occurs during human development and provides evidence for a cortical gradient of neurodevelopmental plasticity during childhood and adolescence. Specifically, we demonstrate that declines in the amplitude of intrinsic activity are initiated heterochronously across regions, coupled to the maturation of a plasticity-restricting structural feature, and temporally staggered along a hierarchical sensorimotor-association axis from ages 8 to 18. Youth from disadvantaged environments exhibit reduced intrinsic activity in regions further up the sensorimotor-association axis, suggestive of a reduced level of plasticity in late-maturing cortices. Our results uncover a hierarchical axis of neurodevelopment and offer insight into the temporal sequence of protracted neurodevelopmental plasticity in humans.
Prior work has shown that there is substantial interindividual variation in the spatial distribut... more Prior work has shown that there is substantial interindividual variation in the spatial distribution of functional networks across the cerebral cortex, or functional topography. However, it remains unknown whether there are sex differences in the topography of individualized networks in youth. Here, we leveraged an advanced machine learning method (sparsity-regularized non-negative matrix factorization) to define individualized functional networks in 693 youth (ages 8 to 23 y) who underwent functional MRI as part of the Philadelphia Neurodevelopmental Cohort. Multivariate pattern analysis using support vector machines classified participant sex based on functional topography with 82.9% accuracy ( P < 0.0001). Brain regions most effective in classifying participant sex belonged to association networks, including the ventral attention, default mode, and frontoparietal networks. Mass univariate analyses using generalized additive models with penalized splines provided convergent res...
ABSTRACTThe Brain Imaging Data Structure (BIDS) is a specification accompanied by a software ecos... more ABSTRACTThe Brain Imaging Data Structure (BIDS) is a specification accompanied by a software ecosystem that was designed to create reproducible and automated workflows for processing neuroimaging data. BIDS Apps flexibly build workflows based on the metadata detected in a dataset. However, even BIDS valid metadata can include incorrect values or omissions that result in inconsistent processing across sessions. Additionally, in large-scale, heterogeneous neuroimaging datasets, hidden variability in metadata is difficult to detect and classify. To address these challenges, we created a Python-based software package titled “Curation of BIDS” (CuBIDS), which provides an intuitive workflow that helps users validate and manage the curation of their neuroimaging datasets. CuBIDS includes a robust implementation of BIDS validation that scales to large samples and incorporates DataLad––a version control software package for data––to ensure reproducibility and provenance tracking throughout t...
Task force 2.2 of the Open Science Initiative for Perfusion Imaging (OSIPI) is developing a libra... more Task force 2.2 of the Open Science Initiative for Perfusion Imaging (OSIPI) is developing a library of open-source functions, and scripts for Arterial Spin Labeled (ASL) perfusion imaging preprocessing and analysis. This is aimed for developers of ASL perfusion methods looking for specific functionalities or development templates, or who want to share their own in-house code with others. The collected source code will be organized and documented so as to support the open library development.
With the increasing availability of neuroimaging data from multiple modalities—each providing a d... more With the increasing availability of neuroimaging data from multiple modalities—each providing a different lens through which to study brain structure or function—new techniques for comparing, integrating, and interpreting information within and across modalities have emerged. Recent developments include hypothesis tests of associations between neuroimaging modalities, which can be used to determine the statistical significance of intermodal associations either throughout the entire brain or within anatomical subregions or functional networks. While these methods provide a crucial foundation for inference on intermodal relationships, they cannot be used to answer questions about where in the brain these associations are most pronounced. In this paper, we introduce a new method, called CLEAN-R, that can be used both to test intermodal correspondence throughout the brain and also to localize this correspondence. Our method involves first adjusting for the underlying spatial autocorrela...
Le travail realise au cours de cette these a porte sur l'etude de la connectivite cerebrale f... more Le travail realise au cours de cette these a porte sur l'etude de la connectivite cerebrale fonctionnelle des reseaux epileptiques chez des enfants presentant des epilepsies avec pointes centro temporales (EPCT), et sur l'organisation fonctionnelle des reseaux de repos chez des nouveaux-nes sains et des prematures. Les patients epileptiques presentent une desorganisation fonctionnelle cerebrale qui participe a une alteration des reseaux de repos selon la gamme de frequence des activites cerebrales. Cette desorganisation fonctionnelle bien que plus importante durant les periodes de pointes epileptiques intercritiques est aussi observee dans les periodes sans pointes intercritiques. Les regions impliquees dans la genese et la propagation des pointes intercritiques englobent la region centrale (zone epileptiques), la region rolandique et l'aire premotrice. Chez le nouveau-ne et le premature la connectivite fonctionnelle est majeure dans les regions frontales et posterieures. Les activites endogenes theta temporales du premature presentent une connectivite restreinte aux seules regions temporales. Chez le nouveau-ne a terme l'organisation fonctionnelle est similaire avec une forte connectivite dans les regions frontales temporales et posterieures dans le sommeil calme et le sommeil agite
ABSTRACT Background / Purpose: Benign childhood epilepsy with centrotemporal spikes (BCECTS) is t... more ABSTRACT Background / Purpose: Benign childhood epilepsy with centrotemporal spikes (BCECTS) is the most common idiopathic epileptic syndrome with prevalence of approximately 15% in children with seizures. Cognitive impairments in memory and language are often associated with BCECTS. Functional connectivity analysis may provide key information to better understand the functional interactions of neural dynamics in patients with BCECTS. Main conclusion: BCECTS patients were characterized with altered resting state brain dynamics and impaired functional connectivity.
bioRxiv (Cold Spring Harbor Laboratory), Apr 14, 2022
To better understand complex human phenotypes, large-scale studies have increasingly collected mu... more To better understand complex human phenotypes, large-scale studies have increasingly collected multiple data modalities across domains such as imaging, mobile health, and physical activity. The properties of each data type often differ substantially and require either separate analyses or extensive processing to obtain comparable features for a combined analysis. Multimodal data fusion enables certain analyses on matrix-valued and vector-valued data, but it generally cannot integrate modalities of different dimensions and data structures. For a single data modality, multivariate distance matrix regression provides a distance-based framework for regression accommodating a wide range of data types. However, no distancebased method exists to handle multiple complementary types of data. We propose a novel distance-based regression model, which we refer to as Similarity-based Multimodal Regression (SiMMR), that enables simultaneous regression of multiple modalities through their distance profiles. We demonstrate through simulation, imaging studies, and longitudinal mobile health analyses that our proposed method can detect associations in multimodal data of differing properties and dimensionalities, even with modest sample sizes. We perform experiments to evaluate several different test statistics and provide recommendations for applying our method across a broad range of scenarios.
bioRxiv (Cold Spring Harbor Laboratory), Sep 11, 2020
Many key findings in neuroimaging studies involve similarities between brain maps, but statistica... more Many key findings in neuroimaging studies involve similarities between brain maps, but statistical methods used to measure these findings have varied. Current state-of-the-art methods involve comparing observed group-level brain maps (after averaging intensities at each image location across multiple subjects) against spatial null models of these group-level maps. However, these methods typically make strong and potentially unrealistic statistical assumptions, such as covariance stationarity. To address these issues, in this paper we propose using subject-level data and a classical permutation testing framework to test and assess similarities between brain maps. Our method is comparable to traditional permutation tests in that it involves randomly permuting subjects to generate a null distribution of intermodal correspondence statistics, which we compare to an observed statistic to estimate a p-value. We apply and compare our method in simulated and real neuroimaging data from the Philadelphia Neurodevelopmental Cohort. We show that our method performs well for detecting relationships between modalities known to be strongly related (cortical thickness and sulcal depth), and it is conservative when an association would not be expected (cortical thickness and activation on the n-back working memory task). Notably, our method is the most flexible and reliable for localizing intermodal relationships within subregions of the brain and allows for generalizable statistical inference.
bioRxiv (Cold Spring Harbor Laboratory), Aug 15, 2022
Animal studies of neurodevelopmental plasticity have shown that intrinsic brain activity evolves ... more Animal studies of neurodevelopmental plasticity have shown that intrinsic brain activity evolves from high amplitude and globally synchronized to suppressed and sparse as plasticity declines and the cortex matures. Leveraging resting-state functional MRI data from 1033 individuals (8-23 years), we reveal that this stereotyped refinement of intrinsic activity occurs during human development and provides evidence for a cortical gradient of neurodevelopmental plasticity during childhood and adolescence. Specifically, we demonstrate that declines in the amplitude of intrinsic activity are initiated heterochronously across regions, coupled to the maturation of a plasticity-restricting structural feature, and temporally staggered along a hierarchical sensorimotor-association axis from ages 8 to 18. Youth from disadvantaged environments exhibit reduced intrinsic activity in regions further up the sensorimotor-association axis, suggestive of a reduced level of plasticity in late-maturing cortices. Our results uncover a hierarchical axis of neurodevelopment and offer insight into the temporal sequence of protracted neurodevelopmental plasticity in humans.
Prior work has shown that there is substantial interindividual variation in the spatial distribut... more Prior work has shown that there is substantial interindividual variation in the spatial distribution of functional networks across the cerebral cortex, or functional topography. However, it remains unknown whether there are sex differences in the topography of individualized networks in youth. Here, we leveraged an advanced machine learning method (sparsity-regularized non-negative matrix factorization) to define individualized functional networks in 693 youth (ages 8 to 23 y) who underwent functional MRI as part of the Philadelphia Neurodevelopmental Cohort. Multivariate pattern analysis using support vector machines classified participant sex based on functional topography with 82.9% accuracy ( P < 0.0001). Brain regions most effective in classifying participant sex belonged to association networks, including the ventral attention, default mode, and frontoparietal networks. Mass univariate analyses using generalized additive models with penalized splines provided convergent res...
ABSTRACTThe Brain Imaging Data Structure (BIDS) is a specification accompanied by a software ecos... more ABSTRACTThe Brain Imaging Data Structure (BIDS) is a specification accompanied by a software ecosystem that was designed to create reproducible and automated workflows for processing neuroimaging data. BIDS Apps flexibly build workflows based on the metadata detected in a dataset. However, even BIDS valid metadata can include incorrect values or omissions that result in inconsistent processing across sessions. Additionally, in large-scale, heterogeneous neuroimaging datasets, hidden variability in metadata is difficult to detect and classify. To address these challenges, we created a Python-based software package titled “Curation of BIDS” (CuBIDS), which provides an intuitive workflow that helps users validate and manage the curation of their neuroimaging datasets. CuBIDS includes a robust implementation of BIDS validation that scales to large samples and incorporates DataLad––a version control software package for data––to ensure reproducibility and provenance tracking throughout t...
Task force 2.2 of the Open Science Initiative for Perfusion Imaging (OSIPI) is developing a libra... more Task force 2.2 of the Open Science Initiative for Perfusion Imaging (OSIPI) is developing a library of open-source functions, and scripts for Arterial Spin Labeled (ASL) perfusion imaging preprocessing and analysis. This is aimed for developers of ASL perfusion methods looking for specific functionalities or development templates, or who want to share their own in-house code with others. The collected source code will be organized and documented so as to support the open library development.
With the increasing availability of neuroimaging data from multiple modalities—each providing a d... more With the increasing availability of neuroimaging data from multiple modalities—each providing a different lens through which to study brain structure or function—new techniques for comparing, integrating, and interpreting information within and across modalities have emerged. Recent developments include hypothesis tests of associations between neuroimaging modalities, which can be used to determine the statistical significance of intermodal associations either throughout the entire brain or within anatomical subregions or functional networks. While these methods provide a crucial foundation for inference on intermodal relationships, they cannot be used to answer questions about where in the brain these associations are most pronounced. In this paper, we introduce a new method, called CLEAN-R, that can be used both to test intermodal correspondence throughout the brain and also to localize this correspondence. Our method involves first adjusting for the underlying spatial autocorrela...
Uploads
Papers by Azeez Adebimpe