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H. Gerry Taylor

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4 papers

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YNICL Journal 2022 Journal Article

Multimodal classification of extremely preterm and term adolescents using the fusiform gyrus: A machine learning approach

Connor Grannis
Andy Hung
Roberto C. French
Whitney I. Mattson
Xiaoxue Fu
Kristen R. Hoskinson
H. Gerry Taylor
Eric E. Nelson

OBJECTIVE: Extremely preterm birth has been associated with atypical visual and neural processing of faces, as well as differences in gray matter structure in visual processing areas relative to full-term peers. In particular, the right fusiform gyrus, a core visual area involved in face processing, has been shown to have structural and functional differences between preterm and full-term individuals from childhood through early adulthood. The current study used multiple neuroimaging modalities to build a machine learning model based on the right fusiform gyrus to classify extremely preterm birth status. METHOD: Extremely preterm adolescents (n = 20) and full-term peers (n = 24) underwent structural and functional magnetic resonance imaging. Group differences in gray matter density, measured via voxel-based morphometry (VBM), and blood-oxygen level-dependent (BOLD) response to face stimuli were explored within the right fusiform. Using group difference clusters as seed regions, analyses investigating outgoing white matter streamlines, regional homogeneity, and functional connectivity during a face processing task and at rest were conducted. A data driven approach was utilized to determine the most discriminative combination of these features within a linear support vector machine classifier. RESULTS: Group differences in two partially overlapping clusters emerged: one from the VBM analysis showing less density in the extremely preterm cohort and one from BOLD response to faces showing greater activation in the extremely preterm relative to full-term youth. A classifier fit to the data from the cluster identified in the BOLD analysis achieved an accuracy score of 88.64% when BOLD, gray matter density, regional homogeneity, and functional connectivity during the task and at rest were included. A classifier fit to the data from the cluster identified in the VBM analysis achieved an accuracy score of 95.45% when only BOLD, gray matter density, and regional homogeneity were included. CONCLUSION: Consistent with previous findings, we observed neural differences in extremely preterm youth in an area that plays an important role in face processing. Multimodal analyses revealed differences in structure, function, and connectivity that, when taken together, accurately distinguish extremely preterm from full-term born youth. Our findings suggest a compensatory role of the fusiform where less dense gray matter is countered by increased local BOLD signal. Importantly, sub-threshold differences in many modalities within the same region were informative when distinguishing between extremely preterm and full-term youth.

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YNICL Journal 2022 Journal Article

Surface-based abnormalities of the executive frontostriatial circuit in pediatric TBI

Kaitlyn M. Greer
Aubretia Snyder
Chase Junge
Madeleine Reading
Sierra Jarvis
Chad Squires
Erin D. Bigler
Karteek Popuri

Childhood traumatic brain injury (TBI) is one of the most common causes of acquired disability and has significant implications for executive functions (EF), such as impaired attention, planning, and initiation that are predictive of everyday functioning. Evidence has suggested attentional features of executive functioning require behavioral flexibility that is dependent on frontostriatial circuitry. The purpose of this study was to evaluate surface-based deformation of a specific frontostriatial circuit in pediatric TBI and its role in EF. Regions of interest included: the dorsolateral prefrontal cortex (DLPFC), caudate nucleus, globus pallidus, and the mediodorsal nucleus of the thalamus (MD). T1-weighted magnetic resonance images were obtained in a sample of children ages 8–13 with complicated mild, moderate, or severe TBI (n = 32) and a group of comparison children with orthopedic injury (OI; n = 30). Brain regions were characterized using high-dimensional surface-based brain mapping procedures. Aspects of EF were assessed using select subtests from the Test of Everyday Attention for Children (TEA-Ch). General linear models tested group and hemisphere differences in DLPFC cortical thickness and subcortical shape of deep-brain regions; Pearson correlations tested relationships with EF. Main effects for group were found in both cortical thickness of the DLPFC (F1, 60 = 4. 30, p = 0. 042) and MD mean deformation (F1, 60 = 6. 50, p = 0. 01) all with lower values in the TBI group. Statistical surface maps revealed significant inward deformation on ventral-medial aspects of the caudate in TBI relative to OI, but null results in the globus pallidus. No significant relationships between EF and any region of interest were observed. Overall, findings revealed abnormalities in multiple aspects of a frontostriatial circuit in pediatric TBI, which may reflect broader pathophysiological mechanisms. Increased consideration for the role of deep-brain structures in pediatric TBI can aid in the clinical characterization of anticipated long-term developmental effects of these individuals.

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YNICL Journal 2020 Journal Article

Post-acute white matter microstructure predicts post-acute and chronic post-concussive symptom severity following mild traumatic brain injury in children

Ashley L. Ware
Ayushi Shukla
Naomi J. Goodrich-Hunsaker
Catherine Lebel
Elisabeth A. Wilde
Tracy J. Abildskov
Erin D. Bigler
Daniel M. Cohen

INTRODUCTION: Mild traumatic brain injury (TBI) is a global public health concern that affects millions of children annually. Mild TBI tends to result in subtle and diffuse alterations in brain tissue, which challenges accurate clinical detection and prognostication. Diffusion tensor imaging (DTI) holds promise as a diagnostic and prognostic tool, but little research has examined DTI in post-acute mild TBI. The current study compared post-acute white matter microstructure in children with mild TBI versus those with mild orthopedic injury (OI), and examined whether post-acute DTI metrics can predict post-acute and chronic post-concussive symptoms (PCS). MATERIALS AND METHODS: Children aged 8-16.99 years with mild TBI (n = 132) or OI (n = 69) were recruited at emergency department visits to two children's hospitals, during which parents rated children's pre-injury symptoms retrospectively. Children completed a post-acute (<2 weeks post-injury) assessment, which included a 3T MRI, and 3- and 6-month post-injury assessments. Parents and children rated PCS at each assessment. Mean diffusivity (MD) and fractional anisotropy (FA) were derived from diffusion-weighted MRI using Automatic Fiber Quantification software. Multiple multivariable linear and negative binomial regression models were used to test study aims, with False Discovery Rate (FDR) correction for multiple comparisons. RESULTS: No significant group differences were found in any of the 20 white matter tracts after FDR correction. DTI metrics varied by age and sex, and site was a significant covariate. No interactions involving group, age, and sex were significant. DTI metrics in several tracts robustly predicted PCS ratings at 3- and 6-months post-injury, but only corpus callosum genu MD was significantly associated with post-acute PCS after FDR correction. Significant group by DTI metric interactions on chronic PCS ratings indicated that left cingulum hippocampus and thalamic radiation MD was positively associated with 3-month PCS in the OI group, but not in the mild TBI group. CONCLUSIONS: Post-acute white matter microstructure did not differ for children with mild TBI versus OI after correcting for multiple comparisons, but was predictive of post-acute and chronic PCS in both injury groups. These findings support the potential prognostic utility of this advanced DTI technique.

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YNICL Journal 2018 Journal Article

Decreased functional connectivity in the fronto-parietal network in children with mood disorders compared to children with dyslexia during rest: An fMRI study

Tzipi Horowitz-Kraus
Mackenzie Woodburn
Akila Rajagopal
Amelia L. Versace
Robert A. Kowatch
Michele A. Bertocci
Genna Bebko
Jorge R.C. Almeida

Background: The DSM-5 separates the diagnostic criteria for mood and behavioral disorders. Both types of disorders share neurocognitive deficits of executive function and reading difficulties in childhood. Children with dyslexia also have executive function deficits, revealing a role of executive function circuitry in reading. The aim of the current study is to determine whether there is a significant relationship of functional connectivity within the fronto-parietal and cingulo-opercular cognitive control networks to reading measures for children with mood disorders, behavioral disorders, dyslexia, and healthy controls (HC). Method: Behavioral reading measures of phonological awareness, decoding, and orthography were collected. Resting state fMRI data were collected, preprocessed, and then analyzed for functional connectivity. Differences in the reading measures were tested for significance among the groups. Global efficiency (GE) measures were also tested for correlation with reading measures in 40 children with various disorders and 17 HCs. Results: Significant differences were found between the four groups on all reading measures. Relative to HCs and children with mood disorders or behavior disorders, children with dyslexia as a primary diagnosis scored significantly lower on all three reading measures. Children with mood disorders scored significantly lower than controls on a test of phonological awareness. Phonological awareness deficits correlated with reduced resting state functional connectivity MRI (rsfcMRI) in the cingulo-opercular network for children with dyslexia. A significant difference was also found in fronto-parietal global efficiency in children with mood disorders relative to the other three groups. We also found a significant difference in cingulo-opercular global efficiency in children with mood disorders relative to the Dyslexia and Control groups. However, none of these differences correlate significantly with reading measures. Conclusions/significance: Reading difficulties involve abnormalities in different cognitive control networks in children with dyslexia compared to children with mood disorders. Findings of the current study suggest increased functional connectivity of one cognitive control network may compensate for reduced functional connectivity in the other network in children with mood disorders. These findings provide guidance to clinical professionals for design of interventions tailored for children suffering from reading difficulties originating from different pathologies.

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