Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Matthew Marzelli is active.

Publication


Featured researches published by Matthew Marzelli.


Diabetes Care | 2014

Alterations in White Matter Structure in Young Children With Type 1 Diabetes

Naama Barnea-Goraly; Mira Raman; Paul K. Mazaika; Matthew Marzelli; Tamara Hershey; Stuart A. Weinzimer; Tandy Aye; Bruce Buckingham; Nelly Mauras; Neil H. White; Larry A. Fox; Michael Tansey; Roy W. Beck; Katrina J. Ruedy; Craig Kollman; Peiyao Cheng; Allan L. Reiss

OBJECTIVE To investigate whether type 1 diabetes affects white matter (WM) structure in a large sample of young children. RESEARCH DESIGN AND METHODS Children (ages 4 to <10 years) with type 1 diabetes (n = 127) and age-matched nondiabetic control subjects (n = 67) had diffusion weighted magnetic resonance imaging scans in this multisite neuroimaging study. Participants with type 1 diabetes were assessed for HbA1c history and lifetime adverse events, and glucose levels were monitored using a continuous glucose monitor (CGM) device and standardized measures of cognition. RESULTS Between-group analysis showed that children with type 1 diabetes had significantly reduced axial diffusivity (AD) in widespread brain regions compared with control subjects. Within the type 1 diabetes group, earlier onset of diabetes was associated with increased radial diffusivity (RD) and longer duration was associated with reduced AD, reduced RD, and increased fractional anisotropy (FA). In addition, HbA1c values were significantly negatively associated with FA values and were positively associated with RD values in widespread brain regions. Significant associations of AD, RD, and FA were found for CGM measures of hyperglycemia and glucose variability but not for hypoglycemia. Finally, we observed a significant association between WM structure and cognitive ability in children with type 1 diabetes but not in control subjects. CONCLUSIONS These results suggest vulnerability of the developing brain in young children to effects of type 1 diabetes associated with chronic hyperglycemia and glucose variability.


Diabetes | 2014

Neuroanatomical Correlates of Dysglycemia in Young Children With Type 1 Diabetes

Matthew Marzelli; Paul K. Mazaika; Naama Barnea-Goraly; Tamara Hershey; Eva Tsalikian; William V. Tamborlane; Nelly Mauras; Neil H. White; Bruce Buckingham; Roy W. Beck; Katrina J. Ruedy; Craig Kollman; Peiyao Cheng; Allan L. Reiss

Studies of brain structure in type 1 diabetes (T1D) describe widespread neuroanatomical differences related to exposure to glycemic dysregulation in adults and adolescents. In this study, we investigate the neuroanatomical correlates of dysglycemia in very young children with early-onset T1D. Structural magnetic resonance images of the brain were acquired in 142 children with T1D and 68 age-matched control subjects (mean age 7.0 ± 1.7 years) on six identical scanners. Whole-brain volumetric analyses were conducted using voxel-based morphometry to detect regional differences between groups and to investigate correlations between regional brain volumes and measures of glycemic exposure (including data from continuous glucose monitoring). Relative to control subjects, the T1D group displayed decreased gray matter volume (GMV) in bilateral occipital and cerebellar regions (P < 0.001) and increased GMV in the left inferior prefrontal, insula, and temporal pole regions (P = 0.002). Within the T1D group, hyperglycemic exposure was associated with decreased GMV in medial frontal and temporal-occipital regions and increased GMV in lateral prefrontal regions. Cognitive correlations of intelligence quotient to GMV were found in cerebellar-occipital regions and medial prefrontal cortex for control subjects, as expected, but not for the T1D group. Thus, early-onset T1D affects regions of the brain that are associated with typical cognitive development.


Trends in Biotechnology | 2010

Neuroimaging-based approaches in the brain–computer interface

Byoung Kyong Min; Matthew Marzelli; Seung-Schik Yoo

Techniques to enable direct communication between the brain and computers/machines, such as the brain-computer interface (BCI) or the brain-machine interface (BMI), are gaining momentum in the neuroscientific realm, with potential applications ranging from medicine to general consumer electronics. Noninvasive BCI techniques based on neuroimaging modalities are reviewed in terms of their methodological approaches as well as their similarities and differences. Trends in automated data interpretation through machine learning algorithms are also introduced. Applications of functional neuromodulation techniques to BCI systems would allow for bidirectional communication between the brain and the computer. Such bidirectional interfaces can relay information directly from one brain to another using a computer as a medium, ultimately leading to the concept of a brain-to-brain interface (BBI).


Diabetes | 2015

Longitudinal Assessment of Neuroanatomical and Cognitive Differences in Young Children with Type 1 Diabetes: Association with Hyperglycemia

Nelly Mauras; Paul Mazaika; Bruce Buckingham; Stuart A. Weinzimer; Neil H. White; Eva Tsalikian; Tamara Hershey; Allison Cato; Peiyao Cheng; Craig Kollman; Roy W. Beck; Katrina J. Ruedy; Tandy Aye; Larry A. Fox; Ana Maria Arbelaez; Darrell M. Wilson; Michael Tansey; William V. Tamborlane; Daniel Peng; Matthew Marzelli; Karen K. Winer; Allan L. Reiss

Significant regional differences in gray and white matter volume and subtle cognitive differences between young diabetic and nondiabetic children have been observed. Here, we assessed whether these differences change over time and the relation with dysglycemia. Children ages 4 to <10 years with (n = 144) and without (n = 72) type 1 diabetes (T1D) had high-resolution structural MRI and comprehensive neurocognitive tests at baseline and 18 months and continuous glucose monitoring and HbA1c performed quarterly for 18 months. There were no differences in cognitive and executive function scores between groups at 18 months. However, children with diabetes had slower total gray and white matter growth than control subjects. Gray matter regions (left precuneus, right temporal, frontal, and parietal lobes and right medial-frontal cortex) showed lesser growth in diabetes, as did white matter areas (splenium of the corpus callosum, bilateral superior-parietal lobe, bilateral anterior forceps, and inferior-frontal fasciculus). These changes were associated with higher cumulative hyperglycemia and glucose variability but not with hypoglycemia. Young children with T1D have significant differences in total and regional gray and white matter growth in brain regions involved in complex sensorimotor processing and cognition compared with age-matched control subjects over 18 months, suggesting that chronic hyperglycemia may be detrimental to the developing brain.


NeuroImage | 2011

Neuroanatomical spatial patterns in Turner syndrome.

Matthew Marzelli; Fumiko Hoeft; David S. Hong; Allan L. Reiss

Turner syndrome (TS) is a highly prevalent genetic condition caused by partial or complete absence of one X-chromosome in a female and is associated with a lack of endogenous estrogen during development secondary to gonadal dysgenesis. Prominent cognitive weaknesses in executive and visuospatial functions in the context of normal overall IQ also occur in affected individuals. Previous neuroimaging studies of TS point to a profile of neuroanatomical variation relative to age and sex matched controls. However, there are no neuroimaging studies focusing on young girls with TS before they receive exogenous estrogen treatment to induce puberty. Information obtained from young girls with TS may help to establish an early neural correlate of the cognitive phenotype associated with the disorder. Further, univariate analysis has predominantly been the method of choice in prior neuroimaging studies of TS. Univariate approaches examine between-group differences on the basis of individual image elements (i.e., a single voxels intensity or the volume of an a priori defined brain region). This is in contrast to multivariate methods that can elucidate complex neuroanatomical profiles in a clinical population by determining the pattern of between-group differences from many image elements evaluated simultaneously. In this case, individual image elements might not be significantly different between groups but can still contribute to a significantly different overall spatial pattern. In this study, voxel-based morphometry (VBM) of high-resolution magnetic resonance images was used to investigate differences in brain morphology between 13 pediatric, pre-estrogen girls with monosomic TS and 13 age-matched typically developing controls (3.0 T imaging: mean age 9.1±2.1). A similar analysis was performed with an older cohort of 13 girls with monosomic TS and 13 age-matched typically developing controls (1.5 T imaging: mean age 15.8±4.5). A multivariate, linear support vector machine analysis using leave-one-out cross-validation was then employed to discriminate girls with TS from typically developing controls based on differences in neuroanatomical spatial patterns and to assess how accurately such patterns translate across heterogeneous cohorts. VBM indicated that both TS cohorts had significantly reduced gray matter volume in the precentral, postcentral, and supramarginal gyri and enlargement of the left middle and superior temporal gyri. Support vector machine (SVM) classifiers achieved high accuracy for discriminating brain morphology patterns in TS from typically developing controls and also displayed spatial patterns consistent with the VBM results. Furthermore, the SVM classifiers identified additional neuroanatomical variations in individuals with TS, localized in the hippocampus, orbitofrontal cortex, insula, caudate, and cuneus. Our results demonstrate robust spatial patterns of altered brain morphology in developmentally dynamic populations with TS, providing further insight into the neuroanatomical correlates of cognitive-behavioral features in this condition.


The Journal of Neuroscience | 2013

Genomic imprinting effects of the X chromosome on brain morphology.

Jean-François Lepage; David S. Hong; Paul K. Mazaika; Mira Raman; Kristen Sheau; Matthew Marzelli; Joachim Hallmayer; Allan L. Reiss

There is increasing evidence that genomic imprinting, a process by which certain genes are expressed in a parent-of-origin-specific manner, can influence neurogenetic and psychiatric manifestations. While some data suggest possible imprinting effects of the X chromosome on physical and cognitive characteristics in humans, there is no compelling evidence that X-linked imprinting affects brain morphology. To address this issue, we investigated regional cortical volume, thickness, and surface area in 27 healthy controls and 40 prepubescent girls with Turner syndrome (TS), a condition caused by the absence of one X chromosome. Of the young girls with TS, 23 inherited their X chromosome from their mother (Xm) and 17 from their father (Xp). Our results confirm the existence of significant differences in brain morphology between girls with TS and controls, and reveal the presence of a putative imprinting effect among the TS groups: girls with Xp demonstrated thicker cortex than those with Xm in the temporal regions bilaterally, while Xm individuals showed bilateral enlargement of gray matter volume in the superior frontal regions compared with Xp. These data suggest the existence of imprinting effects of the X chromosome that influence both cortical thickness and volume during early brain development, and help to explain variability in cognitive and behavioral manifestations of TS with regard to the parental origin of the X chromosome.


Medical Image Analysis | 2009

Automated classification of fMRI data employing trial-based imagery tasks.

Jong Hwan Lee; Matthew Marzelli; Ferenc A. Jolesz; Seung-Schik Yoo

Automated interpretation and classification of functional MRI (fMRI) data is an emerging research field that enables the characterization of underlying cognitive processes with minimal human intervention. In this work, we present a method for the automated classification of human thoughts reflected on a trial-based paradigm using fMRI with a significantly shortened data acquisition time (less than one minute). Based on our preliminary experience with various cognitive imagery tasks, six characteristic thoughts were chosen as target tasks for the present work: right-hand motor imagery, left-hand motor imagery, right foot motor imagery, mental calculation, internal speech/word generation, and visual imagery. These six tasks were performed by five healthy volunteers and functional images were obtained using a T(*)(2)-weighted echo planar imaging (EPI) sequence. Feature vectors from activation maps, necessary for the classification of neural activity, were automatically extracted from the regions that were consistently and exclusively activated for a given task during the training process. Extracted feature vectors were classified using the support vector machine (SVM) algorithm. Parameter optimization, using a k-fold cross validation scheme, allowed the successful recognition of the six different categories of administered thought tasks with an accuracy of 74.5% (mean)+/-14.3% (standard deviation) across all five subjects. Our proposed study for the automated classification of fMRI data may be utilized in further investigations to monitor/identify human thought processes and their potential link to hardware/computer control.


Diabetes | 2016

Variations in Brain Volume and Growth in Young Children With Type 1 Diabetes

Paul K. Mazaika; Stuart A. Weinzimer; Nelly Mauras; Bruce Buckingham; Neil H. White; Eva Tsalikian; Tamara Hershey; Allison Cato; Tandy Aye; Larry A. Fox; Darrell M. Wilson; Michael Tansey; William V. Tamborlane; Daniel Peng; Mira Raman; Matthew Marzelli; Allan L. Reiss

Early-onset type 1 diabetes may affect the developing brain during a critical window of rapid brain maturation. Structural MRI was performed on 141 children with diabetes (4–10 years of age at study entry) and 69 age-matched control subjects at two time points spaced 18 months apart. For the children with diabetes, the mean (±SD) HbA1c level was 7.9 ± 0.9% (63 ± 9.8 mmol/mol) at both time points. Relative to control subjects, children with diabetes had significantly less growth of cortical gray matter volume and cortical surface area and significantly less growth of white matter volume throughout the cortex and cerebellum. For the population with diabetes, the change in the blood glucose level at the time of scan across longitudinal time points was negatively correlated with the change in gray and white matter volumes, suggesting that fluctuating glucose levels in children with diabetes may be associated with corresponding fluctuations in brain volume. In addition, measures of hyperglycemia and glycemic variation were significantly negatively correlated with the development of surface curvature. These results demonstrate that early-onset type 1 diabetes has widespread effects on the growth of gray and white matter in children whose blood glucose levels are well within the current treatment guidelines for the management of diabetes.


The Journal of Neuroscience | 2014

Influence of the X-Chromosome on Neuroanatomy: Evidence from Turner and Klinefelter Syndromes

David S. Hong; Fumiko Hoeft; Matthew Marzelli; Jean-François Lepage; David P. Roeltgen; Judith L. Ross; Allan L. Reiss

Studies of sex effects on neurodevelopment have traditionally focused on animal models investigating hormonal influences on brain anatomy. However, more recent evidence suggests that sex chromosomes may also have direct upstream effects that act independently of hormones. Sex chromosome aneuploidies provide ideal models to examine this framework in humans, including Turner syndrome (TS), where females are missing one X-chromosome (45X), and Klinefelter syndrome (KS), where males have an additional X-chromosome (47XXY). As these disorders essentially represent copy number variants of the sex chromosomes, investigation of brain structure across these disorders allows us to determine whether sex chromosome gene dosage effects exist. We used voxel-based morphometry to investigate this hypothesis in a large sample of children in early puberty, to compare regional gray matter volumes among individuals with one (45X), two (typically developing 46XX females and 46XY males), and three (47XXY) sex chromosomes. Between-group contrasts of TS and KS groups relative to respective sex-matched controls demonstrated highly convergent patterns of volumetric differences with the presence of an additional sex chromosome being associated with relatively decreased parieto-occipital gray matter volume and relatively increased temporo-insular gray matter volumes. Furthermore, z-score map comparisons between TS and KS cohorts also suggested that this effect occurs in a linear dose-dependent fashion. We infer that sex chromosome gene expression directly influences brain structure in children during early stages of puberty, extending our understanding of genotype–phenotype mechanisms underlying sex differences in the brain.


Cerebral Cortex | 2012

White Matter Aberrations in Prepubertal Estrogen-Naive Girls with Monosomic Turner Syndrome

Bun Yamagata; Naama Barnea-Goraly; Matthew Marzelli; Yaena Park; David S. Hong; Masaru Mimura; Allan L. Reiss

Turner syndrome (TS) offers a unique opportunity to investigate associations among genes, the brain, and cognitive phenotypes. In this study, we used 3 complementary analyses of diffusion tensor imaging (DTI) data (whole brain, region of interest, and fiber tractography) and a whole brain volumetric imaging technique to investigate white matter (WM) structure in prepubertal, nonmosaic, estrogen-naive girls with TS compared with age and sex matched typically developing controls. The TS group demonstrated significant WM aberrations in brain regions implicated in visuospatial abilities, face processing, and sensorimotor and social abilities compared with controls. Extensive spatial overlap between regions of aberrant WM structure (from DTI) and regions of aberrant WM volume were observed in TS. Our findings indicate that complete absence of an X chromosome in young females (prior to receiving exogenous estrogen) is associated with WM aberrations in specific regions implicated in characteristic cognitive features of TS.

Collaboration


Dive into the Matthew Marzelli's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Neil H. White

Washington University in St. Louis

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Craig Kollman

National Marrow Donor Program

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Katrina J. Ruedy

Washington University in St. Louis

View shared research outputs
Researchain Logo
Decentralizing Knowledge