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Dive into the research topics where Chad T. Jackson is active.

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Featured researches published by Chad T. Jackson.


NeuroImage | 2014

Neuroimaging of the Philadelphia neurodevelopmental cohort.

Theodore D. Satterthwaite; Mark A. Elliott; Kosha Ruparel; James Loughead; Karthik Prabhakaran; Monica E. Calkins; Ryan Hopson; Chad T. Jackson; Jack R. Keefe; Marisa Riley; Frank D. Mentch; Patrick Sleiman; Ragini Verma; Christos Davatzikos; Hakon Hakonarson; Ruben C. Gur; Raquel E. Gur

The Philadelphia Neurodevelopmental Cohort (PNC) is a large-scale, NIMH funded initiative to understand how brain maturation mediates cognitive development and vulnerability to psychiatric illness, and understand how genetics impacts this process. As part of this study, 1445 adolescents ages 8-21 at enrollment underwent multimodal neuroimaging. Here, we highlight the conceptual basis for the effort, the study design, and the measures available in the dataset. We focus on neuroimaging measures obtained, including T1-weighted structural neuroimaging, diffusion tensor imaging, perfusion neuroimaging using arterial spin labeling, functional imaging tasks of working memory and emotion identification, and resting state imaging of functional connectivity. Furthermore, we provide characteristics regarding the final sample acquired. Finally, we describe mechanisms in place for data sharing that will allow the PNC to become a freely available public resource to advance our understanding of normal and pathological brain development.


NeuroImage | 2013

Heterogeneous impact of motion on fundamental patterns of developmental changes in functional connectivity during youth

Theodore D. Satterthwaite; Daniel H. Wolf; Kosha Ruparel; Guray Erus; Mark A. Elliott; Simon B. Eickhoff; Efstathios D. Gennatas; Chad T. Jackson; Karthik Prabhakaran; Alex R. Smith; Hakon Hakonarson; Ragini Verma; Christos Davatzikos; Raquel E. Gur; Ruben C. Gur

Several independent studies have demonstrated that small amounts of in-scanner motion systematically bias estimates of resting-state functional connectivity. This confound is of particular importance for studies of neurodevelopment in youth because motion is strongly related to subject age during this period. Critically, the effects of motion on connectivity mimic major findings in neurodevelopmental research, specifically an age-related strengthening of distant connections and weakening of short-range connections. Here, in a sample of 780 subjects ages 8-22, we re-evaluate patterns of change in functional connectivity during adolescent development after rigorously controlling for the confounding influences of motion at both the subject and group levels. We find that motion artifact inflates both overall estimates of age-related change as well as specific distance-related changes in connectivity. When motion is more fully accounted for, the prevalence of age-related change as well as the strength of distance-related effects is substantially reduced. However, age-related changes remain highly significant. In contrast, motion artifact tends to obscure age-related changes in connectivity associated with segregation of functional brain modules; improved preprocessing techniques allow greater sensitivity to detect increased within-module connectivity occurring with development. Finally, we show that subjects age can still be accurately estimated from the multivariate pattern of functional connectivity even while controlling for motion. Taken together, these results indicate that while motion artifact has a marked and heterogeneous impact on estimates of connectivity change during adolescence, functional connectivity remains a valuable phenotype for the study of neurodevelopment.


NeuroImage | 2016

The impact of quality assurance assessment on diffusion tensor imaging outcomes in a large-scale population-based cohort.

David R. Roalf; Megan Quarmley; Mark A. Elliott; Theodore D. Satterthwaite; Simon N. Vandekar; Kosha Ruparel; Efstathios D. Gennatas; Monica E. Calkins; Tyler M. Moore; Ryan Hopson; Karthik Prabhakaran; Chad T. Jackson; Ragini Verma; Hakon Hakonarson; Ruben C. Gur; Raquel E. Gur

BACKGROUND Diffusion tensor imaging (DTI) is applied in investigation of brain biomarkers for neurodevelopmental and neurodegenerative disorders. However, the quality of DTI measurements, like other neuroimaging techniques, is susceptible to several confounding factors (e.g., motion, eddy currents), which have only recently come under scrutiny. These confounds are especially relevant in adolescent samples where data quality may be compromised in ways that confound interpretation of maturation parameters. The current study aims to leverage DTI data from the Philadelphia Neurodevelopmental Cohort (PNC), a sample of 1601 youths with ages of 8-21 who underwent neuroimaging, to: 1) establish quality assurance (QA) metrics for the automatic identification of poor DTI image quality; 2) examine the performance of these QA measures in an external validation sample; 3) document the influence of data quality on developmental patterns of typical DTI metrics. METHODS All diffusion-weighted images were acquired on the same scanner. Visual QA was performed on all subjects completing DTI; images were manually categorized as Poor, Good, or Excellent. Four image quality metrics were automatically computed and used to predict manual QA status: Mean voxel intensity outlier count (MEANVOX), Maximum voxel intensity outlier count (MAXVOX), mean relative motion (MOTION) and temporal signal-to-noise ratio (TSNR). Classification accuracy for each metric was calculated as the area under the receiver-operating characteristic curve (AUC). A threshold was generated for each measure that best differentiated visual QA status and applied in a validation sample. The effects of data quality on sensitivity to expected age effects in this developmental sample were then investigated using the traditional MRI diffusion metrics: fractional anisotropy (FA) and mean diffusivity (MD). Finally, our method of QA is compared with DTIPrep. RESULTS TSNR (AUC=0.94) best differentiated Poor data from Good and Excellent data. MAXVOX (AUC=0.88) best differentiated Good from Excellent DTI data. At the optimal threshold, 88% of Poor data and 91% Good/Excellent data were correctly identified. Use of these thresholds on a validation dataset (n=374) indicated high accuracy. In the validation sample 83% of Poor data and 94% of Excellent data was identified using thresholds derived from the training sample. Both FA and MD were affected by the inclusion of poor data in an analysis of an age, sex and race matched comparison sample. In addition, we show that the inclusion of poor data results in significant attenuation of the correlation between diffusion metrics (FA and MD) and age during a critical neurodevelopmental period. We find higher correspondence between our QA method and DTIPrep for Poor data, but we find our method to be more robust for apparently high-quality images. CONCLUSION Automated QA of DTI can facilitate large-scale, high-throughput quality assurance by reliably identifying both scanner and subject induced imaging artifacts. The results present a practical example of the confounding effects of artifacts on DTI analysis in a large population-based sample, and suggest that estimates of data quality should not only be reported but also accounted for in data analysis, especially in studies of development.


NeuroImage | 2016

The Philadelphia Neurodevelopmental Cohort: A publicly available resource for the study of normal and abnormal brain development in youth.

Theodore D. Satterthwaite; John J. Connolly; Kosha Ruparel; Monica E. Calkins; Chad T. Jackson; Mark A. Elliott; David R. Roalf; Ryan Hopson; Karthik Prabhakaran; Meckenzie Behr; Haijun Qiu; Frank D. Mentch; Rosetta M. Chiavacci; Patrick Sleiman; Ruben C. Gur; Hakon Hakonarson; Raquel E. Gur

The Philadelphia Neurodevelopmental Cohort (PNC) is a large-scale study of child development that combines neuroimaging, diverse clinical and cognitive phenotypes, and genomics. Data from this rich resource is now publicly available through the Database of Genotypes and Phenotypes (dbGaP). Here we focus on the data from the PNC that is available through dbGaP and describe how users can access this data, which is evolving to be a significant resource for the broader neuroscience community for studies of normal and abnormal neurodevelopment.


Journal of the American Academy of Child and Adolescent Psychiatry | 2014

Sex Differences in the Effect of Puberty on Hippocampal Morphology

Theodore D. Satterthwaite; Simon N. Vandekar; Daniel H. Wolf; Kosha Ruparel; David R. Roalf; Chad T. Jackson; Mark A. Elliott; Warren B. Bilker; Monica E. Calkins; Karthik Prabhakaran; Christos Davatzikos; Hakon Hakonarson; Raquel E. Gur; Ruben C. Gur

OBJECTIVE Puberty is the defining process of adolescence, and is accompanied by divergent trajectories of behavior and cognition for males and females. Here we examine whether sex differences exist in the effect of puberty on the morphology of the hippocampus and amygdala. METHOD T1-weighted structural neuroimaging was performed in a sample of 524 pre- or postpubertal individuals ages 10 to 22 years. Hippocampal and amygdala volume and shape were quantified using the Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library (FSL) FIRST procedure and scaled by intracranial volume. The effects on regional volume of age, sex, puberty, and their interactions were examined using linear regression. Postpubertal sex differences were examined using a vertex analysis. RESULTS Prepubertal males and females had similar hippocampal volumes, whereas postpubertal females had significantly larger bilateral hippocampi, resulting in a significant puberty-by-sex interaction even when controlling for age and age-by-sex. This effect was regionally specific and was not apparent in the amygdala. Vertex analysis revealed that postpubertal differences were most prominent in the lateral aspect of the hippocampus bilaterally, corresponding to the CA1 subfield. CONCLUSIONS These results establish that there are regionally specific sex differences in the effect of puberty on the hippocampus. These findings are relevant for the understanding of psychiatric disorders that have both hippocampal dysfunction and prominent gender disparities during adolescence.


JAMA Psychiatry | 2015

Functional Neuroimaging Abnormalities in Youth With Psychosis Spectrum Symptoms

Daniel H. Wolf; Theodore D. Satterthwaite; Monica E. Calkins; Kosha Ruparel; Mark A. Elliott; Ryan Hopson; Chad T. Jackson; Karthik Prabhakaran; Warren B. Bilker; Hakon Hakonarson; Ruben C. Gur; Raquel E. Gur

IMPORTANCE The continuum view of the psychosis spectrum (PS) implies that, in population-based samples, PS symptoms should be associated with neural abnormalities similar to those found in help-seeking clinical risk individuals and in schizophrenia. To our knowledge, functional neuroimaging has not previously been applied in large population-based PS samples and can help us understand the neural architecture of psychosis more broadly and identify brain phenotypes beyond symptoms that are associated with the extended psychosis phenotype. OBJECTIVE To examine the categorical and dimensional relationships of PS symptoms to prefrontal hypoactivation during working memory and to amygdala hyperactivation during threat emotion processing. DESIGN, SETTING, AND PARTICIPANTS The Philadelphia Neurodevelopmental Cohort is a genotyped, prospectively accrued, population-based sample of almost 10,000 youths who received a structured psychiatric evaluation and a computerized neurocognitive battery. The study was conducted at an academic and childrens hospital health care network, between November 1, 2009 to November 30, 2011. A subsample of 1445 youths underwent neuroimaging, including functional magnetic resonance imaging tasks examined herein. Participants were youth aged 11 to 22 years old identified through structured interview as having PS features (PS group) (n = 260) and typically developing (TD) comparison youth without significant psychopathology (TD group) (n = 220). MAIN OUTCOMES AND MEASURES Two functional magnetic resonance imaging paradigms were used: a fractal n-back working memory task probing executive system function and an emotion identification task probing amygdala responses to threatening faces. RESULTS In the n-back task, working memory evoked lower activation in the PS group than the TD group throughout the executive control circuitry, including dorsolateral prefrontal cortex (cluster-corrected P < .05). Within the PS group, dorsolateral prefrontal cortex activation correlated with cognitive deficits (r = .32, P < .001), but no correlation was found with positive symptom severity. During emotion identification, PS demonstrated elevated responses to threatening facial expressions in amygdala, as well as left fusiform cortex and right middle frontal gyrus (cluster-corrected P < .05). The response in the amygdala correlated with positive symptom severity (r = .16, P = .01) but not with cognitive deficits. CONCLUSIONS AND RELEVANCE The pattern of functional abnormalities observed in the PS group is similar to that previously found in schizophrenia and help-seeking risk samples. Specific circuit dysfunction during cognitive and emotion-processing tasks is present early in the development of psychopathology and herein could not be attributed to chronic illness or medication confounds. Hypoactivation in executive circuitry and limbic hyperactivation to threat could reflect partly independent risk factors for PS symptoms, with the former relating to cognitive deficits that increase the risk for developing psychotic symptoms and the latter contributing directly to positive psychotic symptoms.


Biological Psychiatry | 2015

Heritability of Subcortical and Limbic Brain Volume and Shape in Multiplex-Multigenerational Families with Schizophrenia

David R. Roalf; Simon N. Vandekar; Laura Almasy; Kosha Ruparel; Theodore D. Satterthwaite; Mark A. Elliott; Jamie Podell; Sean Gallagher; Chad T. Jackson; Konasale M. Prasad; Joel Wood; Michael F. Pogue-Geile; Vishwajit L. Nimgaonkar; Ruben C. Gur; Raquel E. Gur

BACKGROUND Brain abnormalities of subcortical and limbic nuclei are common in patients with schizophrenia, and variation in these structures is considered a putative endophenotype for the disorder. Multiplex-multigenerational families with schizophrenia provide an opportunity to investigate the impact of shared genetic ancestry, but these families have not been previously examined to study structural brain abnormalities. We estimate the heritability of subcortical and hippocampal brain volumes in multiplex-multigenerational families and the heritability of subregions using advanced shape analysis. METHODS The study comprised 439 participants from two sites who underwent 3T structural magnetic resonance imaging. The participants included 190 European-Americans from 32 multiplex-multigenerational families with schizophrenia and 249 healthy comparison subjects. Subcortical and hippocampal volume and shape were measured in 14 brain structures. Heritability was estimated for volume and shape. RESULTS Volume and shape were heritable in families. Estimates of heritability in subcortical and limbic volumes ranged from .45 in the right hippocampus to .84 in the left putamen. The shape of these structures was heritable (range, .40-.49), and specific subregional shape estimates of heritability tended to exceed heritability estimates of volume alone. CONCLUSIONS These results demonstrate that volume and shape of subcortical and limbic brain structures are potential endophenotypic markers in schizophrenia. The specificity obtained using shape analysis may improve selection of imaging phenotypes that better reflect the underlying neurobiology. Our findings can aid in the identification of specific genetic targets that affect brain structure and function in schizophrenia.


Psychological Assessment | 2015

Development of an Abbreviated Form of the Penn Line Orientation Test Using Large Samples and Computerized Adaptive Test Simulation

Tyler M. Moore; J. Cobb Scott; Steven P. Reise; Allison M. Port; Chad T. Jackson; Kosha Ruparel; Adam Savitt; Raquel E. Gur; Ruben C. Gur

Visuospatial processing is a commonly assessed neurocognitive domain with deficits linked to dysfunction in right posterior regions of the brain. With the growth of large-scale clinical research studies, there is an increased need for efficient and scalable assessments of neurocognition, including visuospatial processing. The purpose of the current study was to use a novel method that combines item response theory (IRT) and computerized adaptive testing (CAT) approaches to create an abbreviated form of the computerized Penn Line Orientation Test (PLOT). The 24-item PLOT was administered to 8,498 youths (aged 8-21 years) as part of the Philadelphia Neurodevelopmental Cohort study and, by Web-based data collection, in an independent sample of 4,593 adults from Great Britain as part of a TV documentary. IRT-based CAT simulations were used to select the best PLOT items for an abbreviated form by performing separate simulations in each group and choosing only items that were selected as useful (i.e., high item discrimination and in the appropriate difficulty range) in at least 1 of the simulations. Fifteen items were chosen for the final, short form of the PLOT, indicating substantial agreement among the models in how they evaluated each items usefulness. Moreover, this abbreviated version performed comparably to the full version in tests of sensitivity to age and sex effects. This abbreviated version of the PLOT cuts administration time by 50% without detectable loss of information, which points to its feasibility for large-scale clinical and genomic studies.


Psychology of Addictive Behaviors | 2017

Cognitive functioning of adolescent and young adult cannabis users in the Philadelphia Neurodevelopmental Cohort.

J. Cobb Scott; Daniel H. Wolf; Monica E. Calkins; Emily C. Bach; Jennifer Weidner; Kosha Ruparel; Tyler M. Moore; Jason D. Jones; Chad T. Jackson; Raquel E. Gur; Ruben C. Gur

Cannabis use in youth is rising and has been linked to deficits in cognitive functioning. However, cognitive findings have primarily been based on small samples of users seeking treatment, and few studies have evaluated cognition in occasional cannabis users. Here, we examined 4,568 adolescents and young adults (ages 14–21 years) drawn from the Philadelphia Neurodevelopmental Cohort, a prospective, population-based study. Participants were classified as cannabis Non-Users (n = 3,401), Occasional Users (twice per week or less; n = 940), or Frequent Users (>3 times per week; n = 227). Mixed-model analyses examined main effects of cannabis use and interactions between age and cannabis use on cognitive functioning. There was a significant interaction between cannabis group and age such that adolescent (but not young adult) Frequent Users performed worse than Non-Users on measures of executive control (p = .002). Earlier age of cannabis use was associated with worse performance in executive control in Occasional Users (p = .04). Unexpectedly, Occasional Users exhibited better executive control, memory, and social cognition than Non-Users (ps < .05). Although mild executive control deficits in adolescent frequent users and a relation between early cannabis initiation and cognitive performance are partially consistent with prior research, cognitive deficits were not found in other hypothesized domains in this community-based sample. Moreover, occasional cannabis users displayed equivalent or even slightly better executive control, social–cognitive, and memory abilities compared with nonusers, suggesting complex relationships between cannabis use and cognition in youth. Longitudinal studies with community samples are needed to identify variables affecting risk and resilience to cognitive deficits associated with cannabis.


Aerospace medicine and human performance | 2017

Validation of the Cognition Test Battery for Spaceflight in a Sample of Highly Educated Adults

Tyler M. Moore; Mathias Basner; Jad Nasrini; Emanuel Hermosillo; Sushila Kabadi; David R. Roalf; Sarah McGuire; Adrian J. Ecker; Kosha Ruparel; Allison M. Port; Chad T. Jackson; David F. Dinges; Ruben C. Gur

BACKGROUND Neuropsychological changes that may occur due to the environmental and psychological stressors of prolonged spaceflight motivated the development of the Cognition Test Battery. The battery was designed to assess multiple domains of neurocognitive functions linked to specific brain systems. Tests included in Cognition have been validated, but not in high-performing samples comparable to astronauts, which is an essential step toward ensuring their usefulness in long-duration space missions. METHODS We administered Cognition (on laptop and iPad) and the WinSCAT, counterbalanced for order and version, in a sample of 96 subjects (50% women; ages 25-56 yr) with at least a Masters degree in science, technology, engineering, or mathematics (STEM). We assessed the associations of age, sex, and administration device with neurocognitive performance, and compared the scores on the Cognition battery with those of WinSCAT. Confirmatory factor analysis compared the structure of the iPad and laptop administration methods using Wald tests. RESULTS Age was associated with longer response times (mean β = 0.12) and less accurate (mean β = -0.12) performance, women had longer response times on psychomotor (β = 0.62), emotion recognition (β = 0.30), and visuo-spatial (β = 0.48) tasks, men outperformed women on matrix reasoning (β = -0.34), and performance on an iPad was generally faster (mean β = -0.55). The WinSCAT appeared heavily loaded with tasks requiring executive control, whereas Cognition assessed a larger variety of neurocognitive domains. DISCUSSION Overall results supported the interpretation of Cognition scores as measuring their intended constructs in high performing astronaut analog samples.Moore TM, Basner M, Nasrini J, Hermosillo E, Kabadi S, Roalf DR, McGuire S, Ecker AJ, Ruparel K, Port AM, Jackson CT, Dinges DF, Gur RC. Validation of the Cognition Test Battery for spaceflight in a sample of highly educated adults. Aerosp Med Hum Perform. 2017; 88(10):937-946.

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Dive into the Chad T. Jackson's collaboration.

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Kosha Ruparel

University of Pennsylvania

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Ruben C. Gur

University of Washington

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Raquel E. Gur

University of Pennsylvania

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Theodore D. Satterthwaite

Children's Hospital of Philadelphia

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David R. Roalf

Children's Hospital of Philadelphia

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Monica E. Calkins

University of Pennsylvania

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Tyler M. Moore

University of Pennsylvania

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Mark A. Elliott

University of Pennsylvania

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Hakon Hakonarson

Children's Hospital of Philadelphia

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