Karthik Prabhakaran
University of Pennsylvania
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Publication
Featured researches published by Karthik Prabhakaran.
Journal of Magnetic Resonance Imaging | 2006
Vivek Sehgal; Zachary DelProposto; D. Haddar; E. Mark Haacke; Andrew E. Sloan; Lucia J. Zamorano; Geoffery Barger; Jiani Hu; Yingbiao Xu; Karthik Prabhakaran; Ilaya Raja Elangovan; Jaladhar Neelavalli; Jürgen R. Reichenbach
To evaluate the diagnostic value of susceptibility‐weighted imaging (SWI) for studying brain masses.
NeuroImage | 2014
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
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.
The Journal of Neuroscience | 2013
Theodore D. Satterthwaite; Daniel H. Wolf; Guray Erus; Kosha Ruparel; Mark A. Elliott; Efstathios D. Gennatas; Ryan Hopson; Chad R. Jackson; Karthik Prabhakaran; Warren B. Bilker; Monica E. Calkins; James Loughead; Alex J. Smith; David R. Roalf; Hakon Hakonarson; Ragini Verma; Christos Davatzikos; Ruben C. Gur; Raquel E. Gur
Adolescence is characterized by rapid development of executive function. Working memory (WM) is a key element of executive function, but it is not known what brain changes during adolescence allow improved WM performance. Using a fractal n-back fMRI paradigm, we investigated brain responses to WM load in 951 human youths aged 8–22 years. Compared with more limited associations with age, WM performance was robustly associated with both executive network activation and deactivation of the default mode network. Multivariate patterns of brain activation predicted task performance with a high degree of accuracy, and also mediated the observed age-related improvements in WM performance. These results delineate a process of functional maturation of the executive system, and suggest that this process allows for the improvement of cognitive capability seen during adolescence.
Proceedings of the National Academy of Sciences of the United States of America | 2014
Theodore D. Satterthwaite; Russell T. Shinohara; Daniel H. Wolf; Ryan Hopson; Mark A. Elliott; Simon N. Vandekar; Kosha Ruparel; Monica E. Calkins; David R. Roalf; Efstathios D. Gennatas; Chad R. Jackson; Guray Erus; Karthik Prabhakaran; Christos Davatzikos; John A. Detre; Hakon Hakonarson; Ruben C. Gur; Raquel E. Gur
Significance Blood perfusion is a fundamental property of brain physiology and is known to be higher in adult females than in males. However, it is unknown when such a sex difference emerges during the lifespan, or what biological processes may cause it. In the largest study of brain perfusion yet reported, we establish for the first time to our knowledge that patterns of development of cerebral perfusion during adolescence are markedly different in males and females, and such differences are attributable in part to the effects of puberty. These results may have important implications for neuropsychiatric disorders with adolescent onset and strong gender disparities, such as mood disorders, anxiety disorders, and schizophrenia. Puberty is the defining biological process of adolescent development, yet its effects on fundamental properties of brain physiology such as cerebral blood flow (CBF) have never been investigated. Capitalizing on a sample of 922 youths ages 8–22 y imaged using arterial spin labeled MRI as part of the Philadelphia Neurodevelopmental Cohort, we studied normative developmental differences in cerebral perfusion in males and females, as well as specific associations between puberty and CBF. Males and females had conspicuously divergent nonlinear trajectories in CBF evolution with development as modeled by penalized splines. Seventeen brain regions, including hubs of the executive and default mode networks, showed a robust nonlinear age-by-sex interaction that surpassed Bonferroni correction. Notably, within these regions the decline in CBF was similar between males and females in early puberty and only diverged in midpuberty, with CBF actually increasing in females. Taken together, these results delineate sex-specific growth curves for CBF during youth and for the first time to our knowledge link such differential patterns of development to the effects of puberty.
NeuroImage | 2016
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
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
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.
American Journal of Neuroradiology | 2013
Raquel E. Gur; D. Kaltman; Elias R. Melhem; Kosha Ruparel; Karthik Prabhakaran; M. Riley; E. Yodh; Hakon Hakonarson; Theodore D. Satterthwaite; Ruben C. Gur
Incidental abnormalities seen in research MRI brain studies of 1400 “normal” volunteer individuals aged 8-23 years were assessed. Ten percent showed incidental findings and 12 of these required further follow-up. Findings were not related to age but whites had higher numbers of pineal cysts and males had a higher incidence of cavum septum pellucidum, which was associated with psychosis-related symptoms. BACKGROUND AND PURPOSE: MRIs are obtained in research in healthy and clinical populations, and incidental findings have been reported. Most studies have examined adults with variability in parameters of image acquisition and clinical measures available. We conducted a prospective study of youths and documented the frequency and concomitants of incidental findings. MATERIALS AND METHODS: Youths (n = 1400) with an age range from 8–23 years were imaged on the same 3T scanner, with a standard acquisition protocol providing 1.0 mm3 isotropic resolution of anatomic scans. All scans were reviewed by an experienced board-certified neuroradiologist and were categorized into 3 groups: 1) normal: no incidental findings; 2) coincidental: incidental finding(s) were noted, further reviewed with an experienced pediatric neuroradiologist, but were of no clinical significance; 3) incidental findings that on further review were considered to have potential clinical significance and participants were referred for appropriate clinical follow-up. RESULTS: Overall, 148 incidental findings (10.6% of sample) were noted, and of these, 12 required clinical follow-up. Incidental findings were not related to age. However, whites had a higher incidence of pineal cysts, and males had a higher incidence of cavum septum pellucidum, which was associated with psychosis-related symptoms. CONCLUSIONS: Incidental findings, moderated by race and sex, occur in approximately one-tenth of participants volunteering for pediatric research, with few requiring follow-up. The incidence supports a 2-tiered approach of neuroradiologic reading and clinical input to determine the potential significance of incidental findings detected on research MR imaging scans.
JAMA Psychiatry | 2015
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.