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Dive into the research topics where Monica E. Calkins is active.

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Featured researches published by Monica E. Calkins.


NeuroImage | 2013

An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data.

Theodore D. Satterthwaite; Mark A. Elliott; Raphael T. Gerraty; Kosha Ruparel; James Loughead; Monica E. Calkins; Simon B. Eickhoff; Hakon Hakonarson; Ruben C. Gur; Raquel E. Gur; Daniel H. Wolf

Several recent reports in large, independent samples have demonstrated the influence of motion artifact on resting-state functional connectivity MRI (rsfc-MRI). Standard rsfc-MRI preprocessing typically includes regression of confounding signals and band-pass filtering. However, substantial heterogeneity exists in how these techniques are implemented across studies, and no prior study has examined the effect of differing approaches for the control of motion-induced artifacts. To better understand how in-scanner head motion affects rsfc-MRI data, we describe the spatial, temporal, and spectral characteristics of motion artifacts in a sample of 348 adolescents. Analyses utilize a novel approach for describing head motion on a voxelwise basis. Next, we systematically evaluate the efficacy of a range of confound regression and filtering techniques for the control of motion-induced artifacts. Results reveal that the effectiveness of preprocessing procedures on the control of motion is heterogeneous, and that improved preprocessing provides a substantial benefit beyond typical procedures. These results demonstrate that the effect of motion on rsfc-MRI can be substantially attenuated through improved preprocessing procedures, but not completely removed.


American Journal of Psychiatry | 2007

Neurocognitive Endophenotypes in a Multiplex Multigenerational Family Study of Schizophrenia

Raquel E. Gur; Vishwajit L. Nimgaonkar; Laura Almasy; Monica E. Calkins; J. Daniel Ragland; Michael F. Pogue-Geile; Stephen J. Kanes; John Blangero; Ruben C. Gur

OBJECTIVE Genetic factors contribute to the development of schizophrenia where cognitive dysfunction is a hallmark. The purpose of this article was to examine computerized neurocognitive measures as candidate endophenotypic markers of liability for schizophrenia in a genetically informative cohort. METHOD European Americans from 35 multiplex multigenerational families (N=349) and healthy participants (N=154) underwent clinical assessments and neurocognitive measurements and provided blood samples. The neurocognitive measures included performance (accuracy and speed) from a computerized battery that assessed abstraction/mental flexibility; attention; verbal, face, and spatial memory; spatial processing; sensorimotor processing; and emotion intensity discrimination. RESULTS Probands, relatives, and comparison subjects differed from each other in performance. Probands demonstrated greatest impairment relative to comparison subjects, followed by family members. Liability for schizophrenia affected the speed-accuracy tradeoff differently for specific neurocognitive domains. Significant heritability estimates were obtained for accuracy of verbal, facial, and spatial memory and spatial and emotion processing. For speed, estimates of heritability were significant for abstraction/mental flexibility, attention, face memory, and spatial and sensorimotor processing. CONCLUSIONS In a multigenerational multiplex design, the authors demonstrated that neurocognitive measures are associated with schizophrenia, differentiate unaffected relatives from comparison subjects, and may have significant presumed heritability. Therefore, they are endophenotypes suitable for genetic studies. Accuracy and speed can be differentially sensitive to presumed genetic liability.


Journal of Neuroscience Methods | 2010

A cognitive neuroscience based computerized battery for efficient measurement of individual differences: Standardization and initial construct validation

Ruben C. Gur; Jan Richard; Paul Hughett; Monica E. Calkins; Larry Macy; Warren B. Bilker; Colleen M. Brensinger; Raquel E. Gur

There is increased need for efficient computerized methods to collect reliable data on a range of cognitive domains that can be linked to specific brain systems. Such need arises in functional neuroimaging studies, where individual differences in cognitive performance are variables of interest or serve as confounds. In genetic studies of complex behavior, which require particularly large samples, such trait measures can serve as endophenotypes. Traditional neuropsychological tests, based on clinical pathological correlations, are protracted, require extensive training in administration and scoring, and leave lengthy paper trails (double-entry for analysis). We present a computerized battery that takes an average of 1h and provides measures of accuracy and speed on 9 neurocognitive domains. They are cognitive neuroscience-based in that they have been linked experimentally to specific brain systems with functional neuroimaging studies. We describe the process of translating tasks used in functional neuroimaging to tests for assessing individual differences. Data are presented on each test with samples ranging from 139 (81 female) to 536 (311 female) of carefully screened healthy individuals ranging in age from 18 to 84. Item consistency was established with acceptable to high Cronbach alpha coefficients. Inter-item correlations were moderate to high within domain and low to nil across domains, indicating construct validity. Initial criterion validity was demonstrated by sensitivity to sex differences and the effects of age, education and parental education. These results encourage the use of this battery in studies needing an efficient assessment of major neurocognitive domains such as multi-site genetic studies and clinical trials.


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.


Neuropsychologia | 2005

Working memory functioning in schizophrenia patients and their first-degree relatives: Cognitive functioning shedding light on etiology

Heather M. Conklin; Clayton E. Curtis; Monica E. Calkins; William G. Iacono

There is accumulating evidence for involvement of the prefrontal cortex (PFC) in the pathophysiology of schizophrenia. A primary function supported by the PFC is working memory (WM). Findings from WM studies in schizophrenia can provide insight into the nature of clinical symptoms and cognitive deficits associated with this disorder, as well as begin to suggest areas of underlying neuropathology. To date, studies have not adequately investigated different WM domains (e.g., verbal, spatial, or object) or processing requirements (e.g., maintenance, monitoring, or manipulation), shown to be associated with distinct patterns of neural activation, in schizophrenia patients and their well relatives. Accordingly, this study evaluated the performance of schizophrenia patients, their first-degree biological relatives, and nonpsychiatric controls on a comprehensive battery of WM tasks and investigated the association among WM deficits and schizophrenia-spectrum psychopathology. The findings indicate that schizophrenia patients are consistently impaired on WM tasks, irrespective of WM domain or processing requirements. In contrast, their unaffected relatives are only impaired on WM tasks with higher central executive processing requirements. This pattern of WM performance may further implicate DLPFC dysfunction in the liability for schizophrenia and has implications for future cognitive, genetic, and neurodevelopmental research.


Schizophrenia Research | 2006

A comparison of cognitive structure in schizophrenia patients and healthy controls using confirmatory factor analysis

Dwight Dickinson; J. Daniel Ragland; Monica E. Calkins; James M. Gold; Ruben C. Gur

There is evidence that cognitive task performance breaks down into the same broad domains in schizophrenia as in healthy populations. However, this does not mean that the domains are independent of one another or that the interrelationships among domains are the same between groups. We used confirmatory factor analysis (CFA) to compare the latent structure of a broad neuropsychological battery in schizophrenia patients (n = 148) and healthy controls (n = 157). Main analyses examined the fit of a hierarchical six-factor model, in which associations among the factors were assumed to reflect their strong shared relationship to a general cognitive ability factor. The model incorporated the factors of verbal comprehension, perceptual organization, verbal memory, spatial memory, processing speed, and executive/working memory. The hierarchical model provided a good overall fit to data from both groups. However multiple groups CFA revealed significant differences in factor loadings between groups, reflecting a more generalized latent structure of cognitive ability in schizophrenia. This was also evident in higher bivariate correlations among cognitive domain composite scores calculated from the observed test data. Cognitive ability, as reflected in test performance, appears to be more unitary in schizophrenia than in healthy subjects. This finding may have measurement and treatment implications.


Biological Psychiatry | 2008

Unaffected Family Members and Schizophrenia Patients Share Brain Structure Patterns: A High-Dimensional Pattern Classification Study

Yong Fan; Raquel E. Gur; Ruben C. Gur; Xiaoying Wu; Dinggang Shen; Monica E. Calkins; Christos Davatzikos

BACKGROUND A number of studies have provided evidence for genetic modulation of brain structure in unaffected family members (FM) of schizophrenia patients using conventional volumetric analysis. High-dimensional pattern classification methods have been reported to have the capacity to determine subtle and spatially complex structural patterns that distinguish schizophrenia patients from healthy control subjects using standard magnetic resonance imaging. This study investigates whether such endophenotypic patterns are found in FM via similar image analysis approaches. METHODS A high-dimensional pattern classifier was constructed from a group of 69 patients and 79 control subjects, via an analysis that identified a subtle and spatially complex pattern of reduced brain volumes. The constructed classifier was applied to examine brain structure of 30 FM. RESULTS The classifier indicated that FM had highly overlapping structural profiles with those of patients. Moreover, an orbitofrontal region of relatively increased white matter was found to contribute significantly to the classification, indicating that white matter alterations, along with reductions of gray matter volumes, might be present in patients and unaffected FM. CONCLUSIONS These findings provide evidence that high-dimensional pattern classification can identify complex and subtle structural endophenotypes that are shared by probands and their unaffected FM.


The Journal of Neuroscience | 2013

Functional Maturation of the Executive System during Adolescence

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.


NeuroImage | 2012

Being right is its own reward: load and performance related ventral striatum activation to correct responses during a working memory task in youth.

Theodore D. Satterthwaite; Kosha Ruparel; James Loughead; Mark A. Elliott; Raphael T. Gerraty; Monica E. Calkins; Hakon Hakonarson; Ruben C. Gur; Raquel E. Gur; Daniel H. Wolf

The ventral striatum (VS) is a critical brain region for reinforcement learning and motivation. Intrinsically motivated subjects performing challenging cognitive tasks engage reinforcement circuitry including VS even in the absence of external feedback or incentives. However, little is known about how such VS responses develop with age, relate to task performance, and are influenced by task difficulty. Here we used fMRI to examine VS activation to correct and incorrect responses during a standard n-back working memory task in a large sample (n=304) of healthy children, adolescents and young adults aged 8-22. We found that bilateral VS activates more strongly to correct than incorrect responses, and that the VS response scales with the difficulty of the working memory task. Furthermore, VS response was correlated with discrimination performance during the task, and the magnitude of VS response peaked in mid-adolescence. These findings provide evidence for scalable intrinsic reinforcement signals during standard cognitive tasks, and suggest a novel link between motivation and cognition during adolescent development.


Brain and Cognition | 2008

Eye Movement Dysfunction in First-Degree Relatives of Patients with Schizophrenia: A Meta-Analytic Evaluation of Candidate Endophenotypes.

Monica E. Calkins; William G. Iacono; Deniz S. Ones

Several forms of eye movement dysfunction (EMD) are regarded as promising candidate endophenotypes of schizophrenia. Discrepancies in individual study results have led to inconsistent conclusions regarding particular aspects of EMD in relatives of schizophrenia patients. To quantitatively evaluate and compare the candidacy of smooth pursuit, saccade and fixation deficits in first-degree biological relatives, we conducted a set of meta-analytic investigations. Among 18 measures of EMD, memory-guided saccade accuracy and error rate, global smooth pursuit dysfunction, intrusive saccades during fixation, antisaccade error rate and smooth pursuit closed-loop gain emerged as best differentiating relatives from controls (standardized mean differences ranged from .46 to .66), with no significant differences among these measures. Anticipatory saccades, but no other smooth pursuit component measures were also increased in relatives. Visually-guided reflexive saccades were largely normal. Moderator analyses examining design characteristics revealed few variables affecting the magnitude of the meta-analytically observed effects. Moderate effect sizes of relatives v. controls in selective aspects of EMD supports their endophenotype potential. Future work should focus on facilitating endophenotype utility through attention to heterogeneity of EMD performance, relationships among forms of EMD, and application in molecular genetics studies.

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Raquel E. Gur

University of Pennsylvania

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Ruben C. Gur

University of Pennsylvania

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Bruce I. Turetsky

University of Pennsylvania

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Tyler M. Moore

University of Pennsylvania

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Kosha Ruparel

University of Pennsylvania

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