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Dive into the research topics where Daniel H. Wolf is active.

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Featured researches published by Daniel H. Wolf.


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.


NeuroImage | 2012

Impact of In-Scanner Head Motion on Multiple Measures of Functional Connectivity: Relevance for Studies of Neurodevelopment in Youth

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

It has recently been reported (Van Dijk et al., 2011) that in-scanner head motion can have a substantial impact on MRI measurements of resting-state functional connectivity. This finding may be of particular relevance for studies of neurodevelopment in youth, confounding analyses to the extent that motion and subject age are related. Furthermore, while Van Dijk et al. demonstrated the effect of motion on seed-based connectivity analyses, it is not known how motion impacts other common measures of connectivity. Here we expand on the findings of Van Dijk et al. by examining the effect of motion on multiple types of resting-state connectivity analyses in a large sample of children and adolescents (n=456). Following replication of the effect of motion on seed-based analyses, we examine the influence of motion on graphical measures of network modularity, dual-regression of independent component analysis, as well as the amplitude and fractional amplitude of low frequency fluctuation. In the entire sample, subject age was highly related to motion. Using a subsample where age and motion were unrelated, we demonstrate that motion has marked effects on connectivity in every analysis examined. While subject age was associated with increased within-network connectivity even when motion was accounted for, controlling for motion substantially attenuated the strength of this relationship. The results demonstrate the pervasive influence of motion on multiple types functional connectivity analysis, and underline the importance of accounting for motion in studies of neurodevelopment.


Molecular Psychiatry | 2016

Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium

T G M van Erp; Derrek P. Hibar; Jerod Rasmussen; David C. Glahn; Godfrey D. Pearlson; Ole A. Andreassen; Ingrid Agartz; Lars T. Westlye; Unn K. Haukvik; Anders M. Dale; Ingrid Melle; Cecilie B. Hartberg; Oliver Gruber; Bernd Kraemer; David Zilles; Gary Donohoe; Sinead Kelly; Colm McDonald; Derek W. Morris; Dara M. Cannon; Aiden Corvin; Marise W J Machielsen; Laura Koenders; L. de Haan; Dick J. Veltman; Theodore D. Satterthwaite; Daniel H. Wolf; R.C. Gur; Raquel E. Gur; Steve Potkin

The profile of brain structural abnormalities in schizophrenia is still not fully understood, despite decades of research using brain scans. To validate a prospective meta-analysis approach to analyzing multicenter neuroimaging data, we analyzed brain MRI scans from 2028 schizophrenia patients and 2540 healthy controls, assessed with standardized methods at 15 centers worldwide. We identified subcortical brain volumes that differentiated patients from controls, and ranked them according to their effect sizes. Compared with healthy controls, patients with schizophrenia had smaller hippocampus (Cohen’s d=−0.46), amygdala (d=−0.31), thalamus (d=−0.31), accumbens (d=−0.25) and intracranial volumes (d=−0.12), as well as larger pallidum (d=0.21) and lateral ventricle volumes (d=0.37). Putamen and pallidum volume augmentations were positively associated with duration of illness and hippocampal deficits scaled with the proportion of unmedicated patients. Worldwide cooperative analyses of brain imaging data support a profile of subcortical abnormalities in schizophrenia, which is consistent with that based on traditional meta-analytic approaches. This first ENIGMA Schizophrenia Working Group study validates that collaborative data analyses can readily be used across brain phenotypes and disorders and encourages analysis and data sharing efforts to further our understanding of severe mental illness.


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.


Psychiatry Research-neuroimaging | 2007

Alterations of fronto-temporal connectivity during word encoding in schizophrenia

Daniel H. Wolf; Ruben C. Gur; Jeffrey N. Valdez; James Loughead; Mark A. Elliott; Raquel E. Gur; J. Daniel Ragland

Cognitive deficits, including impaired verbal memory, are prominent in schizophrenia and lead to increased disability. Functional neuroimaging of patients with schizophrenia performing memory tasks has revealed abnormal activation patterns in prefrontal cortex and temporo-limbic regions. Aberrant fronto-temporal interactions thus represent a potential pathophysiological mechanism underlying verbal memory deficits, yet this hypothesis of disturbed connectivity is not tested directly with standard activation studies. We performed within-subject correlations of frontal and temporal timeseries to measure functional connectivity during verbal encoding. Our results confirm earlier findings of aberrant fronto-temporal connectivity in schizophrenia, and extend them by identifying distinct alterations within dorsal and ventral prefrontal cortex. Relative to healthy controls, patients with schizophrenia had reduced connectivity between the dorsolateral prefrontal cortex (DLPFC) and temporal lobe areas including parahippocampus and superior temporal gyrus. In contrast, patients showed increased connectivity between a region of ventrolateral prefrontal cortex (VLPFC) and these same temporal lobe regions. Higher temporal-DLPFC connectivity during encoding was associated with better subsequent recognition accuracy in controls, but not patients. Temporal-VLPFC connectivity was uncorrelated with recognition accuracy in either group. The results suggest that reduced temporal-DLPFC connectivity in schizophrenia could underlie encoding deficits, and increased temporal-VLPFC connectivity may represent an ineffective compensatory effort.


Frontiers in Human Neuroscience | 2010

“It’s not what you say, but how you say it” : A reciprocal temporo-frontal network for affective prosody

David I. Leitman; Daniel H. Wolf; J. Daniel Ragland; Petri Laukka; James Loughead; Jeffrey N. Valdez; Daniel C. Javitt; Bruce I. Turetsky; Ruben C. Gur

Humans communicate emotion vocally by modulating acoustic cues such as pitch, intensity and voice quality. Research has documented how the relative presence or absence of such cues alters the likelihood of perceiving an emotion, but the neural underpinnings of acoustic cue-dependent emotion perception remain obscure. Using functional magnetic resonance imaging in 20 subjects we examined a reciprocal circuit consisting of superior temporal cortex, amygdala and inferior frontal gyrus that may underlie affective prosodic comprehension. Results showed that increased saliency of emotion-specific acoustic cues was associated with increased activation in superior temporal cortex [planum temporale (PT), posterior superior temporal gyrus (pSTG), and posterior superior middle gyrus (pMTG)] and amygdala, whereas decreased saliency of acoustic cues was associated with increased inferior frontal activity and temporo-frontal connectivity. These results suggest that sensory-integrative processing is facilitated when the acoustic signal is rich in affective information, yielding increased activation in temporal cortex and amygdala. Conversely, when the acoustic signal is ambiguous, greater evaluative processes are recruited, increasing activation in inferior frontal gyrus (IFG) and IFG STG connectivity. Auditory regions may thus integrate acoustic information with amygdala input to form emotion-specific representations, which are evaluated within inferior frontal regions.


NeuroImage | 2017

Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity.

Rastko Ciric; Daniel H. Wolf; Jonathan D. Power; David R. Roalf; Graham L. Baum; Kosha Ruparel; Russell T. Shinohara; Mark A. Elliott; Simon B. Eickhoff; Christos Davatzikos; Ruben C. Gur; Raquel E. Gur; Danielle S. Bassett; Theodore D. Satterthwaite

&NA; Since initial reports regarding the impact of motion artifact on measures of functional connectivity, there has been a proliferation of participant‐level confound regression methods to limit its impact. However, many of the most commonly used techniques have not been systematically evaluated using a broad range of outcome measures. Here, we provide a systematic evaluation of 14 participant‐level confound regression methods in 393 youths. Specifically, we compare methods according to four benchmarks, including the residual relationship between motion and connectivity, distance‐dependent effects of motion on connectivity, network identifiability, and additional degrees of freedom lost in confound regression. Our results delineate two clear trade‐offs among methods. First, methods that include global signal regression minimize the relationship between connectivity and motion, but result in distance‐dependent artifact. In contrast, censoring methods mitigate both motion artifact and distance‐dependence, but use additional degrees of freedom. Importantly, less effective de‐noising methods are also unable to identify modular network structure in the connectome. Taken together, these results emphasize the heterogeneous efficacy of existing methods, and suggest that different confound regression strategies may be appropriate in the context of specific scientific goals. HighlightsWe evaluate 14 participant‐level de‐noising pipelines for functional connectivity.Pipeline performance is markedly heterogeneous.GSR minimizes the impact of motion but introduces distance dependence.Censoring reduces motion and improves network identifiability.


Molecular Psychiatry | 2016

Subcortical volumetric abnormalities in bipolar disorder.

Derrek P. Hibar; Lars T. Westlye; T G M van Erp; Jerod Rasmussen; Cassandra D. Leonardo; Joshua Faskowitz; Unn K. Haukvik; Cecilie B. Hartberg; Nhat Trung Doan; Ingrid Agartz; Anders M. Dale; Oliver Gruber; Bernd Krämer; Sarah Trost; Benny Liberg; Christoph Abé; C J Ekman; Martin Ingvar; Mikael Landén; Scott C. Fears; Nelson B. Freimer; Carrie E. Bearden; Emma Sprooten; David C. Glahn; Godfrey D. Pearlson; Louise Emsell; Joanne Kenney; C. Scanlon; Colm McDonald; Dara M. Cannon

Considerable uncertainty exists about the defining brain changes associated with bipolar disorder (BD). Understanding and quantifying the sources of uncertainty can help generate novel clinical hypotheses about etiology and assist in the development of biomarkers for indexing disease progression and prognosis. Here we were interested in quantifying case–control differences in intracranial volume (ICV) and each of eight subcortical brain measures: nucleus accumbens, amygdala, caudate, hippocampus, globus pallidus, putamen, thalamus, lateral ventricles. In a large study of 1710 BD patients and 2594 healthy controls, we found consistent volumetric reductions in BD patients for mean hippocampus (Cohen’s d=−0.232; P=3.50 × 10−7) and thalamus (d=−0.148; P=4.27 × 10−3) and enlarged lateral ventricles (d=−0.260; P=3.93 × 10−5) in patients. No significant effect of age at illness onset was detected. Stratifying patients based on clinical subtype (BD type I or type II) revealed that BDI patients had significantly larger lateral ventricles and smaller hippocampus and amygdala than controls. However, when comparing BDI and BDII patients directly, we did not detect any significant differences in brain volume. This likely represents similar etiology between BD subtype classifications. Exploratory analyses revealed significantly larger thalamic volumes in patients taking lithium compared with patients not taking lithium. We detected no significant differences between BDII patients and controls in the largest such comparison to date. Findings in this study should be interpreted with caution and with careful consideration of the limitations inherent to meta-analyzed neuroimaging comparisons.


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.


Schizophrenia Bulletin | 2014

Amotivation in Schizophrenia: Integrated Assessment With Behavioral, Clinical, and Imaging Measures

Daniel H. Wolf; Theodore D. Satterthwaite; Jacob J. Kantrowitz; Natalie Katchmar; Lillie Vandekar; Mark A. Elliott; Kosha Ruparel

Motivational deficits play a central role in disability caused by schizophrenia and constitute a major unmet therapeutic need. Negative symptoms have previously been linked to hypofunction in ventral striatum (VS), a core component of brain motivation circuitry. However, it remains unclear to what extent this relationship holds for specific negative symptoms such as amotivation, and this question has not been addressed with integrated behavioral, clinical, and imaging measures. Here, 41 individuals with schizophrenia and 37 controls performed a brief, computerized progressive ratio task (PRT) that quantifies effort exerted in pursuit of monetary reward. Clinical amotivation was assessed using the recently validated Clinical Assessment Interview for Negative Symptoms (CAINS). VS function was probed during functional magnetic resonance imaging using a monetary guessing paradigm. We found that individuals with schizophrenia had diminished motivation as measured by the PRT, which significantly and selectively related to clinical amotivation as measured by the CAINS. Critically, lower PRT motivation in schizophrenia was also dimensionally related to VS hypofunction. Our results demonstrate robust dimensional associations between behavioral amotivation, clinical amotivation, and VS hypofunction in schizophrenia. Integrating behavioral measures such as the PRT will facilitate translational efforts to identify biomarkers of amotivation and to assess response to novel therapeutic interventions.

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Raquel E. Gur

University of Pennsylvania

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Ruben C. Gur

University of Pennsylvania

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Kosha Ruparel

University of Pennsylvania

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Mark A. Elliott

University of Pennsylvania

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Monica E. Calkins

University of Pennsylvania

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David R. Roalf

University of Pennsylvania

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Tyler M. Moore

University of Pennsylvania

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Hakon Hakonarson

Children's Hospital of Philadelphia

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