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Your search keyword '"Pekar, James J."' showing total 388 results
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388 results on '"Pekar, James J."'

1. Quantifying brain development in the HEALthy Brain and Child Development (HBCD) Study: The magnetic resonance imaging and spectroscopy protocol

Author

Dean, Douglas C., III, Tisdall, M Dylan, Wisnowski, Jessica L., Feczko, Eric, Gagoski, Borjan, Alexander, Andrew L., Edden, Richard A.E., Gao, Wei, Hendrickson, Timothy J., Howell, Brittany R., Huang, Hao, Humphreys, Kathryn L., Riggins, Tracy, Sylvester, Chad M., Weldon, Kimberly B., Yacoub, Essa, Ahtam, Banu, Beck, Natacha, Banerjee, Suchandrima, Boroday, Sergiy, Caprihan, Arvind, Caron, Bryan, Carpenter, Samuel, Chang, Yulin, Chung, Ai Wern, Cieslak, Matthew, Clarke, William T., Dale, Anders, Das, Samir, Davies-Jenkins, Christopher W., Dufford, Alexander J., Evans, Alan C., Fesselier, Laetitia, Ganji, Sandeep K., Gilbert, Guillaume, Graham, Alice M., Gudmundson, Aaron T., Macgregor-Hannah, Maren, Harms, Michael P., Hilbert, Tom, Hui, Steve C.N., Irfanoglu, M. Okan, Kecskemeti, Steven, Kober, Tobias, Kuperman, Joshua M., Lamichhane, Bidhan, Landman, Bennett A., Lecour-Bourcher, Xavier, Lee, Erik G., Li, Xu, MacIntyre, Leigh, Madjar, Cecile, Manhard, Mary Kate, Mayer, Andrew R., Mehta, Kahini, Moore, Lucille A., Murali-Manohar, Saipavitra, Navarro, Cristian, Nebel, Mary Beth, Newman, Sharlene D., Newton, Allen T., Noeske, Ralph, Norton, Elizabeth S., Oeltzschner, Georg, Ongaro-Carcy, Regis, Ou, Xiawei, Ouyang, Minhui, Parrish, Todd B., Pekar, James J., Pengo, Thomas, Pierpaoli, Carlo, Poldrack, Russell A., Rajagopalan, Vidya, Rettmann, Dan W., Rioux, Pierre, Rosenberg, Jens T., Salo, Taylor, Satterthwaite, Theodore D., Scott, Lisa S., Shin, Eunkyung, Simegn, Gizeaddis, Simmons, W. Kyle, Song, Yulu, Tikalsky, Barry J., Tkach, Jean, van Zijl, Peter C.M., Vannest, Jennifer, Versluis, Maarten, Zhao, Yansong, Zöllner, Helge J., Fair, Damien A., Smyser, Christopher D., and Elison, Jed T.

Published
2024
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3. Stability and Localization of inter-individual differences in functional connectivity

Author

Airan, Raag D., Vogelstein, Joshua T., Pillai, Jay J., Caffo, Brian, Pekar, James J., and Sair, Haris I.

Subjects
Statistics - Applications, Quantitative Biology - Neurons and Cognition
Abstract

Much recent attention has been paid to quantifying anatomic and functional neuroimaging on the individual subject level. For optimal individual subject characterization, specific acquisition and analysis features need to be identified that maximize inter-individual variability while concomitantly minimizing intra-subject variability. Here we develop a non-parametric statistical metric that quantifies the degree to which a parameter set allows this individual subject differentiation. We apply this metric to analyzing publicly available test-retest resting-state fMRI (rs-fMRI) data sets. We find that for the question of maximizing individual differentiation, there is a relative tradeoff between increasing sampling through increased sampling frequency or increased acquisition time; that for the sizes of the interrogated data sets, only 4-5 min of acquisition time is necessary to perfectly differentiate each subject; and that brain regions that most contribute to individuals unique characterization lie in association cortices thought to contribute to higher cognitive function. These findings may guide optimal rs-fMRI experiment design and may aid elucidation of the neural bases for subject-to-subject differences., Comment: 14 pages, 5 figures

Published
2015

4. Improving Reliability of Subject-Level Resting-State fMRI Parcellation with Shrinkage Estimators

Author

Mejia, Amanda F., Nebel, Mary Beth, Shou, Haochang, Crainiceanu, Ciprian M., Pekar, James J., Mostofsky, Stewart, Caffo, Brian, and Lindquist, Martin A.

Subjects
Statistics - Methodology
Abstract

A recent interest in resting state functional magnetic resonance imaging (rsfMRI) lies in subdividing the human brain into anatomically and functionally distinct regions of interest. For example, brain parcellation is often used for defining the network nodes in connectivity studies. While inference has traditionally been performed on group-level data, there is a growing interest in parcellating single subject data. However, this is difficult due to the low signal-to-noise ratio of rsfMRI data, combined with typically short scan lengths. A large number of brain parcellation approaches employ clustering, which begins with a measure of similarity or distance between voxels. The goal of this work is to improve the reproducibility of single-subject parcellation using shrinkage estimators of such measures, allowing the noisy subject-specific estimator to "borrow strength" in a principled manner from a larger population of subjects. We present several empirical Bayes shrinkage estimators and outline methods for shrinkage when multiple scans are not available for each subject. We perform shrinkage on raw intervoxel correlation estimates and use both raw and shrinkage estimates to produce parcellations by performing clustering on the voxels. Our proposed method is agnostic to the choice of clustering method and can be used as a pre-processing step for any clustering algorithm. Using two datasets---a simulated dataset where the true parcellation is known and is subject-specific and a test-retest dataset consisting of two 7-minute rsfMRI scans from 20 subjects---we show that parcellations produced from shrinkage correlation estimates have higher reliability and validity than those produced from raw estimates. Application to test-retest data shows that using shrinkage estimators increases the reproducibility of subject-specific parcellations of the motor cortex by up to 30%., Comment: body 21 pages, 11 figures

Published
2014

6. Homotopic Group ICA for Multi-Subject Brain Imaging Data

Author

Yang, Juemin, Eloyan, Ani, Barber, Anita, Nebel, Mary Beth, Mostofsky, Stewart, Pekar, James J., Crainiceanu, Ciprian, and Caffo, Brian

Subjects
Statistics - Applications
Abstract

Independent Component Analysis (ICA) is a computational technique for revealing latent factors that underlie sets of measurements or signals. It has become a standard technique in functional neuroimaging. In functional neuroimaging, so called group ICA (gICA) seeks to identify and quantify networks of correlated regions across subjects. This paper reports on the development of a new group ICA approach, Homotopic Group ICA (H-gICA), for blind source separation of resting state functional magnetic resonance imaging (fMRI) data. Resting state brain functional homotopy is the similarity of spontaneous fluctuations between bilaterally symmetrically opposing regions (i.e. those symmetric with respect to the mid-sagittal plane) (Zuo et al., 2010). The approach we proposed improves network estimates by leveraging this known brain functional homotopy. H-gICA increases the potential for network discovery, effectively by averaging information across hemispheres. It is theoretically proven to be identical to standard group ICA when the true sources are both perfectly homotopic and noise-free, while simulation studies and data explorations demonstrate its benefits in the presence of noise. Moreover, compared to commonly applied group ICA algorithms, the structure of the H-gICA input data leads to significant improvement in computational efficiency. A simulation study comfirms its effectiveness in homotopic, non-homotopic and mixed settings, as well as on the landmark ADHD-200 dataset. From a relatively small subset of data, several brain networks were found including: the visual, the default mode and auditory networks, as well as others. These were shown to be more contiguous and clearly delineated than the corresponding ordinary group ICA. Finally, in addition to improving network estimation, H-gICA facilitates the investigation of functional homotopy via ICA-based networks., Comment: 35 pages, 13 figures

Published
2013

21. Differential Laminar Activation Dissociates Encoding and Retrieval in the Human Medial and Lateral Entorhinal Cortex.

Author

Kaihua Zhang, Liuyi Chen, Yinghao Li, Paez, Adrian G., Xinyuan Miao, Di Cao, Chunming Gu, Pekar, James J., van Zijl, Peter C. M., Jun Hua, and Bakker, Arnold

Subjects
ENTORHINAL cortex, TEMPORAL lobe, FUNCTIONAL magnetic resonance imaging, EPISODIC memory, ENCODING, MEMORY disorders
Abstract

The hierarchically organized structures of the medial temporal lobe are critically important for episodic memory function. Accumulating evidence suggests dissociable information processing pathways are maintained throughout these structures including in the medial and lateral entorhinal cortex. Cortical layers provide an additional dimension of dissociation as the primary input to the hippocampus derives from layer 2 neurons in the entorhinal cortex, whereas the deeper layers primarily receive output from the hippocampus. Here, novel high-resolution T2-prepared functional MRI methods were successfully used to mitigate susceptibility artifacts typically affecting MRI signals in this region providing uniform sensitivity across the medial and lateral entorhinal cortex. During the performance of a memory task, healthy human subjects (age 25-33 years, mean age 28.2 ± 3.3 years, 4 female) showed differential functional activation in the superficial and deep layers of the entorhinal cortex associated with task-related encoding and retrieval conditions, respectively. The methods provided here offer an approach to probe layer-specific activation in normal cognition and conditions contributing to memory impairment. [ABSTRACT FROM AUTHOR]

Published
2023
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24. Functional and Structural Brain Connectivity in Children With Bilateral Cerebral Palsy Compared to Age-Related Controls and in Response to Intensive Rapid-Reciprocal Leg Training

Author

Damiano, Diane L., primary, Pekar, James J., additional, Mori, Susumu, additional, Faria, Andreia Vasconcellos, additional, Ye, X., additional, Stashinko, Elaine, additional, Stanley, Christopher J., additional, Alter, Katharine E., additional, Hoon, Alec H., additional, and Chin, Eric M., additional

Published
2022
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26. Toward discovery science of human brain function

Author

Biswal, Bharat B., Mennes, Maarten, Zuo, Xi-Nian, Gohel, Suril, Kelly, Clare, Smith, Steve M., Beckmann, Christian F., Adelstein, Jonathan S., Buckner, Randy L., Colcombe, Stan, Dogonowski, Anne-Marie, Ernst, Monique, Fair, Damien, Hampson, Michelle, Hoptman, Matthew J., Hyde, James S., Kiviniemi, Vesa J., Kötter, Rolf, Li, Shi-Jiang, Lin, Ching-Po, Lowe, Mark J., Mackay, Clare, Madden, David J., Madsen, Kristoffer H., Margulies, Daniel S., Mayberg, Helen S., McMahon, Katie, Monk, Christopher S., Mostofsky, Stewart H., Nagel, Bonnie J., Pekar, James J., Peltier, Scott J., Petersen, Steven E., Riedl, Valentin, Rombouts, Serge A. R. B., Rypma, Bart, Schlaggar, Bradley L., Schmidt, Sein, Seidler, Rachael D., Siegle, Greg J., Sorg, Christian, Teng, Gao-Jun, Veijola, Juha, Villringer, Arno, Walter, Martin, Wang, Lihong, Weng, Xu-Chu, Whitfield-Gabrieli, Susan, Williamson, Peter, Windischberger, Christian, Zang, Yu-Feng, Zhang, Hong-Ying, Castellanos, F. Xavier, Milham, Michael P., and Raichle, Marcus E.

Published
2010

48. Functional magnetic resonance imaging evidence for abnormalities in response selection in attention deficit hyperactivity disorder: differences in activation associated with response inhibition but not habitual motor response

Author

Suskauer, Stacy J., Simmonds, Daniel J., Fotedar, Sunaina, Blankner, Joanna G., Pekar, James J., Denckla, Martha B., and Mostofsky, Stewart H.

Subjects
Magnetic resonance imaging -- Methods, Attention-deficit hyperactivity disorder -- Physiological aspects, Reaction time -- Observations, Inhibition (Neurophysiology) -- Influence, Health, Psychology and mental health
Published
2008

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