Medicine and Health Sciences Commons^™

Multi-Site Benchmark Classification Of Major Depressive Disorder Using Machine Learning On Cortical And Subcortical Measures, Vladimir Belov, Tracy Erwin-Grabner, Moji Aghajani, Andre Aleman, Alyssa R Amod, Zeynep Basgoze, Francesco Benedetti, Bianca Besteher, Robin Bülow, Christopher R K Ching, Colm G Connolly, Kathryn Cullen, Christopher G Davey, Danai Dima, Annemiek Dols, Jennifer W Evans, Cynthia H Y Fu, Ali Saffet Gonul, Ian H Gotlib, Hans J Grabe, Nynke Groenewold, J Paul Hamilton, Ben J Harrison, Tiffany C Ho, Benson Mwangi, Natalia Jaworska, Neda Jahanshad, Bonnie Klimes-Dougan, Sheri-Michelle Koopowitz, Thomas Lancaster, Meng Li, David E J Linden, Frank P Macmaster, David M A Mehler, Elisa Melloni, Bryon A Mueller, Amar Ojha, Mardien L Oudega, Brenda W J H Penninx, Sara Poletti, Edith Pomarol-Clotet, Maria J Portella, Elena Pozzi, Liesbeth Reneman, Matthew D Sacchet, Philipp G Sämann, Anouk Schrantee, Kang Sim, Jair C Soares, Dan J Stein, Sophia I Thomopoulos, Aslihan Uyar-Demir, Nic J A Van Der Wee, Steven J A Van Der Werff, Henry Völzke, Sarah Whittle, Katharina Wittfeld, Margaret J Wright, Mon-Ju Wu, Tony T Yang, Carlos Zarate, Dick J Veltman, Lianne Schmaal, Paul M Thompson, Roberto Goya-Maldonado, Enigma Major Depressive Disorder Working Group

Student and Faculty Publications

Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy …

Delineating The Mechanism Of Fragility At Bcl6 Breakpoint Region Associated With Translocations In Diffuse Large B Cell Lymphoma, Vidya Gopalakrishnan, Urbi Roy, Shikha Srivastava, Khyati M Kariya, Shivangi Sharma, Saniya M Javedakar, Bibha Choudhary, Sathees C Raghavan

Student and Faculty Publications

BCL6 translocation is one of the most common chromosomal translocations in cancer and results in its enhanced expression in germinal center B cells. It involves the fusion of BCL6 with any of its twenty-six Ig and non-Ig translocation partners associated with diffuse large B cell lymphoma (DLBCL). Despite being discovered long back, the mechanism of BCL6 fragility is largely unknown. Analysis of the translocation breakpoints in 5' UTR of BCL6 reveals the clustering of most of the breakpoints around a region termed Cluster II. In silico analysis of the breakpoint cluster sequence identified sequence motifs that could potentially fold into …

Gene-Sgan: Discovering Disease Subtypes With Imaging And Genetic Signatures Via Multi-View Weakly-Supervised Deep Clustering, Zhijian Yang, John C Morris, Pamela Lamontagne, Daniel S Marcus, Tammie L S Benzinger, Et Al.

2020-Current year OA Pubs

Disease heterogeneity has been a critical challenge for precision diagnosis and treatment, especially in neurologic and neuropsychiatric diseases. Many diseases can display multiple distinct brain phenotypes across individuals, potentially reflecting disease subtypes that can be captured using MRI and machine learning methods. However, biological interpretability and treatment relevance are limited if the derived subtypes are not associated with genetic drivers or susceptibility factors. Herein, we describe Gene-SGAN - a multi-view, weakly-supervised deep clustering method - which dissects disease heterogeneity by jointly considering phenotypic and genetic data, thereby conferring genetic correlations to the disease subtypes and associated endophenotypic signatures. We first …

Inhibiting Metabotropic Glutamate Receptor 5 After Stroke Restores Brain Function And Connectivity, Jakob Hakon, Miriana J Quattromani, Carin Sjölund, Daniela Talhada, Byungchan Kim, Slavianka Moyanova, Federica Mastroiacovo, Luisa Di Menna, Roger Olsson, Elisabet Englund, Ferdinando Nicoletti, Karsten Ruscher, Adam Q Bauer, Tadeusz Wieloch

2020-Current year OA Pubs

Stroke results in local neural disconnection and brain-wide neuronal network dysfunction leading to neurological deficits. Beyond the hyper-acute phase of ischaemic stroke, there is no clinically-approved pharmacological treatment that alleviates sensorimotor impairments. Functional recovery after stroke involves the formation of new or alternative neuronal circuits including existing neural connections. The type-5 metabotropic glutamate receptor (mGluR5) has been shown to modulate brain plasticity and function and is a therapeutic target in neurological diseases outside of stroke. We investigated whether mGluR5 influences functional recovery and network reorganization rodent models of focal ischaemia. Using multiple behavioural tests, we observed that treatment with negative …

Neurosteroids: Mechanistic Considerations And Clinical Prospects, Jamie L Maguire, Steven Mennerick

2020-Current year OA Pubs

Like other classes of treatments described in this issue's section, neuroactive steroids have been studied for decades but have risen as a new class of rapid-acting, durable antidepressants with a distinct mechanism of action from previous antidepressant treatments and from other compounds covered in this issue. Neuroactive steroids are natural derivatives of progesterone but are proving effective as exogenous treatments. The best understood mechanism is that of positive allosteric modulation of GABA

Automatic Hemorrhage Segmentation In Brain Ct Scans Using Curriculum-Based Semi-Supervised Learning, Solayman H. Emon, Tzu-Liang (Bill) Tseng, Michael Pokojovy, Peter Mccaffrey, Scott Moen, Md Fashiar Rahman

Mathematics & Statistics Faculty Publications

One of the major neuropathological consequences of traumatic brain injury (TBI) is intracranial hemorrhage (ICH), which requires swift diagnosis to avert perilous outcomes. We present a new automatic hemorrhage segmentation technique via curriculum-based semi-supervised learning. It employs a pre-trained lightweight encoder-decoder framework (MobileNetV2) on labeled and unlabeled data. The model integrates consistency regularization for improved generalization, offering steady predictions from original and augmented versions of unlabeled data. The training procedure employs curriculum learning to progressively train the model at diverse complexity levels. We utilize the PhysioNet dataset to train and evaluate the proposed approach. The performance results surpass those of …

A Global Multicohort Study To Map Subcortical Brain Development And Cognition In Infancy And Early Childhood, Ann M Alex, Kelly Botteron, Et Al.

2020-Current year OA Pubs

The human brain grows quickly during infancy and early childhood, but factors influencing brain maturation in this period remain poorly understood. To address this gap, we harmonized data from eight diverse cohorts, creating one of the largest pediatric neuroimaging datasets to date focused on birth to 6 years of age. We mapped the developmental trajectory of intracranial and subcortical volumes in ∼2,000 children and studied how sociodemographic factors and adverse birth outcomes influence brain structure and cognition. The amygdala was the first subcortical volume to mature, whereas the thalamus exhibited protracted development. Males had larger brain volumes than females, and …

Expanding Awareness Of Tbi Resources In The North Country, Nicholas W. Krant

Family Medicine Clerkship Student Projects

Disability, emotional dysregulation and financial stress are only some of the issues that many patients who suffer TBI encounter. While resources are available to alleviate some of these burdens on patients who suffer TBI in New York's North Country, patients often struggle to find these resources. This project endeavors to create a resource for patients, family members and practitioners to find available resources.

Colonial Drivers And Cultural Protectors Of Brain Health Among Indigenous Peoples Internationally, Rita Henderson, Joyla A Furlano, Shayla Scott Claringbold, Ashley Cornect-Benoit, Anh Ly, Jennifer Walker, Lisa Zaretsky, Pamela Roach

Student and Faculty Publications

Despite relatively higher rates of dementia among Indigenous populations internationally, research into drivers of disparities in brain health and cognitive function has tended to focus on modifiable risk factors over cultural understandings and contextual determinants. By seeking to characterize social and cultural factors that shape brain health and cognition in Indigenous populations, this mini scoping review expands prevailing schools of thought to include Indigenous knowledge systems. This reveals important gaps in culturally aligned care. It also reclaims horizons for research important to Indigenous Peoples that have garnered diminished attention in biomedical approaches. Twenty-three sources were included for data extraction. This …

The Emerging Importance Of Skull-Brain Interactions In Traumatic Brain Injury, Grant W Goodman, Patrick Devlin, Bryce E West, Rodney M Ritzel

Student and Faculty Publications

The recent identification of skull bone marrow as a reactive hematopoietic niche that can contribute to and direct leukocyte trafficking into the meninges and brain has transformed our view of this bone structure from a solid, protective casing to a living, dynamic tissue poised to modulate brain homeostasis and neuroinflammation. This emerging concept may be highly relevant to injuries that directly impact the skull such as in traumatic brain injury (TBI). From mild concussion to severe contusion with skull fracturing, the bone marrow response of this local myeloid cell reservoir has the potential to impact not just the acute inflammatory …

The Contribution Of Age-Related Changes In The Gut-Brain Axis To Neurological Disorders, Romeesa Khan, Claudia M Di Gesù, Juneyoung Lee, Louise D Mccullough

Student and Faculty Publications

Trillions of microbes live symbiotically in the host, specifically in mucosal tissues such as the gut. Recent advances in metagenomics and metabolomics have revealed that the gut microbiota plays a critical role in the regulation of host immunity and metabolism, communicating through bidirectional interactions in the microbiota-gut-brain axis (MGBA). The gut microbiota regulates both gut and systemic immunity and contributes to the neurodevelopment and behaviors of the host. With aging, the composition of the microbiota changes, and emerging studies have linked these shifts in microbial populations to age-related neurological diseases (NDs). Preclinical studies have demonstrated that gut microbiota-targeted therapies can …

Anesthetized Animal Experiments For Neuroscience Research, Shin Nagayama, Sanae Hasegawa-Ishii, Shu Kikuta

Student and Faculty Publications

Brain research has progressed with anesthetized animal experiments for a long time. Recent progress in research techniques allows us to measure neuronal activity in awake animals combined with behavioral tasks. The trends became more prominent in the last decade. This new research style triggers the paradigm shift in the research of brain science, and new insights into brain function have been revealed. It is reasonable to consider that awake animal experiments are more ideal for understanding naturalistic brain function than anesthetized ones. However, the anesthetized animal experiment still has advantages in some experiments. To take advantage of the anesthetized animal …

Accuracy Of True-Net In Comparison To Established White Matter Hyperintensity Segmentation Methods: An Independent Validation Study, Jeremy F Strain, Maryam Rahmani, Donna Dierker, Christopher Owen, Hussain Jafri, Andrei G Vlassenko, Kyle Womack, Jurgen Fripp, Duygu Tosun, Tammie L S Benzinger, Michael Weiner, Colin Masters, Jin-Moo Lee, John C Morris, Manu S Goyal, Adopic And Adni Investigators

2020-Current year OA Pubs

White matter hyperintensities (WMH) are nearly ubiquitous in the aging brain, and their topography and overall burden are associated with cognitive decline. Given their numerosity, accurate methods to automatically segment WMH are needed. Recent developments, including the availability of challenge data sets and improved deep learning algorithms, have led to a new promising deep-learning based automated segmentation model called TrUE-Net, which has yet to undergo rigorous independent validation. Here, we compare TrUE-Net to six established automated WMH segmentation tools, including a semi-manual method. We evaluated the techniques at both global and regional level to compare their ability to detect the …

Accuracy Of True-Net In Comparison To Established White Matter Hyperintensity Segmentation Methods: An Independent Validation Study, Jeremy F Strain, Maryam Rahmani, Donna Dierker, Christopher Owen, Hussain Jafri, Andrei G Vlassenko, Kyle Womack, Jurgen Fripp, Duygu Tosun, Tammie L S Benzinger, Michael Weiner, Colin Masters, Jin-Moo Lee, John C Morris, Manu S Goyal, Adopic And Adni Investigators

2020-Current year OA Pubs

White matter hyperintensities (WMH) are nearly ubiquitous in the aging brain, and their topography and overall burden are associated with cognitive decline. Given their numerosity, accurate methods to automatically segment WMH are needed. Recent developments, including the availability of challenge data sets and improved deep learning algorithms, have led to a new promising deep-learning based automated segmentation model called TrUE-Net, which has yet to undergo rigorous independent validation. Here, we compare TrUE-Net to six established automated WMH segmentation tools, including a semi-manual method. We evaluated the techniques at both global and regional level to compare their ability to detect the …

Role Of Surgery In The Prognosis Of Pediatric Thalamic Tumors, Mohamed Khaled Eissa, Mohamed Elbeltagy, Hesham Abou-Rahma, Hazem Mohamed Negm, Ahmed Said Mansour, Yasser Bahgat Elsisi

Menoufia Medical Journal

Objective: This study aimed to present the authors' experience in managing 20 cases of pediatric thalamic brain tumors. Background: Thalamic tumors constitute a small percentage (approximately 0.84-5.2%) of all brain tumors and are even rarer in the pediatric population, accounting for about 2-5% of pediatric brain tumors. These tumors present a significant challenge to neurosurgeons due to their intricate location within the brain and their proximity to crucial structures, especially in children. The management of these tumors necessitates careful consideration and expertise due to the potential risks associated with their critical position. Patients and Methods: In this retrospective study, the …

Influence Of Beta And Theta Waves As Predictors Of Simple And Complex Reaction Times In Examined Groups Of Judo Athletes During The Vienna Test, Magdalena Pronczuk, Tomasz Chamera, Alicja Markiel, Jerzy Markowski, Jan Pilch, Piotr Żmijewski, Adam Maszczyk

Baltic Journal of Health and Physical Activity

Introduction: This research aimed to investigate which waves, Theta or Beta, are significant predictors of visual simple and complex reaction times during the Vienna test, using regression modeling. The research material comprised the test results of male judo athletes (n = 24), selected through mixed sampling (purposive and random). The study was conducted in two cycles, differentiated by frequency but with the same duration of EEG biofeedback sessions, in both the control and experimental groups. The first cycle of the study consisted of 15 sessions held every other day. Each training session lasted for 4 minutes. The second series …

Genomic Loci Influence Patterns Of Structural Covariance In The Human Brain, Junhao Wen, Aristeidis Sotiras, Daniel S Marcus, Pamela Lamontagne, John C Morris, Et Al.

2020-Current year OA Pubs

Normal and pathologic neurobiological processes influence brain morphology in coordinated ways that give rise to patterns of structural covariance (PSC) across brain regions and individuals during brain aging and diseases. The genetic underpinnings of these patterns remain largely unknown. We apply a stochastic multivariate factorization method to a diverse population of 50,699 individuals (12 studies and 130 sites) and derive data-driven, multi-scale PSCs of regional brain size. PSCs were significantly correlated with 915 genomic loci in the discovery set, 617 of which are newly identified, and 72% were independently replicated. Key pathways influencing PSCs involve reelin signaling, apoptosis, neurogenesis, and …

Development Of White Matter Fiber Covariance Networks Supports Executive Function In Youth, Joëlle Bagautdinova, Aristeidis Sotiras, Et Al.

2020-Current year OA Pubs

During adolescence, the brain undergoes extensive changes in white matter structure that support cognition. Data-driven approaches applied to cortical surface properties have led the field to understand brain development as a spatially and temporally coordinated mechanism that follows hierarchically organized gradients of change. Although white matter development also appears asynchronous, previous studies have relied largely on anatomical tract-based atlases, precluding a direct assessment of how white matter structure is spatially and temporally coordinated. Harnessing advances in diffusion modeling and machine learning, we identified 14 data-driven patterns of covarying white matter structure in a large sample of youth. Fiber covariance networks …

Advanced Structural Brain Aging In Preclinical Autosomal Dominant Alzheimer Disease, Peter R Millar, Brian A Gordon, Julie K Wisch, Tammie L.S. Benzinger, Carlos Cruchaga, Jason J Hassenstab, Laura Ibanez, Celeste Karch, Jorge J Llibre-Guerra, John C Morris, Richard J Perrin, Charlene Supnet-Bell, Chengjie Xiong, Randall J Bateman, Beau M Ances, Eric M Mcdade, Et Al.

2020-Current year OA Pubs

BACKGROUND: "Brain-predicted age" estimates biological age from complex, nonlinear features in neuroimaging scans. The brain age gap (BAG) between predicted and chronological age is elevated in sporadic Alzheimer disease (AD), but is underexplored in autosomal dominant AD (ADAD), in which AD progression is highly predictable with minimal confounding age-related co-pathology.

METHODS: We modeled BAG in 257 deeply-phenotyped ADAD mutation-carriers and 179 non-carriers from the Dominantly Inherited Alzheimer Network using minimally-processed structural MRI scans. We then tested whether BAG differed as a function of mutation and cognitive status, or estimated years until symptom onset, and whether it was associated with established …

Dna Methylation-Based Epigenetic Biomarkers In Cell-Type Deconvolution And Tumor Tissue Of Origin Identification, Ze Zhang

Dartmouth College Ph.D Dissertations

DNA methylation is an epigenetic modification that regulates gene expression and is essential to establishing and preserving cellular identity. Genome-wide DNA methylation arrays provide a standardized and cost-effective approach to measuring DNA methylation. When combined with a cell-type reference library, DNA methylation measures allow the assessment of underlying cell-type proportions in heterogeneous mixtures. This approach, known as DNA methylation deconvolution or methylation cytometry, offers a standardized and cost-effective method for evaluating cell-type proportions. While this approach has succeeded in discerning cell types in various human tissues like blood, brain, tumors, skin, breast, and buccal swabs, the existing methods have major …

Chromosome 10q2432 Variants Associate With Brain Arterial Diameters In Diverse Populations: A Genome-Wide Association Study, Minghua Liu, Farid Khasiyev, Sanjeev Sariya, Antonio Spagnolo-Allende, Danurys L Sanchez, Howard Andrews, Qiong Yang, Alexa Beiser, Ye Qiao, Emy A Thomas, Jose Rafael Romero, Tatjana Rundek, Adam M Brickman, Jennifer J Manly, Mitchell Sv Elkind, Sudha Seshadri, Christopher Chen, Saima Hilal, Bruce A Wasserman, Giuseppe Tosto, Myriam Fornage, Jose Gutierrez

Student and Faculty Publications

BACKGROUND: Brain arterial diameters (BADs) are novel imaging biomarkers of cerebrovascular disease, cognitive decline, and dementia. Traditional vascular risk factors have been associated with BADs, but whether there may be genetic determinants of BADs is unknown.

METHODS AND RESULTS: The authors studied 4150 participants from 6 geographically diverse population-based cohorts (40% European, 14% African, 22% Hispanic, 24% Asian ancestries). Brain arterial diameters for 13 segments were measured and averaged to obtain a global measure of BADs as well as the posterior and anterior circulations. A genome-wide association study revealed 14 variants at one locus associated with global BAD at genome-wide …

Maternal Diet During Early Gestation Influences Postnatal Taste Activity-Dependent Pruning By Microglia, Chengsan Sun, Shuqiu Zheng, Justin S A Perry, Geoffrey T Norris, Mei Cheng, Fanzhen Kong, Rolf Skyberg, Jianhua Cang, Alev Erisir, Jonathan Kipnis, David L Hill

2020-Current year OA Pubs

A key process in central sensory circuit development involves activity-dependent pruning of exuberant terminals. Here, we studied gustatory terminal field maturation in the postnatal mouse nucleus of the solitary tract (NST) during normal development and in mice where their mothers were fed a low NaCl diet for a limited period soon after conception. Pruning of terminal fields of gustatory nerves in controls involved the complement system and is likely driven by NaCl-elicited taste activity. In contrast, offspring of mothers with an early dietary manipulation failed to prune gustatory terminal fields even though peripheral taste activity developed normally. The ability to …

Plasma Exchange Reduces Aβ Levels In Plasma And Decreases Amyloid Plaques In The Brain In A Mouse Model Of Alzheimer's Disease, Santiago Ramirez, Suelyn Koerich, Natalia Astudillo, Nicole De Gregorio, Rabab Al-Lahham, Tyler Allison, Natalia Pessoa Rocha, Fei Wang, Claudio Soto

Student and Faculty Publications

Alzheimer's disease (AD) is the most common type of dementia, characterized by the abnormal accumulation of protein aggregates in the brain, known as neurofibrillary tangles and amyloid-β (Aβ) plaques. It is believed that an imbalance between cerebral and peripheral pools of Aβ may play a relevant role in the deposition of Aβ aggregates. Therefore, in this study, we aimed to evaluate the effect of the removal of Aβ from blood plasma on the accumulation of amyloid plaques in the brain. We performed monthly plasma exchange with a 5% mouse albumin solution in the APP/PS1 mouse model from 3 to 7 …

Identifying Canonical And Replicable Multi-Scale Intrinsic Connectivity Networks In 100k+ Resting-State Fmri Datasets., A Iraji, Z Fu, A Faghiri, M Duda, J Chen, S Rachakonda, T Deramus, P Kochunov, B M Adhikari, A Belger, J M Ford, D H Mathalon, G D Pearlson, S G Potkin, A Preda, J A Turner, T G M Van Erp, J R Bustillo, K Yang, K Ishizuka, A Faria, A Sawa, K Hutchison, E A Osuch, Jean Theberge, C Abbott, B A Mueller, D Zhi, C Zhuo, S Liu, Y Xu, M Salman, J Liu, Y Du, J Sui, T Adali, V D Calhoun

Department of Medicine Publications

Despite the known benefits of data-driven approaches, the lack of approaches for identifying functional neuroimaging patterns that capture both individual variations and inter-subject correspondence limits the clinical utility of rsfMRI and its application to single-subject analyses. Here, using rsfMRI data from over 100k individuals across private and public datasets, we identify replicable multi-spatial-scale canonical intrinsic connectivity network (ICN) templates via the use of multi-model-order independent component analysis (ICA). We also study the feasibility of estimating subject-specific ICNs via spatially constrained ICA. The results show that the subject-level ICN estimations vary as a function of the ICN itself, the data length, …

Enlarged Perivascular Spaces In Infancy And Autism Diagnosis, Cerebrospinal Fluid Volume, And Later Sleep Problems, Dea Garic, Robert C Mckinstry, Kelly N Botteron, Et Al.

2020-Current year OA Pubs

IMPORTANCE: Perivascular spaces (PVS) and cerebrospinal fluid (CSF) are essential components of the glymphatic system, regulating brain homeostasis and clearing neural waste throughout the lifespan. Enlarged PVS have been implicated in neurological disorders and sleep problems in adults, and excessive CSF volume has been reported in infants who develop autism. Enlarged PVS have not been sufficiently studied longitudinally in infancy or in relation to autism outcomes or CSF volume.

OBJECTIVE: To examine whether enlarged PVS are more prevalent in infants who develop autism compared with controls and whether they are associated with trajectories of extra-axial CSF volume (EA-CSF) and sleep …

Single-Cell Analysis Of Chromatin Accessibility In The Adult Mouse Brain, Songpeng Zu, Yang Eric Li, Et Al.

2020-Current year OA Pubs

Recent advances in single-cell technologies have led to the discovery of thousands of brain cell types; however, our understanding of the gene regulatory programs in these cell types is far from complete

Isoform-Level Transcriptome-Wide Association Uncovers Genetic Risk Mechanisms For Neuropsychiatric Disorders In The Human Brain, Arjun Bhattacharya, Daniel D Vo, Connor Jops, Minsoo Kim, Cindy Wen, Jonatan L Hervoso, Bogdan Pasaniuc, Michael J Gandal

Student and Faculty Publications

Methods integrating genetics with transcriptomic reference panels prioritize risk genes and mechanisms at only a fraction of trait-associated genetic loci, due in part to an overreliance on total gene expression as a molecular outcome measure. This challenge is particularly relevant for the brain, in which extensive splicing generates multiple distinct transcript-isoforms per gene. Due to complex correlation structures, isoform-level modeling from cis-window variants requires methodological innovation. Here we introduce isoTWAS, a multivariate, stepwise framework integrating genetics, isoform-level expression and phenotypic associations. Compared to gene-level methods, isoTWAS improves both isoform and gene expression prediction, yielding more testable genes, and increased power …

Neuroimaging-Based Classification Of Ptsd Using Data-Driven Computational Approaches: A Multisite Big Data Study From The Enigma-Pgc Ptsd Consortium., Xi Zhu, Yoojean Kim, Orren Ravid, Xiaofu He, Benjamin Suarez-Jimenez, Sigal Zilcha-Mano, Amit Lazarov, Seonjoo Lee, Chadi G Abdallah, Michael Angstadt, Christopher L Averill, C Lexi Baird, Lee A Baugh, Jennifer U Blackford, Jessica Bomyea, Steven E Bruce, Richard A Bryant, Zhihong Cao, Kyle Choi, Josh Cisler, Andrew S Cotton, Judith K Daniels, Nicholas D Davenport, Richard J Davidson, Michael D Debellis, Emily L Dennis, Maria Densmore, Terri Deroon-Cassini, Seth G Disner, Wissam El Hage, Amit Etkin, Negar Fani, Kelene A Fercho, Jacklynn Fitzgerald, Gina L Forster, Jessie L Frijling, Elbert Geuze, Atilla Gonenc, Evan M Gordon, Staci Gruber, Daniel W Grupe, Jeffrey P Guenette, Courtney C Haswell, Ryan J Herringa, Julia Herzog, David Bernd Hofmann, Bobak Hosseini, Anna R Hudson, Ashley A Huggins, Jonathan C Ipser, Neda Jahanshad, Meilin Jia-Richards, Tanja Jovanovic, Milissa L Kaufman, Mitzy Kennis, Anthony King, Philipp Kinzel, Saskia B J Koch, Inga K Koerte, Sheri M Koopowitz, Mayuresh S Korgaonkar, John H Krystal, Ruth Lanius, Christine L Larson, Lauren A M Lebois, Gen Li, Israel Liberzon, Guang Ming Lu, Yifeng Luo, Vincent A Magnotta, Antje Manthey, Adi Maron-Katz, Geoffery May, Katie Mclaughlin, Sven C Mueller, Laura Nawijn, Steven M Nelson, Richard W J Neufeld, Jack B Nitschke, Erin M O'Leary, Bunmi O Olatunji, Miranda Olff, Matthew Peverill, K Luan Phan, Rongfeng Qi, Yann Quidé, Ivan Rektor, Kerry Ressler, Pavel Riha, Marisa Ross, Isabelle M Rosso, Lauren E Salminen, Kelly Sambrook, Christian Schmahl, Martha E Shenton, Margaret Sheridan, Chiahao Shih, Maurizio Sicorello, Anika Sierk, Alan N Simmons, Raluca M Simons, Jeffrey S Simons, Scott R Sponheim, Murray B Stein, Dan J Stein, Jennifer S Stevens, Thomas Straube, Delin Sun, Jean Theberge, Paul M Thompson, Sophia I Thomopoulos, Nic J A Van Der Wee, Steven J A Van Der Werff, Theo G M Van Erp, Sanne J H Van Rooij, Mirjam Van Zuiden, Tim Varkevisser, Dick J Veltman, Robert R J M Vermeiren, Henrik Walter, Li Wang, Xin Wang, Carissa Weis, Sherry Winternitz, Hong Xie, Ye Zhu, Melanie Wall, Yuval Neria, Rajendra A Morey

Department of Medicine Publications

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group.

METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls …

Neuroimaging-Based Classification Of Ptsd Using Data-Driven Computational Approaches: A Multisite Big Data Study From The Enigma-Pgc Ptsd Consortium, Xi Zhu, Evan M Gordon, Et Al.

2020-Current year OA Pubs

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group.

METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls …

Denoising Task-Related Fmri: Balancing Noise Reduction Against Signal Loss, M E Hoeppli, M A Garenfeld, C K Mortensen, H Nahman-Averbuch, C D King, R C Coghill

2020-Current year OA Pubs

Preprocessing fMRI data requires striking a fine balance between conserving signals of interest and removing noise. Typical steps of preprocessing include motion correction, slice timing correction, spatial smoothing, and high-pass filtering. However, these standard steps do not remove many sources of noise. Thus, noise-reduction techniques, for example, CompCor, FIX, and ICA-AROMA have been developed to further improve the ability to draw meaningful conclusions from the data. The ability of these techniques to minimize noise while conserving signals of interest has been tested almost exclusively in resting-state fMRI and, only rarely, in task-related fMRI. Application of noise-reduction techniques to task-related fMRI …