Search

Your search keyword '"Fox, Peter T"' showing total 1,869 results
Start Over Author "Fox, Peter T"
1,869 results on '"Fox, Peter T"'

2. Deep neural network heatmaps capture Alzheimer's disease patterns reported in a large meta-analysis of neuroimaging studies

Author

Wang, Di, Honnorat, Nicolas, Fox, Peter T., Ritter, Kerstin, Eickhoff, Simon B., Seshadri, Sudha, and Habes, Mohamad

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Deep neural networks currently provide the most advanced and accurate machine learning models to distinguish between structural MRI scans of subjects with Alzheimer's disease and healthy controls. Unfortunately, the subtle brain alterations captured by these models are difficult to interpret because of the complexity of these multi-layer and non-linear models. Several heatmap methods have been proposed to address this issue and analyze the imaging patterns extracted from the deep neural networks, but no quantitative comparison between these methods has been carried out so far. In this work, we explore these questions by deriving heatmaps from Convolutional Neural Networks (CNN) trained using T1 MRI scans of the ADNI data set, and by comparing these heatmaps with brain maps corresponding to Support Vector Machines (SVM) coefficients. Three prominent heatmap methods are studied: Layer-wise Relevance Propagation (LRP), Integrated Gradients (IG), and Guided Grad-CAM (GGC). Contrary to prior studies where the quality of heatmaps was visually or qualitatively assessed, we obtained precise quantitative measures by computing overlap with a ground-truth map from a large meta-analysis that combined 77 voxel-based morphometry (VBM) studies independently from ADNI. Our results indicate that all three heatmap methods were able to capture brain regions covering the meta-analysis map and achieved better results than SVM coefficients. Among them, IG produced the heatmaps with the best overlap with the independent meta-analysis.

Published
2022

3. Chronic neuropsychiatric sequelae of SARS‐CoV‐2: Protocol and methods from the Alzheimer's Association Global Consortium

Author

Erausquin, Gabriel A, Snyder, Heather, Brugha, Traolach S, Seshadri, Sudha, Carrillo, Maria, Sagar, Rajesh, Huang, Yueqin, Newton, Charles, Tartaglia, Carmela, Teunissen, Charlotte, Håkanson, Krister, Akinyemi, Rufus, Prasad, Kameshwar, D'Avossa, Giovanni, Gonzalez‐Aleman, Gabriela, Hosseini, Akram, Vavougios, George D, Sachdev, Perminder, Bankart, John, Mors, Niels Peter Ole, Lipton, Richard, Katz, Mindy, Fox, Peter T, Katshu, Mohammad Zia, Iyengar, M Sriram, Weinstein, Galit, Sohrabi, Hamid R, Jenkins, Rachel, Stein, Dan J, Hugon, Jacques, Mavreas, Venetsanos, Blangero, John, Cruchaga, Carlos, Krishna, Murali, Wadoo, Ovais, Becerra, Rodrigo, Zwir, Igor, Longstreth, William T, Kroenenberg, Golo, Edison, Paul, Mukaetova‐Ladinska, Elizabeta, Staufenberg, Ekkehart, Figueredo‐Aguiar, Mariana, Yécora, Agustín, Vaca, Fabiana, Zamponi, Hernan P, Re, Vincenzina Lo, Majid, Abdul, Sundarakumar, Jonas, Gonzalez, Hector M, Geerlings, Mirjam I, Skoog, Ingmar, Salmoiraghi, Alberto, Boneschi, Filippo Martinelli, Patel, Vibuthi N, Santos, Juan M, Arroyo, Guillermo Rivera, Moreno, Antonio Caballero, Felix, Pascal, Gallo, Carla, Arai, Hidenori, Yamada, Masahito, Iwatsubo, Takeshi, Sharma, Malveeka, Chakraborty, Nandini, Ferreccio, Catterina, Akena, Dickens, Brayne, Carol, Maestre, Gladys, Blangero, Sarah Williams, Brusco, Luis I, Siddarth, Prabha, Hughes, Timothy M, Zuñiga, Alfredo Ramírez, Kambeitz, Joseph, Laza, Agustin Ruiz, Allen, Norrina, Panos, Stella, Merrill, David, Ibáñez, Agustín, Tsuang, Debby, Valishvili, Nino, Shrestha, Srishti, Wang, Sophia, Padma, Vasantha, Anstey, Kaarin J, Ravindrdanath, Vijayalakshmi, Blennow, Kaj, Mullins, Paul, Łojek, Emilia, Pria, Anand, Mosley, Thomas H, Gowland, Penny, Girard, Timothy D, Bowtell, Richard, and Vahidy, Farhaan S

Subjects
Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Brain Disorders, Alzheimer's Disease, Infectious Diseases, Emerging Infectious Diseases, Clinical Research, Dementia, Neurodegenerative, Prevention, Acquired Cognitive Impairment, Aging, Aetiology, 2.1 Biological and endogenous factors, Neurological, Good Health and Well Being, cognitive impairment, dementia, neuropsychiatric sequelae, predictors, SARS-CoV-2, SARS‐CoV‐2
Abstract

IntroductionCoronavirus disease 2019 (COVID-19) has caused >3.5 million deaths worldwide and affected >160 million people. At least twice as many have been infected but remained asymptomatic or minimally symptomatic. COVID-19 includes central nervous system manifestations mediated by inflammation and cerebrovascular, anoxic, and/or viral neurotoxicity mechanisms. More than one third of patients with COVID-19 develop neurologic problems during the acute phase of the illness, including loss of sense of smell or taste, seizures, and stroke. Damage or functional changes to the brain may result in chronic sequelae. The risk of incident cognitive and neuropsychiatric complications appears independent from the severity of the original pulmonary illness. It behooves the scientific and medical community to attempt to understand the molecular and/or systemic factors linking COVID-19 to neurologic illness, both short and long term.MethodsThis article describes what is known so far in terms of links among COVID-19, the brain, neurological symptoms, and Alzheimer's disease (AD) and related dementias. We focus on risk factors and possible molecular, inflammatory, and viral mechanisms underlying neurological injury. We also provide a comprehensive description of the Alzheimer's Association Consortium on Chronic Neuropsychiatric Sequelae of SARS-CoV-2 infection (CNS SC2) harmonized methodology to address these questions using a worldwide network of researchers and institutions.ResultsSuccessful harmonization of designs and methods was achieved through a consensus process initially fragmented by specific interest groups (epidemiology, clinical assessments, cognitive evaluation, biomarkers, and neuroimaging). Conclusions from subcommittees were presented to the whole group and discussed extensively. Presently data collection is ongoing at 19 sites in 12 countries representing Asia, Africa, the Americas, and Europe.DiscussionThe Alzheimer's Association Global Consortium harmonized methodology is proposed as a model to study long-term neurocognitive sequelae of SARS-CoV-2 infection.Key pointsThe following review describes what is known so far in terms of molecular and epidemiological links among COVID-19, the brain, neurological symptoms, and AD and related dementias (ADRD)The primary objective of this large-scale collaboration is to clarify the pathogenesis of ADRD and to advance our understanding of the impact of a neurotropic virus on the long-term risk of cognitive decline and other CNS sequelae. No available evidence supports the notion that cognitive impairment after SARS-CoV-2 infection is a form of dementia (ADRD or otherwise). The longitudinal methodologies espoused by the consortium are intended to provide data to answer this question as clearly as possible controlling for possible confounders. Our specific hypothesis is that SARS-CoV-2 triggers ADRD-like pathology following the extended olfactory cortical network (EOCN) in older individuals with specific genetic susceptibility.The proposed harmonization strategies and flexible study designs offer the possibility to include large samples of under-represented racial and ethnic groups, creating a rich set of harmonized cohorts for future studies of the pathophysiology, determinants, long-term consequences, and trends in cognitive aging, ADRD, and vascular disease.We provide a framework for current and future studies to be carried out within the Consortium. and offers a "green paper" to the research community with a very broad, global base of support, on tools suitable for low- and middle-income countries aimed to compare and combine future longitudinal data on the topic.The Consortium proposes a combination of design and statistical methods as a means of approaching causal inference of the COVID-19 neuropsychiatric sequelae. We expect that deep phenotyping of neuropsychiatric sequelae may provide a series of candidate syndromes with phenomenological and biological characterization that can be further explored. By generating high-quality harmonized data across sites we aim to capture both descriptive and, where possible, causal associations.

Published
2022

4. Convergent regional brain abnormalities in behavioral variant frontotemporal dementia: A neuroimaging meta‐analysis of 73 studies

Author

Kamalian, Aida, Khodadadifar, Tina, Saberi, Amin, Masoudi, Maryam, Camilleri, Julia A, Eickhoff, Claudia R, Zarei, Mojtaba, Pasquini, Lorenzo, Laird, Angela R, Fox, Peter T, Eickhoff, Simon B, and Tahmasian, Masoud

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Acquired Cognitive Impairment, Clinical Research, Dementia, Neurosciences, Behavioral and Social Science, Brain Disorders, Neurodegenerative, Alzheimer's Disease Related Dementias (ADRD), Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Rare Diseases, Basic Behavioral and Social Science, Frontotemporal Dementia (FTD), Aetiology, 2.1 Biological and endogenous factors, Neurological, activation likelihood estimation, behavioral variant frontotemporal dementia, functional decoding, hierarchical clustering, meta-analytic connectivity modeling, resting state functional connectivity, voxel-based physiology, voxel-based morphometry, meta‐analytic connectivity modeling, voxel‐based morphometry, voxel‐based physiology, Genetics, Biological psychology
Abstract

IntroductionNumerous studies have reported brain alterations in behavioral variant frontotemporal dementia (bvFTD). However, they pointed to inconsistent findings.MethodsWe used a meta-analytic approach to identify the convergent structural and functional brain abnormalities in bvFTD. Following current best-practice neuroimaging meta-analysis guidelines, we searched PubMed and Embase databases and performed reference tracking. Then, the coordinates of group comparisons between bvFTD and controls from 73 studies were extracted and tested for convergence using activation likelihood estimation.ResultsWe identified convergent abnormalities in the anterior cingulate cortices, anterior insula, amygdala, paracingulate, striatum, and hippocampus. Task-based and resting-state functional connectivity pointed to the networks that are connected to the obtained consistent regions. Functional decoding analyses suggested associated dysfunction of emotional processing, interoception, reward processing, higher-order cognitive functions, and olfactory and gustatory perceptions in bvFTD.DiscussionOur findings highlighted the key role of the salience network and subcortical regions in the pathophysiology of bvFTD.

Published
2022

11. The Genetic contribution to solving the cocktail-party problem

Author

Mathias, Samuel R., Knowles, Emma E.M., Mollon, Josephine, Rodrigue, Amanda L., Woolsey, Mary K., Hernandez, Alyssa M., Garrett, Amy S., Fox, Peter T., Olvera, Rene L., Peralta, Juan M., Kumar, Satish, Göring, Harald H.H., Duggirala, Ravi, Curran, Joanne E., Blangero, John, and Glahn, David C.

Published
2022
Full Text
View/download PDF

12. BrainMap

Author

Riedel, Michael C., Ray, Kimberly, Fox, P. Mickle, Uecker, Angela M., Eickhoff, Simon B., Fox, Peter T., Laird, Angela Marie Richmond, Migliore, Michele, Section editor, Linster, Christiane, Section editor, Cavarretta, Francesco, Section editor, Jaeger, Dieter, editor, and Jung, Ranu, editor

Published
2022
Full Text
View/download PDF

15. DSM-5 Criterion-A-Based Trauma Types in Service Members and Veterans Seeking Treatment for Posttraumatic Stress Disorder.

Author

Benfer, Natasha, Grunthal, Breanna, Dondanville, Katherine A., Young-McCaughan, Stacey, Blankenship, Abby, Abdallah, Chadi G., Back, Sudie E., Flanagan, Julianne, Foa, Edna B., Fox, Peter T., Krystal, John H., Marx, Brian P., McGeary, Donald D., McLean, Carmen P., Pruiksma, Kristi E., Resick, Patricia A., Roache, John D., Shiroma, Paulo, Sloan, Denise M., and Taylor, Daniel J.

Published
2024
Full Text
View/download PDF

16. Estimating the Prevalence of Missing Experiments in a Neuroimaging Meta-Analysis

Author

Samartsidis, Pantelis, Montagna, Silvia, Laird, Angela R., Fox, Peter T., Johnson, Timothy D., and Nichols, Thomas E.

Abstract

Coordinate-based meta-analyses (CBMA) allow researchers to combine the results from multiple functional magnetic resonance imaging experiments with the goal of obtaining results that are more likely to generalize. However, the interpretation of CBMA findings can be impaired by the file drawer problem, a type of publication bias that refers to experiments that are carried out but are not published. Using foci per contrast count data from the BrainMap database, we propose a zero-truncated modeling approach that allows us to estimate the prevalence of nonsignificant experiments. We validate our method with simulations and real coordinate data generated from the Human Connectome Project. Application of our method to the data from BrainMap provides evidence for the existence of a file drawer effect, with the rate of missing experiments estimated as at least 6 per 100 reported. The R code that we used is available at https://osf.io/ayhfv/.

Published
2020
Full Text
View/download PDF

19. STRONG STAR and the Consortium to Alleviate PTSD: Shaping the future of combat PTSD and related conditions in military and veteran populations

Author

Peterson, Alan L., Young-McCaughan, Stacey, Roache, John D., Mintz, Jim, Litz, Brett T., Williamson, Douglas E., Resick, Patricia A., Foa, Edna B., McGeary, Donald D., Dondanville, Katherine A., Taylor, Daniel J., Wachen, Jennifer Schuster, Fox, Peter T., Bryan, Craig J., McLean, Carmen P., Pruiksma, Kristi E., Yarvis, Jeffrey S., Niles, Barbara L., Abdallah, Chadi G., Averill, Lynnette A., Back, Sudie E., Baker, Monty T., Blount, Tabatha H., Borah, Adam M., Borah, Elisa V., Brock, Matthew S., Brown, Lily A., Burg, Matthew M., Cigrang, Jeffrey A., DeBeer, Bryann B., DeVoe, Ellen R., Fina, Brooke A., Flanagan, Julianne C., Fredman, Steffany J., Gardner, Cubby L., Gatchel, Robert R., Goodie, Jeffrey L., Gueorguieva, Ralitza, Higgs, Jay B., Jacoby, Vanessa M., Kelly, Kevin M., Krystal, John H., Lapiz-Bluhm, M. Danet, López-Roca, Argelio L., Marx, Brian P., Maurer, Douglas M., McDevitt-Murphy, Meghan E., McGeary, Cindy A., Meyer, Eric C., Miles, Shannon R., Monson, Candice M., Morilak, David A., Moring, John C., Mysliwiec, Vincent, Nicholson, Karin L., Rauch, Sheila A.M., Riggs, David S., Rosen, Craig S., Rudd, M. David, Schobitz, Richard P., Schrader, Christian C., Shinn, Antoinette M., Shiroma, Paulo R., Sloan, Denise M., Stern, Stephen L., Strong, Randy, Vannoy, Steven D., Young, Keith A., and Keane, Terence M.

Published
2021
Full Text
View/download PDF

20. Imaging local genetic influences on cortical folding

Author

Alexander-Bloch, Aaron F., Raznahan, Armin, Vandekar, Simon N., Seidlitz, Jakob, Lu, Zhixin, Mathias, Samuel R., Knowles, Emma, Mollon, Josephine, Rodrigue, Amanda, Curran, Joanne E., Görring, Harald H. H., Satterthwaite, Theodore D., Gur, Raquel E., Bassett, Danielle S., Hoftman, Gil D., Pearlson, Godfrey, Shinohara, Russell T., Liu, Siyuan, Fox, Peter T., Almasy, Laura, Blangero, John, and Glahn, David C.

Published
2020

23. Activation Likelihood Estimation Neuroimaging Meta-Analysis: a Powerful Tool for Emotion Research.

Author

Costa, Tommaso, Ferraro, Mario, Manuello, Jordi, Camasio, Alessia, Nani, Andrea, Mancuso, Lorenzo, Cauda, Franco, Fox, Peter T, and Liloia, Donato

Abstract

Over the past two decades, functional magnetic resonance imaging (fMRI) has become the primary tool for exploring neural correlates of emotion. To enhance the reliability of results in understanding the complex nature of emotional experiences, researchers combine findings from multiple fMRI studies using coordinate-based meta-analysis (CBMA). As one of the most widely employed CBMA methods worldwide, activation likelihood estimation (ALE) is of great importance in affective neuroscience and neuropsychology. This comprehensive review provides an introductory guide for implementing the ALE method in emotion research, outlining the experimental steps involved. By presenting a case study about the emotion of disgust, with regard to both its core and social processing, we offer insightful commentary as to how ALE can enable researchers to produce consistent results and, consequently, fruitfully investigate the neural mechanisms underpinning emotions, facilitating further progress in this field. [ABSTRACT FROM AUTHOR]

Published
2024
Full Text
View/download PDF

34. The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data

Author

Thompson, Paul M, Stein, Jason L, Medland, Sarah E, Hibar, Derrek P, Vasquez, Alejandro Arias, Renteria, Miguel E, Toro, Roberto, Jahanshad, Neda, Schumann, Gunter, Franke, Barbara, Wright, Margaret J, Martin, Nicholas G, Agartz, Ingrid, Alda, Martin, Alhusaini, Saud, Almasy, Laura, Almeida, Jorge, Alpert, Kathryn, Andreasen, Nancy C, Andreassen, Ole A, Apostolova, Liana G, Appel, Katja, Armstrong, Nicola J, Aribisala, Benjamin, Bastin, Mark E, Bauer, Michael, Bearden, Carrie E, Bergmann, Ørjan, Binder, Elisabeth B, Blangero, John, Bockholt, Henry J, Bøen, Erlend, Bois, Catherine, Boomsma, Dorret I, Booth, Tom, Bowman, Ian J, Bralten, Janita, Brouwer, Rachel M, Brunner, Han G, Brohawn, David G, Buckner, Randy L, Buitelaar, Jan, Bulayeva, Kazima, Bustillo, Juan R, Calhoun, Vince D, Cannon, Dara M, Cantor, Rita M, Carless, Melanie A, Caseras, Xavier, Cavalleri, Gianpiero L, Chakravarty, M Mallar, Chang, Kiki D, Ching, Christopher RK, Christoforou, Andrea, Cichon, Sven, Clark, Vincent P, Conrod, Patricia, Coppola, Giovanni, Crespo-Facorro, Benedicto, Curran, Joanne E, Czisch, Michael, Deary, Ian J, de Geus, Eco JC, den Braber, Anouk, Delvecchio, Giuseppe, Depondt, Chantal, de Haan, Lieuwe, de Zubicaray, Greig I, Dima, Danai, Dimitrova, Rali, Djurovic, Srdjan, Dong, Hongwei, Donohoe, Gary, Duggirala, Ravindranath, Dyer, Thomas D, Ehrlich, Stefan, Ekman, Carl Johan, Elvsåshagen, Torbjørn, Emsell, Louise, Erk, Susanne, Espeseth, Thomas, Fagerness, Jesen, Fears, Scott, Fedko, Iryna, Fernández, Guillén, Fisher, Simon E, Foroud, Tatiana, Fox, Peter T, Francks, Clyde, Frangou, Sophia, Frey, Eva Maria, Frodl, Thomas, Frouin, Vincent, Garavan, Hugh, Giddaluru, Sudheer, Glahn, David C, Godlewska, Beata, Goldstein, Rita Z, Gollub, Randy L, and Grabe, Hans J

Subjects
Biological Psychology, Health Sciences, Psychology, Brain Disorders, Schizophrenia, Human Genome, Biomedical Imaging, Genetics, Mental Illness, Mental Health, Neurosciences, 2.1 Biological and endogenous factors, Neurological, Mental health, Good Health and Well Being, Brain Mapping, Cooperative Behavior, Genome-Wide Association Study, Humans, Meta-Analysis as Topic, Neuroimaging, MRI, GWAS, Consortium, Meta-analysis, Multi-site, Alzheimer’s Disease Neuroimaging Initiative, EPIGEN Consortium, IMAGEN Consortium, Saguenay Youth Study (SYS) Group, Medical and Health Sciences, Psychology and Cognitive Sciences, Experimental Psychology, Biomedical and clinical sciences, Health sciences
Abstract

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

Published
2014

35. Convergent functional effects of antidepressants in major depressive disorder: a neuroimaging meta-analysis

Author

Saberi, Amin, primary, Ebneabbasi, Amir, additional, Rahimi, Sama, additional, Sarebannejad, Sara, additional, Sen, Zumrut Duygu, additional, Graf, Heiko, additional, Walter, Martin, additional, Sorg, Christian, additional, Camilleri, Julia A, additional, Laird, Angela R., additional, Fox, Peter T, additional, Valk, Sofie L, additional, Eickhoff, Simon B, additional, and Tahmasian, Masoud, additional

Published
2023
Full Text
View/download PDF

36. A randomized placebo-controlled trial of nicotinamide riboside in older adults with mild cognitive impairment

Author

Orr, Miranda E., primary, Kotkowski, Eithan, additional, Ramirez, Paulino, additional, Bair-Kelps, Darcy, additional, Liu, Qianqian, additional, Brenner, Charles, additional, Schmidt, Mark S., additional, Fox, Peter T., additional, Larbi, Anis, additional, Tan, Crystal, additional, Wong, Glenn, additional, Gelfond, Jonathan, additional, Frost, Bess, additional, Espinoza, Sara, additional, Musi, Nicolas, additional, and Powers, Becky, additional

Published
2023
Full Text
View/download PDF

37. Postmortem Brain Imaging in Alzheimer’s Disease and Related Dementias: The South Texas Alzheimer’s Disease Research Center Repository

Author

Li, Karl, primary, Rashid, Tanweer, additional, Li, Jinqi, additional, Honnorat, Nicolas, additional, Nirmala, Anoop Benet, additional, Fadaee, Elyas, additional, Wang, Di, additional, Charisis, Sokratis, additional, Liu, Hangfan, additional, Franklin, Crystal, additional, Maybrier, Mallory, additional, Katragadda, Haritha, additional, Abazid, Leen, additional, Ganapathy, Vinutha, additional, Valaparla, Vijaya Lakshmi, additional, Bagudu, Pradeepthi, additional, Vasquez, Eliana, additional, Solano, Leigh, additional, Clarke, Geoffrey, additional, Maestre, Gladys, additional, Richardson, Tim, additional, Walker, Jamie, additional, Fox, Peter T., additional, Bieniek, Kevin, additional, Seshadri, Sudha, additional, and Habes, Mohamad, additional

Published
2023
Full Text
View/download PDF

41. Ten simple rules for neuroimaging meta-analysis

Author

Müller, Veronika I., Cieslik, Edna C., Laird, Angela R., Fox, Peter T., Radua, Joaquim, Mataix-Cols, David, Tench, Christopher R., Yarkoni, Tal, Nichols, Thomas E., Turkeltaub, Peter E., Wager, Tor D., and Eickhoff, Simon B.

Published
2018
Full Text
View/download PDF

42. The challenge of connecting the dots in the B.R.A.I.N.

Author

Devor, Anna, Bandettini, Peter A, Boas, David A, Bower, James M, Buxton, Richard B, Cohen, Lawrence B, Dale, Anders M, Einevoll, Gaute T, Fox, Peter T, Franceschini, Maria Angela, Friston, Karl J, Fujimoto, James G, Geyer, Mark A, Greenberg, Joel H, Halgren, Eric, Hämäläinen, Matti S, Helmchen, Fritjof, Hyman, Bradley T, Jasanoff, Alan, Jernigan, Terry L, Judd, Lewis L, Kim, Seong-Gi, Kleinfeld, David, Kopell, Nancy J, Kutas, Marta, Kwong, Kenneth K, Larkum, Matthew E, Lo, Eng H, Magistretti, Pierre J, Mandeville, Joseph B, Masliah, Eliezer, Mitra, Partha P, Mobley, William C, Moskowitz, Michael A, Nimmerjahn, Axel, Reynolds, John H, Rosen, Bruce R, Salzberg, Brian M, Schaffer, Chris B, Silva, Gabriel A, So, Peter TC, Spitzer, Nicholas C, Tootell, Roger B, Van Essen, David C, Vanduffel, Wim, Vinogradov, Sergei A, Wald, Lawrence L, Wang, Lihong V, Weber, Bruno, and Yodh, Arjun G

Subjects
Animals, Humans, Brain Mapping, Neurosciences, Biomedical Research, Brain Disorders, Neurological, Psychology, Cognitive Sciences, Neurology & Neurosurgery
Abstract

The Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative has focused scientific attention on the necessary tools to understand the human brain and mind. Here, we outline our collective vision for what we can achieve within a decade with properly targeted efforts and discuss likely technological deliverables and neuroscience progress.

Published
2013

45. Anatomical Global Spatial Normalization

Author

Lancaster, Jack L., Cykowski, Matthew D., McKay, David Reese, Kochunov, Peter V., Fox, Peter T., Rogers, William, Toga, Arthur W., Zilles, Karl, Amunts, Katrin, and Mazziotta, John

Subjects
Biomedicine, Computational Biology/Bioinformatics, Biotechnology, Neurology, Computer Appl. in Life Sciences, Neurosciences, Size preservation, Linear distance, Area, Mean volume, aGSN, GSN, Variance
Abstract

Anatomical global spatial normalization (aGSN) is presented as a method to scale high-resolution brain images to control for variability in brain size without altering the mean size of other brain structures. Two types of mean preserving scaling methods were investigated, “shape preserving” and “shape standardizing”. aGSN was tested by examining 56 brain structures from an adult brain atlas of 40 individuals (LPBA40) before and after normalization, with detailed analyses of cerebral hemispheres, all gyri collectively, cerebellum, brainstem, and left and right caudate, putamen, and hippocampus. Mean sizes of brain structures as measured by volume, distance, and area were preserved and variance reduced for both types of scale factors. An interesting finding was that scale factors derived from each of the ten brain structures were also mean preserving. However, variance was best reduced using whole brain hemispheres as the reference structure, and this reduction was related to its high average correlation with other brain structures. The fractional reduction in variance of structure volumes was directly related to ρ 2, the square of the reference-to-structure correlation coefficient. The average reduction in variance in volumes by aGSN with whole brain hemispheres as the reference structure was approximately 32%. An analytical method was provided to directly convert between conventional and aGSN scale factors to support adaptation of aGSN to popular spatial normalization software packages.

Published
2010

46. DSM-5 criterion-a-based trauma types in service members and veterans seeking treatment for posttraumatic stress disorder.

Author

Benfer, Natasha, primary, Grunthal, Breanna, additional, Dondanville, Katherine A., additional, Young-McCaughan, Stacey, additional, Blankenship, Abby, additional, Abdallah, Chadi G., additional, Back, Sudie E., additional, Flanagan, Julianne, additional, Foa, Edna B., additional, Fox, Peter T., additional, Krystal, John H., additional, Marx, Brian P., additional, McGeary, Donald D., additional, McLean, Carmen P., additional, Pruiksma, Kristi E., additional, Resick, Patricia A., additional, Roache, John D., additional, Shiroma, Paulo, additional, Sloan, Denise M., additional, Taylor, Daniel J., additional, Wachen, Jennifer Schuster, additional, López-Roca, Argelio L., additional, Nicholson, Karin L., additional, Schobitz, Richard P., additional, Schrader, Christian C., additional, Sharrieff, Allah-Fard M., additional, Yarvis, Jeffrey S., additional, Mintz, Jim, additional, Keane, Terence M., additional, Peterson, Alan L., additional, and Litz, Brett T., additional

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results