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The Neuroscience of Sadness: A Multidisciplinary Synthesis and Collaborative Review for the Human Affectome Project

Juan A. Arias, Claire Williams, Rashmi Raghvani, Moji Aghajani, Sandra Baez, Catherine Belzung, Linda Booij, Geraldo Busatto, Julian Chiarella, Cynthia HY Fu, Agustin Ibanez, Belinda J. Liddell (+4 others)
2020 Neuroscience and Biobehavioral Reviews  
cortex as an antidepressant target.  ...  We suggest that the field may be moving toward a theoretical consensus, in which different models relating to basic emotion theory and psychological constructionism may be considered as complementary,  ...  AHK received funding for an International Mobility Fellowship from CHERISH-DE, a multidisciplinary research centre based at Swansea University, enabling him to lead this multinational collaborative effort  ... 
doi:10.1016/j.neubiorev.2020.01.006 pmid:32001274 fatcat:febagda2pbcv5aegwy5ukgtesy

A spectrum of sharing: maximization of information content for brain imaging data

Vince D Calhoun
2015 GigaScience  
flexible analytic approaches, such as independent component analysis and multivariate classification approaches, such as deep learning.  ...  mapping standards; 2) sharing of time-series data (not just summary maps or regions); and 3) the use of analytic approaches which maximize sharing potential as much as possible.  ...  Acknowledgements The work was in part funded by NIH via a COBRE grant P20GM103472 and grants R01EB005846 and 1R01EB006841.  ... 
doi:10.1186/s13742-014-0042-5 pmid:25653850 pmcid:PMC4316396 fatcat:lqac6bj6cjc5dc4lhvwn4zdkvy

Clinical applications of the functional connectome

F. Xavier Castellanos, Adriana Di Martino, R. Cameron Craddock, Ashesh D. Mehta, Michael P. Milham
2013 NeuroImage  
Resting state fMRI (R-fMRI) is emerging as a mainstream approach for imaging-based biomarker identification, detecting variations in the functional connectome that can be attributed to clinical variables  ...  Central to the development of clinical applications of functional connectomics for neurology and psychiatry is the discovery and validation of biomarkers.  ...  Acknowledgments The authors thank Eva Petkova, PhD for computing the ROC curves and providing Fig. 1 .  ... 
doi:10.1016/j.neuroimage.2013.04.083 pmid:23631991 pmcid:PMC3809093 fatcat:5oen72do2zf5liz43pwlp3krom

Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls

Mohammad R. Arbabshirani, Sergey Plis, Jing Sui, Vince D. Calhoun
2017 NeuroImage  
Using a variety of neuroimaging modalities such as structural, functional and diffusion MRI, along with machine learning techniques, hundreds of studies have been carried out for accurate classification  ...  prediction of brain disorders during an exciting time.  ...  studies.  ... 
doi:10.1016/j.neuroimage.2016.02.079 pmid:27012503 pmcid:PMC5031516 fatcat:7kxm7yeugrgvdlxmitccneqxc4

Insights into multimodal imaging classification of ADHD

John B. Colby, Jeffrey D. Rudie, Jesse A. Brown, Pamela K. Douglas, Mark S. Cohen, Zarrar Shehzad
2012 Frontiers in Systems Neuroscience  
This provided motivation for the ADHD-200 machine learning (ML) competition, a multisite collaborative effort to investigate imaging classifiers for ADHD.  ...  Site-specific RBF-SVMs using these optimal feature sets from each imaging modality were used to predict the class labels of an independent hold-out test set.  ...  ADHD-200 COMPETITION RESULTS The performance of our ML approach was judged on an independent hold-out test set of 197 individuals as part of the ADHD-200 Global Competition.  ... 
doi:10.3389/fnsys.2012.00059 pmid:22912605 pmcid:PMC3419970 fatcat:5anmjk6opndlpoe2xivni46v5m

Schizophrenia: A Survey of Artificial Intelligence Techniques Applied to Detection and Classification

Joel Weijia Lai, Candice Ke En Ang, U. Rajendra Acharya, Kang Hao Cheong
2021 International Journal of Environmental Research and Public Health  
Multiple artificial intelligence and machine learning algorithms have been utilized to analyze the different components of schizophrenia, such as in prediction of disease, and assessment of current prevention  ...  These are carried out in hope of assisting with diagnosis and provision of viable options for individuals affected.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/ijerph18116099 pmid:34198829 pmcid:PMC8201065 fatcat:fz5ht4zguneylb6hh26fxbjiia

A Review of Hyperscanning and Its Use in Virtual Environments

Amit Barde, Ihshan Gumilar, Ashkan F. Hayati, Arindam Dey, Gun Lee, Mark Billinghurst
2020 Informatics  
Similarly, there has been an increase in the use of virtual reality (VR) for collaboration, and an increase in the frequency of social interactions being carried out in virtual environments (VE).  ...  This is done using one of several neuroimaging methods, such as electroencephalography (EEG), functional magnetic resonance imaging (fMRI), and functional near-infrared spectroscopy (fNIRS).  ...  Cooperation and competition tasks: Cooperation and competition form an intrinsic part of human life. Oftentimes, people need to work together to achieve a common goal, across all spheres of life.  ... 
doi:10.3390/informatics7040055 fatcat:eu425vjh4jet7jkmzc7je3wsw4

Advances in neuroimaging to support translational medicine in dementia

Thomas Edmund Cope, Rimona Sharon Weil, Emrah Düzel, Bradford C Dickerson, James Benedict Rowe
2021 Journal of Neurology, Neurosurgery and Psychiatry  
We illustrate their potential as safe, robust and sufficiently scalable to be viable for experimental medicine studies and clinical trials.  ...  Developments in MRI-based imaging and neurophysiology provide complementary quantitative assays of brain function and connectivity, for the direct testing of hypotheses of human pathophysiology.  ...  both at rest, 48 and when engaged in a task. w234 These changes can support disease classification even between patients in whom the localisation of pathology is similar, providing a first step towards  ... 
doi:10.1136/jnnp-2019-322402 pmid:33568448 pmcid:PMC8862738 fatcat:kfzojf7vpncq7pgln7xiaue324

Distinct neural patterns of social cognition for cooperation versus competition

Lily Tsoi, James Dungan, Adam Waytz, Liane Young
2016 NeuroImage  
The present fMRI study examined activity in brain regions for ToM (bilateral temporoparietal junction, precuneus, dorsomedial prefrontal cortex) across cooperative and competitive interactions with the  ...  Specifically, ToM regions encoded differences between cooperation and competition when people believed the outcome was determined by their and their partner's choices but not when the computer determined  ...  Acknowledgments We thank members of the Boston College Morality Lab, Elizabeth Kensinger, and Scott Slotnick for their feedback and Yune-Sang Lee for his multivariate pattern analysis scripts, which we  ... 
doi:10.1016/j.neuroimage.2016.04.069 pmid:27165762 fatcat:czrmpv6oyrb6hp7xwatikrzo24

Big data, open science and the brain: lessons learned from genomics

Suparna Choudhury, Jennifer R. Fishman, Michelle L. McGowan, Eric T. Juengst
2014 Frontiers in Human Neuroscience  
ACKNOWLEDGMENTS The authors would like to thank Marcie Lambrix, Richard Settersten and anonymous reviewers for their constructive comments on earlier versions of this manuscript.  ...  Support for the preparation of this article was provided by the US National Human Genome Research Institute, Grant NIH R01 HG005277.  ...  and traditional taskbased fMRI studies.  ... 
doi:10.3389/fnhum.2014.00239 pmid:24904347 pmcid:PMC4032989 fatcat:aswgibdg45edvn7se5el3lfm2q

Multivariate analyses applied to fetal, neonatal and pediatric MRI of neurodevelopmental disorders

Jacob Levman, Emi Takahashi
2015 NeuroImage: Clinical  
Multivariate analysis (MVA) is a class of statistical and pattern recognition methods that involve the processing of data that contains multiple measurements per sample.  ...  The goal of this manuscript is to provide a concise review of the state of the scientific literature on studies employing brain MRI and MVA in a pre-adult population.  ...  Acknowledgments This article was supported financially by the National Institute of Health grants R01HD078561 and R03NS091587 to ET.  ... 
doi:10.1016/j.nicl.2015.09.017 pmid:26640765 pmcid:PMC4625213 fatcat:2sff6o4avrgudbwkepawwrbpta

Building better biomarkers: brain models in translational neuroimaging

Choong-Wan Woo, Luke J Chang, Martin A Lindquist, Tor D Wager
2017 Nature Neuroscience  
We review the state of translational neuroimaging and outline an approach to developing brain signatures that can be shared, tested in multiple contexts and applied in clinical settings.  ...  The approach rests on three pillars: (i) the use of multivariate pattern-recognition techniques to develop brain signatures for clinical outcomes and relevant mental processes; (ii) assessment and optimization  ...  AckNowleDGmeNTs We thank our colleagues for discussion of issues surrounding biomarker development and consortium data, including V. Apkarian, M. Banich, D.  ... 
doi:10.1038/nn.4478 pmid:28230847 pmcid:PMC5988350 fatcat:53smgjswmbea3ingvpjhqy6oha

ASD-DiagNet: A Hybrid Learning Approach for Detection of Autism Spectrum Disorder Using fMRI Data

Taban Eslami, Vahid Mirjalili, Alvis Fong, Angela R. Laird, Fahad Saeed
2019 Frontiers in Neuroinformatics  
We designed and implemented a joint learning procedure using an autoencoder and a single layer perceptron (SLP) which results in improved quality of extracted features and optimized parameters for the  ...  In order to move the field toward more quantitative diagnosis, we need advanced and scalable machine learning infrastructure that will allow us to identify reliable biomarkers of mental health disorders  ...  Our previous study on ADHD disorder has shown that EROS is an effective similarity measure for fMRI data and using it along with k-Nearest-Neighbor achieves high classification accuracy (Eslami and Saeed  ... 
doi:10.3389/fninf.2019.00070 pmid:31827430 pmcid:PMC6890833 fatcat:3xxhf4fxzjeehfbusng5yaslsi

Neuroimaging-based biomarkers for pain

Maite M. van der Miesen, Martin A. Lindquist, Tor D. Wager
2019 PAIN Reports  
Chronic pain is an endemic problem involving both peripheral and brain pathophysiology.  ...  In this review, we explicate the need for brain-based biomarkers for pain, some of their potential uses, and some of the most popular machine learning approaches that have been brought to bear.  ...  Acknowledgements The authors thank Glenn van der Lande and Guido van Wingen for valuable discussions and comments on earlier drafts.  ... 
doi:10.1097/pr9.0000000000000751 pmid:31579847 pmcid:PMC6727991 fatcat:dj4o5h2vtvcyvjchkjhgbhkzsq

Brain Imaging Techniques and Their Applications in Decision-Making Research

Gui XUE, Chuansheng CHEN, Zhong-Lin LU, Qi DONG
2010 Acta Psychologica Sinica  
In this article, we first provide an overview of brain imaging techniques, focusing on the recent developments in multivariate analysis and multi-modal data integration.  ...  This article aims at providing readers with an overview of the recent advances in neuroimaging techniques and their applications in the study of human decision-making.  ...  Acknowledgement This article was written while the authors were partially supported by grants from NSF Award #BCS-0823624 and #BCS-0823495 and by the Project 111 of the Ministry of Education of China.  ... 
doi:10.3724/sp.j.1041.2010.00120 pmid:20376329 pmcid:PMC2849100 fatcat:7gdlct3e2bcrdfu7wsiizffvmy
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