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Modeling Shared Responses in Neuroimaging Studies through MultiView ICA [article]

Hugo Richard, Luigi Gresele, Aapo Hyvärinen, Bertrand Thirion, Alexandre Gramfort, Pierre Ablin
2020 arXiv   pre-print
We propose a novel MultiView Independent Component Analysis (ICA) model for group studies, where data from each subject are modeled as a linear combination of shared independent sources plus noise.  ...  Contrary to most group-ICA procedures, the likelihood of the model is available in closed form.  ...  SR-ICA [63] fMRI/Temporal SR-ICA SR-ICA incorporates ICA assumptions into the shared response model.  ... 
arXiv:2006.06635v4 fatcat:nx4oktnnargetj3i2vdakbcgki

COINSTAC: Decentralizing the future of brain imaging analysis

Jing Ming, Eric Verner, Anand Sarwate, Ross Kelly, Cory Reed, Torran Kahleck, Rogers Silva, Sandeep Panta, Jessica Turner, Sergey Plis, Vince Calhoun
2017 F1000Research  
In the era of Big Data, sharing neuroimaging data across multiple sites has become increasingly important.  ...  To remove these barriers to enable easier data sharing and analysis, we introduced a new, decentralized, privacy-enabled infrastructure model for brain imaging data called COINSTAC in 2016.  ...  Sharing data via a DUA is advantageous in that all the variables collected can be studied.  ... 
doi:10.12688/f1000research.12353.1 pmid:29123643 pmcid:PMC5657031 fatcat:drf45koyazgytkhwoxdjgdl4mu

Modern Views of Machine Learning for Precision Psychiatry [article]

Zhe Sage Chen, Prathamesh Kulkarni, Isaac R. Galatzer-Levy, Benedetta Bigio, Carla Nasca, Yu Zhang
2022 arXiv   pre-print
In this review, we provide a comprehensive review of the ML methodologies and applications by combining neuroimaging, neuromodulation, and advanced mobile technologies in psychiatry practice.  ...  In light of the NIMH's Research Domain Criteria (RDoC), the advent of functional neuroimaging, novel technologies and methods provide new opportunities to develop precise and personalized prognosis and  ...  Multimodal Neuroimaging Studies Neuroimaging data types are intrinsically dissimilar in nature, having different spatial and temporal resolutions [258] .  ... 
arXiv:2204.01607v2 fatcat:coo557v2jzh6debycy3mhccfze

Mapping individual differences in cortical architecture using multi-view representation learning

Akrem Sellami, Francois-Xavier Dupe, Bastien Cagna, Hachem Kadri, Stephane Ayache, Thierry Artieres, Sylvain Takerkart
2020 2020 International Joint Conference on Neural Networks (IJCNN)  
In this paper, we introduce a novel machine learning method which allows combining the activation-and connectivity-based information respectively measured through these two fMRI protocols to identify markers  ...  of individual differences in the functional organization of the brain.  ...  It was also funded in part by the French Agence Nationale de la Recherche (grants ANR-15-CE23-0026 and ANR-16-CE23-0006).  ... 
doi:10.1109/ijcnn48605.2020.9206887 dblp:conf/ijcnn/SellamiDCKAAT20 fatcat:e44flsaddff47fy4wtmfj6kl3m

Mapping individual differences in cortical architecture using multi-view representation learning [article]

Akrem Sellami
2020 arXiv   pre-print
In this paper, we introduce a novel machine learning method which allows combining the activation-and connectivity-based information respectively measured through these two fMRI protocols to identify markers  ...  of individual differences in the functional organization of the brain.  ...  It was also funded in part by the French Agence Nationale de la Recherche (grants ANR-15-CE23-0026 and ANR-16-CE23-0006).  ... 
arXiv:2004.02804v1 fatcat:3rh65fcmm5gchogbmxvgw6dfly

The Incomplete Rosetta Stone Problem: Identifiability Results for Multi-View Nonlinear ICA [article]

Luigi Gresele, Paul K. Rubenstein, Arash Mehrjou, Francesco Locatello, Bernhard Schölkopf
2019 arXiv   pre-print
In contrast to known identifiability results for nonlinear ICA, we prove that independent latent sources with arbitrary mixing can be recovered as long as multiple, sufficiently different noisy views are  ...  When the views are considered separately, this reduces to nonlinear Independent Component Analysis (ICA) for which it is provably impossible to undo the mixing.  ...  the two views are linked through the shared latent variable s.  ... 
arXiv:1905.06642v2 fatcat:mlis7vcwkndrplu5tzh2vxm7fa

A Convolutional Autoencoder for Multi-Subject fMRI Data Aggregation [article]

Po-Hsuan Chen, Xia Zhu, Hejia Zhang, Javier S. Turek, Janice Chen, Theodore L. Willke, Uri Hasson, Peter J. Ramadge
2016 arXiv   pre-print
It is of increasing interest in contemporary fMRI studies of human cognition due to the scarcity of data per subject and the variability of brain anatomy and functional response across subjects.  ...  Both approaches preserve spatial locality and have competitive or better performance compared with standard searchlight analysis and the shared response model applied across the whole brain.  ...  The most recent work in this vein, called the shared response model (SRM) [14] , has focused on learning probabilistic latent factors that jointly model subject specific functional topographies and a  ... 
arXiv:1608.04846v1 fatcat:2227k6htenavtf7wlfhhfhu6g4

Evolving Signal Processing for Brain–Computer Interfaces

S. Makeig, C. Kothe, T. Mullen, N. Bigdely-Shamlo, Zhilin Zhang, Kenneth Kreutz-Delgado
2012 Proceedings of the IEEE  
user cognitive state, intent, and response to events are of increasing interest.  ...  , and contextual data that may in the future be increasingly ubiquitous.  ...  modeling that follows ICA decomposition.  ... 
doi:10.1109/jproc.2012.2185009 fatcat:ebed3ribeneptnatoxaoyzn4xm

Epileptic Seizures Detection Using Deep Learning Techniques: A Review

Afshin Shoeibi, Marjane Khodatars, Navid Ghassemi, Mahboobeh Jafari, Parisa Moridian, Roohallah Alizadehsani, Maryam Panahiazar, Fahime Khozeimeh, Assef Zare, Hossein Hosseini-Nejad, Abbas Khosravi, Amir F. Atiya (+5 others)
2021 International Journal of Environmental Research and Public Health  
In this study, a comprehensive overview of works focused on automated epileptic seizure detection using DL techniques and neuroimaging modalities is presented.  ...  Finally, the most promising DL models proposed and possible future works on automated epileptic seizure detection are delineated.  ...  A multiview convolution encoding layer, in combination with CNN, has also been used to train the integrated DL model.  ... 
doi:10.3390/ijerph18115780 pmid:34072232 fatcat:vdok6mql4rfxln737tjb23ufte

The Application of Artificial Intelligence in the Genetic Study of Alzheimer's Disease

Rohan Mishra, Bin Li
2020 Aging and Disease  
creativity may play a role in theory model building, verification, and designing new intervention protocols for AD.  ...  Although many studies have yielded some meaningful results, they are still in a preliminary stage.  ...  Acknowledgements This study was supported by the Washington Institute for Health Sciences grant (G20190710).  ... 
doi:10.14336/ad.2020.0312 pmid:33269107 pmcid:PMC7673858 fatcat:72rkx7bjvbaf7earfiu5d44rqm

Advances in Multimodal Emotion Recognition Based on Brain–Computer Interfaces

Zhipeng He, Zina Li, Fuzhou Yang, Lei Wang, Jingcong Li, Chengju Zhou, Jiahui Pan
2020 Brain Sciences  
With the continuous development of portable noninvasive human sensor technologies such as brain–computer interfaces (BCI), multimodal emotion recognition has attracted increasing attention in the area  ...  weight sharing  ...  The delay in the hemodynamic response has been estimated by modeling simulations and computational methods [84, 85] . More invasive methods also demonstrate delayed hemodynamic responses [86] .  ... 
doi:10.3390/brainsci10100687 pmid:33003397 pmcid:PMC7600724 fatcat:juzx77asgrh2zpl3s2jvw6tdcq

Functional MRI applications for psychiatric disease subtyping: a review

Lucas Miranda, Riya Paul, Benno Pütz, Bertram Müller-Myhsok
2020 Zenodo  
No trans-diagnostic studies were retrieved.  ...  With the advent of new technologies that allowed researchers to investigate brain mechanisms in a more direct manner, interest in not only the mechanistic rationale behind defined pathologies but also  ...  Results A total of 144 related articles were retrieved from PubMed in the first place, of which 120 were retained after filtering for duplicated studies and reviews. 2 studies identified through manual  ... 
doi:10.5281/zenodo.3923918 fatcat:y33tncjqtbfpphlmkceg3hnd7y

Brain Imaging Genomics: Integrated Analysis and Machine Learning

Li Shen, Paul M. Thompson
2019 Proceedings of the IEEE  
Given the increasingly important role of statistical and machine learning in biomedicine and rapidly growing literature in brain imaging genomics, we provide an up-to-date and comprehensive review of statistical  ...  It has enormous potential to contribute significantly to biomedical discoveries in brain science.  ...  neuroimaging studies using the ACE model).  ... 
doi:10.1109/jproc.2019.2947272 pmid:31902950 pmcid:PMC6941751 fatcat:rx5b44yv55d2xicdiznnwjdac4

COINSTAC: decentralizing the future of brain imaging analysis

Jing Ming, Eric Verner, Anand D. Sarwate, Ross Kelly, Cory Reed, Torran Kahleck, Rogers Silva, Sandeep Panta, Jessica Turner, Sergey Plis, Vince Calhoun
2017
Sharing data via a DUA is advantageous in that all the variables collected can be studied.  ...  the global model without sharing any original data.  ...  The authors provide a thorough and easily understandable introduction into recent advances and challenges for neuroimaging data analysis: as technological barriers preventing the open sharing of large  ... 
doi:10.7282/t3-bc5z-m745 fatcat:dh46lvecwbc43nudr4rfzfpf3u

Saturday, December 5, 2009�Poster Session 1�1:00 p.m.-8:00 p.m

2009 Epilepsia  
Rationale: This descriptive study was undertaken to retrospectively review the variables associated with bone health in a population of veterans followed by the Durham VA Epilepsy Center.  ...  The following demographic variables were studied. Age, gender, years with epilepsy, BMI, and maximum number of anti epileptic drugs used in combination. See table 1.  ...  GLM and ICA analyses confirmed the known BOLD responses in this patient group.  ... 
doi:10.1111/j.1528-1167.2009.02377_1.x pmid:19817824 fatcat:75g2b4qnwrbrnpmcvebgz24dvq
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