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Identifying group discriminative and age regressive sub-networks from DTI-based connectivity via a unified framework of non-negative matrix factorization and graph embedding

Yasser Ghanbari, Alex R. Smith, Robert T. Schultz, Ragini Verma
2014 Medical Image Analysis  
We propose a unified framework of non-negative matrix factorization and graph embedding for learning sub-network patterns of connectivity by their projective non-negative decomposition into a reconstructive  ...  Such a network representation of brain connectivity has provided a novel means of investigating brain changes arising from pathology, development or aging.  ...  Acknowledgments This research was supported by the following grants from National Institutes of Health: MH092862 and MH098010 (PI: Ragini Verma), and grants from the Pennsylvania Department of Health:  ... 
doi:10.1016/j.media.2014.06.006 pmid:25037933 pmcid:PMC4205764 fatcat:vghm2bpjcndb5bobwjy623rxqy

A Network Neuroscience Approach to Typical and Atypical Brain Development

Sarah E. Morgan, Simon R. White, Edward T. Bullmore, Petra E. Vértes
2018 Biological Psychiatry: Cognitive Neuroscience and Neuroimaging  
Human brain networks based on neuroimaging data have already proven useful in characterizing both normal and abnormal brain structure and function.  ...  We begin with an overview of recent large-scale efforts to map healthy brain development, and we describe the key role played by longitudinal data including repeated measurements over a long period of  ...  via a unified framework of nonnegative matrix factorization and graph embedding Ghanbari et al [111] 2014 24 ASD, 59 controls 6-18 No DWI The Emergence of Network Inefficiencies in Infants With  ... 
doi:10.1016/j.bpsc.2018.03.003 pmid:29703679 pmcid:PMC6986924 fatcat:jlpx2gvecrceflaux3g2z6l4rm

Linking Brain Biology to Intellectual Endowment: A Review on the Associations of Human Intelligence With Neuroimaging Data

Aslan Satary Dizaji, Bruno Hebling Vieira, Mohmmad Reza Khodaei, Mahnaz Ashrafi, Elahe Parham, Gholam Ali Hosseinzadeh, Carlos Ernesto Garrido Salmon, Hamid Soltanianzadeh
2021 Basic and Clinical Neuroscience  
Finally, we discuss the state-of-the-art of individualized prediction of intelligence from neuroimaging data and point out future strategies.  ...  Future studies hold promising outcomes for machine learning-based predictive frameworks using neuroimaging features to estimate human intelligence.  ...  Acknowledgments The authors thank the Cognitive Sciences and Technologies Council, CSTC, Iran, and the São Paulo Research Foundation, FAPESP, Brazil for supporting the project.  ... 
doi:10.32598/bcn.12.1.574.1 pmid:33995924 pmcid:PMC8114859 fatcat:vkdjjavpyzgs7ejma2ajog77ua

Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future [article]

David Ahmedt-Aristizabal, Mohammad Ali Armin, Simon Denman, Clinton Fookes, Lars Petersson
2021 arXiv   pre-print
We provide an overview of these methods in a systematic manner, organized by their domain of application including functional connectivity, anatomical structure and electrical-based analysis.  ...  them as a matrix.  ...  In the framework which is illustrated in Fig. 16 , each pathology is illustrated with semantic vectors via a word embedding, and the graph representation is learned from the co-occurrence matrix of training  ... 
arXiv:2105.13137v1 fatcat:gm7d2ziagba7bj3g34u4t3k43y

Introduction to JINS Special Issue on Human Brain Connectivity in the Modern Era: Relevance to Understanding Health and Disease

Deanna M. Barch, Mieke Verfaellie, Stephen M. Rao
2016 Journal of the International Neuropsychological Society  
JINS Vo l u m e 2 2 , N u m b e r 2 F e b r u a r y 2 0 1 6 I S S N 1 3 5 5 -6 1 7 7  ...  Medial prefrontal cortex and self-referential mental activity: Relation to a default mode of brain function.  ...  Martinos Center for Biomedical Imaging at the Massachusetts General Hospital, which receives funding from P41EB015896, a Biotechnology Resource Grant supported by the National Institute of Biomedical Imaging  ... 
doi:10.1017/s1355617716000047 fatcat:f2preenihbes5ftkrxbo7tgt64

Graph Neural Networks for Natural Language Processing: A Survey [article]

Lingfei Wu, Yu Chen, Kai Shen, Xiaojie Guo, Hanning Gao, Shucheng Li, Jian Pei, Bo Long
2021 arXiv   pre-print
We propose a new taxonomy of GNNs for NLP, whichsystematically organizes existing research of GNNs for NLP along three axes: graph construction,graph representation learning, and graph based encoder-decoder  ...  As a result, thereis a surge of interests in developing new deep learning techniques on graphs for a large numberof NLP tasks.  ...  ., 2018) on the sub-graph only from the knowledge base and then take average of the linked words’ feature in the connected documents.  ... 
arXiv:2106.06090v1 fatcat:zvkhinpcvzbmje4kjpwjs355qu

Subject-adaptive Integration of Multiple SICE Brain Networks with Different Sparsity

Jianjia Zhang, Luping Zhou, Lei Wang
2017 Pattern Recognition  
Both covariance descriptor and SICE matrix belong to the set of symmetric positive-definite (SPD) ma-  ...  In many contexts of computer vision, the data are represented by or converted to covariance-based representations, including covariance descriptor and sparse inverse covariance estimation (SICE), due to  ...  This chapter proposes a learning based framework that integrates a set of SICE networks with the aim of attaining more discriminative power.  ... 
doi:10.1016/j.patcog.2016.09.024 fatcat:mkwvr4jtxbgyjb2fxjcszp3d4i

Poster Session I

2013 Neuropsychopharmacology  
Results: Thirty-five subjects with a mean age of 50±9 years and 70% Caucasian.  ...  KYNA-based animal model of SZ; and (3) the relative roles of a7nAChRs vs NMDA receptors in performance in the DNMTP task.To this end, we determined, in a separate group of intact animals, the effects  ...  Slifstein, A. Abi-Dargham, and S. Kapur, Arch Gen Psychiatry 69, 776 (2012). 2  ... 
doi:10.1038/npp.2013.279 fatcat:54ipecxjarcvljrvn5fgtgif5u

25th Annual Computational Neuroscience Meeting: CNS-2016

Tatyana O. Sharpee, Alain Destexhe, Mitsuo Kawato, Vladislav Sekulić, Frances K. Skinner, Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári, Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett (+597 others)
2016 BMC Neuroscience  
These results outline a framework for categorizing neuronal types based on their functional properties.  ...  I will discuss theoretical results that point to functional advantages of splitting neural populations into subtypes, both in feedforward and recurrent networks.  ...  Acknowledgements: The work of JB, RG, and SMC was supported in part by R01MH1006674 from the National Institutes of Health.  ... 
doi:10.1186/s12868-016-0283-6 pmid:27534393 pmcid:PMC5001212 fatcat:bt45etzj2bbolfcxlxo7hlv6ju

Modeling & Analysis

2003 NeuroImage  
The computation of the functional interactions through correlation coefficients (functional connectivity) or through linear regression (effective connectivity) are based on an average over many subjects  ...  Abstract Constrained Principal Component Analysis (CPCA) is introduced as a correlation-based method of identifying (a) connectivity between neuronal structures and (b) functional interactions between  ...  Acknowledgement This study was conducted by the authors on behalf of the NEST-DD consortium with support from the European Commission (Framework V).  ... 
doi:10.1016/s1053-8119(05)70006-9 fatcat:zff2suxcofbxvetfrwfwcxi3zm

Final Program, Fortieth Annual Meeting International Neuropsychological Society February 15–18, 2012 Montréal, Québec, Canada

2012 Journal of the International Neuropsychological Society  
In this symposium a panel of neuropsychologists will provide direction and insights towards developing a program of sustained externally funded research.  ...  Securing external funding from NIH or other federal agencies is critical to support research costs and academic promotion.  ...  Results: An F-test on the thalamic connection density maps reveals that children with RD show a different connectivity-based sub-thalamic pattern from controls.  ... 
doi:10.1017/s1355617712000537 fatcat:4p2fkgxxzna3vcf3uxxgac6rsi

30th Annual Computational Neuroscience Meeting: CNS*2021–Meeting Abstracts

2021 Journal of Computational Neuroscience  
within the constraints of biological networks.  ...  Recently, the framework of predictive coding (Sajikumar et al., 2014  ...  Acknowledgments This project was funded by the Helmholtz Association Initiative and Networking Fund (project number SO-092, Advanced Computing Architectures), and the European Union's Horizon 2020 Framework  ... 
doi:10.1007/s10827-021-00801-9 pmid:34931275 pmcid:PMC8687879 fatcat:evpmmfpaivgpxdqpive5xdgmwu

A sequential distance-based approach for imputing missing data: Forward Imputation

Nadia Solaro, Alessandro Barbiero, Giancarlo Manzi, Pier Alda Ferrari
2016 Advances in Data Analysis and Classification  
The aim is to identify the structure of the graph from data, assuming that the variables satisfy a given ordering.  ...  Optimal embedding parameters used in the DVV analysis are obtained via a differential entropy based method using wavelet-based surrogates.  ... 
doi:10.1007/s11634-016-0243-0 fatcat:yvrqlgllsbesbnvnzzci2egpl4

ACNP 58th Annual Meeting: Poster Session III

2019 Neuropsychopharmacology  
This study obtains the approval from Japanese association of Neuro-Psychiatric Clinics Study Ethical Review Board, and the data investigated were retrieved from databases and de-identified before data  ...  Methods: Participants were 4,964 youths (ages 5-17 years) from seven international sites, presenting with a wide range of symptom severity (healthy, non-selected, high-risk, or clinicallyanxious youth)  ...  Graph-based network analysis is a technique used to interrogate topological properties of functional brain networks.  ... 
doi:10.1038/s41386-019-0547-9 pmid:31801974 pmcid:PMC6957926 fatcat:dd7d43ysfvc5bbbstfl73szya4

2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

Michael W. Weiner, Dallas P. Veitch, Paul S. Aisen, Laurel A. Beckett, Nigel J. Cairns, Jesse Cedarbaum, Robert C. Green, Danielle Harvey, Clifford R. Jack, William Jagust, Johan Luthman, John C. Morris (+7 others)
2015 Alzheimer's & Dementia  
of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker  ...  fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients.  ...  served as a consultant for Astra Zeneca, Araclon, Medivation/Pfizer, Ipsen, TauRx Therapeutics LTD, Bayer Healthcare, Biogen Idec, Exonhit Therapeutics, SA, Servier, Synarc, Pfizer, and Janssen; has received  ... 
doi:10.1016/j.jalz.2014.11.001 pmid:26073027 pmcid:PMC5469297 fatcat:2k7ag6astffy5gphqxf5lodkdq
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