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On characterizing population commonalities and subject variations in brain networks

Yasser Ghanbari, Luke Bloy, Birkan Tunc, Varsha Shankar, Timothy P.L. Roberts, J. Christopher Edgar, Robert T. Schultz, Ragini Verma
2017 Medical Image Analysis  
The method determines an atlas of network hubs that describes the population, as well as weights that characterize subjectwise variation in terms of within-and between-hub connectivity.  ...  (ASD), and using the structural and functional networks of a population to determine the subject-level variation of these hubs and their inter-connectivity.  ...  SAP # 4100042728 and SAP # 4100047863 (PI: Robert T.  ... 
doi:10.1016/ pmid:26674972 pmcid:PMC4887425 fatcat:ctm2t7mnjjdond2sflriqb6kze

Postmortem human brain genomics in neuropsychiatric disorders—how far can we go?

Andrew E Jaffe
2016 Current Opinion in Neurobiology  
Technological advances, larger sample sizes, and focused research questions can continue to further leverage postmortem human brain research to better identify and understand the molecular etiology of  ...  Large-scale collection of postmortem human brain tissue and subsequent genomic data generation has become a useful approach for better identifying etiological factors contributing to neuropsychiatric disorders  ...  Acknowledgments I am grateful for the vision and generosity of the Lieber and Maltz Families who made this work possible. I also thank Joel E. Kleinman and Thomas M.  ... 
doi:10.1016/j.conb.2015.11.002 pmid:26685806 pmcid:PMC4857188 fatcat:ppu5wp55r5gtpeumfop5hfktfi

Predictive Modeling of Neurobehavioral State and Trait Variation Across Development

Sara Sanchez-Alonso, Richard N. Aslin
2020 Developmental Cognitive Neuroscience  
However, it remains challenging to develop models that enable prediction of both within-subject and between-subject neurodevelopmental variation.  ...  We focus on mapping variation across a range of neural and behavioral measurements and consider concurrent alterations of state and trait variation across development.  ...  Acknowledgment Research reported in this publication was supported by National Institutes of Health Grant HD-037082 (R.N.A).  ... 
doi:10.1016/j.dcn.2020.100855 pmid:32942148 pmcid:PMC7501421 fatcat:ub4tyyenhrbh5fyispb6dvbufy

Normalization enhances brain network features that predict individual intelligence in children with epilepsy

Michael J. Paldino, Farahnaz Golriz, Wei Zhang, Zili D. Chu, Tavpritesh Sethi
2019 PLoS ONE  
We compared two network normalization strategies in terms of their ability to optimize subject-level inferences on the relationship between brain network architecture and brain function.  ...  However, subject-level prediction on this basis, a crucial step toward harnessing network analyses for the benefit of children with epilepsy, has yet to be achieved.  ...  The goal of this study was to compare these two fundamental strategies in terms of their ability to optimize subject-level inferences on the relationship between brain network architecture and brain function  ... 
doi:10.1371/journal.pone.0212901 pmid:30835738 pmcid:PMC6400436 fatcat:hwvopback5cfllsvaqh2jw7jdq

Functional resting state networks characterization through global network measurements for patients with disorders of consciousness

Darwin E. Martinez, Johann H. Martinez, Jorge Rudas, Athena Demertzi, Lizette Heine, Luaba Tshibanda, Andrea Soddu, Steven Laureys, Francisco Gomez
2015 2015 10th Computing Colombian Conference (10CCC)  
The proposed approach was evaluated on a population of 27 healthy controls and 49 subjects with DOC conditions. fMRI data was obtained and processed for each subject to built a FNC at individual level.  ...  These results highlight the importance of graph based features to characterize brain complexity, and in particular, complex phenomena as consciousness emergence.  ...  CONCLUSIONS In this paper we study the use of global network measurements to characterize the properties variations of patients with disorder of consciousness (MCS and VS/UWS).  ... 
doi:10.1109/columbiancc.2015.7333436 fatcat:z6z4hhbxbvbmbdcqvrefuhhtt4

A common brain network links development, aging, and vulnerability to disease

Gwenaëlle Douaud, Adrian R. Groves, Christian K. Tamnes, Lars Tjelta Westlye, Eugene P. Duff, Andreas Engvig, Kristine B. Walhovd, Anthony James, Achim Gass, Andreas U. Monsch, Paul M. Matthews, Anders M. Fjell (+2 others)
2014 Proceedings of the National Academy of Sciences of the United States of America  
We further demonstrate that this network of brain regions, which develops relatively late during adolescence and shows accelerated degeneration in old age compared with the rest of the brain, characterizes  ...  Specifically, this network, while derived solely from healthy subjects, spatially recapitulates the pattern of brain abnormalities observed in both schizophrenia and Alzheimer's disease.  ...  André Adoutte for his wonderful and unforgettable lectures in evo-devo.  ... 
doi:10.1073/pnas.1410378111 pmid:25422429 pmcid:PMC4267352 fatcat:cen6rwpvqfhglbfa5wiib6x33e

Machine learning in resting-state fMRI analysis [article]

Meenakshi Khosla, Keith Jamison, Gia H. Ngo, Amy Kuceyeski, Mert R. Sabuncu
2018 arXiv   pre-print
We identify three major divisions of unsupervised learning methods with regard to their applications to rs-fMRI, based on whether they discover principal modes of variation across space, time or population  ...  Next, we survey the algorithms and rs-fMRI feature representations that have driven the success of supervised subject-level predictions.  ...  Acknowledgements This work was supported by NIH R01 grants (R01LM012719 and R01AG053949), the NSF NeuroNex grant 1707312, and NSF CAREER grant (1748377).  ... 
arXiv:1812.11477v1 fatcat:nd6j5jbspzh2rmxyyufdyesxom

Individual Variability in Brain Activity: A Nuisance or an Opportunity?

John Darrell Van Horn, Scott T. Grafton, Michael B. Miller
2008 Brain Imaging and Behavior  
respect to a reference population; and (3) Understanding the sources of intersubject variability in brain activity.  ...  Functional imaging research has been heavily influenced by results based on population-level inference.  ...  the International Brain Research Organization (IBRO).  ... 
doi:10.1007/s11682-008-9049-9 pmid:19777073 pmcid:PMC2748344 fatcat:idasp7hevbba3cglms4htr5s4u

Unifying inference on brain network variations in neurological diseases: The Alzheimer's case [article]

Daniele Durante, Madelaine Daianu, Neda Jahanshad, Paul M. Thompson, David B. Dunson
2015 arXiv   pre-print
We enable dramatic gains in biological insight via a novel unifying methodology for inference on brain network variations associated to the occurrence of neurological diseases.  ...  information and allow the probability mass function for the brain network-valued random variable to vary flexibly across the group of patients characterized by a specific neurological disease and the  ...  In particular, it is of interest to test for global variation in the overall brain network structure across groups, while identifying specific local variations to understand if and which brain connections  ... 
arXiv:1510.05391v1 fatcat:l3vr7j5jsjdknphtktmyxvf26q

Reconfiguration of large‐scale functional connectivity in patients with disorders of consciousness

Darwin E. Martínez, Jorge Rudas, Athena Demertzi, Vanessa Charland‐Verville, Andrea Soddu, Steven Laureys, Francisco Gómez
2019 Brain and Behavior  
We study changes in integration, segregation, and centrality properties of the functional connectivity between the RSNs in subjects with different levels of consciousness.  ...  If these alterations influence the interaction quality with other RNSs, then, brain alterations in patients with DOC would be characterized by connectivity changes in the large-scale model composed of  ...  Significant differences (p < .005) in strength values were observed for HC compared to subjects with MCS and for HC versus the population of DOC, in auditory network, DMN and visual medial network.  ... 
doi:10.1002/brb3.1476 pmid:31773918 pmcid:PMC6955826 fatcat:2gwgztkvancqlbdej4giyneqvu

Clinical Concepts Emerging from fMRI Functional Connectomics

Paul M. Matthews, Adam Hampshire
2016 Neuron  
Studies demonstrating the network plasticity possible in adults and the global consequences of even focal brain injuries or disease have had substantial impact on modern concepts of disease evolution and  ...  Applications of functional connectomics in studies of clinical populations are challenging traditional disease classifications and helping to clarify biological relationships between clinical syndromes  ...  PMM is in receipt of generous personal and research support from the Edmond J Safra Foundation and Lily Safra, the Medical Research Council and the Engineering and Physics Science Research Council for  ... 
doi:10.1016/j.neuron.2016.07.031 pmid:27497220 fatcat:plsrga55wfeh5jr6a7htpbqtw4

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  
variation in the population.  ...  basis set, as well as, additional basis sets representing variational sources in the population like age and pathology.  ...  SAP # 4100042728 and SAP # 4100047863 (PI: Robert T.  ... 
doi:10.1016/ pmid:25037933 pmcid:PMC4205764 fatcat:vghm2bpjcndb5bobwjy623rxqy

Human Brain Connectomics: Networks, Techniques, and Applications [Life Sciences

Pew-Thian Yap, Guorong Wu, Dinggang Shen
2010 IEEE Signal Processing Magazine  
Factors such as genetics, gender, pathologies, injury, and growth induce structural variations in the brain.  ...  CLASSIFICATION AND IDENTIFYING POPULATION DIFFERENCES Research has moved on to utilize wholebrain connectivity information as the basis for classification and locating population regional differences.  ... 
doi:10.1109/msp.2010.936775 fatcat:sud6ad57gne7xa7pgd23atilne

Convergent Lines of Evidence Support LRP8 as a Susceptibility Gene for Psychosis

Ming Li, Liang Huang, Maria Grigoroiu-Serbanescu, Sarah E. Bergen, Mikael Landén, Christina M. Hultman, Andreas J. Forstner, Jana Strohmaier, Julian Hecker, Thomas G. Schulze, Bertram Müller-Myhsok, Andreas Reif (+13 others)
2015 Molecular Neurobiology  
To detect whether LRP8 is a susceptibility gene for SCZ and BPD, we analyzed the associations of single nucleotide polymorphisms (SNPs) in LRP8 in a total of 47,187 subjects (including 9379 SCZ patients  ...  Protein-protein interaction (PPI) analysis demonstrated that LRP8 significantly participated in a highly interconnected PPI network build by top risk genes for SCZ and BPD (P=7.0×10 −4 ).  ...  We also wish to thank the and KI Biobank at Karolinska Institutet for professional biobank service.  ... 
doi:10.1007/s12035-015-9559-6 pmid:26637325 fatcat:xps33sw7pvbwfavbzgk4arxjg4

Finding Landmarks in the Functional Brain: Detection and Use for Group Characterization [chapter]

Bertrand Thirion, Philippe Pinel, Jean-Baptiste Poline
2005 Lecture Notes in Computer Science  
We call these Brain Functional Landmarks (BFLs), and define them based on cross-validation techniques using 38 subjects.  ...  We explore a dataset acquired while subjects were involved in several cognitive and sensori-motor processes, and show that this representation allows to classify subjects into sub-groups on the basis of  ...  Jobert, for their participation in this project for helpful discussions and ideas.  ... 
doi:10.1007/11566489_59 fatcat:q6ycexiorzajnisnppzbqfi5rm
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