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On characterizing population commonalities and subject variations in brain networks
2017
Medical Image Analysis
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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/j.media.2015.10.009
pmid:26674972
pmcid:PMC4887425
fatcat:ctm2t7mnjjdond2sflriqb6kze
Postmortem human brain genomics in neuropsychiatric disorders—how far can we go?
2016
Current Opinion in Neurobiology
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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
2020
Developmental Cognitive Neuroscience
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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
2019
PLoS ONE
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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
2015
2015 10th Computing Colombian Conference (10CCC)
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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
2014
Proceedings of the National Academy of Sciences of the United States of America
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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]
2018
arXiv
pre-print
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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?
2008
Brain Imaging and Behavior
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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]
2015
arXiv
pre-print
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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
2019
Brain and Behavior
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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
2016
Neuron
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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
2014
Medical Image Analysis
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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/j.media.2014.06.006
pmid:25037933
pmcid:PMC4205764
fatcat:vghm2bpjcndb5bobwjy623rxqy
Human Brain Connectomics: Networks, Techniques, and Applications [Life Sciences
2010
IEEE Signal Processing Magazine
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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
2015
Molecular Neurobiology
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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 BBMRI.se 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]
2005
Lecture Notes in Computer Science
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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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