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Andrew Zalesky
University of Melbourne
PsychologyNeuroscienceWhite matterComputer networkSchizophrenia
214Publications
45H-index
9,652Citations
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Publications 206
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#1Vanessa Cropley (University of Melbourne)H-Index: 20
#2Ye Tian (University of Melbourne)H-Index: 4
Last. Andrew Zalesky (University of Melbourne)H-Index: 45
view all 7 authors...
Background: This study aims to investigate whether dimensional constructs of psychopathology relate to advanced, attenuated or normal patterns of brain development, and to determine whether these constructs share common neurodevelopmental profiles. Methods: Psychiatric symptom ratings from 9312 youths (8-21 years) were parsed into 7 independent dimensions of clinical psychopathology representing conduct, anxiety, obsessive-compulsive, attention, depression, bipolar, and psychosis symptoms. Using...
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#1Robin F. H. Cash (University of Melbourne)H-Index: 14
#2Anne Weigand (Humboldt University of Berlin)H-Index: 11
Last. Michael D. Fox (Harvard University)H-Index: 42
view all 7 authors...
Abstract Transcranial magnetic stimulation (TMS) is an effective treatment for depression but is limited in that the optimal therapeutic target remains unknown. Early TMS trials lacked a focal target, and thus positioned the TMS coil over the prefrontal cortex using scalp measurements. Over time, it became clear that this method leads to variation in the stimulation site and that this could contribute to heterogeneity in antidepressant response. Newer methods allow for precise positioning of the...
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#1Akhil Kottaram (University of Melbourne)H-Index: 2
#2Leigh A. Johnston (University of Melbourne)H-Index: 25
Last. Vanessa Cropley (RMIT: RMIT University)H-Index: 20
view all 11 authors...
In a machine learning setting, this study aims to compare the prognostic utility of connectomic, brain structural, and clinical/demographic predictors of individual change in symptom severity in individuals with schizophrenia. Symptom severity at baseline and 1-year follow-up was assessed in 30 individuals with a schizophrenia-spectrum disorder using the Brief Psychiatric Rating Scale. Structural and functional neuroimaging was acquired in all individuals at baseline. Machine learning classifier...
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#1Ye Tian (University of Melbourne)H-Index: 4
#2Daniel S Margulies (CNRS: Centre national de la recherche scientifique)H-Index: 1
Last. Andrew Zalesky (University of Melbourne)H-Index: 45
view all 4 authors...
Understanding the topographic organization of the human brain remains a major goal in neuroscience. Brain atlases are fundamental to this goal, yet many contemporary human atlases cover only the cerebral cortex, leaving the subcortex a terra incognita. We revealed the astoundingly complex topographic organization of the human subcortex by disambiguating smooth connectivity gradients from discrete areal boundaries in resting-state fMRI data acquired from more than 1000 healthy adults. This unveil...
4 CitationsSource
#1Maria Di Biase (Harvard University)
#2Suheyla Cetin Karayumak (Brigham and Women's Hospital)H-Index: 4
Last. Alan Anticevic (Yale University)H-Index: 39
view all 25 authors...
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#1Rebecca Cooper (University of Melbourne)
#2Tamsyn E. Van Rheenen (University of Melbourne)H-Index: 15
Last. Vanessa Cropley (University of Melbourne)H-Index: 20
view all 9 authors...
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#1Vanessa Cropley (University of Melbourne)H-Index: 20
#2Ye Tian (University of Melbourne)H-Index: 4
Last. Andrew Zalesky (University of Melbourne)H-Index: 45
view all 7 authors...
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#1Tabinda Sarwar (University of Melbourne)H-Index: 2
#2Caio Seguin (University of Melbourne)H-Index: 5
Last. Andrew Zalesky (University of Melbourne)H-Index: 45
view all 4 authors...
Abstract We propose a new framework to map structural connectomes using deep learning and diffusion MRI. We show that our framework not only enables connectome mapping with a convolutional neural network (CNN), but can also be straightforwardly incorporated into conventional connectome mapping pipelines to enhance accuracy. Our framework involves decomposing the entire brain volume into overlapping blocks. Blocks are sufficiently small to ensure that a CNN can be efficiently trained to predict e...
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#1Dan Jin (CAS: Chinese Academy of Sciences)H-Index: 2
#2Pan Wang (TJU: Tianjin University)H-Index: 1
Last. Hongxiang Yao (Chinese PLA General Hospital)H-Index: 11
view all 22 authors...
Alzheimer's disease (AD) is associated with disruptions in brain activity and networks. However, there is substantial inconsistency among studies that have investigated functional brain alterations in AD; such contradictions have hindered efforts to elucidate the core disease mechanisms. In this study, we aim to comprehensively characterize AD-associated functional brain alterations using one of the world's largest resting-state functional MRI (fMRI) biobank for the disorder. The biobank include...
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#1Caio Seguin (University of Melbourne)H-Index: 5
#2Ye Tian (University of Melbourne)H-Index: 4
Last. Andrew Zalesky (University of Melbourne)H-Index: 45
view all 3 authors...
The structure and function of the human connectome are coupled, but the correspondence is far from exact. We aimed to establish whether accounting for polysynaptic (multi-hop) paths in structural brain networks would improve prediction of interindividual variation in behavior as well as the strength of coupling with functional brain networks. Diffusion-weighted MRI and tractography were used to map structural connectomes for 889 healthy adults participating in the Human Connectome Project. To ac...
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