Stuart Oldham

ORCID: 0000-0002-9619-6102
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About
Contact & Profiles
Research Areas
  • Functional Brain Connectivity Studies
  • Advanced Neuroimaging Techniques and Applications
  • Neural dynamics and brain function
  • Advanced MRI Techniques and Applications
  • Genetic Neurodegenerative Diseases
  • Bioinformatics and Genomic Networks
  • Complex Network Analysis Techniques
  • Mental Health Research Topics
  • Genetics and Physical Performance
  • Neurological disorders and treatments
  • Schizophrenia research and treatment
  • Fibromyalgia and Chronic Fatigue Syndrome Research
  • Opinion Dynamics and Social Influence
  • Social Capital and Networks
  • Cerebral Palsy and Movement Disorders
  • Memory and Neural Mechanisms
  • Tryptophan and brain disorders
  • Transcranial Magnetic Stimulation Studies
  • Cardiovascular Disease and Adiposity
  • Traumatic Brain Injury Research
  • Neural and Behavioral Psychology Studies
  • Congenital Diaphragmatic Hernia Studies
  • Neonatal and fetal brain pathology
  • MRI in cancer diagnosis
  • Pregnancy and preeclampsia studies

Monash University
2016-2025

Murdoch Children's Research Institute
2021-2025

University of Wollongong
2024

Deakin University
2024

Royal Children's Hospital
2022-2024

Australian Regenerative Medicine Institute
2020-2024

Hologic (Germany)
2024

The University of Melbourne
2024

Allen Institute for Brain Science
2023

Australian Catholic University
2022

The roles of different nodes within a network are often understood through centrality analysis, which aims to quantify the capacity node influence, or be influenced by, other via its connection topology. Many measures have been proposed, but degree they offer unique information, and such whether it is advantageous use multiple define roles, unclear. Here we calculate correlations between 17 across 212 diverse real-world networks, examine how these relate variations in density global...

10.1371/journal.pone.0220061 article EN cc-by PLoS ONE 2019-07-26

Brain network hubs are both highly connected and inter-connected, forming a critical communication backbone for coherent neural dynamics. The mechanisms driving this organization poorly understood. Using diffusion-weighted magnetic resonance imaging in twins, we identify major role genes, showing that they preferentially influence connectivity strength between of the human connectome. transcriptomic atlas data, show demonstrate tight coupling transcriptional activity related to metabolic...

10.1038/s41467-021-24306-2 article EN cc-by Nature Communications 2021-07-09

Regional heterogeneity in the brain’s transcriptional landscape supports complex neuronal dynamics.

10.1126/sciadv.abf4752 article EN cc-by-nc Science Advances 2021-07-14

The complex connectivity of nervous systems is thought to have been shaped by competitive selection pressures minimize wiring costs and support adaptive function. Accordingly, recent modeling work indicates that stochastic processes, putative trade-offs between the cost value each connection, can successfully reproduce many topological properties macroscale human connectomes measured with diffusion magnetic resonance imaging. Here, we derive a new formalism more accurately captures competing...

10.1126/sciadv.abm6127 article EN cc-by-nc Science Advances 2022-06-03

Head motion is a major confounding factor in neuroimaging studies. While numerous studies have investigated how impacts estimates of functional connectivity, the effects on structural connectivity measured using diffusion MRI not received same level attention, despite fact that, like MRI, relies elaborate preprocessing pipelines that require multiple choices at each step. Here, we report comprehensive analysis these influence motion-related contamination estimates. Using healthy adult sample...

10.1016/j.neuroimage.2020.117252 article EN cc-by NeuroImage 2020-08-13

Intrinsic timescales of activity fluctuations vary hierarchically across the brain. This variation reflects a broad gradient functional specialization in information storage and processing, with integrative association areas displaying slower that are thought to reflect longer temporal processing windows. The organization is associated cognitive function, distinctive between individuals, disrupted disease, but we do not yet understand how properties dynamics shaped by brain’s underlying...

10.1162/netn_a_00151 article EN cc-by Network Neuroscience 2020-01-01

Brain networks exhibit non-trivial modular organization, with groups of densely connected areas participating in specialized functions. Traditional community detection algorithms assign each node to one module, but this representation cannot capture integrative, multi-functional nodes that span multiple communities. Despite the increasing availability overlapping (OCDAs) such integrative nodes, there is no objective procedure for selecting most appropriate method and its parameters a given...

10.1101/2025.03.19.643839 preprint EN cc-by-nc bioRxiv (Cold Spring Harbor Laboratory) 2025-03-20

Generative models of the human connectome enable in silico generation brain networks based on probabilistic wiring rules. These rules are governed by a small number parameters that typically fitted to individual connectomes and quantify extent which geometry topology shape generative process. A significant shortcoming modeling large cohort studies is parameter estimation computationally burdensome, accuracy reliability current methods remain untested. Here, we propose fast, reliable,...

10.1016/j.neuroimage.2023.119962 article EN cc-by-nc-nd NeuroImage 2023-02-22

Recent years have seen a surge in the use of diffusion MRI to map connectomes humans, paralleled by similar increase processing and analysis choices. Yet these different steps their effects are rarely compared systematically. Here, healthy young adult population (n = 294), we characterized impact range pipelines on one widely studied property human connectome: its degree distribution. We evaluated 40 (comparing common choices parcellation, streamline seeding, tractography algorithm,...

10.1162/netn_a_00324 article EN cc-by Network Neuroscience 2023-01-01

Large-scale dynamics of the brain are routinely modelled using systems nonlinear dynamical equations that describe evolution population-level activity, with distinct neural populations often coupled according to an empirically measured structural connectivity matrix. This modelling approach has been used generate insights into underpinnings spontaneous dynamics, as recorded techniques such resting state functional MRI (fMRI). In fMRI, researchers have many degrees freedom in way they can...

10.1016/j.neuroimage.2022.119051 article EN cc-by-nc-nd NeuroImage 2022-03-08

The thalamus enables key sensory, motor, emotive, and cognitive processes via connections to the cortex. These projection patterns are traditionally considered originate from discrete thalamic nuclei, however recent work showing gradients of molecular connectivity features in suggests organisation thalamocortical occurs along a continuous dimension. By performing joint decomposition densely sampled gene expression non-invasive diffusion tractography adult human thalamus, we define principal...

10.1038/s41467-023-41722-8 article EN cc-by Nature Communications 2023-09-27

Resting-state connectivity measures the temporal coherence of spontaneous neural activity spatially distinct regions, and is commonly measured using BOLD-fMRI. The BOLD response follows neuronal activity, when changes in relative concentration oxygenated deoxygenated haemoglobin cause fluctuations MRI T2* signal. Since signal detects concentrations oxy/deoxy-haemoglobin, individual differences levels may influence signal-to-noise ratio a manner independent degree activity. In this study, we...

10.1016/j.neuroimage.2020.117196 article EN cc-by-nc-nd NeuroImage 2020-07-25

Abstract The third trimester of human gestation is characterised by rapid increases in brain volume and cortical surface area. A growing catalogue cells the prenatal has revealed remarkable molecular diversity across areas. 1,2 Despite this, little known about how this translates into patterns differential expansion observed humans during latter stages gestation. Here we present a new resource, μBrain, to facilitate knowledge translation between anatomical descriptions developing brain....

10.1101/2024.02.13.580198 preprint EN cc-by bioRxiv (Cold Spring Harbor Laboratory) 2024-02-13

Abstract While cortical patterning has been a perennial research topic in neuroscience, the mechanism for its consequence, namely functional specialization at macro scale, remains an open question human brain. Here, we focused on age-dependent changes of resting-state thalamocortical connectivity to investigate role emergence large-scale networks across infancy, childhood and young adulthood. We found that during infancy reflects early differentiation sensorimotor genetically-influenced...

10.1101/2024.03.11.584415 preprint EN cc-by-nc-nd bioRxiv (Cold Spring Harbor Laboratory) 2024-03-12

Abstract The third trimester of human gestation is characterised by rapid increases in brain volume and cortical surface area. Recent studies have revealed a remarkable molecular diversity across the prenatal cortex but little known about how this translates into differential rates expansion observed during gestation. We present digital resource, μBrain, to facilitate knowledge translation between anatomical descriptions brain. Using we evaluate signatures preferentially-expanded regions,...

10.1038/s41467-024-54034-2 article EN cc-by Nature Communications 2024-11-08

Brain network hubs are both highly connected and inter-connected, forming a critical communication backbone for coherent neural dynamics. The mechanisms driving this organization poorly understood. Using diffusion-weighted imaging in twins, we identify major role genes, showing that they preferentially influence connectivity strength between of the human connectome. transcriptomic atlas data, show demonstrate tight coupling transcriptional activity related to metabolic cytoarchitectonic...

10.1101/2020.06.21.163915 preprint EN cc-by bioRxiv (Cold Spring Harbor Laboratory) 2020-06-22
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