ArticleDialogues in clinical neuroscience2018
Data-driven approaches for identifying links between brain structure and function in health and disease.
Article in Dialogues in clinical neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed.
- Comprehensive mapping of cognitive and emotion networks in stress, anxiety, and depression implicates the precuneus as a critical hub.Research square · 2025Article
- Neurobiology-based cognitive biotypes using multi-scale intrinsic connectivity networks in psychotic disorders.Schizophrenia (Heidelberg, Germany) · 2025Article
- Simulated driving behavior over the adult age span.Frontiers in aging neuroscience · 2025Article
- Artificial Intelligence in the Diagnosis and Quantitative Phenotyping of Hyperkinetic Movement Disorders: A Systematic Review.Journal of clinical medicine · 2024Review
- Symptom-guided multimodal neuroimage fusion patterns in children with attention-deficit/hyperactivity disorder and its potential "brain structure-function-cognition-behavior" pathological pathways.European child & adolescent psychiatry · 2024Article
- A spatially constrained independent component analysis jointly informed by structural and functional network connectivity.bioRxiv : the preprint server for biology · 2024Article
- Searching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities.NeuroImage · 2024Article
- A spatially constrained independent component analysis jointly informed by structural and functional network connectivity.Network neuroscience (Cambridge, Mass.) · 2024Article
- Genes Associated with Altered Brain Structure and Function in Obstructive Sleep Apnea.Biomedicines · 2023Article
- Resting state network connectivity is associated with cognitive flexibility performance in youth in the Adolescent Brain Cognitive Development Study.Neuropsychologia · 2023Article
- Voxel-wise Fusion of Resting fMRI Networks and Gray Matter Volume for Alzheimer's Disease Classification using Deep Multimodal Learning.Research square · 2023Article
- Alcohol use is associated with affective and interoceptive network alterations in bipolar disorder.Brain and behavior · 2023Article
- Multimodal fusion analysis of functional, cerebrovascular and structural neuroimaging in healthy aging subjects.Human brain mapping · 2022Article
- Structure-function clustering in weighted brain networks.Scientific reports · 2022Article
- Parallel factor analysis for multidimensional decomposition of functional near-infrared spectroscopy data.Neurophotonics · 2022Article
- The integrative functional connectivity analysis between seafarer's brain networks using functional magnetic resonance imaging data of different states.Frontiers in neuroscience · 2022Article
- Joint Analysis of Functional and Structural Connectomes Between Preterm and Term Infant Brains via Canonical Correlation Analysis With Locality Preserving Projection.Frontiers in neuroscience · 2021Article
- Automated classification of depression from structural brain measures across two independent community-based cohorts.Human brain mapping · 2020Article
- Executive Impairment in Alcohol Use Disorder Reflects Structural Changes in Large-Scale Brain Networks: A Joint Independent Component Analysis on Gray-Matter and White-Matter Features.Frontiers in psychology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
Brain imaging technology provides a powerful tool to visualize the living human brain, provide insights into disease mechanisms, and potentially provide a tool to assist clinical decision-making. The brain has a very specific structural substrate providing a foundation for functional information; however, most studies ignore the very interesting and complex relationships between brain structure and brain function. While a variety of approaches have been used to study how brain structure informs function, the study of such relationships in living humans in most cases is limited to noninvasive approaches at the macroscopic scale. The use of data-driven approaches to link structure and function provides a tool which is especially important at the macroscopic scale at which we can study the human brain. This paper reviews data-driven approaches, with a focus on independent component analysis approaches, which leverage higher order statistics to link together macroscopic structural and functional MRI data. Such approaches provide the benefit of allowing us to identify links which do not necessarily correspond spatially (eg, structural changes in one region related to functional changes in other regions). They also provide a "network level" perspective on the data, by enabling us to identify sets of brain regions that covary together. This also opens up the ability to evaluate both within and between network relationships. A variety of examples are presented, including several showing the potential of such approaches to inform us about mental illness, particularly about schizophrenia.
Indexed as
Identifiers
30250386PMC6136124What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.