Artificial intelligence for brain diseases: A systematic review
Artificial intelligence (AI) is a major branch of computer science that is fruitfully used for
analyzing complex medical data and extracting meaningful relationships in datasets, for …
analyzing complex medical data and extracting meaningful relationships in datasets, for …
[HTML][HTML] What have we really learned from functional connectivity in clinical populations?
Functional connectivity (FC), or the statistical interdependence of blood-oxygen dependent
level (BOLD) signals between brain regions using fMRI, has emerged as a widely used tool …
level (BOLD) signals between brain regions using fMRI, has emerged as a widely used tool …
[HTML][HTML] Task fMRI paradigms may capture more behaviorally relevant information than resting-state functional connectivity
Characterizing the optimal fMRI paradigms for detecting behaviorally relevant functional
connectivity (FC) patterns is a critical step to furthering our knowledge of the neural basis of …
connectivity (FC) patterns is a critical step to furthering our knowledge of the neural basis of …
Individual variation in functional topography of association networks in youth
The spatial distribution of large-scale functional networks on the cerebral cortex differs
between individuals and is particularly variable in association networks that are responsible …
between individuals and is particularly variable in association networks that are responsible …
[HTML][HTML] Deep neural networks and kernel regression achieve comparable accuracies for functional connectivity prediction of behavior and demographics
There is significant interest in the development and application of deep neural networks
(DNNs) to neuroimaging data. A growing literature suggests that DNNs outperform their …
(DNNs) to neuroimaging data. A growing literature suggests that DNNs outperform their …
A set of functionally-defined brain regions with improved representation of the subcortex and cerebellum
An important aspect of network-based analysis is robust node definition. This issue is critical
for functional brain network analyses, as poor node choice can lead to spurious findings and …
for functional brain network analyses, as poor node choice can lead to spurious findings and …
[HTML][HTML] Beyond fingerprinting: Choosing predictive connectomes over reliable connectomes
ES Finn, MD Rosenberg - NeuroImage, 2021 - Elsevier
Recent years have seen a surge of research on variability in functional brain connectivity
within and between individuals, with encouraging progress toward understanding the …
within and between individuals, with encouraging progress toward understanding the …
Machine learning with neuroimaging: evaluating its applications in psychiatry
Psychiatric disorders are complex, involving heterogeneous symptomatology and
neurobiology that rarely involves the disruption of single, isolated brain structures. In an …
neurobiology that rarely involves the disruption of single, isolated brain structures. In an …
[HTML][HTML] Multimodal brain-age prediction and cardiovascular risk: The Whitehall II MRI sub-study
Brain age is becoming a widely applied imaging-based biomarker of neural aging and
potential proxy for brain integrity and health. We estimated multimodal and modality-specific …
potential proxy for brain integrity and health. We estimated multimodal and modality-specific …
Defining individual-specific functional neuroanatomy for precision psychiatry
Studies comparing diverse groups have shown that many psychiatric diseases involve
disruptions across distributed large-scale networks of the brain. There is hope that functional …
disruptions across distributed large-scale networks of the brain. There is hope that functional …