Individual characteristics outperform resting-state fMRI for the prediction of behavioral phenotypes.

In this study, we aimed to compare imaging-based features of brain function, measured by resting-state fMRI (rsfMRI), with individual characteristics such as age, gender, and total intracranial volume to predict behavioral measures. We developed a machine learning framework based on rsfMRI features in a dataset of 20,000 healthy individuals from the UK Biobank, focusing on temporal complexity and functional connectivity measures. Our analysis across four behavioral phenotypes revealed that both temporal complexity and functional connectivity measures provide comparable predictive performance.

Intermediately synchronised brain states optimise trade-off between subject specificity and predictive capacity.

Functional connectivity (FC) refers to the statistical dependencies between activity of distinct brain areas. To study temporal fluctuations in FC within the duration of a functional magnetic resonance imaging (fMRI) scanning session, researchers have proposed the computation of an edge time series (ETS) and their derivatives. Evidence suggests that FC is driven by a few time points of high-amplitude co-fluctuation (HACF) in the ETS, which may also contribute disproportionately to interindividual differences.

Insight does not come at random: Individual gray matter networks relate to clinical and cognitive insight in schizophrenia.

Background: Impaired clinical and cognitive insight are prevalent in schizophrenia and relate to poorer outcome. Good insight has been suggested to depend on social cognitive and metacognitive abilities requiring global integration of brain signals. Impaired insight has been related to numerous focal gray matter (GM) abnormalities distributed across the brain suggesting dysconnectivity at the global level.

Alpha Power and Functional Connectivity in Cognitive Decline: A Systematic Review and Meta-Analysis.

Background: Mild cognitive impairment (MCI) is a stage between expected age-related cognitive decline and dementia. Dementias have been associated with changes in neural oscillations across the frequency spectrum, including the alpha range. Alpha is the most prominent rhythm in human EEG and is best detected during awake resting state (RS).

Brain areas associated with clinical and cognitive insight in psychotic disorders: A systematic review and meta-analysis.

In the past years, ample interest in brain abnormalities related to clinical and cognitive insight in psychosis has contributed several neuroimaging studies to the literature. In the current study, published findings on the neural substrates of clinical and cognitive insight in psychosis are integrated by performing a systematic review and meta-analysis. Coordinate-based meta-analyses were performed with the parametric coordinate-based meta-analysis approach, non-coordinate based meta-analyses were conducted with the metafor package in R.