Functional alteration due to structural damage is network dependent: insight from multiple sclerosis.

Little is known about how the brain's functional organization changes over time with respect to structural damage. Using multiple sclerosis as a model of structural damage, we assessed how much functional connectivity (FC) changed within and between preselected resting-state networks (RSNs) in 122 subjects (72 with multiple sclerosis and 50 healthy controls). We acquired the structural, diffusion, and functional MRI to compute functional connectomes and structural disconnectivity profiles.

Time-resolved multivariate pattern analysis of infant EEG data: A practical tutorial.

Time-resolved multivariate pattern analysis (MVPA), a popular technique for analyzing magneto- and electro-encephalography (M/EEG) neuroimaging data, quantifies the extent and time-course by which neural representations support the discrimination of relevant stimuli dimensions. As EEG is widely used for infant neuroimaging, time-resolved MVPA of infant EEG data is a particularly promising tool for infant cognitive neuroscience. MVPA has recently been applied to common infant imaging methods such as EEG and fNIRS.

Diagnosis of depression in multiple sclerosis is predicted by frontal-parietal white matter tract disruption.

Background: Persons with multiple sclerosis (PwMS) are at an elevated risk of depression. Decreased Conscientiousness may affect patient outcomes in PwMS. Low Conscientiousness has a strong correlation with depression.

Preserved network functional connectivity underlies cognitive reserve in multiple sclerosis.

Cognitive reserve is one's mental resilience or resistance to the effects of structural brain damage. Reserve effects are well established in people with multiple sclerosis (PwMS) and Alzheimer's disease, but the neural basis of this phenomenon is unclear. We aimed to investigate whether preservation of functional connectivity explains cognitive reserve.

Lower self-report fatigue in multiple sclerosis is associated with localized white matter tract disruption between amygdala, temporal pole, insula, and other connected structures.

Background: Fatigue, a frequent and disabling symptom for people with multiple sclerosis (PwMS), inconsistently correlates with white matter (WM) pathology. Network-based analysis, accounting for the manner in which lesions disrupt networks of structurally connected gray matter (GM) regions, may provide additional insight.

Objective: To identify patterns of WM tract disruption which explain self-reported fatigue severity in PwMS.