Multi-model order spatially constrained ICA reveals highly replicable group differences and consistent predictive results from resting data: A large N fMRI schizophrenia study.

Brain functional networks identified from resting functional magnetic resonance imaging (fMRI) data have the potential to reveal biomarkers for brain disorders, but studies of complex mental illnesses such as schizophrenia (SZ) often yield mixed results across replication studies. This is likely due in part to the complexity of the disorder, the short data acquisition time, and the limited ability of the approaches for brain imaging data mining. Therefore, the use of analytic approaches which can both capture individual variability while offering comparability across analyses is highly preferred.

Multi-spatial-scale dynamic interactions between functional sources reveal sex-specific changes in schizophrenia.

We introduce an extension of independent component analysis (ICA), called multiscale ICA, and design an approach to capture dynamic functional source interactions within and between multiple spatial scales. Multiscale ICA estimates functional sources at multiple spatial scales without imposing direct constraints on the size of functional sources, overcomes the limitation of using fixed anatomical locations, and eliminates the need for model-order selection in ICA analysis. We leveraged this approach to study sex-specific and sex-common connectivity patterns in schizophrenia.

Reduced Amplitude of Low-Frequency Brain Oscillations in the Psychosis Risk Syndrome and Early Illness Schizophrenia.

Low-frequency oscillations (LFOs) of the blood oxygen level-dependent (BOLD) signal are gaining interest as potential biomarkers sensitive to neuropsychiatric pathology. Schizophrenia has been associated with alterations in intrinsic LFOs that covary with cognitive deficits and symptoms. However, the extent to which LFO dysfunction is present before schizophrenia illness onset remains unknown.

A novel method for quantifying scanner instability in fMRI.

A method was developed to quantify the effect of scanner instability on functional MRI data by comparing the instability noise to endogenous noise present when scanning a human. The instability noise was computed from agar phantom data collected with two flip angles, allowing for a separation of the instability from the background noise. This method was used on human data collected at four 3 T scanners, allowing the physiological noise level to be extracted from the data.

Brain-performance correlates of working memory retrieval in schizophrenia: a cognitive modeling approach.

Correlations of cognitive functioning with brain activation during a sternberg item recognition paradigm (SIRP) were investigated in patients with schizophrenia and in healthy controls studied at 8 sites. To measure memory scanning times, 4 response time models were fit to SIRP data. The best fitting model assumed exhaustive serial memory scanning followed by self-terminating memory search and involved one intercept parameter to represent SIRP processes not contributing directly to memory scanning.