The best compromise between task duration and interpretability occurred on a version with a short ISI and a strong prepotency.

Improved fMRI data analysis methods hold promise for breakthroughs in cognitive and affective neuroscience. Group probabilistic independent component analysis (pICA), such as that implemented by MELODIC (Beckmann & Smith IEEE Transactions on Medical Imaging 23:137-152, 2004), is one popular technique that typifies this development. Recently pICA has been proposed to be a reliable method for studying connectivity networks (Zuo et al. NeuroImage 49:2163-2177, 2010); however, there is no "standard" way to complete a pICA, and the full impact of the options on neurometric properties of resulting components is unknown. In the present study, we sought to assess the robustness, reproducibility, and within-subject test-retest reliability of ICA in two data sets: The first included 30 subjects imaged 3 weeks apart while completing a cognitive control task, and the second included 27 subjects imaged 9 months apart during rest. In addition to examining the impact of analytic parameters on the neurometrics, this study was the first to simultaneously investigate within-subject reliability of ICA-derived components from rest and task fMRI data. Results suggested that for both task and rest, meta-level analyses using 25 subject orders optimized robustness of the components. The impact of dimensionality and voxel threshold for components was subsequently examined regarding properties of reproducibility and within-subject retest reliability. Component thresholds between 0.2 and 0.6 of the maximum value optimized reproducibility across multiple dimensionalities and produced generally fair to moderate reliability estimates (Cicchetti & Sparrow American Journal of Mental Deficiency 86:127-137, 1981). These guidelines strengthen the foundation for this data-driven approach to fMRI analysis by providing prescriptive findings and a descriptive set of neurometrics for resting-state and task fMRI.

Patients with schizophrenia (SZ) previously demonstrated specific deficits in an executive function known as goal maintenance, associated with reduced middle frontal gyrus (MFG) activity. This study aimed to validate a new tool-the Dot Pattern Expectancy (DPX) task-developed to facilitate multisite imaging studies of goal maintenance deficits in SZ or other disorders. Additionally, it sought to arrive at recommendations for scan length for future studies using the DPX. Forty-seven SZ and 56 healthy controls (HC) performed the DPX in 3-Tesla functional magnetic resonance imaging (fMRI) scanners at 5 sites. Group differences in DPX-related activity were examined with whole brain voxelwise analyses. SZs showed the hypothesized specific performance deficits with as little as 1 block of data. Reduced activity in SZ compared with HC was observed in bilateral frontal pole/MFG, as well as left posterior parietal lobe. Efficiency analyses found significant group differences in activity using 18 minutes of scan data but not 12 minutes. Several behavioral and imaging findings from the goal maintenance literature were robustly replicated despite the use of different scanners at different sites. We did not replicate a previous correlation with disorganization symptoms among patients. Results were consistent with an executive/attention network dysfunction in the higher levels of a cascading executive system responsible for goal maintenance. Finally, efficiency analyses found that 18 minutes of scanning during the DPX task is sufficient to detect group differences with a similar sample size.

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