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Previous studies have found neural alterations in regions involved in cognitive and affective functions among Crohn’s disease (CD) patients. The present work recruited 18 CD patients and 18 age-gender matched healthy controls (HC) and specifically compared differences in resting-state functional connectivity (RSFC) within the executive control network (ECN) which has been implicated in cognitive function and default mode network (DMN), which has been implicated in affective function. Additionally, we examined the correlations between RSFC in ECN and verbal fluency (VF) in both groups as well as RSFC in DMN and anxiety level in the CD group. Results showed significantly increased RSFC between the right middle frontal gyrus and right inferior parietal lobule in ECN, as well as increased RSFC between the right precuneus and right posterior cingulate cortex in DMN, among CD patients compared to HC. However, the correlations between ECN/DMN and behavioral scores in each group were not significant, which was possibility due to the limited sample size. These findings suggest that CD patients may experience changes in the connectivity patterns in ECN and DMN. Increased connectivity observed on these networks could be a potential biomarker of a neuropsychiatric manifestation of CD.

Patients with inflammatory bowel disease have been shown to have abnormal brain morphometry or function, which are associated with psychological symptoms such as stress, depression or anxiety. The present work recruited 20 Crohn’s disease patients in remission (CDs) and 20 age-gender-handedness-education matched healthy controls (HCs) and compared their brain white matter microstructural properties using Diffusion Tensor Imaging (DTI). Additionally, we examined the correlations between the microstructural properties and cognition (verbal fluency language task, VF) and affect (anxiety) in both groups as well as disease duration in CDs. Results showed that CDs exhibited significant alterations in microstructural properties compared to HCs in various white matter tracts relevant to language function despite no significant difference in VF scores. Furthermore, CDs’ microstructural changes exhibited correlations with anxiety level and disease duration. These findings suggest that CD patients may experience changes in white matter microstructural properties which may be a biomarker of neuropsychiatric comorbidities of CD.

Functional magnetic resonance imaging (fMRI)-based functional connectivity (FC) commonly characterizes the functional connections in the brain. Conventional quantification of FC by Pearson's correlation captures linear, time-domain dependencies among blood-oxygen-level-dependent (BOLD) signals. We examined measures to quantify FC by investigating: (i) Is Pearson's correlation sufficient to characterize FC? (ii) Can alternative measures better quantify FC? (iii) What are the implications of using alternative FC measures? FMRI analysis in healthy adult population suggested that: (i) Pearson's correlation cannot comprehensively capture BOLD inter-dependencies. (ii) Eight alternative FC measures were similarly consistent between task and resting-state fMRI, improved age-based classification and provided better association with behavioral outcomes. (iii) Formulated hypotheses were: first, in lieu of Pearson’s correlation, an augmented, composite and multi-metric definition of FC is more appropriate; second, canonical large-scale brain networks may depend on the chosen FC measure. A thorough notion of FC promises better understanding of variations within a given population.

Cortical thickness is traditionally derived from T1-weighted MRI images. Recent studies have shown an improvement in segmentation with the combination of T1 + T2-FLAIR images. MRI data from 54 adults (mean: 71 years, 65–81 years, 48% females) that are part of an ongoing cohort study were analyzed to investigate whether T1 + T2-FLAIR cortical thickness measurements were superior to those derived from T1-weighted images in identifying age-related atrophy. T1-weighted and T2-FLAIR MRI images were processed through FreeSurfer v6.0. Data was extracted using the Desikan-Killiany (DKT) atlas. FreeSurfer’s GUI QDEC examined age-related atrophy. Nonparametric tests, effect sizes, and Pearson correlations examined differences between T1-only and T1 + T2-FLAIR cortical thickness data. These analyses demonstrated that T1 + T2-FLAIR processed images significantly improved the segmentation of gray matter (chi-square x2, p