Neuroimaging predictors of longitudinal disability and cognition outcomes in multiple sclerosis patients: A systematic review and meta-analysis.

BACKGROUND: Cross-sectional magnetic resonance imaging (MRI) studies have generated substantial evidence relating neuroimaging abnormalities to clinical and cognitive decline in multiple sclerosis (MS). Longitudinal neuroimaging studies may have additional value for predicting future cognitive deficits or clinical impairment, potentially leading to earlier interventions and better disease management. We conducted a meta-analysis of longitudinal studies using neuroimaging to predict cognitive decline (i.e. the Symbol Digits Modalities Test, SDMT) and disability outcomes (i.e. the Expanded Disability Status Scale, EDSS) in MS. METHODS: Our systematic literature search yielded 64 relevant publications encompassing 105 distinct sub-analyses. We performed a multilevel random-effects meta-analysis to estimate overall effect size for neuroimaging's ability to predict longitudinal cognitive and clinical decline, and a meta-regression to investigate the impact of distinct study factors on pooled effect size. RESULTS: In the EDSS analyses, the meta-analysis yielded a medium overall pooled effect size (Pearson's correlation coefficient r = 0.42, 95% CI [0.37; 0.46]). The meta-regression further indicated that analyses exclusively evaluating gray matter tissue had significantly stronger effect sizes than analyses of white matter tissue or whole brain analyses (p < 0.05). No other study factors significantly influenced the pooled effect size (all p > 0.05). In the SDMT analyses, the meta-analysis yielded a medium overall pooled effect size (r = 0.47, 95% CI [0.32; 0.60]). The meta-regression found no significant study factors influencing the pooled effect size. CONCLUSION: The present findings indicate that brain imaging is a medium predictor of longitudinal change in both disability progression (EDSS) and cognitive decline (SDMT). These findings reinforce the need for further longitudinal studies standardizing methods, using multimodal approaches, creating data consortiums, and publishing more complete datasets investigating MRI modalities to predict longitudinal disability and cognitive decline.

Implicit emotion regulation in adolescent girls: An exploratory investigation of Hidden Markov Modeling and its neural correlates.

Numerous data demonstrate that distracting emotional stimuli cause behavioral slowing (i.e. emotional conflict) and that behavior dynamically adapts to such distractors. However, the cognitive and neural mechanisms that mediate these behavioral findings are poorly understood. Several theoretical models have been developed that attempt to explain these phenomena, but these models have not been directly tested on human behavior nor compared. A potential tool to overcome this limitation is Hidden Markov Modeling (HMM), which is a computational approach to modeling indirectly observed systems. Here, we administered an emotional Stroop task to a sample of healthy adolescent girls (N = 24) during fMRI and used HMM to implement theoretical behavioral models. We then compared the model fits and tested for neural representations of the hidden states of the most supported model. We found that a modified variant of the model posited by Mathews et al. (1998) was most concordant with observed behavior and that brain activity was related to the model-based hidden states. Particularly, while the valences of the stimuli themselves were encoded primarily in the ventral visual cortex, the model-based detection of threatening targets was associated with increased activity in the bilateral anterior insula, while task effort (i.e. adaptation) was associated with reduction in the activity of these areas. These findings suggest that emotional target detection and adaptation are accomplished partly through increases and decreases, respectively, in the perceived immediate relevance of threatening cues and also demonstrate the efficacy of using HMM to apply theoretical models to human behavior.

Brain activation by disgust-inducing pictures in obsessive-compulsive disorder.

BACKGROUND: There is growing interest in the role of disgust in the pathogenesis of obsessive-compulsive disorder (OCD). METHODS: Eight OCD subjects with contamination preoccupations and eight gender- and age-matched healthy volunteers viewed pictures from the International Affective Picture System during functional magnetic resonance imaging scans. RESULTS: A different distribution of brain activations was found during disgust-inducing visual stimulation in several areas, most notably the insula, compared with neutral stimulation in both OCD subjects and healthy volunteers. Furthermore, whereas activation during the threat-inducing task in OCD subjects showed a pattern similar to that in healthy volunteers, the pattern of activation during the disgust-inducing task was significantly different, including greater increases in the right insula, parahippocampal region, and inferior frontal sites. CONCLUSIONS: This pilot study supports the relevance of disgust in the neurocircuitry of OCD with contamination-preoccupation symptoms; future studies looking at non-OCD individuals with high disgust ratings, non-contamination-preoccupied OCD individuals, and individuals with other anxiety disorders are needed.