Shi, T. C. | bioRxiv Science

bioRxiv2019

Aversive learning strengthens episodic memory in both adolescents and adults

Adolescence is often filled with positive and negative emotional experiences that may change how individuals remember and respond to stimuli in their environment. In adults, aversive events can both enhance memory for associated stimuli as well as generalize to enhance memory for unreinforced but conceptually related stimuli. The present study tested whether learned aversive associations similarly lead to better memory and generalization across a category of stimuli in adolescents. Participants completed an olfactory Pavlovian category conditioning task in which trial-unique exemplars from one of two categories were partially reinforced with an aversive odor. Participants then returned 24-hours later to complete a surprise recognition memory test. We found better corrected recognition memory for the reinforced versus the unreinforced category of stimuli in both adults and adolescents. Further analysis revealed that enhanced recognition memory was driven specifically by better memory for the reinforced exemplars. Autonomic arousal during learning was also related to subsequent memory. These findings build on previous work in adolescent and adult humans and rodents showing comparable acquisition of aversive Pavlovian conditioned responses across age groups and demonstrate that memory for stimuli with an acquired aversive association is enhanced in both adults and adolescents.

animal behavior and cognition↗

bioRxiv2018

Functional and Optogenetic Approaches to Discovering Stable Subtype-Specific Circuit Mechanisms in Depression

BackgroundUsing canonical correlation analysis (CCA), hierarchical clustering, and machine learning methods, we recently identified four subtypes of depression defined by distinct patterns of abnormal functional connectivity in depression-related brain networks, which in turn predicted differing clinical symptom profiles and individual differences in treatment response. However, whether and how dysfunction in specific circuits may give rise to specific depressive symptoms and behaviors remains unclear. Furthermore, this approach assumes that there are robust and stable canonical correlations between functional connectivity and depressive symptoms--an assumption that was not extensively tested in our earlier work.\n\nMethodsFirst, we comprehensively re-evaluate the stability of canonical correlations between functional connectivity and symptoms, using optimized approaches for large-scale statistical testing, and we validate methods for improving stability. Next, we illustrate one approach to formulating hypotheses regarding subtype-specific circuit mechanisms driving depressive symptoms and behaviors and then testing them in animal models using optogenetic fMRI. We review recent work in this field and describe one example of this approach.\n\nResultsCorrelations between connectivity features and clinical symptoms are robustly significant, and CCA solutions tested repeatedly on held-out data generalize, but they are sensitive to data quality, preprocessing decisions, and clinical sample heterogeneity, which can reduce effect sizes. Generalization can be markedly improved by adding L2-regularization to CCA, which decreases variance, increases canonical correlations in left-out data, and stabilizes feature selection. This approach, in turn, can be used to identify candidate circuits for optogenetic interrogation in rodent models.\n\nConclusionsMulti-view approaches like CCA are a conceptually useful framework for discovering stable patient subtypes by synthesizing multiple clinical and functional measures. Optogenetic fMRI holds substantial promise for testing hypotheses regarding subtype-specific mechanisms driving specific symptoms and behaviors in depression.

neuroscience↗