An Unguided, Computerized Cognitive Behavioral Therapy Intervention (TreadWill) in a Lower Middle-Income Country: Pragmatic Randomized Controlled Trial.

BACKGROUND: Globally, most individuals who are susceptible to depression do not receive adequate or timely treatment. Unguided computerized cognitive behavioral therapy (cCBT) has the potential to bridge this treatment gap. However, the real-world effectiveness of unguided cCBT interventions, particularly in low- and middle-income countries (LMICs), remains inconclusive. OBJECTIVE: In this study, we aimed to report the design and development of a new unguided cCBT-based multicomponent intervention, TreadWill, and its pragmatic evaluation. TreadWill was designed to be fully automated, engaging, easy to use, and accessible to LMICs. METHODS: To evaluate the effectiveness of TreadWill and the engagement level, we performed a double-blind, fully remote, and randomized controlled trial with 598 participants in India and analyzed the data using a completer's analysis. RESULTS: The users who completed at least half of the modules in TreadWill showed significant reduction in depression-related (P=.04) and anxiety-related (P=.02) symptoms compared with the waitlist control. Compared with a plain-text version with the same therapeutic content, the full-featured version of TreadWill showed significantly higher engagement (P=.01). CONCLUSIONS: Our study provides a new resource and evidence for the use of unguided cCBT as a scalable intervention in LMICs. TRIAL REGISTRATION: ClinicalTrials.gov NCT03445598; https://clinicaltrials.gov/ct2/show/NCT03445598.

Computational insights into mRNA and protein dynamics underlying synaptic plasticity rules.

Recent advances in experimental techniques provide an unprecedented peek into the intricate molecular dynamics inside synapses and dendrites. The experimental insights into the molecular turnover revealed that such processes as diffusion, active transport, spine uptake, and local protein synthesis could dynamically modulate the copy numbers of plasticity-related molecules in synapses. Subsequently, theoretical models were designed to understand the interaction of these processes better and to explain how local synaptic plasticity cues can up or down-regulate the molecular copy numbers across synapses. In this review, we discuss the recent advances in experimental techniques and computational models to highlight how these complementary approaches can provide insight into molecular cross-talk across synapses, ultimately allowing us to develop biologically-inspired neural network models to understand brain function.

Development and testing of a game-based digital intervention for working memory training in autism spectrum disorder.

Autism spectrum disorder (ASD) is prevalent globally, yet it lacks cost-effective treatment approaches. Deficits in executive functions occur frequently in autism spectrum disorder and present a target for intervention. Here we report the design and development of five smartphone-based games for training working memory in children with ASD. These open-source games, available free of cost to the community, were designed to match the behavioral preferences and sensorimotor abilities of children with ASD. We then conducted a preliminary trial to test the effectiveness of a month-long intervention using these games. Although we did not see a significant change in the working memory of all children with a month-long training, children who performed better on the games also showed more improvement in their working memory, suggesting that a longer intervention with the games might be useful in improving working memory. Using a Hindi translation of the autism treatment evaluation checklist, we also tested the collateral gains of the training in reducing autistic symptoms. We found no significant change in the autistic symptoms after the intervention. Further, there was no correlation between the change in the working memory and the change in the autistic symptoms.