Inducing Mirth to Improve Memory in Depression

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Major Depressive Disorder (MDD) impacts an estimated 17.3 million adult Americans per year, which places an enormous burden on the affected individuals as well as our healthcare system. An understudied but pernicious component of depression is its harmful impact on people’s ability to remember happy events. If we gained a clear understanding of neural processes that underly this positive memory deficit, we would be better equipped to alleviate this disruption. A promising model of this memory deficit posits that encoding of positive memories is weakened by depression because of dampened dopaminergic (DA) bursts that typically help encode positive information (Dillon & Pizzagalli, 2018). Furthermore, pleasant events might not effectively translate into long-term memory storage (and consequently be harder to retrieve) because of their incongruity with depressed individuals’ dysphoric mood. The goals of the current proposal are to use Event-Related- Potentials (ERPs) and computational modeling to test and extend this model by determining whether positive mood induction (via mirth) can alleviate the positive memory deficit in individuals with MDD. The PI will evoke a P300 ERP in adult participants (96 MDD and 96 Healthy Controls; HCs) during a memory encoding task and examine whether its amplitude (i.e. strength of neural response) relates to participants’ diagnosis and memory performance. All subjects will complete a clinical interview on day 1 (Session 1), complete a positive mood induction (or a control task) and encode 120 pictures day 2 (Session 2). On day 3, following 24-hours to allow for memory consolidation, participants will complete a memory recognition test (Session 3). P300 ERP will be triggered in response to positive, negative, and neutral images during memory encoding, by presenting these pictures at an infrequent (9%) rate intermixed with squares (91% rate). This design will allow us to measure whether P300 amplitude (which signals DA mediated prediction errors) is lowed in participants with MDD, relative to HCs, when they encode positive pictures (Aim 1). We will also apply the Hierarchical Drift Diffusion Model to memory recognition data, in order to test the prediction that adults with MDD will exhibit slower evidence accumulation (thus, impaired memory reconstruction) as they retrieve positive images, in contrast to HCs (Aim 2). Finally, we will test the prediction that a mirth induction will raise positive affect, boost P300 responses to positive pictures, and reduce the positive memory deficit in adults with MDD (Aim 3). By completing this project, the PI will obtain excellent training in applying electroencephalography (EEG), computational modeling, and mood induction techniques towards translational research. This training will build on the PI’s expertise in structural neuroimaging and enable him to conduct more clinically impactful research. McLean Hospital will provide the PI with a world-class environment for conducting this study, with full support for the PI’s training. Completion of this project and training will ultimately enable the PI to accomplish his goal of becoming a leader in translational research with a focus on alterations in positive affect.