Neurocomputational Mechanisms of Affective Semantic Memory Development

PROJECT SUMMARY / ABSTRACT My career goal is to lead an interdisciplinary team that investigates the developmental neurocomputational mechanisms that link early-life adversity to mental health. To reach this goal, I require intensive training in human neuroimaging methods, cognitive computational neuroscience, and dyadic methodologies. My training to date has provided a strong foundation of skills in developmental neuroscience, early-life adversity, statistical modeling, experience sampling, and machine learning. I identified the best possible mentorship team and scientific environment to support me in expanding this skill set with essential training in emotional memory, fMRI analysis, computational modeling, real-world dyadic (parent-child) behavior methods, and professional skills. With this protected training time, I will be poised to successfully transition to a competitive postdoctoral position and ultimately obtain a tenure-track faculty position at the forefront of developmental neuroscience. Research: More than one-third of children experience early caregiving adversity such as abuse, neglect, and parental abandonment/separation, which accounts for the onset of at least 30-45% of mental health disorders world-wide. Clinical association studies show that this increased risk for psychopathology is linked to perturbations in midline cortico-subcortical circuitry, comprised of the midcingulo-insular “salience” network and posterior-medial “default mode” network. At the same time, experimental studies in cognitive neuroscience find that this circuitry has a broader functional role in semantic social and affective knowledge. Might the neural alterations that give rise to psychopathology risk following early caregiving adversity be one and the same as the neurobiology found to represent learned affective semantic memories? In line with my preliminary data, I will test the hypothesis that alterations in midline cortico-subcortical circuitry following early adversity represent the affective semantic knowledge learned during early caregiving experiences. During the F99-phase, I will identify the midline cortico-subcortical activity patterns associated with children’s affective semantic memories during fMRI in a developmental sample enriched for early caregiving adversity (Aim 1.1), and then examine the links between affective semantic neural representations and real-world parent-child emotional behaviors using dyadic ecological momentary assessments (Aim 1.2). In the K00-phase, I will determine whether Bayesian predictive coding in midline cortico-subcortical circuitry explains the neural computations underlying affective semantic memory in childhood and examine how these neurocomputational mechanisms differ as a function of age, socioemotional context, and early adversity exposure (Aim 2). This research will result in more powerful, ecologically-sensitive computational models of human development through the integration of cutting-edge approaches to neurocomputation, real-time parent-child behavior, and affective semantic memory. Such advances have the potential to significantly extend neurodevelopmental models of psychopathology, which is essential for developing interventions tailored to age, early experience, and neurocomputational mechanism.