Research Knowledge Graph

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Semantic topology

A live map of the conceptual space underlying this research. Nodes are key constructs weighted by theoretical centrality; edges encode semantic proximity between ideas.

The contour lines show spreading activation — a computational model of how concepts in memory illuminate each other along associative pathways (Collins & Loftus, 1975). The topography is the same mathematics as a gradient descent loss landscape: peaks form where activation concentrates, valleys where it is absent. Tighter contours = steeper gradient = faster change in activation.

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Activation intensity

low activationhigh activation

Contour lines show activation density. Tighter spacing = steeper gradient. Peaks form where semantically related concepts activate together.

Self-Regulation

Core cognitive processes enabling adaptive responses to context: emotion regulation, executive function, and flexible goal pursuit.

Predictive Brain

Computational frameworks for how the brain forms predictions, encodes surprise, and updates beliefs in response to expectancy violations.

Generative AI

Large language models, text-to-image systems, and their applications in behavior change, creativity support, and intervention design.

Interventions

Translational work designing, testing, and personalizing behavior change interventions — from health apps to AI-assisted driving interfaces.

Neuroeconomics

Neural and computational basis of value, reward learning, intertemporal choice, and how motivation shapes decision-making under uncertainty.

Social Neuroscience

How social context and emotion modulate cognition — including social learning, moral judgment, empathy, and bias in consequential decisions.

Consumer & Preference

Preference elicitation, cognitive complexity of choice, and how perceptual and linguistic features of products predict consumer decisions.