Coevolutionary Psychology and the Embodied Social Brain: A Functionalist Approach to Social Signal Detection
My research explores how social and emotional signals are detected and remembered, applying classic methods of cognitive science to real-world content and scenarios. I begin with the assumption that humans share a suite of fundamental Motivational and Emotional Systems (MES), designed to learn to pick up information about threats and opportunities relevant to our basic social goals. Experiments on threat detection illustrate both the biasing and sensitizing effects of such MES, including limits to threat-detection imposed by bottom-up properties of the signal. Related work on attention and memory suggest that even transitory activations of MES can enhance information pick-up in measurable ways. At a more theoretical level, these results suggest that dynamic internal simulations underlie both perception and action, providing a shared workspace in which MES maintain vigilance for goal-relevant stimuli and interact with one another when multiple conflicting goals arise. The central tendencies of these systems are like Jung’s Archetypes, representational proclivities that span the gap between proximate online embodiment and ancient drives, grounding the symbolic and propositional models of traditional cognitive science. My research program is now seeking international collaborations in an effort to generalize our sense of how social signal detection works in the real world. Such cross-cultural work has the potential to uncover universal principles of emotion-cognition interactions lurking beneath culturally variable but functionally equivalent content.