Beyond the Isolated Brain: The Promise and Challenge of Interacting Minds

The growth and form of knowledge networks by kinesthetic curiosity

“…The dancer lacks a direct analog to the trait curiosity self-report measures and classical psychological axes of specific-diversive and perceptual-epistemic curiosity [16,4,2]. Yet, due to its emphasis on linking prior knowledge with leaps to new unknowns, the dancer may be the mode of curiosity that best explains the links of curiosity with creativity, learning, and social behavior [103,104,21,105,15,22]. A highly creative person's semantic network displays robustness and hierarchical organization, as does efficient communication [22,21,23,74].…”

“…Yet, due to its emphasis on linking prior knowledge with leaps to new unknowns, the dancer may be the mode of curiosity that best explains the links of curiosity with creativity, learning, and social behavior [103,104,21,105,15,22]. A highly creative person's semantic network displays robustness and hierarchical organization, as does efficient communication [22,21,23,74]. Thus, it would seem natural in future studies of curiosity, creativity, and social behavior to determine whether the dancer, moreso than other modes, builds knowledge networks with greater robustness and more hierarchical organization.…”

“…The paths of movement from one piece of information to another are threads creating webs of interlinked information, which we call knowledge networks. As the byproduct of searching movement, knowledge network structures may support learning, creativity, and social behavior, without the need for task-specific goals, utility, and feedback [18,19,20,21,22,23,24,25].…”

Brain-to-Brain Synchrony in the STEM Classroom

“…The lack of studies investigating these phenomena is most likely due to the high cost and fragility of traditional cognitive neuroscience methods, limiting the vast majority of research on the human brain to studies in which one participant at a time performs a task in a highly constrained environment (e.g., inside a brain scanner). In the past few years, researchers have begun to approach the neural basis of social interactions by comparing the brain responses of multiple individuals during a variety of tasks (Hasson et al, 2012;Babiloni and Astolfi, 2014;Wheatley et al, 2019). In pioneering research, Hasson and colleagues (2004) used functional magnetic resonance imaging (fMRI) to demonstrate that the brains of different people who watch the same movie show increasingly similar activity patterns over time (a phenomenon called "brain-to-brain synchrony").…”

Arbitrating Computational Models of Observational Learning

“…However, one potential limitation to this approach is whether these models are specific to this particular experiment or whether they will generalize to other observational learning contexts. Looking to the future, we hope the field will begin to embrace the use of naturalistic designs when studying the neurocomputational mechanisms underlying social cognition (Wheatley et al, 2019). Real social interactions reflect non-stationary dynamic processes as people mutually adapt their behavior and may have different types of signals and error structures than will be present in an artificial interaction.…”