This mini configurative review links theory of mind research with school-based social skills interventions to reframe theoretical understanding of ToM ability based on a conceptual mapping exercise. The review’s aim was to bridge areas of psychology and education concerned with social cognition. Research questions included: how do dependent variables in interventions designed to enhance child social-cognitive skills map onto ToM constructs empirically validated within psychology? In which ways do these mappings reframe conceptualization of ToM ability? Thirty-one studies on social-cognitive skill (...) with typically-developing children ages 3–11 were included as opposed to explicit ToM trainings in light of an identified performance plateau on ToM tasks in children. Intervention DVs mapped onto the following ToM constructs in at least 87% of studies: “Representation of Others and/or Self,” “Knowledge/Awareness of Mental States,” “Attributions/Explanations of Mental States,” “Social Competence,” “Predicting Behavior,” and “Understanding Complex Social Situations.” The absence of false-belief understanding as an intervention DV indicated a lack of direct training in ToM ability. A hierarchy to further organize the review’s ToM framework constructs as either skills or competences within the construct of ‘Representation of Others and/or Self’ is proposed. Implications for the conceptualization of ToM and social-cognitive research as well as educational practice are discussed, namely how school social skill interventions conceptualize skill along a continuum in contrast to the common artificial dichotomous assessment of ToM skill, yet the development of ToM can nevertheless be supported by the school environment. (shrink)

Neurotechnologies that collect and interpret data about brain activity are already in use for medical and nonmedical applications. Refinements of existing noninvasive techniques and the discovery of new ones will likely encourage broader uptake. The increased collection and use of brain data and, in particular, their use to infer the existence of mental states have led to questions about whether mental privacy may be threatened. It may be threatened if the brain data actually support inferences about the mind or if (...) decisions are made about a person in the belief that the inferences are justified. This article considers the chain of inferences lying between data about neural activity and a particular mental state as well as the ethico-legal issues raised by making these inferences, focusing here on what the threshold of reliability should be for using brain data to infer mental states. (shrink)

Dancers and musicians are experts in spatial and temporal processing which allows them to coordinate movement with music. This high-level processing has been associated with structural and functional adaptation of the brain for high performance sensorimotor integration. For these integration processes, adaptation does not only take place in primary and secondary sensory and motor areas but tertiary brain areas, such as the lateral prefrontal cortex (lPFC) and the intraparietal sulcus (IPS), also provide vital resources for highly specialized performance. Here, we (...) review evidence for the role of these brain areas in multimodal training protocols and integrate these findings into a new model of sensorimotor processing in complex motor learning. (shrink)

In the last year or so (and going back many decades) there has been extensive claims by major computational scientists, engineers, and others that AGI (artificial general intelligence) is 5 or 10 years away, but without a scintilla of scientific evidence, for a broad body of these claims: Computers will become conscious, have a “theory of mind,” think and reason, will become more intelligent than humans, and so on. But the claims are science fiction, not science. -/- This article reviews (...) evidence for the following three (3) propositions using extensive body of scientific research and related sources from the cognitive and neurosciences; evolutionary evidence; linguistics; data science; comparative psychology; self-driving cars, and robotics; and the learning sciences. (1) Do computing machines think or reason? (2) Are computing machines sentient or conscious? (3) Do computing machines have a theory of mind? (shrink)