"Conduct Problems in the Classroom and the Clinic: Disruptions in Specific Form of Cognitive Function and Individualized Assessments of these Cognitive Functions via Machine Learning"

Conduct problems are one of main forms of disruption in the classroom and one of the major reasons for a child’s referral to psychiatric services (and diagnoses of Oppositional Defiant Disorder or Conduct Disorder [CD]).  Over the past twenty years, considerable advances have been made in determining the forms of neuro-cognitive dysfunction that increase the risk for conduct problems/ the emergence of CD.  Data indicating the specific contributions of dysfunction in “empathy”, acute threat responding, response control and reinforcement-based decision-making will be briefly described.  Our recent work has built on this to use machine learning to determine cognitive function classifiers that, when applied to individual patient’s neural data, allow percentile markers of the extent of that individual’s neuro-cognitive dysfunction.  The talk will end with brief discussion of cheaper forms of neuro-cognitive assessment and options for treatment suggested by the presented data.