Discovering the sequential structure of thought.
Multi-voxel pattern recognition techniques combined with Hidden Markov models can be used to discover the mental states that people go through in performing a task. The combined method identifies both the mental states and how their durations vary with experimental conditions. We apply this method to a task where participants solve novel mathematical problems. We identify four states in the solution of these problems: Encoding, Planning, Solving, and Respond. The method allows us to interpret what participants are doing on individual problem-solving trials. The duration of the planning state varies on a trial-to-trial basis with novelty of the problem. The duration of solution stage similarly varies with the amount of computation needed to produce a solution once a plan is devised. The response stage similarly varies with the complexity of the answer produced. In addition, we identified a number of effects that ran counter to a prior model of the task. Thus, we were able to decompose the overall problem-solving time into estimates of its components and in way that serves to guide theory.
Department of Psychology, Carnegie Mellon University.
John R
JR
Anderson
Jon M
JM
Fincham
D000293:Adolescent; D000328:Adult; D005260:Female; D006801:Humans; D008297:Male; D008433:Mathematics; D011340:Problem Solving / Q000502:physiology*; D011930:Reaction Time / Q000502:physiology; D013850:Thinking / Q000502:physiology*; D055815:Young Adult
Cognitive models; Hidden markov models; Multi-voxel pattern recognition; Problem solving