The Hierarchical Reinforcement Learning Task measures participants’ ability to discover and use higher-order structure in their environment. Participants are presented with 18 stimuli composed of three dimensions: shape, orientation, and border color. The task requires that participants respond to stimuli by pressing one of three keys in response to each of the stimuli. In a "flat" condition, the keys are randomly associated with the shapes so that the participant must learn each association independently. In a "hierarchical" condition, the stimulus-response mappings are instead structured, such that participants can use a rule to determine the correct response based on the combination of the three features. In this condition, the colored borders indicate whether "orientation" or "shape" determine the response (e.g., if the border is red, the correct response is based on the orientation). If participants learn this hierarchical structure, then performance is improved.
Differential activation in anterior regions of the frontal cortex for the hierarchical and flat conditions support the notion that this task indexes the discovery of abstract rules (Badre, Kavser, & D’Esposito, 2010). Individuals can be modeled as learners who differentially bias their attention to hierarchical structure. This "attention to hierarchy" has been associated with signal change in frontal cortex, consistent with the idea that this task captures cognitive processes associated with discovery of higher-order structure in the environment (Frank & Badre, 2012). The cognitive ability to discover abstract rules may influence behavior change by altering the efficiency of learning processes in ways that may be related to self-regulatory control.
[+] PMCID, PUBMED ID, or CITATION
Text Citation: Badre, D., Kayser, A. S., & D’Esposito, M. (2010). Frontal cortex and the discovery of abstract action rules. Neuron, 66, 315-326.
Text Citation: Frank, M. J., & Badre, D. (2012). Mechanisms of hierarchical reinforcement learning in corticostriatal circuits 1: Computational analysis. Cerebral Cortex, 22(3), 509–526.
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The Science of Behavior Change (SOBC) program seeks to promote basic research on the initiation, personalization and maintenance of behavior change. By integrating work across disciplines, this effort will lead to an improved understanding of the underlying principles of behavior change. The SOBC program aims to implement a mechanisms-focused, experimental medicine approach to behavior change research and to develop the tools required to implement such an approach. The experimental medicine approach involves: identifying an intervention target, developing measures to permit verification of the target, engaging the target through experimentation or intervention, and testing the degree to which target engagement produces the desired behavior change.
Within the SOBC Measures Repository, researchers have access to measures of mechanistic targets that have been (or are in the processing of being) validated by SOBC Research Network Members and other experts in the field. The SOBC Validation Process includes three important stages of evaluation for each proposed measure: Identification, Measurement, and Influence.
The first stage of validation requires a measure to be Identified within the field; there must be theoretical support for the specific measure of the proposed mechanistic target or potential mechanism of behavior change. This evidence may include references for the proposed measure, or theoretical support for the construct that the proposed measure is intended to assess. The second stage of validation requires demonstration that the level and change in level of the chosen mechanistic target can be Measured with the proposed measure (assay). For example, if the proposed measure is a questionnaire, the score on the measure should indicate the activity of the target process, and it must have strong psychometric properties. The third stage of validation requires demonstration that the measure can be Influenced; there must be evidence that the measured target is malleable and responsive to manipulation. Evidence relating to each stage includes at least one peer-reviewed publication or original data presentation (if no peer-reviewed research is available to support the claim) and is evaluated by SOBC Research Network Members and experts in the field.
Once a measure has gone through these three stages, it will then either be Validated or Not validated according to SOBC Research Network standards. If a measure is Validated, then change in the measured target was reliably associated with Behavior Change. If a measure is Not validated, then change in the measured target was not reliably associated with Behavior Change. Why would we share measures that are not validated? The SOBC Research Network values open, rigorous, and transparent research. Our goal is to make meaningful progress and develop replicable and effective interventions in behavior change science. Therefore, the SOBC sees value in providing other researchers in the field with information regarding measures that work and measures that fall short for specific targets. Further, a measure that is not validated for one target in one population may be validated in another target or population.
Want to learn more? For any questions regarding the SOBC Validation Process or Measures Repository, please email firstname.lastname@example.org.
Has the mechanism been identified as a potential target for behavior change? This section summarizes theoretical support for the mechanism.
Have the psychometric properties of this measure been assessed? This section includes information such as content validity, internal consistency, and test-retest reliability.
Has a study manipulation led to change in the mechanism? This section addresses evidence that this measure is modifiable by experimental manipulation or clinical intervention.
Has a change in this mechanism been associated with behavior change? This section addresses empirical evidence that causing change in the measure reliably produces subsequent behavior change.