Probabilistic Classification Learning Task

HED Task ID: hedtsk_probabilistic_classification_learning

Also known as: Weather Prediction, Probabilistic Classification Learning, Weather Prediction Task, WPT

Multi-cue probabilistic prediction of a binary outcome with trial-by-trial feedback; learning curves index gradual procedural category learning.

Description

The Weather Prediction Task presents 1-3 cues from a set of 4 possible cards; participants predict a binary outcome (rain/sunshine). Each cue is probabilistically associated with outcomes (e.g., 75%/25%), requiring participants to learn from statistical patterns. Feedback is provided after each prediction. Critically, amnesic patients with medial temporal lobe damage show intact learning despite impaired conscious awareness of the task structure, implicating basal ganglia and striatal systems in implicit probabilistic learning.

Inclusion test

Procedure

Participants predict an outcome (e.g., rain/sun) based on combinations of cues (cards), where each cue is probabilistically (not deterministically) related to outcomes. Learning is incremental across hundreds of trials.

Manipulation

Cue-outcome probability structure; number of cues per trial; feedback type (corrective, observational); concurrent vs. single task.

Measurement

Accuracy learning curve; optimal response rate; strategy analysis (multi-cue vs. single-cue); comparison to Parkinson patients (basal ganglia involvement).

Variations

Variation

Description

Justification

Standard Weather Prediction (4 cues, binary outcome)

Four cards with probabilistic associations to rain/sun.

Canonical probabilistic categorization with cue combinations

Deterministic Version

100% cue-outcome mappings; becomes explicit rule learning.

Cues perfectly predict outcome; removes probabilistic uncertainty

Varying Probability Levels

Different probabilistic strengths (60/40 to 90/10).

Cue-outcome reliability systematically manipulated; different learning statistics

Information-Integration Category Learning

Multi-dimensional continuous stimuli; optimal categorization requires integration across dimensions.

Categories defined by integration of dimensions; different decision rule

Rule-Based Category Learning (comparison)

Stimuli categorizable by single explicit rule; dissociates from implicit systems.

Explicit rule applicable; contrasts implicit vs. explicit learning systems

Feedback vs. Observation Learning

Learning from trial-by-trial feedback vs. observing cue-outcome pairings.

Active feedback vs. observational learning; different learning mechanism

Transfer Test Variants

New cue combinations or reversed contingencies after initial learning.

Probe generalization with novel cue combinations; different test phase

Cognitive processes

This task engages the following cognitive processes:

Key references

  • {‘authors’: ‘Knowlton, B. J., Squire, L. R., & Gluck, M. A.’, ‘year’: 1994, ‘title’: ‘Probabilistic classification learning in amnesia.’, ‘venue’: ‘Learning & Memory’, ‘venue_type’: ‘journal’, ‘journal’: ‘Learning & Memory’, ‘volume’: ‘1’, ‘issue’: ‘2’, ‘pages’: ‘106-120’, ‘doi’: ‘10.1101/lm.1.2.106’, ‘openalex_id’: None, ‘pmid’: None, ‘citation_string’: ‘Knowlton, B. J., Squire, L. R., & Gluck, M. A. (1994). Probabilistic classification learning in amnesia. Learning & Memory, 1(2), 106-120.’, ‘url’: ‘https://doi.org/10.1101/lm.1.2.106’, ‘source’: ‘crossref’, ‘confidence’: ‘high’, ‘verified_on’: ‘2026-04-20’}

  • {‘authors’: ‘Poldrack, R. A., Prabhakaran, V., Seger, C. A., & Gabrieli, J. D. E.’, ‘year’: 1999, ‘title’: ‘Striatal activation during acquisition of a cognitive skill.’, ‘venue’: ‘Neuropsychology’, ‘venue_type’: ‘journal’, ‘journal’: ‘Neuropsychology’, ‘volume’: ‘13’, ‘issue’: ‘4’, ‘pages’: ‘564-574’, ‘doi’: ‘10.1037//0894-4105.13.4.564’, ‘openalex_id’: None, ‘pmid’: None, ‘citation_string’: ‘Poldrack, R. A., Prabhakaran, V., Seger, C. A., & Gabrieli, J. D. (1999). Striatal activation during acquisition of a cognitive skill. Neuropsychology, 13(4), 564-574.’, ‘url’: ‘https://doi.org/10.1037//0894-4105.13.4.564’, ‘source’: ‘crossref’, ‘confidence’: ‘high’, ‘verified_on’: ‘2026-04-20’}

  • {‘authors’: ‘Seger, C. A.’, ‘year’: 2008, ‘title’: ‘How do the basal ganglia contribute to categorization? Their roles in generalization, response selection, and learning via feedback’, ‘venue’: ‘Neuroscience & Biobehavioral Reviews’, ‘venue_type’: ‘journal’, ‘journal’: ‘Neuroscience & Biobehavioral Reviews’, ‘volume’: ‘32’, ‘issue’: ‘2’, ‘pages’: ‘265-278’, ‘doi’: ‘10.1016/j.neubiorev.2007.07.010’, ‘openalex_id’: None, ‘pmid’: None, ‘citation_string’: ‘Seger, C. A. (2008). How do the basal ganglia contribute to categorization? Their roles in generalization, response selection, and learning via feedback. Neuroscience & Biobehavioral Reviews, 32(2), 265-278.’, ‘url’: ‘https://doi.org/10.1016/j.neubiorev.2007.07.010’, ‘source’: ‘crossref’, ‘confidence’: ‘high’, ‘verified_on’: ‘2026-04-20’}

Recent references

  • {‘authors’: ‘Patterson, T. K., & Knowlton, B. J.’, ‘year’: 2018, ‘title’: ‘Subregional specificity in human striatal habit learning: a meta-analytic review of the fMRI literature’, ‘venue’: ‘Current Opinion in Behavioral Sciences’, ‘venue_type’: ‘journal’, ‘journal’: ‘Current Opinion in Behavioral Sciences’, ‘volume’: ‘20’, ‘issue’: None, ‘pages’: ‘75-82’, ‘doi’: ‘10.1016/j.cobeha.2017.10.005’, ‘openalex_id’: None, ‘pmid’: None, ‘citation_string’: ‘Knowlton, B. J., & Patterson, T. K. (2018). Habit formation and the striatum. Current Topics in Behavioral Neurosciences, 37, 275–295.’, ‘url’: ‘https://doi.org/10.1016/j.cobeha.2017.10.005’, ‘source’: ‘crossref’, ‘confidence’: ‘high’, ‘verified_on’: ‘2026-04-20’}

  • {‘authors’: ‘Meeter, M., Myers, C. E., Shohamy, D., Hopkins, R. O., & Gluck, M. A.’, ‘year’: 2006, ‘title’: ‘Strategies in probabilistic categorization: Results from a new way of analyzing performance’, ‘venue’: ‘Learning & Memory’, ‘venue_type’: ‘journal’, ‘journal’: ‘Learning & Memory’, ‘volume’: ‘13’, ‘issue’: ‘2’, ‘pages’: ‘230-239’, ‘doi’: ‘10.1101/lm.43006’, ‘openalex_id’: None, ‘pmid’: None, ‘citation_string’: ‘Meeter, M., Myers, C. E., Shohamy, D., Hopkins, R. O., & Gluck, M. A. (2006). Strategies in probabilistic categorization: Results from a new way of analyzing performance. Learning & Memory, 13(2), 230–239.’, ‘url’: ‘https://doi.org/10.1101/lm.43006’, ‘source’: ‘crossref’, ‘confidence’: ‘high’, ‘verified_on’: ‘2026-04-20’}

  • {‘authors’: ‘Price, A. L.’, ‘year’: 2009, ‘title’: ‘Distinguishing the contributions of implicit and explicit processes to performance of the weather prediction task’, ‘venue’: ‘Memory & Cognition’, ‘venue_type’: ‘journal’, ‘journal’: ‘Memory & Cognition’, ‘volume’: ‘37’, ‘issue’: ‘2’, ‘pages’: ‘210-222’, ‘doi’: ‘10.3758/mc.37.2.210’, ‘openalex_id’: None, ‘pmid’: None, ‘citation_string’: ‘Price, A. L. (2009). Distinguishing the contributions of implicit and explicit processes to performance of the weather prediction task. Memory & Cognition, 37(2), 210–222.’, ‘url’: ‘https://doi.org/10.3758/mc.37.2.210’, ‘source’: ‘crossref’, ‘confidence’: ‘high’, ‘verified_on’: ‘2026-04-20’}

  • {‘authors’: ‘Foerde, K., Knowlton, B. J., & Poldrack, R. A.’, ‘year’: 2006, ‘title’: ‘Modulation of competing memory systems by distraction’, ‘venue’: ‘Proceedings of the National Academy of Sciences’, ‘venue_type’: ‘journal’, ‘journal’: ‘Proceedings of the National Academy of Sciences’, ‘volume’: ‘103’, ‘issue’: ‘31’, ‘pages’: ‘11778-11783’, ‘doi’: ‘10.1073/pnas.0602659103’, ‘openalex_id’: None, ‘pmid’: None, ‘citation_string’: ‘Foerde, K., Knowlton, B. J., & Poldrack, R. A. (2006). Modulation of competing memory systems by distraction. Proceedings of the National Academy of Sciences, 103(31), 11778–11783.’, ‘url’: ‘https://doi.org/10.1073/pnas.0602659103’, ‘source’: ‘crossref’, ‘confidence’: ‘high’, ‘verified_on’: ‘2026-04-20’}