Three Approaches to the Study of Human Learning

The capacity for logical inference is a critical aspect of human learning, reasoning, and decision-making. One important logical inference is the disjunctive syllogism: given A or B, if not A, then B. Although the explicit formation of this logic requires symbolic thought, previous work has shown that nonhuman animals are capable of reasoning by exclusion, one aspect of the disjunctive syllogism (e.g., not A = avoid empty). However, it is unknown whether nonhuman animals are capable of the deductive aspects of a disjunctive syllogism (the dependent relation between A and B and the inference that “if not A, then B” must be true). Here, we used a food-choice task to test whether monkeys can reason through an entire disjunctive syllogism. Our results show that monkeys do have this capacity. Therefore, the capacity is not unique to humans and does not require language.

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Interacting with volatile environments stabilizes hidden-state inference and its brain signatures

Nature Communications ◽

10.1038/s41467-021-22396-6 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Aurélien Weiss ◽

Valérian Chambon ◽

Junseok K. Lee ◽

Jan Drugowitsch ◽

Valentin Wyart

Keyword(s):

Cognitive Processes ◽

Learning Task ◽

Human Learning ◽

Sensory Cues ◽

Uncertain Environments ◽

Behavioral Difference ◽

Neural Interaction ◽

Degree Of Control ◽

Uncertain Outcomes ◽

State Inference

AbstractMaking accurate decisions in uncertain environments requires identifying the generative cause of sensory cues, but also the expected outcomes of possible actions. Although both cognitive processes can be formalized as Bayesian inference, they are commonly studied using different experimental frameworks, making their formal comparison difficult. Here, by framing a reversal learning task either as cue-based or outcome-based inference, we found that humans perceive the same volatile environment as more stable when inferring its hidden state by interaction with uncertain outcomes than by observation of equally uncertain cues. Multivariate patterns of magnetoencephalographic (MEG) activity reflected this behavioral difference in the neural interaction between inferred beliefs and incoming evidence, an effect originating from associative regions in the temporal lobe. Together, these findings indicate that the degree of control over the sampling of volatile environments shapes human learning and decision-making under uncertainty.

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