Behavioral evidence suggests that beliefs about causal structure constrain associative
learning, determining which stimuli can enter into association, as well as the functional form …

Highlights•Structure learning may be key to inference from sparse data.•The psychological
and neural bases of structure learning are key challenges.•Normative accounts of structure …

Learning depends on surprise and is not engendered by predictable occurrences. In this
functional magnetic resonance imaging (fMRI) study of causal associative learning, we show …

Highlights•The brain is an expert in extracting predictive structure without explicit
reward.•The brain adapts to changes in the environment's statistics to predict.•Individual …

Prediction error—a mismatch between expected and actual outcome—is critical to
associative accounts of inferential learning. However, it has proven difficult to explore the …

The orbitofrontal cortex (OFC) has been implicated in both the representation of “state,” in
studies of reinforcement learning and decision making, and also in the representation of …

Associative learning theories offer one account of the way animals and humans assess the
relationship between events and adapt their behavior according to resulting expectations …

We use functional magnetic resonance imaging (fMRI) and behavioral analyses to study the
neural roots of biases in causal reasoning. Fourteen participants were given a task requiring …

Making predictions about future events relies on interpreting streams of information that may
initially appear incomprehensible. This skill relies on extracting regular patterns in space …

Associative learning theory assumes that prediction error is a driving force in learning. A
competing view, probabilistic contrast (PC) theory, is that learning and prediction error are …