Download "Neural substrates of cognitive biases during probabilistic inference"

Decision making often requires simultaneously learning about and combining evidence from
various sources of information. However, when making inferences from these sources,
humans show systematic biases that are often attributed to heuristics or limitations in
cognitive processes. Here we use a combination of experimental and modelling approaches to
reveal neural substrates of probabilistic inference and corresponding biases. We find
systematic deviations from normative accounts of inference when alternative options are not
equally rewarding; subjects’ choice behaviour is biased towards the more rewarding option,
whereas their inferences about individual cues show the opposite bias. Moreover, inference
bias about combinations of cues depends on the number of cues. Using a biophysically
plausible model, we link these biases to synaptic plasticity mechanisms modulated by reward
expectation and attention. We demonstrate that inference relies on direct estimation of
posteriors, not on combination of likelihoods and prior. Our work reveals novel mechanisms
underlying cognitive biases and contributions of interactions between reward-dependent
learning, decision making and attention to high-level reasoning.