Abstract
Making accurate decisions based on unreliable sensory evidence requires cognitive inference. Dysfunction of n-methyl-d-aspartate (NMDA) receptors impairs the integration of noisy input in theoretical models of neural circuits, but whether and how this synaptic alteration impairs human inference and confidence during uncertain decisions remains unknown. Here we use placebo-controlled infusions of ketamine to characterize the causal effect of human NMDA receptor hypofunction on cognitive inference and its neural correlates. At the behavioral level, ketamine triggers inference errors and elevated decision uncertainty. At the neural level, ketamine is associated with imbalanced coding of evidence and premature response preparation in electroencephalographic (EEG) activity. Through computational modeling of inference and confidence, we propose that this specific pattern of behavioral and neural impairments reflects an early commitment to inaccurate decisions, which aims at resolving the abnormal uncertainty generated by NMDA receptor hypofunction.
Highlights
Making accurate decisions based on unreliable sensory evidence requires cognitive inference
Theoretical work has conferred a central role to NMDA receptors in the computational accuracy of neural circuits implementing cognitive inference
By administering sub-anesthetic infusions of ketamine to healthy volunteers engaged in a cognitive task requiring the accumulation of multiple pieces of evidence, we provide direct experimental support for a causal effect of human NMDA receptor hypofunction on cognitive inference
Summary
Making accurate decisions based on unreliable sensory evidence requires cognitive inference. 1234567890():,; In uncertain environments where sensory observations are unreliable, making decisions requires the combination of multiple pieces of ambiguous or even conflicting sensory information to form accurate beliefs about their generative cause or their consequences[1] This form of “cognitive inference” can be described in terms of probabilistic (Bayesian) reasoning, where beliefs correspond to posterior distributions of hidden states of the environment given the available evidence[2]. This synaptic alteration is thought to impair inference in a way that can trigger decision biases13, “jumping to conclusions”[14,15], and deficits in confidence[16] Together, this theoretical work confers a central role to NMDA receptors in the computational precision of neural circuits implementing cognitive inference. Using computational modeling of inference and confidence, we show how this mechanism compensates for the elevated decision uncertainty generated by NMDA receptor hypofunction
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