Behavior exhibited by humans and other organisms is generally inconsistent and biased and, thus, is often labeled irrational. However, the origins of this seemingly suboptimal behavior remain elusive. We developed a behavioral task and normative framework to reveal how organisms should allocate their limited processing resources such that sensory precision and its related metabolic investment are balanced to guarantee maximal utility. We found that mice act as rational inattentive agents by adaptively allocating their sensory resources in a way that maximizes reward consumption in previously unexperienced stimulus-reward association environments. Unexpectedly, perception of commonly occurring stimuli was relatively imprecise; however, this apparent statistical fallacy implies “awareness” and efficient adaptation to their neurocognitive limitations. Arousal systems carry reward distribution information of sensory signals, and distributional reinforcement learning mechanisms regulate sensory precision via top-down normalization. These findings reveal how organisms efficiently perceive and adapt to previously unexperienced environmental contexts within the constraints imposed by neurobiology.

Confidence, the subjective estimate of decision quality, is a cognitive process necessary for learning from mistakes and guiding future actions. The origins of confidence judgments resulting from economic decisions remain unclear. We devise a task and computational framework that allowed us to formally tease apart the impact of various sources of confidence in value-based decisions, such as uncertainty emerging from encoding and decoding operations, as well as the interplay between gaze-shift dynamics and attentional effort. In line with canonical decision theories, trial-to-trial fluctuations in the precision of value encoding impact economic choice consistency. However, this uncertainty has no influence on confidence reports. Instead, confidence is associated with endogenous attentional effort towards choice alternatives and down-stream noise in the comparison process. These findings provide an explanation for confidence (miss)attributions in value-guided behaviour, suggesting mechanistic influences of endogenous attentional states for guiding decisions and metacognitive awareness of choice certainty.

Weber's law appears to be a universal principle describing how we discriminate physical magnitudes. However, this law remained purely descriptive for nearly two centuries. A new study by Pardo-Vazquez et al. finally provides a mechanistic explanation, revealing how both accuracy and reaction time performance lawfully emerge during sensory discrimination tasks. Main text Weber's law (WL) [1] is one of the few psychophysical laws that is largely conserved across species and sensory modalities. WL states that when comparing the magnitude of two stimuli, our accuracy does not depend on their absolute difference but rather on the ratio of the compared stimuli. Critically, this law results from empirical observations describing psychophysical performance, while ignoring temporal dynamics underlying the

Behavior exhibited by humans and other organisms is generally inconsistent and biased, and thus is often labeled irrational. However, the origins of this seemingly suboptimal behavior remain elusive. We developed a behavioral task and normative framework to reveal how organisms should allocate their limited processing resources such that there is an advantage to being imprecise and biased for a given metabolic investment that guarantees maximal utility. We found that mice act as rational-inattentive agents by adaptively allocating their sensory resources in a way that maximizes reward consumption in novel stimulus-reward association environments. Surprisingly, perception to commonly occurring stimuli was relatively imprecise, however this apparent statistical fallacy implies "awareness" and efficient adaptation to their neurocognitive limitations. Interestingly, distributional reinforcement learning mechanisms efficiently regulate sensory precision via top-down normalization. These findings establish a neurobehavioral foundation for how organisms efficiently perceive and adapt to environmental states of the world within the constraints imposed by neurobiology.

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