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Biology subjects

Benon, J.

Publications and source records attributed to Benon, J..

2 recordsLinked to original sources

Biological profits of irrational computations in the orbitofrontal cortex

Making good decisions is essential for survival and success, yet humans and animals often exhibit perplexing irrational decision-making whose biological origin remains poorly understood. Recent empirical and computational work suggests that altered computations in perceptual, motor and memory systems in the brain may arise from informational, metabolic or robustness constraints on their internal connectivity structure. However, whether and how such neurobiological constraints may have molded the architecture of decision systems (such as the orbitofrontal cortex) and eventually distorted decision-relevant computations, remains largely unknown. We first train cohorts of artificial neural nets to perform ten variants of rational decision-relevant computations. Those variants that operate under a specific option-encoding format exhibit most of the electrophysiological coding properties observed in orbitofrontal neurons of monkeys making decisions under risk. We then distort these neural nets internal wiring to reproduce monkeys irrational choices. This induces deterministic spillover interferences in decision-relevant computations that generalize across individuals, at both the behavioral and neural level. Importantly, although irrational nets do not seem to bring informational or metabolic benefits, they display enhanced tolerance to damage and noise when compared to their rational counterparts. This suggests that some forms of irrational behavior may be the incidental outcome of distal evolutionary pressure on the robustness of orbitofrontal circuits.

neuroscience↗

The online metacognitive control of decisions

Difficult decisions typically involve mental effort, which scales with the deployment of cognitive (e.g., mnesic, attentional) resources engaged in processing decision-relevant information. But how does the brain regulate mental effort? A possibility is that the brain optimizes a resource allocation problem, whereby the amount of invested resources balances its expected cost (i.e. effort) and benefit. Our working assumption is that subjective decision confidence serves as the benefit term of the resource allocation problem, hence the "metacognitive" nature of decision control. Here, we present a computational model for the online metacognitive control of decisions or oMCD. Formally, oMCD is a Markov Decision Process that optimally solves the ensuing resource allocation problem under agnostic assumptions about the inner workings of the underlying decision system. We demonstrate how this makes oMCD a quasi-optimal control policy for a broad class of decision processes, including -but not limited to- progressive attribute integration. We disclose oMCDs main properties (in terms of choice, confidence and response time), and show that they reproduce most established empirical results in the field of value-based decision making. Finally, we discuss the possible connections between oMCD and most prominent neurocognitive theories about decision control and mental effort regulation.

animal behavior and cognition↗