Noradrenergic and Dopaminergic modulation of meta-cognition and meta-control.

IF 3.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS PLoS Computational Biology Pub Date : 2025-02-26 DOI:10.1371/journal.pcbi.1012675
Sara Ershadmanesh, Sahar Rajabi, Reza Rostami, Rani Moran, Peter Dayan
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Abstract

Humans and animals use multiple control systems for decision-making. This involvement is subject to meta-cognitive regulation - as a form of control over control or meta-control. However, the nature of this meta-control is unclear. For instance, Model-based (MB) control may be boosted when decision-makers generally lack confidence as it is more statistically efficient; or it may be suppressed, since the MB controller can correctly assess its own unreliability. Since control and metacontrol are themselves subject to the influence of neuromodulators, we examined the effects of perturbing the noradrenergic and dopaminergic systems with propranolol and L-DOPA, respectively. We first administered a simple perceptual task to examine the effects of the manipulations on meta-cognitive ability. Using Bayesian analyses, we found that 81% of group M-ratio samples were lower under propranolol relative to Placebo, suggesting a decrease of meta-cognitive ability; and 60% of group M-ratio samples were higher under L-DOPA relative to Placebo, considered as no effect of L-DOPA on meta-cognitive ability . We then asked subjects to provide choices and confidence ratings in a two-outcome decision-making task that has been used to dissociate Model-free (MF) and MB control. MB behavior was enhanced by propranolol, while MF behavior was not significantly affected by either drug. The interaction between confidence and MF/MB behavior was highly variable under propranolol, but under L-DOPA, the interaction was significantly lower/higher relative to Placebo. Our results suggest a decrease in metacognitive ability under the influence of propranolol and an enhancement of MB behavior and meta-control under the influence of propranolol and L-DOPA, respectively. These findings shed light on the role of NE and DA in different aspects of control and meta-control and suggest potential avenues for mitigating dysfunction.

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来源期刊
PLoS Computational Biology
PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
自引率
4.70%
发文量
820
审稿时长
2.5 months
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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