Biology subjects

Lefebvre, G.

Publications and source records attributed to Lefebvre, G..

6 recordsLinked to original sources

bioRxiv2025

Neural and Behavioural Correlates of Variance of Sensory Evidence

Neurobiology of perceptual decisions has largely focused on the neural correlates of the mean strength of sensory evidence. Much less is known about the neural coding of sensory variability. Here, we analyzed the EEG signals obtained from participants who judged the mean orientation of a sequence of gratings with varying variance but constant mean to identify the neural signatures of sensory variance and their relation to individual differences in choice confidence. The neural responses in the stimulus-entrained (4 Hz) and alpha (9-11 Hz) bands tracked variability independently of mean. The frontal and centro-parietal regions demonstrated a quadratic relationship (i.e., strongest responses to intermediate levels of uncertainty) to the standard deviation of the sequence. The occipital response coded the visual stimulus variability linearly. These neural markers of variability were correlated with inter-individual differences in computational components of metacognition. Centro-parietal activity was most predictive of metacognitive sensitivity, aligning with its known role in evidence accumulation. These findings advance our understanding of how the brain dynamically encodes uncertainty and help better characterise the electrophysiological basis of individual differences in metacognitive evaluation.

neuroscience↗

bioRxiv2023

The genome and population genomics of allopolyploid Coffea arabica reveal the diversification history of modern coffee cultivars

Coffea arabica, an allotetraploid hybrid of C. eugenioides and C. canephora, is the source of approximately 60% of coffee products worldwide, and its cultivated accessions have undergone several population bottlenecks. We present chromosome-level assemblies of a di-haploid C. arabica accession and modern representatives of its diploid progenitors, C. eugenioides and C. canephora. The three species exhibit largely conserved genome structures between diploid parents and descendant subgenomes, with no obvious global subgenome dominance. We find evidence for a founding polyploidy event 350,000-610,000 years ago, followed by several pre-domestication bottlenecks, resulting in narrow genetic variation. A split between wild accessions and cultivar progenitors occurred [~]30.5 kya, followed by a period of migration between the two populations. Analysis of modern varieties, including lines historically introgressed with C. canephora, highlights their breeding histories and loci that may contribute to pathogen resistance, laying the groundwork for future genomics-based breeding of C. arabica.

genomics↗

bioRxiv2020

Trophic niche of the invasive gregarious species Crepidula fornicata, in relation to ontogenic changes

AO_SCPLOWBSTRACTC_SCPLOWThe slipper limpet Crepidula fornicata is a common and widespread invasive gregarious species along the European coast. Among its life-history traits, well documented ontogenic changes in behavior (i.e., motile male to sessile female) suggests a potential shift in feeding strategy across its life stages. Considering the ecological significance of this species in colonized areas, understanding how conspecifics share the trophic resource is crucial. Using fatty acids (FA) and stable isotopes (SI) as complementary trophic markers, we conducted a field survey between late winter and spring to investigate the trophic niche of three ontogenic stages of C. fornicata that bear different sexual (male/female) and motility (motile/sessile) traits. Potential trophic sources were characterized by their pigment, FA and SI compositions and discriminated well over the study period. We showed that the biofilm covering C. fornicata shells harbored a higher biomass of primary producers (i.e., chlorophytes and diatoms) than the surrounding sediment surface. Over the study period, we observed a covariation between the three ontogenic stages for both FA and SI compositions which suggest that the trophic niche of C. fornicata does not change significantly across its benthic life. During periods of low food availability, slipper limpets displayed an opportunistic suspension-feeding behaviour, relying on both fresh and detrital organic matter, likely coming from superficial sedimentary organic matter. During high food availability (i.e., spring phytoplankton bloom), all ontogenic stages largely benefited from this fresh supply of organic matter (pelagic diatoms in this case). However, the three ontogenic stages showed consistent differences in FA composition, and to a lesser extent in SI composition. These differences persist over time, as they originate more likely from ontogenic physiological changes (e.g., differential growth rates, metabolic rate or gametogenesis) rather than diet discrepancies.

ecology↗

bioRxiv2020

A normative account of confirmatory biases during reinforcement learning

Reinforcement learning involves updating estimates of the value of states and actions on the basis of experience. Previous work has shown that in humans, reinforcement learning exhibits a confirmatory bias: when updating the value of a chosen option, estimates are revised more radically following positive than negative reward prediction errors, but the converse is observed when updating the unchosen option value estimate. Here, we simulate performance on a multi-arm bandit task to examine the consequences of a confirmatory bias for reward harvesting. We report a paradoxical finding: that confirmatory biases allow the agent to maximise reward relative to an unbiased updating rule. This principle holds over a wide range of experimental settings and is most influential when decisions are corrupted by noise. We show that this occurs because on average, confirmatory biases lead to overestimating the value of more valuable bandits, and underestimating the value of less valuable bandits, rendering decisions overall more robust in the face of noise. Our results show how apparently suboptimal learning policies can in fact be reward-maximising if decisions are made with finite computational precision.

animal behavior and cognition↗

bioRxiv2018

AMPK promotes induction of a tumor suppressor FLCN through activation of TFEB independently of mTOR

AMP-activated protein kinase (AMPK) is a central energy sensor and master regulator of energy homeostasis. AMPK not only elicits acute metabolic responses, but also promotes metabolic reprogramming and adaptions in the long-term through regulation of specific transcription factors/co-activators. We performed a whole-genome transcriptome profiling in wild-type and AMPK-deficient mouse embryonic fibroblasts (MEF) and mouse primary hepatocytes that had been treated with two distinct classes of small-molecule AMPK activators, namely 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR) or 991. This led to the identification of distinct compound-dependent gene expression signatures and to the discovery of several AMPK-regulated genes, including folliculin (Flcn), a gene encoding for a tumor suppressor and nutrient sensor. Gene set enrichment and pathway analyses identified the lysosomal pathway and the associated transcription factor EB (TFEB) as key transcriptional mediator responsible for AMPK-dependent gene expression changes. AMPK-induced Flcn expression was abolished in TFEB/TFE3 double knockout MEF and the promoter activity of Flcn was profoundly reduced when its putative TFEB-binding site was mutated. Mechanistically, we have found that AMPK promotes the dephosphorylation and nuclear localization of TFEB independently of mTOR activity.\n\nCollectively, we identified the AMPK-TFEB-FLCN axis as a potential key regulator for cellular and metabolic homeostasis. Moreover, data from zebrafish with physiologically and pharmacologically activated AMPK confirmed the AMPK-TFEB-FLCN cascade in vivo.

molecular biology↗

bioRxiv2016

Confirmation bias in human reinforcement learning: evidence from counterfactual feedback processing

Previous studies suggest that factual learning, that is learning from obtained outcomes, is biased, such that participants preferentially take into account positive, as compared to negative, prediction errors. However, whether or not the prediction error valence also affects counterfactual learning, that is, learning from forgone outcomes, is unknown. To address this question, we analysed the performance of two cohorts of participants on reinforcement learning tasks using a computational model that was adapted to test if prediction error valance influences learning. Concerning factual learning, we replicated previous findings of a valence-induced bias, whereby participants learned preferentially from positive, relative to negative, prediction errors. In contrast, for counterfactual learning, we found the opposite valence-induced bias: negative prediction errors were preferentially taken into account relative to positive ones. When considering valence-induced bias in the context of both factual and counterfactual learning, it appears that people tend to preferentially take into account information that confirms their current choice. By documenting these valence-induced learning biases, our findings demonstrate the presence of a confirmation bias in human reinforcement learning.

animal behavior and cognition↗