Biology subjects

Rouault, M.

Publications and source records attributed to Rouault, M..

8 recordsLinked to original sources

bioRxiv2025

Spatially organized cellular communities shape functional tissue architecture in the pancreas

Organ function depends on the precise spatial organization of cells across multiple scales, from individual cells to cellular communities that form specialized local niches and, ultimately, complex higher-order structures. While the identities of individual cell are increasingly well-defined, our understanding of how these diverse cell types are spatially distributed and communicate remains incomplete. In this study, we combine single-cell and spatial transcriptomic analyses to map pancreatic cell populations across space and time, from embryonic development to adult homeostasis in mice. Using these comprehensive maps, we systematically resolve spatial heterogeneity among pancreatic cell types and uncover basic tissue niches, which emerge as epithelial-mesenchymal units. We further characterize these niches functionally in both mouse and human models. We demonstrate that the mesenchymal lineage initially diversifies into various subtypes with specialized supportive roles during embryonic development. However, this complexity gradually diminishes over time, ultimately converging into a limited number of fibroblast sub-types in adult tissue. Our findings shed light on how different progenitor lineages co-develop and organize into structured communities that establish a mature, functional pancreas. This foundational framework could inform strategies for in vitro organogenesis and tissue-engineering in the context of pancreatic diseases.

developmental biology↗

bioRxiv2023

Compulsivity is linked to maladaptive choice variability but unaltered reinforcement learning under uncertainty

Compulsivity has been associated with variable behavior under uncertainty. However, previous work has not distinguished between two main sources of behavioral variability: the stochastic selection of choice options that do not maximize expected reward (choice variability), and random noise in the reinforcement learning process that updates option values from choice outcomes (learning variability). Here we studied the relation between dimensional compulsivity and behavioral variability, using a computational model which dissociates its two sources. We found that compulsivity is associated with more frequent switches between options, triggered by increased choice variability but no change in learning variability. This effect of compulsivity on the trait component of choice variability is observed even in conditions where this source of behavioral variability yields no cognitive benefits. These findings indicate that compulsive individuals make variable and maladaptive choices under uncertainty, but do not hold degraded representations of option values.

animal behavior and cognition↗

bioRxiv2023

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↗

bioRxiv2022

Adaptive tuning of human learning and choice variability to unexpected uncertainty

Human value-based decisions are strikingly variable under uncertainty. This variability is known to arise from two distinct sources: variable choices aimed at exploring available options, and imprecise learning of option values due to limited cognitive resources. However, whether these two sources of decision variability are tuned to their specific costs and benefits remains unclear. To address this question, we compared the effects of expected and unexpected uncertainty on decision-making in the same reinforcement learning task. Across two large behavioral datasets, we found that humans choose more variably between options but simultaneously learn less imprecisely their values in response to unexpected uncertainty. Using simulations of learning agents, we demonstrate that these opposite adjustments reflect adaptive tuning of exploration and learning precision to the structure of uncertainty. Together, these findings indicate that humans regulate not only how much they explore uncertain options, but also how precisely they learn the values of these options. TeaserHumans regulate not only how much they explore uncertain options, but also how precisely they learn their values.

animal behavior and cognition↗

bioRxiv2022

High resolution mapping of the breast cancer tumor microenvironment using integrated single cell, spatial and in situ analysis of FFPE tissue

Single cell and spatial technologies that profile gene expression across a whole tissue are revolutionizing the resolution of molecular states in clinical tissue samples. Commercially available methods that characterize either single cell or spatial gene expression are currently limited by low sample throughput and/or gene plexy, lack of on-instrument analysis, and the destruction of histological features and epitopes during the workflow. Here, we analyzed large, serial formalin-fixed, paraffin-embedded (FFPE) human breast cancer sections using a novel FFPE-compatible single cell gene expression workflow (Chromium Fixed RNA Profiling; scFFPE-seq), spatial transcriptomics (Visium CytAssist), and automated microscopy-based in situ technology using a 313-plex gene panel (Xenium In Situ). Whole transcriptome profiling of the FFPE tissue using scFFPE-seq and Visium facilitated the identification of 17 different cell types. Xenium allowed us to spatially resolve these cell types and their gene expression profiles with single cell resolution. Due to the non-destructive nature of the Xenium workflow, we were able to perform H&E staining and immunofluorescence on the same section post-processing which allowed us to spatially register protein, histological, and RNA data together into a single image. Integration of data from Chromium scFFPE-seq, Visium, and Xenium across serial sections allowed us to do extensive benchmarking of sensitivity and specificity between the technologies. Furthermore, data integration inspired the interrogation of three molecularly distinct tumor subtypes (low-grade and high-grade ductal carcinoma in situ (DCIS), and invasive carcinoma). We used Xenium to characterize cellular composition and differentially expressed genes within these subtypes. This analysis allowed us to draw biological insights about DCIS progression to infiltrating carcinoma, as the myoepithelial layer degrades and tumor cells invade the surrounding stroma. Xenium also allowed us to further predict the hormone receptor status of tumor subtypes, including a small 0.1 mm2 DCIS region that was triple positive for ESR1 (estrogen receptor), PGR (progesterone receptor), and ERBB2 (human epidermal growth factor receptor 2, a.k.a. HER2) RNA. In order to derive whole transcriptome information from these cells, we used Xenium data to interpolate the cell composition of Visium spots, and used Visium whole transcriptome information to discover new biomarkers of breast tumor subtypes. We demonstrate that scFFPE-seq, Visium, and Xenium independently provide information about molecular signatures relevant to understanding cancer heterogeneity. However, it is the integration of these technologies that leads to even deeper insights, ushering in discoveries that will progress oncology research and the development of diagnostics and therapeutics.

cancer biology↗

bioRxiv2022

Transcriptionally defined morphological subtypes of pancreatic ductal adenocarcinoma

Tumour heterogeneity remains a major obstacle to effective and precise therapy for pancreatic ductal adenocarcinoma (PDAC), the most common pancreatic cancer. Several transcriptional subtypes of PDAC with differential prognosis have been described, but they co-occur within tumours and are difficult to distinguish in routine clinical workflows. To investigate the relationship between transcriptional PDAC subtypes, local tissue morphology and the tumour microenvironment, we employed in situ sequencing to profile single cells in their spatial tissue context. We identify five transcriptional subtypes of PDAC cells occurring in three distinct morphological patterns, including secretory tumour cell monolayers, invasive tumour cells with high expression of cell adhesion molecules CEACAM5 and CEACAM6, and spatially distributed tumour cells associated with inflammatory-type fibroblasts. Analysis of bulk RNA-sequencing datasets of the TCGA-PAAD and PACA-AU cohorts according to these spatio-transcriptional subtypes confirmed their prognostic significance. Our results thus indicate an automatable substratification based on spatially-resolved transcriptomics of PDAC and identify distinct subtypes of classical PDAC, representing most cases of this devastating malignancy.

cancer biology↗

bioRxiv2021

A shared brain system forming confidence judgment across cognitive domains

Confidence is typically defined as a subjective judgment about whether a decision is right. Decisions are based on sources of information that come from various cognitive domains and are processed in different brain systems. An unsettled question is whether the brain computes confidence in a similar manner whatever the domain or in a manner that would be idiosyncratic to each domain. To address this issue, human participants of both sexes performed two tasks probing confidence in decisions made about the same material (history and geography statements), but based on different cognitive processes: semantic memory for deciding whether the statement was true or false, and duration perception for deciding whether the statement display was long or short. At the behavioral level, we found that the same factors (difficulty, accuracy, response time and confidence in the preceding decision) predicted confidence judgments in both tasks. At the neural level, we observed using fMRI that confidence judgments in both tasks were associated to activity in the same brain regions: positively in the ventromedial prefrontal cortex and negatively in a prefronto-parietal network. Together, these findings suggest the existence of a shared brain system that generates confidence judgments in a similar manner across cognitive domains.

neuroscience↗

bioRxiv2021

Specific cognitive signatures of information seeking in controllable environments

In uncertain environments, seeking information about alternative choice options is essential for adaptive learning and decision-making. However, information seeking is usually confounded with changes-of-mind about the reliability of the preferred option. Here, we exploited the fact that information seeking requires control over which option to sample to isolate its behavioral and neurophysiological signatures. We found that changes-of-mind occurring with control require more evidence against the current option, are associated with reduced confidence, but are nevertheless more likely to be confirmed on the next decision. Multimodal neurophysiological recordings showed that these changes-of-mind are preceded by stronger activation of the dorsal attention network in magnetoencephalography (MEG), and followed by increased pupil-linked arousal during the presentation of decision outcomes. Together, these findings indicate that information seeking increases the saliency of evidence perceived as the direct consequence of ones own actions. HighlightsO_LIExploration-exploitation dilemmas confound information seeking with changes-of-mind. C_LIO_LIUnlike changes-of-mind, information seeking requires control over information sampling. C_LIO_LIInformation seeking is associated with reduced confidence and active hypothesis testing. C_LIO_LIStronger neurophysiological correlates of attention and arousal during information seeking. C_LI

neuroscience↗