Biology subjects

Tessereau, C.

Publications and source records attributed to Tessereau, C..

5 recordsLinked to original sources

bioRxiv2026

Coordinated behavioural and neural variability in hippocampal reward coding

An environment can be interpreted in multiple ways, with implications for behaviour and neural representations and for revision in these when circumstances change. Using two-photon calcium imaging in mouse CA1 during navigation under structured reward-location uncertainty, we found correlations between variability in anticipatory behaviour and the organization of place fields with respect to position and reward. Greater spatial anticipation was associated with enhanced reward-centred coding and increased generalisability of reward-aligned representations.

neuroscience↗

bioRxiv2026

Coordinated acetylcholine release and adaptation of neuronal representations in the retrosplenial cortex during contextual uncertainty

Accurate learning underpins optimal predictions and requires the brain to navigate uncertainty, identifying important information and distinguishing between expected and unexpected uncertainties. Theoretical models propose that the neuromodulator acetylcholine positively correlates with expected uncertainty, priming neuronal networks for learning. We tested this hypothesis by measuring acetylcholine release and neuronal representations in the retrosplenial cortex of mice whilst challenging them with expected and unexpected uncertainties of reward location. Acetylcholine release did not directly correlate with expected or unexpected uncertainty but instead increased with changes in expected uncertainty. In tandem, increased expected uncertainty shifted neuronal representations from a positional reference frame to focus on salient landmarks, such as reward location. Transitions in expected uncertainty also accelerated remapping of neuronal representations and behavioural adaptation when unexpected uncertainty was experienced. Thus, we demonstrate acetylcholine release in retrosplenial cortex discerns types of uncertainty and correlates with learning speed in uncertain environments.

neuroscience↗

bioRxiv2025

Navigating uncertainty: reward location variability induces reorganization of hippocampal spatial representations

Navigating uncertainty is crucial for survival, with the location and availability of reward varying in different and unsignalled ways. Hippocampal place cell populations over-represent salient locations in an animals environment, including those associated with rewards; however, how the spatial uncertainties impact the cognitive map is unclear. We report a virtual spatial navigation task designed to test the impact of different levels and types of uncertainty about reward on place cell populations. When the reward location changed on a trial-by-trial basis, inducing expected uncertainty, a greater proportion of place cells followed along, and the reward and the track end became anchors of a warped spatial metric. When the reward location then unexpectedly moved, the fraction of reward place cells that followed was greater when starting from a state of expected, compared to low, uncertainty. Overall, we show that different forms of potentially interacting uncertainty generate remapping in parallel, task-relevant, reference frames.

neuroscience↗

bioRxiv2020

Reinforcement Learning approaches to hippocampus-dependant flexible spatial navigation

Humans and non-human animals show great flexibility in spatial navigation, including the ability to return to specific locations based on as few as one single experience. To study spatial navigation in the laboratory, watermaze tasks, in which rats have to find a hidden platform in a pool of cloudy water surrounded by spatial cues, have long been used. Analogous tasks have been developed for human participants using virtual environments. Spatial learning in the watermaze is facilitated by the hippocampus. In particular, rapid, one-trial, allocentric place learning, as measured in the Delayed-Matching-to-Place (DMP) variant of the watermaze task, which requires rodents to learn repeatedly new locations in a familiar environment, is hippocampal dependent. In this article, we review some computational principles, embedded within a Reinforcement Learning (RL) framework, that utilise hippocampal spatial representations for navigation in watermaze tasks. We consider which key elements underlie their efficacy, and discuss their limitations in accounting for hippocampus-dependent navigation, both in terms of behavioural performance (i.e., how well do they reproduce behavioural measures of rapid place learning) and neurobiological realism (i.e., how well do they map to neurobiological substrates involved in rapid place learning). We discuss how an actor-critic architecture, enabling simultaneous assessment of the value of the current location and of the optimal direction to follow, can reproduce one-trial place learning performance as shown on watermaze and virtual DMP tasks by rats and humans, respectively, if complemented with map-like place representations. The contribution of actor-critic mechanisms to DMP performance is consistent with neurobiological findings implicating the striatum and hippocampo-striatal interaction in DMP performance, given that the striatum has been associated with actor-critic mechanisms. Moreover, we illustrate that hierarchical computations embedded within an actor-critic architecture may help to account for aspects of flexible spatial navigation. The hierarchical RL approach separates trajectory control via a temporal-difference error from goal selection via a goal prediction error and may account for flexible, trial-specific, navigation to familiar goal locations, as required in some arm-maze place memory tasks, although it does not capture one-trial learning of new goal locations, as observed in open field, including watermaze and virtual, DMP tasks. Future models of one-shot learning of new goal locations, as observed on DMP tasks, should incorporate hippocampal plasticity mechanisms that integrate new goal information with allocentric place representation, as such mechanisms are supported by substantial empirical evidence.

neuroscience↗

bioRxiv2018

Identification of rare de novo epigenetic variations in congenital disorders

Certain human traits such as neurodevelopmental disorders (NDs) and congenital anomalies (CAs) are believed to be primarily genetic in origin. With recent dramatic advances in genomic technologies, genome-wide surveys of cohorts of patients with ND/CAs for point mutations and structural variations have greatly advanced our understanding of their genetic etiologies1,2. However, even after whole genome sequencing (WGS), a substantial fraction of such disorders remain unexplained3. In contrast, the possibility that constitutive epigenetic variations (epivariations) might underlie such traits has not been well explored. We hypothesized that some cases of ND/CA are caused by aberrations of DNA methylation that lead to a dysregulation of normal genome function. By comparing DNA methylation profiles from 489 individuals with ND/CAs against 1,534 population controls, we identified epivariations as a frequent occurrence in the human genome. De novo epivariations were significantly enriched in cases when compared to controls. RNAseq data from population studies showed that epivariations often have an impact on gene expression comparable to loss-of-function mutations. Additionally, we detected and replicated an enrichment of rare sequence mutations overlapping CTCF binding sites close to epivariations. Thus, some epivariations occur secondary to cis-linked mutations in regulatory regions, providing a rationale for interpreting non-coding genetic variation. We propose that epivariations likely represent the causative genomic defect in 5-10% of patients with unexplained ND/CAs. This constitutes a yield comparable to CNV microarrays, and as such has significant diagnostic relevance.

genomics↗