Biology subjects

Girard, B.

Publications and source records attributed to Girard, B..

13 recordsLinked to original sources

bioRxiv2025

A model-centered introduction to curiosity

AO_SCPLOWBSTRACTC_SCPLOWCuriosity, defined as a transient motivational state for information, explains many non-greedy decisions in humans. Novel, surprising and uncertain situations are thought to elicit curiosity, leading to various models for information-seeking behaviors. We present a unified comparison of curiosity models based on experimental results and previous models from the decision-making and reinforcement learning literature. We provide and explain at least one mathematical formula for each curiosity category, implement them, and compare them on the same uncertain and changing task. This comparison illustrates how motivation and exploration may evolve differently based on what elicits curiosity. This work promises to increase the understanding of curiosity models and provide a synthesized toolbox for future models of information-seeking behaviors in animals or artificial agents.

animal behavior and cognition↗

bioRxiv2025

Topological basal ganglia model with dopamine-modulated spike-timing-dependent plasticity reproduces reinforcement learning, discriminatory learning, and neuropsychiatric disorders

The basal ganglia (BG) are central to action selection and reinforcement learning, yet how the topological organization of the BG circuit with dopamine (DA) D1- and D2-receptors shape learning remains unclear. We present a topologically organized spiking model of macaque BG with cortico-striatal inputs organized into competing channels, D1/D2 medium spiny neurons (MSNs), three-factor DA-modulated STDP for cortical synapses, asymmetric intra-striatal collaterals, and partially overlapping direct/indirect pathways. We validate resting activity and action selection, then study conditioning and generalization-discrimination learning using DA bursts (CS+) and dips (CS). Two structural determinants emerged. First, pathway overlap ({lambda}) trades off selection efficiency and learning speed: higher overlap degrades GPi-based selection efficiency during conditioning, yet accelerates convergence during discrimination by strengthening D2 influence on GPi. Second, lateral inhibition from MSN-D2 to MSNs ({kappa}) helps constrain competing actions but is not sufficient alone; robust discrimination requires DA-dip-dependent up-modulation of D2 collateral efficacy (), which speeds and, at low overlap, enables convergence. Simulations under Parkinsonian and schizophrenia-like settings showed different deficits. A hypodopaminergic "Parkinsonian" STDP regime (D1 LTP loss, D2 LTD loss) impaired conditioning and failed to enhance discrimination. In contrast, attenuated D2 plasticity during DA dips (modeling methamphetamine-induced changes/schizophrenia-related dysregulation) selectively disrupted discrimination while sparing conditioning. Finally, we demonstrate efficient scaling on the Fugaku supercomputer to rodent and non-human primate-relevant sizes, supporting large-scale, biologically grounded BG simulations. Together, the results highlight how pathway overlap and D2 collateral dynamics jointly regulate the speed and reliability of discrimination learning, and how specific DA perturbations map to distinct learning impairments.

neuroscience↗

bioRxiv2025

Multi-model reinforcement learning with online retrospective change-point detection

AO_SCPLOWBSTRACTC_SCPLOWHumans continuously adapt to uncertain and changing situations. However, most reinforcement learning models of human behavior struggle to explain this capability. We propose a novel reinforcement learning agent for uncertain and volatile Markov decision processes, which we call Multi-Model with Retrospective Change Point Detection (MMRCPD). MMRCPD relies on two novel ideas: arbitrating between local models rather than contexts of the environment and retrospectively detecting change points. Arbitrating between local models limits memory costs and enables faster adaptation to new contexts which sub-parts have been experienced before. Retrospective change point detection mimics the capacity of humans to infer the latent cause of a change after it happened and maintain precise models of the environment. MMRCPD can detect local changes online, create new models, retrospectively update its models based on when it estimates that the change happened, reuse past models, merge models if they become similar, and forget unused models. This novel multi-model agent outperforms single-model and context-level change-detection methods in uncertain and locally changing environments. These results yield new insights and predictions concerning optimal decision-making in changing and uncertain environments, which could in turn be tested in behavioral experiments.

animal behavior and cognition↗

bioRxiv2025

Dopaminergic mechanisms of dynamical social specialization in mouse microsocieties

Social organization and division of labor are fundamental to animal societies, but how do these structures emerge from individual interactions, and what role does neuromodulation play in shaping them? Using behavioral tracking in a semi-natural environment, neural recordings, and computational models integrating reinforcement and social learning, we show that groups of three isogenic mice spontaneously develop specialized roles while solving a foraging task requiring individual decisions under social constraints. Moreover, these roles are shaped by dopaminergic activity in the ventral tegmental area. Strikingly, despite minor sex-differences in behavior when mice were tested alone, male triads formed stable worker-scrounger relationships driven by competition, whereas female triads adopted uniform, cooperative strategies. Model analysis revealed how intra- and inter-sex parameter differences in resource exploitation, combined with contingent and dynamic social interactions, drive behavioral specialization and labor division. Most notably, it highlighted how contingency, amplified by competition, magnifies individual differences and shapes social profiles. The plastic, adaptive nature of social organization within triads was confirmed by manipulating dopaminergic cell activity, which reshaped social roles and altered group structure. Our findings support a feedback loop where social context shapes neural states, which in turn reinforce behavioral specialization and stabilize social structures.

neuroscience↗

bioRxiv2025

BlueBerry: Closed-loop wireless optogenetic manipulation in freely moving animals

Optogenetics is a powerful approach for linking neural activity to behavior by enabling precise manipulation of defined neuronal populations. Recent advances in wireless technologies have led to remotely controlled optogenetic devices that facilitate the study of more complex behaviors, including social interactions. However, implementing real-time, automated, closed-loop experiments in large-scale, naturalistic environments and in groups of interacting animals remains challenging. Moreover, many existing devices are difficult to reproduce, requiring specialized engineering expertise or fabrication facilities that are not widely available. Here we introduce BlueBerry (www.OptoBlueBerry.org), a lightweight (1.4 g), battery powered, multi-channel wireless optogenetic device that is openly available for the scientific community and can be assembled entirely from off-the-shelf-components. BlueBerry combines robust long-range wireless communication with flexible control of stimulation parameters, making it particularly suited for behavior-triggered optogenetic experiments in large arenas and in multiple freely interacting animals. We demonstrate that BlueBerry can not only guide decision making during large-scale navigation, but also deliver individually controlled, behavior-triggered optogenetic stimulation to multiple freely interacting mice, enabling modulation of social dynamics in real-time. The open availability, modular design, and straightforward integration with existing behavioral frameworks make BlueBerry a practical and scalable tool for systems neuroscience.

neuroscience↗

bioRxiv2024

Structural serology of polyclonal antibody responses to mRNA-1273 and NVX-CoV2373 COVID-19 vaccines

Current COVID-19 vaccines are largely limited in their ability to induce broad, durable immunity against emerging viral variants. Design and development of improved vaccines utilizing existing platforms requires an in-depth understanding of the antigenic and immunogenic properties of available vaccines. Here we examined the antigenicity of two of the original COVID-19 vaccines, mRNA-1273 and NVX-CoV2373, by electron microscopy-based polyclonal epitope mapping (EMPEM) of serum from immunized non-human primates (NHPs) and clinical trial donors. Both vaccines induce diverse polyclonal antibody (pAb) responses to the N-terminal domain (NTD) in addition to the receptor-binding domain (RBD) of the Spike protein, with the NTD supersite being an immunodominant epitope. High-resolution cryo-EMPEM studies revealed extensive pAb responses to and around the supersite with unique angles of approach and engagement. NTD supersite pAbs were also the most susceptible to variant mutations compared to other specificities, indicating that ongoing Spike ectodomain-based vaccine design strategies should consider immuno-masking this site to prevent induction of these strain-specific responses.

immunology↗

bioRxiv2023

Mutational basis of serum cross-neutralization profiles elicited by infection or vaccination with SARS-CoV-2 variants

A series of SARS-CoV-2 variants emerged during the pandemic under selection for neutralization resistance. Convalescent and vaccinated sera show consistently different cross-neutralization profiles depending on infecting or vaccine variants. To understand the basis of this heterogeneity, we modeled serum cross-neutralization titers for 165 sera after infection or vaccination with historically prominent lineages tested against 18 variant pseudoviruses. Cross-neutralization profiles were well captured by models incorporating autologous neutralizing titers and combinations of specific shared and differing mutations between the infecting/vaccine variants and pseudoviruses. Infecting/vaccine variant-specific models identified mutations that significantly impacted cross-neutralization and quantified their relative contributions. Unified models that explained cross-neutralization profiles across all infecting and vaccine variants provided accurate predictions of holdout neutralization data comprising untested variants as infecting or vaccine variants, and as test pseudoviruses. Finally, comparative modeling of 2-dose versus 3-dose mRNA-1273 vaccine data revealed that the third dose overcame key resistance mutations to improve neutralization breadth. HIGHLIGHTSO_LIModeled SARS-CoV-2 cross-neutralization using mutations at key sites C_LIO_LIIdentified resistance mutations and quantified relative impact C_LIO_LIAccurately predicted holdout variant and convalescent/vaccine sera neutralization C_LIO_LIShowed that the third dose of mRNA-1273 vaccination overcomes resistance mutations C_LI

immunology↗

bioRxiv2022

Insular cortex to ventral striatum synapses encode valence of social interaction

The nature of social interactions determines engagement or avoidance with conspecifics. Here, we explore the circuit mechanisms that guide approach or avoidance behavior in mice based on the valence of previous social interactions. We identify a novel circuit connecting D1 receptor expressing neurons of the anterior insular cortex (AIC) to D1R expressing neurons of the nucleus accumbens (NAc). These cells become active during social interactions in a valence-dependent manner. Lower frequency patterns encoded appetitive interactions, while aversive interactions led to higher activation. These activity patterns elicited distinct forms of synaptic plasticity in the accumbal target neurons, which were causal for subsequent approach or avoidance behavior. Our results unravel the synaptic mechanisms instructing behavior after the social interaction of opposite valence.

neuroscience↗

bioRxiv2021

Modulation of hippocampal network oscillation by PICK1-dependent cell surface expression of mGlu3 receptors

mGlu3 receptors control the sleep/wake architecture which plays a role in the glutamatergic pathophysiology of schizophrenia. Interestingly, mGlu3 receptors expression is decreased in the brain of schizophrenic patients. However, little is known about the molecular mechanisms regulating mGlu3 receptors at the cell membrane. Subcellular receptor localization is strongly dependent on proteinprotein interactions. Here we show that mGlu3 interacts with PICK1 and that their binding is important for receptor surface expression and function. Disruption of their interaction via an mGlu3 C-terminal mimicking peptide or an inhibitor of the PDZ domain of PICK1 altered the functional expression of mGlu3 receptors. Consequently, we investigated whether disruption of the mGlu3-PICK1 interaction affects hippocampal theta oscillations in vitro and in vivo. We found a decreased frequency of theta oscillations in organotypic hippocampal slices, similar to what previously observed in mGlu3 -/- mice. In addition, hippocampal theta power was reduced during REM sleep, NREM sleep and wake states after intra-ventricular administration of the mGlu3 C-terminal mimicking peptide. Targeting the mGlu3-PICK1 complex could thus be relevant to the pathophysiology of schizophrenia.

neuroscience↗

bioRxiv2020

Dopamine neurons of the VTA encode active conspecific interaction and promote social learning through social reward prediction error.

Social interactions motivate behavior in many species, facilitating learning, foraging and cooperative behavior. However, how the brain encodes the reinforcing properties of social interactions remains elusive. Here using in vivo recording in freely moving mice, we show that Dopamine (DA) neurons of the Ventral Tegmental Area (VTA) increase their activity during active interactions with unfamiliar conspecific. Using a social instrumental task, we then show that VTA DA neuron activity signals social reward prediction error and drives social reinforcement learning. Thereby, our findings propose that VTA DA neurons are a neural substrate for a social learning signal driving motivated behavior. One Sentence SummaryDA neurons are a substrate for social reward learning through the Social Reward Prediction Error.

neuroscience↗

bioRxiv2019

The mGlu7 receptor provides protective effects against epileptogenesis and epileptic seizures

Finding new targets to control or reduce seizure activity is essential to improve the management of epileptic patients. We hypothesized that activation of the pre-synaptic and inhibitory metabotropic glutamate receptor type 7 (mGlu7) reduces spontaneous seizures. We tested LSP2-9166, a recently developed mGlu7/4 agonist with unprecedented potency on mGlu7 receptors, in two paradigms of epileptogenesis. In a model of chemically induced epileptogenesis (pentylenetetrazol systemic injection), LSP2-9166 induces an antiepileptogenic effect rarely observed in preclinical studies. In particular, we found a bidirectional modulation of seizure progression by mGlu4 and mGlu7 receptors, the latter preventing kindling. In the intra-hippocampal injection of kainic acid mouse model that mimics the human mesial temporal lobe epilepsy, we found LSP2-9166 reduced seizure frequency and hippocampal sclerosis. LSP2-9166 also acts as an anti epileptic drug on established seizures in both models tested. Specific modulation of the mGlu7 receptor could represent a novel approach to reduce pathological network remodeling.

neuroscience↗

bioRxiv2018

Dopamine regulates the exploration-exploitation trade-off in rats

In a volatile environment where rewards are uncertain, successful performance requires a delicate balance between exploitation of the best option and exploration of alternative choices. It has theoretically been proposed that dopamine controls this exploration-exploitation trade-off, specifically that the higher the level of tonic dopamine, the more exploitation is favored. We demonstrate here that there is a formal relationship between the rescaling of dopamine positive reward prediction errors and the exploration-exploitation trade-off in simple non-stationary multi-armed bandit tasks. We further show in rats performing such a task that systemically antagonizing dopamine receptors greatly increases the number of random choices without affecting learning capacities. Simulations and comparison of a set of different computational models (an extended Q-learning model, a directed exploration model, and a meta-learning model) fitted on each individual confirm that, independently of the model, decreasing dopaminergic activity does not affect learning rate but is equivalent to an increase in exploration rate. This study shows that dopamine could adapt the exploration-exploitation trade-off in decision making when facing changing environmental contingencies.

neuroscience↗

bioRxiv2017

Beta-Band Oscillations without Pathways: the opposing Roles of D2 and D5 Receptors

The timescales of the dynamics of a system depend on the combination of the timescales of its components and of its transmission delays. Parkinsons disease is characterized by the death of dopaminergic neurons and the emergence of strong {beta}-band (15-35Hz) oscillations throughout the basal ganglia nuclei. Here we combine experimental stimulation data from ten studies, that reveal the timing of excitatory and inhibitory events in the basal ganglia circuit, to estimate its set of transmission delays. In doing so, we reveal possible inconsistencies in the existing data, calling for replications, and we propose two possible sets of transmission delays. We then integrate these delays in a model of the primate basal ganglia, that does not rely on direct and indirect pathways segregation, and show that, while much attention has been given to the role of the striatal dopaminergic receptors in Parkinsons disease symptoms, extrastriatal dopaminergic depletion in the external part of the globus pallidus and in the subthalamic nucleus is sufficient to generate {beta}-band oscillations in the high part of the band. More specifically, we show that that D2 and D5 dopamine receptors in these nuclei play opposing roles in the emergence of {beta}-band oscillations, thereby explaining how completely deactivating D5 receptors in the subthalamic nucleus can, paradoxically, cancel oscillations.

neuroscience↗