Biology subjects

Cossart, R.

Publications and source records attributed to Cossart, R..

14 recordsLinked to original sources

bioRxiv2026

CICADA: A unified framework for NWB-based neurophysiological data analysis

Neurophysiology datasets are becoming increasingly complex, combining behavioral measurements with high-dimensional neuronal activity recordings coming from optical and/or electrophysiological measurements. The Neurodata Without Borders (NWB) standard has emerged in the community as the format of record. While standardized and widely used preprocessing tools generating NWB files have been developed, extensible frameworks for scientific analysis downstream of the NWB ecosystem are still under-represented. We present CICADA, a Python framework dedicated to analysis of neurophysiological data in the standardized NWB format. The toolbox is built as three hierarchically-organized packages: cicada-nwb (NWB access layer), cicada-analysis (plugin-based analysis engine and tool library), and cicada-gui (PyQt5 desktop application at the head of the pipeline). Beyond this architectural separation, CICADA is built around a central design principle: supporting a continuum from turnkey use to full modularity. Researchers can use the complete GUI-driven cicada-gui workflow without writing code, programmatically use existing analysis plugins from cicada-analysis, contribute to new analysis plugins, reuse utilities from cicada-tools, or build entirely custom pipelines on top of the cicada-nwb access layer alone. The same analysis plugin runs identically in interactive GUI and parameter-configured headless modes, enabling reproducible multi-session, multi-animal group analyses. We illustrate the versatility of CICADA with example analyses of behavioral, calcium imaging (two-photon and widefield) and extracellular electrophysiology datasets from rodent laboratories. CICADA is open source, actively maintained, and designed so that any laboratory can contribute at any level of the stack without modifying the core framework.

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bioRxiv2025

Distinct developmental trajectories of externally- and internally-generated hippocampal sequences and assemblies

The hippocampus generates cognitive maps through two distinct mechanisms: external representations anchored to environmental landmarks and internal sequences integrating self-referenced information. In adult CA1, these functions segregate radially, with deep cells processing external cues and superficial cells handling internal representations. This anatomical organization suggests that developmental processes constrain the formation of these functionally distinct circuits. However, the developmental timeline for the emergence of these two types of hippocampal representations remains unknown. Using longitudinal two-photon calcium imaging in head-fixed mice during the third postnatal week, we investigated when internal versus external hippocampal representations emerge. We recorded from deep and superficial CA1 layers while mice ran on treadmills that are bare or enriched with tactile cues, addressing the challenge of tracking cells across sessions. Internal sequences emerge during the mid-fourth postnatal week, following the development of cue-based representations. These sequences initially encode elapsed time before evolving to integrate run distance, arising after rest cell assemblies as spatial coding and functional connectivity networks stabilize. These findings identify the mid fourth postnatal week as a critical developmental milestone marking the establishment of a balanced integration between external landmark-based and internal self-referenced spatial representations. This transition period may constitute a vulnerable developmental window during which disruptions could predispose to disorders characterised by altered cognitive maps. HighlightsO_LIP24 is critical for CA1 development C_LIO_LICue-based representations stabilize by P24 C_LIO_LIInternal sequences emerge at P24, encoding run duration before distance C_LIO_LICell assemblies form before internal sequences C_LI

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bioRxiv2025

GABAergic neurons are major contributors of network inhibition in the neonatal hippocampus in-vivo

During development, neural network maturation is activity dependent. During the neonatal period, activity is provided by intermittent, spontaneous network activity patterns (SNAP) that occur independently of environment stimuli. Among the neurotransmitters that take part in neonatal development, the Gamma-amino-butyric acid (GABA) plays a pivotal role. GABAergic cells are the first to emerge the first to form functional synapses. GABA antagonists block hippocampal SNAPs in-vitro and alterations of GABAergic function dramatically impact cortical maturation. Based on these data, the traditional view is that the depolarizing action of GABA, a hallmark of immature networks in slice preparations, is at the core of developmental processes. However, in-vivo evidence for such depolarizing role is not clear, raising questions about the contribution of GABAergic neurons in-vivo. To address this issue we developed an in-vivo approach combining optogenetics and single-unit electrophysiology in non-anesthetized mice. This allowed us to both identify and manipulate hippocampal GABAergic cells while examining their influence on hippocampal SNAP. We found that, even during the first post-natal days, the net action of GABA is inhibitory, but not excitatory. This inhibitory action of GABA drastically increases after the second post-natal week.

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bioRxiv2025

Longitudinal tracking of neuronal activity from the same cells in the developing brain using Track2p

Understanding cortical circuit development requires tracking neuronal activity across days in the growing brain. While in vivo calcium imaging now enables such longitudinal studies, automated tools for reliably tracking large populations of neurons across sessions remain limited. Here, we present a novel cell-tracking method based on sequential image registration, validated on calcium imaging data from the barrel cortex of mouse pups over one postnatal week. Our approach enables robust long-term analysis of several hundreds of individual neurons, allowing quantification of neuronal dynamics and representational stability over time. Using this method, we identified a key developmental transition in neuronal activity statistics, marking the emergence of arousal state modulation. Beyond this key finding, our method provides an essential tool for tracking developmental trajectories of individual neurons, which could help identify potential deviations associated with neurodevelopmental disorders.

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bioRxiv2023

Functional networks of inhibitory neurons orchestrate synchrony in the hippocampus

Inhibitory interneurons are pivotal components of cortical circuits. Beyond providing inhibition, they have been proposed to coordinate the firing of excitatory neurons within cell assemblies. While the roles of specific interneuron subtypes have been extensively studied, their influence on pyramidal cell synchrony in vivo remains elusive. Employing an all-optical approach, we simultaneously recorded hippocampal interneurons and pyramidal cells and probed the network influence of individual interneurons using optogenetics. We demonstrate that CA1 interneurons form a functionally interconnected network that promotes synchrony through disinhibition during awake immobility, while preserving endogenous cell assemblies. Our network model underscores the importance of both cell assemblies and dense, unspecific interneuron connectivity in explaining our experimental findings, suggesting that interneurons may operate not only via division of labor but also through concerted activity.

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bioRxiv2022

Cortical neuronal assemblies coordinate with EEG microstate dynamics during resting wakefulness.

The disruption of cortical assembly activity has been associated with anesthesia-induced loss of consciousness. However, information about the relationship between cortical assembly activity and the variations in consciousness associated with natural vigilance states is currently lacking. To address this, we performed vigilance state-specific clustering analysis on 2-photon calcium imaging data from sensorimotor cortex in combination with global EEG microstate analysis derived from multi-EEG signals obtained from widespread cortical locations. Our analysis revealed no difference in the structure of assembly activity during quiet wakefulness (QW), NREMs, or REMs, despite the latter two vigilance states being associated with significantly reduced levels of consciousness relative to QW. However, we found a significant coordination between global EEG microstate dynamics and local cortical assembly activity during periods of QW, but not sleep. These results suggest that the coordination of cortical assembly activity with global brain dynamics could be a key factor of sustained conscious experience.

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bioRxiv2022

Extrinsic control of the early postnatal CA1 hippocampal circuits

The adult CA1 region of the hippocampus produces coordinated neuronal dynamics with minimal reliance on its extrinsic inputs. In contrast, the neonatal CA1 is tightly linked to externally-generated sensorimotor activity but the circuit mechanisms underlying early synchronous activity in CA1 remain unclear. Here, using a combination of in vivo and ex vivo circuit mapping, calcium imaging and electrophysiological recordings in mouse pups, we show that early dynamics in the ventro-intermediate CA1 are under the mixed influence of entorhinal (EC) and thalamic (VMT) inputs. Both VMT and EC can drive internally-generated synchronous events ex vivo. However, movement-related population bursts detected in vivo are exclusively driven by the EC. These differential effects on synchrony reflect the different intrahippocampal targets of these inputs. Hence, cortical and subcortical pathways act differently on the neonatal CA1, implying distinct contributions to the development of the hippocampal microcircuit and related cognitive maps.

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bioRxiv2021

The rapid developmental rise of somatic inhibition disengages hippocampal dynamics from self-motion

Early electrophysiological brain oscillations recorded in preterm babies and newborn rodents are initially mostly ignited by bottom-up sensorimotor activity and only later can detach from external inputs. This is a hallmark of most developing brain areas including the hippocampus, which in the adult brain, functions in integrating external inputs onto internal dynamics. Such developmental disengagement from external inputs is likely a fundamental step for the proper development of cognitive internal models. Despite its importance, the developmental timeline and circuit basis for this disengagement remain unknown. To address this issue, we have investigated the daily evolution of CA1 dynamics and underlying circuits during the first two postnatal weeks of mouse development using two-photon calcium imaging in non-anesthetized pups. We show that the first postnatal week ends with an abrupt shift in the representation of self-motion in CA1. Indeed, most CA1 pyramidal cells switch from activated to inhibited by self-generated movements at the end of the first postnatal week whereas the majority of GABAergic neurons remain positively modulated throughout this period. This rapid switch occurs within two days and follows the rapid anatomical and functional surge of local somatic GABAergic innervation. The observed change in dynamics is consistent with a two-population model undergoing a strengthening of inhibition. We propose that this abrupt developmental transition inaugurates the emergence of internal cognitive models.

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bioRxiv2021

CA1 pyramidal cell diversity is rooted in the time of neurogenesis.

Cellular diversity supports the computational capacity and flexibility of cortical circuits. Accordingly, principal neurons at the CA1 output node of the hippocampus are increasingly recognized as a heterogeneous population. Their genes, molecular content, intrinsic morpho-physiology, connectivity, and function seem to segregate along the main anatomical axes of the hippocampus. Since these axes reflect the temporal order of principal cell neurogenesis, we directly examined the relationship between birthdate and CA1 pyramidal neuron diversity, focusing on the ventral hippocampus. We used a genetic fate-mapping approach that allowed tagging three groups of agematched principal neurons: pioneer, early- and late-born. Using a combination of neuroanatomy, slice physiology, connectivity tracing and cFos staining, we show that birthdate is a strong predictor of CA1 principal cell diversity. We unravel a subpopulation of pioneer neurons recruited in familiar environments with remarkable positioning, morpho-physiological features, and connectivity. Therefore, despite the expected plasticity of hippocampal circuits, given their role in learning and memory, the diversity of their main components is significantly predetermined at the earliest steps of development.

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bioRxiv2020

The organization and developmental establishment ofcortical interneuron presynaptic circuits

Sensory and cognitive functions are processed in discrete cortical areas and depend upon the integration of long range cortical and subcortical inputs. PV and SST inhibitory interneurons (cINs) gate these inputs and failure to do so properly is implicated in many neurodevelopmental disorders. The logic by which these interneuron populations are integrated into cortical circuits and how these vary across sensory versus associative cortical areas is unknown. To answer this question, we began by surveying the breadth of afferents impinging upon PV and SST cINs within distinct cortical areas. We found that presynaptic inputs to both cIN populations are similar and primarily dictated by their areal location. By contrast, the timing of when they receive these afferents is cell-type specific. In sensory regions, both SST and PV cINs initially receive thalamocortical first order inputs. While by adulthood PV cINs remain heavily skewed towards first order inputs, SST cINs receive an equal balance of first and higher order thalamic afferents. Remarkably, while perturbations to sensory experience affect PV cIN thalamocortical connectivity, SST cIN connectivity is disrupted in a model of fragile X syndrome (Fmr1 loss of function) but not a model of ASD (Shank3B loss of function). Altogether, these data provide a comprehensive map of cIN afferents within different functional cortical areas and reveal the region-specific logic by which PV and SST cIN circuits are established.

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bioRxiv2019

Hippocampal hub neurons maintain unique functional properties throughout their lifetime

The temporal embryonic origins of cortical GABA neurons are critical for their specialization. In the neonatal hippocampus, GABA cells born the earliest (ebGABAs) operate as hubs by orchestrating neuronal dynamics. However, their fate remains largely unknown. To fill this gap, we have examined CA1 ebGABAs using a combination of electrophysiology, neurochemical analysis, optogenetic connectivity mapping as well as ex vivo and in vivo calcium imaging. We show that CA1 ebGABAs not only operate as hubs during development, but also maintain distinct morpho-physiological and connectivity profiles, including a bias for long-range targets and local excitatory inputs. In vivo, ebGABAs signal a variety of network states, including the activation of local CA1 assemblies. Hence, ebGABAs are specified from birth to ensure unique functions throughout their lifetime. In the adult brain, this may take the form of a long-range hub role through the coordination of cell assemblies across distant regions.

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bioRxiv2019

DeepCINAC: a deep-learning-based Python toolbox for inferring calcium imaging neuronal activity based on movie visualization

Two-photon calcium imaging is now widely used to infer neuronal dynamics from changes in fluorescence of an indicator. However, state of the art computational tools are not optimized for the reliable detection of fluorescence transients from highly synchronous neurons located in densely packed regions such as the CA1 pyramidal layer of the hippocampus during early postnatal stages of development. Indeed, the latest analytical tools often lack proper benchmark measurements. To meet this challenge, we first developed a graphical user interface allowing for a precise manual detection of all calcium transients from imaged neurons based on the visualization of the calcium imaging movie. Then, we analyzed the movies using a convolutional neural network with an attention process and a bidirectional long-short term memory network. This method is able to reach human performance and offers a better F1 score (harmonic mean of sensitivity and precision) than CaImAn to infer neural activity in the developing CA1 without any user intervention. It also enables automatically identifying activity originating from GABAergic neurons. Overall, DeepCINAC offers a simple, fast and flexible open-source toolbox for processing a wide variety of calcium imaging datasets while providing the tools to evaluate its performance. Significance statementInferring neuronal activity from calcium imaging data remains a challenge due to the difficulty in obtaining a ground truth using patch clamp recordings and the problem of finding optimal tuning parameters of inference algorithms. DeepCINAC offers a flexible, fast and easy-to-use toolbox to infer neuronal activity from any kind of calcium imaging dataset through visual inspection.

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bioRxiv2018

Internal representation of hippocampal neuronal population span a time-distance continuum

The hippocampus plays a critical role in episodic memory: the sequential representation of visited places and experienced events. This function is mirrored by hippocampal activity that self organizes into sequences of neuronal activation that integrate spatio-temporal information. What are the underlying mechanisms of such integration is still unknown. Single cell activity was recently shown to combine time and distance information; however, it remains unknown whether a degree of tuning between space and time can be defined at the network level. Here, combining daily calcium imaging of CA1 sequence dynamics in running head-fixed mice and network modeling, we show that CA1 network activity tends to represent a specific combination of space and time at any given moment, and that the degree of tuning can shift within a continuum from one day to the next. Our computational model shows that this shift in tuning can happen under the control of the external drive power. We propose that extrinsic global inputs shape the nature of spatio-temporal integration in the hippocampus at the population level depending on the task at hand, a hypothesis which may guide future experimental studies.\n\nSignificance StatementThe hippocampus organizes experience in sequences of events that form episodic memory. How are time and space internally computed in the hippocampus in the absence of sequential external inputs? Here we show that time and space are integrated together within the hippocampal network with different degrees of tuning across days. This was found by recording the activity of hundreds of pyramidal cells for several days. We also propose a mechanism supporting such spatio-temporal integration based on a ring attractor network model: the degree of tuning between space and time can be adjusted by modulating the power of a non-sequential external excitatory drive. In this way, the hippocampus is able to generate a spatio-temporal representation tuned to the task at hand.

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bioRxiv2018

Modeling driver cells in developing neuronal networks

Spontaneous emergence of synchronized population activity is a characteristic feature of developing brain circuits. Recent experiments in the developing neo-cortex showed the existence of driver cells able to impact the synchronization dynamics when single-handedly stimulated. We have developed a spiking network model capable to reproduce the experimental results, thus identifying two classes of driver cells: functional hubs and low functionally connected (LC) neurons. The functional hubs arranged in a clique orchestrated the synchronization build-up, while the LC drivers were lately or not at all recruited in the synchronization process. Notwithstanding, they were able to alter the network state when stimulated by modifying the temporal activation of the functional clique or even its composition. LC drivers can lead either to higher population synchrony or even to the arrest of population dynamics, upon stimulation. Noticeably, some LC driver can display both effects depending on the received stimulus. We show that in the model the presence of inhibitory neurons together with the assumption that younger cells are more excitable and less connected is crucial for the emergence of LC drivers. These results provide a further understanding of the structural-functional mechanisms underlying synchronized firings in developing circuits possibly related to the coordinated activity of cell assemblies in the adult brain.\n\nAuthor SummaryThere is timely interest on the impact of peculiar neurons (driver cells) and of small neuronal sub-networks (cliques) on operational brain dynamics. We first provide experimental data concerning the effect of stimulated driver cells on the bursting activity observable in the developing entorhinal cortex. Secondly, we develop a network model able to fully reproduce the experimental observations. Analogously to the experiments two types of driver cells can be identified: functional hubs and low functionally connected (LC) drivers. We explain the role of hub neurons, arranged in a clique, for the orchestration of the bursting activity in control conditions. Furthermore, we report a new mechanism, which can explain why and how LC drivers emerge in the structural-functional organization of the enthorinal cortex.

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