Biology subjects

Sumbre, G.

Publications and source records attributed to Sumbre, G..

8 recordsLinked to original sources

bioRxiv2025

Critical neuronal avalanches emerge from excitation-inhibition balanced spontaneous activity

Neuronal avalanches are sequences of neural activations exhibiting scale-invariant statistics, indicative of critical dynamics. Theoretical studies proposed that the balance between excitation (E) and inhibition (I), along with neuromodulation, are key factors influencing this critical behavior. Here, we performed in-vivo studies to investigate the role of E and I neurons in generating neuronal avalanches in the optic tectum of zebrafish larvae. For this, we used double-transgenic zebrafish larvae expressing cell-type-specific fluorescent proteins and GCaMP6f, combined with immunostaining and selective-plane illumination microscopy to monitor spontaneous neuronal activity and neurotransmitter identity. We found that neural activity approached criticality at balanced and slightly excitatory-dominated E-I ratios but became disordered when E-I ratios were imbalanced. A stochastic network model operating at a critical point, where excitation and inhibition couplings are balanced and balanced amplification drives network avalanches, successfully reproduced the observed statistics of neuronal avalanches and their dependence on E-I ratio fluctuations.

neuroscience↗

bioRxiv2025

Topological analysis of neuronal assemblies reveals low-rank structure modulated by cholinergic activity

1Neuronal assemblies are fundamental building blocks of brain function (e.g. memory, spatial navigation, eye fixation, etc.). However, the principles underlying the connectivity patterns that support their function have remained elusive. The optic tectum of the zebrafish larva is organized into distinct functional neuronal assemblies. These assemblies display all-or-none preferred activation states and inhibitory competition, mechanisms that improve the decoding of visual information. Here, we combined light-sheet microscopy to capture the dynamics of large neuronal networks ([~]2,000 neurons) in the optic tectum; genetic cell-type markers for studying the physiological and functional properties of tectal assemblies; and techniques from topological data analysis to study the dynamic connectivity patterns that enable the emergence and functional role of the neuronal assemblies. We found that during spontaneous activations, tectal assemblies maintain a tight and stable ratio of E-I activity despite the large increase in activity. Topological analysis of the spontaneous activations indicated a low-rank organization of the assemblies and a discrete number of temporal activation patterns. Finally, we observed that the cholinergic system can modulate the topological features of the assemblies to alter their functional role.

neuroscience↗

bioRxiv2025

Interleukin-22 in enteroendocrine cells controls early-life gut motility through interactions with the microbiota

The gut microbiota, immune system, and enteric nervous system tightly interact to regulate adult gut physiology. Yet the mechanisms establishing gut physiology during development remain unknown. Here, we report that in developing zebrafish, enteroendocrine cells produce IL-22 in response to microbial signals before lymphocytes populate the gut. In larvae, IL-22 is crucial to set gut microbiota composition, and ghrelin hormone expression to promote gut motility. IL-22 developmental function depends on its ability to modulate gut microbiota, as bacterial transfer from wild-type zebrafish restored gut motility in il22-/- by reestablishing ghrelin hormone expression. Additionally, IL-22-deficient mice show impaired gut motility and reduced ghrelin expression in early life, indicating a conserved function. Altogether, we identify a circuit where enteroendocrine cells regulate gut function via cytokine control of the microbiota, showing how gut physiology is set prior to immune system maturation.

immunology↗

bioRxiv2024

Whistle variability and social acoustic interactions in bottlenose dolphins

Bottlenose dolphins exhibit a sophisticated social structure, known as a fission-fusion society. To sustain this complex system, dolphins rely on a rich vocal repertoire: clicks exclusively used for echolocation, burst-pulse sounds associated with emotions during social interactions, and whistles, including signature whistles that serve as individual-specific identifiers ( names). How dolphins maintain their complex social structure based only on a limited repertoire of sounds remains elusive. Previous studies suggest that contextual information can be transferred by the modulation of the whistles. Here, we investigated the whistle variability using a comprehensive computational approach, and studied the structure of the interactions between the whistle variants. Using a unique large dataset, acquired in a natural environment, we observed that signature whistles exhibit variations in their frequency contours. Unsupervised clustering revealed that signature whistles could be classified into sub-categories (signature whistle variants). The existence of these categories, and their independence on the emitter dolphin, indicate that these variations are not random. Analysis of pairwise interactions between sub-categories revealed a clustered structure similar to that of their social hierarchy. Network analysis of this structure showed that whistle sub-categories had different functional roles: some acted as hubs, others as bridges, and certain were used for turn-taking between the main whistle categories. We also found that the dolphins emit signature whistles of their deceased mothers, a phenomenon only observed in human language. Overall, these findings suggest that dolphins modulate signature whistles to transmit additional information beyond individual identity, and that they engage in "dialogue-like" acoustic interactions.

animal behavior and cognition↗

bioRxiv2024

Attractor-like circuits improve visual decoding and behavior in zebrafish

Attractor networks are neural circuits with stable states that represent information or memories. They play a crucial role in memory retrieval, decision-making and integrating noisy cues. In zebrafish larvae, the spontaneous dynamics of the optic tectum is structured according to topographically organized neuronal assemblies exhibiting attractor-like behavior. Here, we took advantage of the Methyl-CpG-binding protein 2 (MeCP2) deficient zebrafish mutant, which displays perturbed tectal dynamics, to study the functional role of the attractor-like circuits in visual processing. In comparison to wild-type larvae, the mecp2-mutant showed reduced functional connectivity in the optic tectum. This abnormal connectivity significantly affected the visual response, and the ability to discriminate between visual stimuli. Finally, the mutant larvae where less efficient in hunting paramecia. We argue that the attractor dynamics of the tectal assemblies improve stimulus discrimination, visual resolution, and increase the sensitivity to behaviorally relevant visual stimuli.

neuroscience↗

bioRxiv2021

Blind cavefish retain functional connectivity in the tectum despite loss of retinal input

Sensory systems display remarkable plasticity and are under strong evolutionary selection. The Mexican cavefish, Astyanax mexicanus, consists of eyed river-dwelling surface populations, and multiple independent cave populations which have converged on eye loss, providing the opportunity to examine the evolution of sensory circuits in response to environmental perturbation. Functional analysis across multiple transgenic populations expressing GCaMP6s showed that functional connectivity of the optic tectum largely did not differ between populations, except for the selective loss of negatively correlated activity within the cavefish tectum, suggesting positively correlated neural activity is resistant to an evolved loss of input from the retina. Further, analysis of surface-cave hybrid fish reveals that changes in the tectum are genetically distinct from those encoding eye-loss. Together, these findings uncover the independent evolution of multiple components of the visual system and establish the use of functional imaging in A. mexicanus to study neural circuit evolution.

neuroscience↗

bioRxiv2019

An open-source and low-cost feeding system for zebrafish facilities

Zebrafish is an established animal model used in the fields of developmental biology and genetics for more than 60 years, and among the first models to become genetically tractable. More recently, zebrafish has also become a model of reference for human diseases and systems neuroscience.\n\nThe current extensive use of zebrafish in research and pharmaceutical companies promoted the development of several commercial husbandry systems specially designed for zebrafish. However, feeding is still a challenging and arduous task that can result in occupational disorders of the personnel working at the zebrafish facilities (e.g. tendinitis, back pain, etc.). To palliate these risks, a commercial robotic approach has been developed, yet its expensive cost makes this solution accessible only to very large fish facilities. Most mid-size and small facilities with limited resources still use manual feeding methods.\n\nHere, we propose two custom-made open-source semi-automatic feeding systems for dry and live food, capable of preventing and/or alleviating occupational disorders, improve feeding accuracy and decrease feeding time. Both systems are designed for mid-size or small fish facilities. They are cheap and can be easily and rapidly built using 3D printing and standard electronic and lab components.

neuroscience↗

bioRxiv2017

A computational toolbox and step-by-step tutorial for the analysis of neuronal population dynamics in calcium imaging data

The development of new imaging and optogenetics techniques to study the dynamics of large neuronal circuits is generating datasets of unprecedented volume and complexity, demanding the development of appropriate analysis tools. We present a tutorial for the use of a comprehensive computational toolbox for the analysis of neuronal population activity imaging. It consists of tools for image pre-processing and segmentation, estimation of significant single-neuron single-trial signals, mapping event-related neuronal responses, detection of activity-correlated neuronal clusters, exploration of population dynamics, and analysis of clusters features against surrogate control datasets. They are integrated in a modular and versatile processing pipeline, adaptable to different needs. The clustering module is capable of detecting flexible, dynamically activated neuronal assemblies, consistent with the distributed population coding of the brain. We demonstrate the suitability of the toolbox for a variety of calcium imaging datasets, and provide a case study to explain its implementation.

neuroscience↗