Biology subjects

Yuste, R.

Publications and source records attributed to Yuste, R..

At least 19 recordsLinked to original sources

bioRxiv2026

Connectivity Logic of Dendritic Spines in Cortex: Increased Inputs and Ensemble Formation

Dendritic spines are the principal postsynaptic targets of excitatory synapses, yet the network logic governing their organization and contribution to cortical computation remains unclear. Here, we combine the MICrONS ultrastructural reconstruction of mouse visual cortex with matched in vivo two-photon calcium imaging to explore the network roles of dendritic spines. Structurally, we show that spine density predicts the number and diversity of both excitatory and inhibitory presynaptic partners, supporting the long-standing "connectivity and diversity" hypothesis. Beyond expanding input space, spines exhibit distinct network-level principles: excitatory axons preferentially target spines with increasing axonal distance from the soma; highly broadcasting ("hub") neurons preferentially innervate spines; and neurons sharing presynaptic partners preferentially route their own outputs onto spines, revealing an input-to-spine/output-to-spine wiring correlations. Functionally, we find that these same structural motifs are found in neuronal ensembles, defined as groups of neurons with correlated calcium activity. Ensemble members are interconnected at more than twice the rate of spatially matched controls; these synapses connecting them are routed almost exclusively onto dendritic spines; and their shared presynaptic partners are almost exclusively inhibitory neurons that themselves also preferentially target spines. We suggest that local recurrent spine-targeted excitation effectively binds ensemble members into a coactive subnetwork, while shared spine-directed inhibition gates, synchronizes, and stabilizes their collective activity, providing a circuit-level architecture that may support attractor dynamics, pattern completion, and other cortical computations.

neuroscience↗

bioRxiv2026

Ultrasensitive voltage imaging reveals distinct electrical microdomains in neurons

For the brain to compute, electrical signals must propagate over the membranes of individual neurons, connecting synaptic inputs to synaptic outputs1. Complex neuronal morphologies coupled with the spatial organization of synaptic inputs and outputs enable diverse voltage transformations that underlie cell-type specific computations2,3. However, measuring these transformations in vivo has remained challenging, leaving a crucial gap in our mechanistic understanding of single neuron computation. Here, we develop ASAP7y, a genetically encoded voltage indicator with unprecedented subthreshold sensitivity and expanded excitation compatibility in both mice and flies. We leveraged ASAP7y combined with two-photon random-access microscopy to record sensory stimulus-evoked voltage dynamics with millisecond, subcellular, and subthreshold resolution along the neurites of individual neurons in Drosophila. We found remarkable heterogeneity in voltage propagation across cell-types, delineating a fundamental axis of electrical diversity. Leveraging a nanoscale EM reconstruction of the visual system4, we modeled the electrotonic properties of single neurons spanning 717 cell types, revealing how morphology shapes voltage transformations. Finally, we demonstrate that confined voltage propagation creates substrates for local computation, producing subcellular domains with distinct feature selectivity across multiple cell types. These results provide mechanistic insight into how critical single neuron computations arise and reveal parallel processing in single neurons.

neuroscience↗

bioRxiv2025

VesiclePy: A Machine Learning Vesicle Analysis Toolbox for Volume Electron Microscopy

Vesicles are critical components of neurons that package neurotransmitters and neuropeptides for their release, in order to communicate with other neurons and cells. However, due to their small size, the reconstruction of the full vesicle endowment across an entire neuronal morphology remains challenging. To achieve this, we have used, as a tool to identify and visualize vesicles, Volume Electron Microscopy (vEM), a method that has the nanoscale resolution to detect individual vesicle boundaries, content, and 3D locations. However, the large volume of vEM datasets poses a challenge in the segmentation, classification, and spatial analysis of tens of thousands of vesicles and their target cell in 3D. Here we report the development of VesiclePy, an integrated pipeline for automated segmentation, classification, proofreading, and spatial analysis of vesicles, relative to neuron masks in large-volume electron microscopy data. Our package integrates the efficiency of deep learning and the accuracy of human proofreading and provides a streamlined package in chunked processing and accurate indexing, localization, and visualization of single vesicle resolution in large vEM data. We demonstrate the viability of VesiclePy using high-pressure frozen serial EM data of Hydra vulgaris and quantify the performance of the package using ground truth manual annotations. We show that VesiclePy can process a multiterabyte serial EM dataset, efficiently annotate 53,851 vesicles from 20 complete neurons, and classify vesicles into 5 types. Each vesicle has a unique ID and 3D location for further spatial analysis in relation to neuron or non-neuronal targets nearby. Finally, by combining vesicle data and morphological information of each neuron, we can quantitatively cluster neurons into subtypes. VesiclePy is available at https://github.com/PytorchConnectomics/VesiclePy under an MIT license.

neuroscience↗

bioRxiv2025

A polymeric, PDMS-based large-scale skull replacement suitable for optical and mechanical access for long-term neuronal imaging, electrophysiology, and optogenetics

Many techniques to record and manipulate neuronal activity across large portions of the vertebrate brain, such as widefield and two-photon calcium imaging, electrophysiology, and optogenetics, are now available. However, few effective approaches enable both optical and mechanical access to the brain. In this work, we offer an in-depth guide for synthesizing, implanting, and using polydimethylsiloxane (PDMS) windows as skull replacements for chronic optical neuronal imaging. Furthermore, we provide instructions to perform viral injections and multi-site silicon probe implantation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/648966v1_ufig1.gif" ALT="Figure 1"> View larger version (71K): org.highwire.dtl.DTLVardef@1900a2dorg.highwire.dtl.DTLVardef@18c436corg.highwire.dtl.DTLVardef@19e6a4corg.highwire.dtl.DTLVardef@154c228_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO C_FIG

neuroscience↗

bioRxiv2024

Spike transmission failures in axons from mouse cortical pyramidal neurons in vivo

The propagation of action potentials along axons is traditionally considered to be reliable, as a consequence of the high safety factor of action potential propagation. However, numerical simulations have suggested that, at high frequencies, spikes could fail to invade distal axonal branches. Given the complex morphologies of axonal trees, with extensive branching and long-distance projections, spike propagation failures could be functionally important. To explore this experimentally in vivo, we used an axonal-targeted calcium indicator to image action potentials at axonal terminal branches in superficial layers from mouse somatosensory cortical pyramidal neurons. We activated axons with an extracellular electrode, varying stimulation frequencies, and computationally extracted axonal morphologies and associated calcium responses. We find that axonal boutons have higher calcium accumulations than their parent axons, as was reported in vitro. But, contrary to previous in vitro results, our data reveal spike failures in a significant subset of branches, as a function of branching geometry and spike frequency. The filtering is correlated with the geometric ratio of the branch diameters, as expected by cable theory. These findings suggest that axonal morphologies contribute to signal processing in the cortex.

neuroscience↗

bioRxiv2023

Aberrant hippocampal Ca2+ micro-waves following synapsin-dependent adenoviral expression of Ca2+ indicators

Genetically encoded calcium indicators (GECIs) such as GCaMP are invaluable tools in neuroscience to monitor neuronal activity using optical imaging. The viral transduction of GECIs is commonly used to target expression to specific brain regions, can be conveniently used with any mouse strain of interest without the need for prior crossing with a GECI mouse line and avoids potential hazards due to the chronic expression of GECIs during development. A key requirement for monitoring neuronal activity with an indicator is that the indicator itself minimally affects activity. Here, using common adeno-associated viral (AAV) transduction procedures, we describe spatially confined aberrant Ca2+ micro-waves slowly travelling through the hippocampus following expression of GCaMP6, GCaMP7 or R-CaMP1.07 driven by the synapsin promoter with AAV-dependent gene transfer, in a titre-dependent fashion. Ca2+ micro-waves developed in hippocampal CA1 and CA3, but not dentate gyrus (DG) nor neocortex, were typically first observed at 4 weeks after viral transduction, and persisted up to at least 8 weeks. The phenomenon was robust, observed across laboratories with various experimenters and setups. Our results indicate that aberrant hippocampal Ca2+ micro-waves depend on the promoter and viral titre of the GECI, density of expression as well as the targeted brain region. We used an alternative viral transduction method of GCaMP which avoids this artifact. The results show that commonly used Ca2+-indicator AAV transduction procedures can produce artefactual Ca2+ responses. Our aim is to raise awareness in the field of these artefactual transduction-induced Ca2+ micro-waves and we provide a potential solution. Impact statement: Common AAV transduction procedures induce artefactual spatially confined Ca2+ waves in the hippocampus.

neuroscience↗

bioRxiv2023

Automatic monitoring of whole-body neural activity in behaving Hydra

The ability to record every spike from every neuron in a behaving animal is one of the holy grails of neuroscience. Here, we report coming one step closer towards this goal with the development of an end-to-end pipeline that automatically tracks and extracts calcium signals from individual neurons in the cnidarian Hydra vulgaris. We imaged dually labeled (nuclear tdTomato and cytoplasmic GCaMP7s) transgenic Hydra and developed an open-source Python platform (TraSE-IN) for the Tracking and Spike Estimation of Individual Neurons in the animal during behavior. The TraSE-IN platform comprises a series of modules that segments and tracks each nucleus over time and extracts the corresponding calcium activity in the GCaMP channel. Another series of signal processing modules allows robust prediction of individual spikes from each neurons calcium signal. This complete pipeline will facilitate the automatic generation and analysis of large-scale datasets of single-cell resolution neural activity in Hydra, and potentially other model organisms, paving the way towards deciphering the neural code of an entire animal.

neuroscience↗

bioRxiv2023

Visually evoked neuronal ensembles reactivate during sleep

Neuronal ensembles, defined as groups of coactive neurons, dominate cortical activity and are causally related to perceptual states and behavior. Interestingly, ensembles occur spontaneously in the absence of sensory stimulation. To better understand the function of ensembles in spontaneous activity, we explored if ensembles also occur during different brain states, including sleep, using two-photon calcium imaging from mouse primary visual cortex. We find that ensembles are present during all wake and sleep states, with different characteristics depending on the exact sleep stage. Moreover, visually evoked ensembles are reactivated during subsequent slow wave sleep cycles. Our results are consistent with the hypothesis that repeated sensory stimulation can reconfigure cortical circuits and imprint neuronal ensembles that are reactivated during sleep for potential processing or memory consolidation. One-Sentence SummaryCortical neuronal ensembles are present across wake and sleep states, and visually evoked ensembles are reactivated in subsequent slow-wave sleep.

neuroscience↗

bioRxiv2022

Morphological analysis of human and mouse dendritic spines reveals a morphological continuum and differences across ages and species

Dendritic spines have diverse morphologies, with a wide range of head and neck sizes, and these morphological differences likely generate different synaptic and functional properties. To explore how this morphological diversity differs across species we analyzed 3D confocal reconstructions of ~8,000 human spines and ~1,700 mouse spines, labeled by intracellular injections in fixed tissue. Using unsupervised machine-learning algorithms, we computationally separated spine heads and necks and systematically measured morphological features of spines in apical and basal dendrites from cortical pyramidal cells. Human spines had unimodal distributions of parameters, without any evidence of morphological subtypes. Their spine necks were longer and thinner in apical than in basal spines, and spine head volumes of an 85-years-old individual were larger than those of a 40-years-old individual. Human spines overall had longer and thicker necks and bigger head volumes than mouse spines. Our results indicate that human spines form part of a morphological continuum, are larger and longer than those of mice, and become larger with increasing adult age. These morphological differences in spines across species could generate functional differences in biochemical and electrical spine compartmentalization, or in synaptic properties, across species and ages.

neuroscience↗

bioRxiv2021

Ultrastructural analysis of dendritic spine necks reveals a continuum of spine morphologies

Dendritic spines are membranous protrusions, with a bulbous head connected to the dendrite by a thin neck, and receive essentially all excitatory inputs in most mammalian neurons. Spines have a wide variety of morphologies that likely have a significant effect on their biochemical and electrical properties. The question of whether spines belong to distinct morphological or functional subtypes or constitute a continuum is still open. To discern this, it is important to measure spine necks objectively. Recent advances in electron microscopy enable automatic reconstructions of 3D spines with nanometer precision. Analyzing ultrastructural reconstructions from mouse neocortical neurons with computer vision algorithms, we demonstrate that the vast majority of spines can be rigorously separated into head and neck components. Analysis of the head and neck morphologies reveals a continuous distribution of parameters. The spine neck diameter, but not the neck length, was correlated with the head volume. Spines with larger head volumes often had a spine apparatus and pairs of spines in a post-synaptic cell contacted by the same axon had similar head volumes. Our data are consistent with a lack of morphological categories of spines and indicate that the morphologies of the spine neck and head are independently regulated. These results have repercussions for our understanding of the function of dendritic spines in neuronal circuits.

neuroscience↗

bioRxiv2020

From neuron to muscle to movement: a complete biomechanical model of Hydra contractile behaviors

How does neural activity drive muscles to produce behavior? The recent development of genetic lines in Hydra that allow complete calcium imaging of both neuronal and muscle activity, as well as systematic machine learning quantification of behaviors, makes this small Cnidarian an ideal model system to understand and model the complete transformation from neural firing to body movements. As a first step to achieve this, we have built a biomechanical model of Hydra, incorporating its neuronal activity, muscle activity and body column biomechanics, incorporating its fluid-filled hydrostatic skeleton. Our model is based on experimental measurements of neuronal and muscle activity, and assumes gap junctional coupling among muscle cells and calcium-dependent force generation y muscles. With these assumptions, we can robustly reproduce a basic set of Hydras behaviors. We can further explain puzzling experimental observations, including the dual kinetics observed in muscle activation and the different engagement of ecto- and endodermal muscle in different behaviors. This work delineates the spatiotemporal control space of Hydra movement and can serve as a template for future efforts to systematically decipher the transformations in the neural basis of behavior.

biophysics↗

bioRxiv2020

Long-term stability of neuronal ensembles in mouse visual cortex

Coactive neuronal ensembles are found in spontaneous and evoked cortical activity and are thought to participate in the internal representation of memories, perceptions, and mental states. In mouse visual cortex, ensembles can be optogenetically imprinted and are causally related to visual percepts, but it is still unknown how stable they are over time. Using two-photon volumetric microscopy, we performed calcium imaging over several weeks of the same neuronal populations in layer 2/3 of visual cortex of awake mice, tracking over time the activity of the same neurons in response to visual stimuli and under spontaneous activity. Only a small number of neurons remained active across days. Analyzing them, we found both stable ensembles, lasting up to 46 days, and transient ones, observed during only one imaging session. The majority of ensembles in visually-evoked activity were stable, whereas in spontaneous activity similar numbers of stable and transient ensembles were found. Among stable ensembles, more than 60 % of neurons still belonged to the same ensemble even after several weeks. These core ensemble cells had stronger functional connectivity than neurons that stopped belonging to the ensemble. Our results demonstrate that spontaneous and evoked neuronal ensembles can last weeks, providing a neuronal mechanism for the long-lasting representation of perceptual states or memories.

neuroscience↗

bioRxiv2020

Extreme stiffness of neuronal synapses and implications for synaptic adhesion and plasticity

Synapses play a critical role in neural circuits, and they are potential sites for learning and memory. Maintenance of synaptic adhesion is critical for neural circuit function, however, biophysical mechanisms that help maintain synaptic adhesion are not clear. Studies with various cell types demonstrated the important role of stiffness in cellular adhesions. Although synaptic stiffness could also play a role in synaptic adhesion, stiffnesses of synapses are difficult to characterize due to their small size and challenges in verifying synapse identity and function. To address these challenges, we have developed an experimental platform that combines atomic force microscopy, fluorescence microscopy, and transmission electron microscopy. Here, using this platform, we report that functional, mature, excitatory synapses had an average elastic modulus of approximately 200 kPa, two orders of magnitude larger than that of the brain tissue, suggesting stiffness might have a role in synapse function. Similar to various functional and anatomical features of neural circuits, synaptic stiffness had a lognormal-like distribution, hinting a possible regulation of stiffness by processes involved in neural circuit function. In further support of this possibility, we observed that synaptic stiffness was correlated with spine size, a quantity known to correlate with synaptic strength. Using established stages of the long-term potentiation timeline and theoretical models of adhesion cluster dynamics, we developed a biophysical model of the synapse that not only explains extreme stiffness of synapses, their statistical distribution, and correlation with spine size, but also offers an explanation to how early biomolecular and structural changes during functional potentiation could lead to strengthening of synaptic adhesion. According to this model, synaptic stiffness serves as an indispensable physical messenger, feeding information back to synaptic adhesion molecules to facilitate maintenance of synaptic adhesion.

biophysics↗

bioRxiv2020

Intrinsic excitability mechanisms of neuronal ensemble formation

Neuronal ensembles are coactive groups of cortical neurons, found in spontaneous and evoked activity, that can mediate perception and behavior. To understand the mechanisms that lead to the formation of ensembles, we co-activated optogenetically and electrically layer 2/3 pyramidal neurons in brain slices from mouse visual cortex, in animals from both sexes, replicating in vitro an optogenetic protocol to generate ensembles in vivo. Using whole-cell and perforated patch-clamp pair recordings we find that, after optogenetic or electrical stimulation, coactivated neurons increase their correlation in spontaneous activity, a hallmark of ensemble formation. Coactivated neurons showed small biphasic changes in presynaptic plasticity, with an initial depression followed by a potentiation after a recovery period. Unexpectedly, optogenetic and electrical stimulation-induced significant increases in frequency and amplitude of spontaneous EPSPs, even after single-cell stimulation. In addition, we observed strong and persistent increases in neuronal excitability after stimulation, with increases in membrane resistance and reduction in spike threshold. A pharmacological agent that blocks changes in membrane resistance can revert this effect. These significant increases in excitability may partly explain the observed biphasic synaptic plasticity. We propose that cell-intrinsic changes in excitability are involved in the formation of neuronal ensembles. We propose an "iceberg" model, by which increased neuronal excitability makes subthreshold connections suprathreshold, enhancing the effect of already existing synapses, and generating a new neuronal ensemble. Significance StatementWe investigated the synaptic and cellular mechanisms underlying the formation of neuronal ensembles, i.e., spontaneously coactive groups of neurons. Using in vitro electrophysiology and optogenetic in slices of mouse neocortex we replicated a protocol that generates ensembles in vivo. After optogenetic and electrical stimulation, we observed biphasic synaptic plasticity and, unexpectedly, major increases in excitability, input resistance, and reductions in firing threshold. The increased excitability can explain the observed synaptic plasticity. Our results reveal a major role for intrinsic excitability in the establishment of neuronal ensembles.

neuroscience↗

bioRxiv2020

Robust single neuron tracking of calcium imaging in behaving Hydra

Measuring the activity of neuronal populations with calcium imaging can capture emergent functional properties of neuronal circuits with single cell resolution. However, the motion of freely behaving animals, together with the intermittent detectability of calcium sensors, can hinder automatic long-term monitoring of neuronal activity and the subsequent functional characterization of neural circuits. We report the development and open-source implementation of a multi-step cellular tracking algorithm (Elastic Motion Correction and Concatenation or EMC2) that compensates for the intermittent disappearance of moving neurons by integrating local deformation information from detectable neurons. We demonstrate the accuracy and versatility of our algorithm using calcium imaging data from two-photon volumetric microscopy in visual cortex of awake mice, and from confocal microscopy in behaving Hydra, which experiences major body deformation during its contractions. We quantify the performance of our algorithm using ground truth manual tracking of neurons, along with synthetic time-lapse sequences, covering a wide range of particle motions and detectability parameters. By monitoring the calcium activity of the same neuronal populations along several days in layer 2/3 of visual cortex of mice, we report important turn-over within the active neurons across days, with only few neurons that remained active across days. Then, by combining automatic tracking of single neuron activity over long time-lapse sequences with statistical clustering, we characterize and map neuronal ensembles in behaving Hydra. We document the existence three major non-overlapping ensembles of neurons (CB, RP1 and RP2) whose activity correlates with contractions and elongations. Our results prove that the EMC2 algorithm can be used as a robust platform for neuronal tracking in behaving animals.

neuroscience↗

bioRxiv2019

Whole-body imaging of neural and muscle activity during behavior in Hydra: bidirectional effects of osmolarity on contraction bursts

The neural code relates the activity of the nervous system to the activity of the muscles to the generation of behavior. To decipher it, it would be ideal to comprehensively measure the activity of the entire nervous system and musculature in a behaving animal. As a step in this direction, we used the cnidarian Hydra vulgaris to explore how physiological and environmental conditions alter the activity of the entire neural and muscle tissue and affect behavior. We used whole-body calcium imaging of neurons and muscle cells and studied the effect of temperature, media osmolarity, nutritional state and body size on body contractions. In mounted Hydra, changes in temperature, nutrition or body size did not have a major effect on neural or muscle activity, or on behavior. But changes in media osmolarity altered body contractions, increasing them in hipo-osmolar media solutions and decreasing them in hyperosmolar media. Similar effects were seen in ectodermal, but not in endodermal muscle. Osmolarity also bidirectionally changed the activity of contraction bursts neurons, but not of rhythmic potential neurons. These findings show osmolarity-dependent changes in neuronal activity, muscle activity, and contractions, consistent with the hypothesis that contraction burst neurons respond to media osmolarity, activating ectodermal muscle to generate contraction bursts. This dedicated circuit could serve as an excretory system to prevent osmotic injury. This work demonstrates the feasibility of studying the entire neuronal and muscle activity of behaving animals. Significance StatementWe imaged whole-body muscle and neuronal activity in Hydra in response to different physiological and environmental conditions. Osmolarity bidirectionally altered Hydra contractile behavior. These changes were accompanied by corresponding changes in the activity of one neuronal circuit and one set of muscles. This work is a step toward comprehensive deciphering of the mechanisms of animal behavior by measuring the activity of all neurons and muscle cells.

neuroscience↗

bioRxiv2019

Prolonged anesthesia alters brain synaptic architecture

Prolonged medically-induced coma (pMIC), a procedure performed in millions of patients worldwide, leads to cognitive impairment, yet the underlying brain mechanism remains unknown. No experimental studies of medically-induced coma (MIC) exceeding ~6 hours exist. For MIC of less than 6 hours, studies in developing rodents have documented transient changes of cortical synapse formation. However, in adulthood, cortical synapses are thought to become stabilized. Here, we establish pMIC (up to 24 hrs) in adolescent and mature mice, and combine repeated behavioral object recognition assessments with longitudinal two-photon imaging of cortical synapses. We find that pMIC affects cognitive function, and is associated with enhanced synaptic turnover, generated by enhanced synapse formation during pMIC, while the post-anesthetic period is dominated by synaptic loss. These results carry profound implications for intensive medical care, as they point out at significant structural side effects of pMIC on cortical brain synaptic architecture across age levels.

neuroscience↗

bioRxiv2018

An increase in spontaneous activity mediates visual habituation

The cerebral cortex is spontaneously active1,2, but the function of this ongoing activity remains unclear3, 4. One possibility is that spontaneous activity provides contextual information in cortical computations, replaying previously learned patterns of activity5-8 that conditions the cortex to respond more efficiently, based on past experience. To test this, we measured the response of neuronal populations in mouse primary visual cortex with chronic two-photon calcium imaging during a visual habituation to a specific oriented stimulus. We unexpectedly found that, during habituation, spontaneous activity increased in neurons across the full range of orientation selectivity, eventually matching that of evoked levels. The increase in spontaneous activity strongly correlated with the degree of habituation. In fact, boosting spontaneous activity with two-photon optogenetic stimulation to the levels of stimulus-evoked activity induced habituation in naive animals. Our study shows that cortical spontaneous activity is causally linked to habituation, which unfolds by minimizing the difference between spontaneous and stimulus-evoked activity levels, rendering the cortex less responsive. We also show how manipulating spontaneous activity can accelerate this type of learning. We hypothesize that spontaneous activity in visual cortex gates incoming sensory information.

neuroscience↗