Calcium Traces Research Articles

A cross species thermoelectric and spatiotemporal analysis of alternans in live explanted hearts using dual voltage-calcium fluorescence optical mapping

Objective. Temperature plays a crucial role in influencing the spatiotemporal dynamics of the heart. Electrical instabilities due to specific thermal conditions typically lead to early period-doubling bifurcations and beat-to-beat alternans. These pro-arrhythmic phenomena manifest in voltage and calcium traces, resulting in compromised contractile behaviors. In such intricate scenario, dual optical mapping technique was used to uncover unexplored multi-scale and nonlinear couplings, essential for early detection and understanding of cardiac arrhythmia. Approach. We propose a methodological analysis of synchronized voltage-calcium signals for detecting alternans, restitution curves, and spatiotemporal alternans patterns under different thermal conditions, based on integral features calculation. To validate our approach, we conducted a cross-species investigation involving rabbit and guinea pig epicardial ventricular surfaces and human endocardial tissue under pacing-down protocols. Main results. We show that the proposed integral feature, as the area under the curve, could be an easily applicable indicator that may enhance the predictability of the onset and progression of cardiac alternans. Insights into spatiotemporal correlation analysis of characteristic spatial lengths across different heart species were further provided. Significance. Exploring cross-species thermoelectric features contributes to understanding temperature-dependent proarrhythmic regimes and their implications on coupled spatiotemporal voltage-calcium dynamics. The findings provide preliminary insights and potential strategies for enhancing arrhythmia detection and treatment.

Calcium Imaging In Electrically Stimulated Flat-Mounted Retinas.

Retinal dystrophies are a leading cause of blindness worldwide. Extensive efforts are underway to develop advanced retinal prostheses that can bypass the impaired light-sensing photoreceptor cells in the degenerated retina, aiming to partially restore vision by inducing visual percepts. One common avenue of investigation involves the design and production of implantable devices with a flexible physical structure, housing a high number of electrodes. This enables the efficient and precise generation of visual percepts. However, with each technological advancement, there arises a need for a reliable and manageable ex vivo method to verify the functionality of the device before progressing to in vivo experiments, where factors beyond the device's performance come into play. This article presents a comprehensive protocol for studying calcium activity in the retinal ganglion cell layer (GCL) following electrical stimulation. Specifically, the following steps are outlined: (1) fluorescently labeling the rat retina using genetically encoded calcium indicators, (2) capturing the fluorescence signal using an inverted fluorescence microscope while applying distinct patterns of electrical stimulation, and (3) extracting and analyzing the calcium traces from individual cells within the GCL. By following this procedure, researchers can efficiently test new stimulation protocols prior to conducting in vivo experiments.

DeCLUTTER2+ - a pipeline to analyze calcium traces in a stem cell model for ventral midbrain patterned astrocytes.

Astrocytes are the most populous cell type of the human central nervous system and are essential for physiological brain function. Increasing evidence suggests multiple roles for astrocytes in Parkinson's disease, nudging a shift in the research focus, which historically pivoted around ventral midbrain dopaminergic neurons (vmDANs). Studying human astrocytes and other cell types in vivo remains challenging. However, in vitro-reprogrammed human stem cell-based models provide a promising alternative. Here, we describe a novel protocol for astrocyte differentiation from human stem cell-derived vmDAN-generating progenitors. This protocol simulates the regionalization, gliogenic switch, radial migration and final differentiation that occur in the developing human brain. We characterized the morphological, molecular and functional features of these ventral midbrain patterned astrocytes with a broad palette of techniques and identified novel candidate midbrain-astrocyte specific markers. In addition, we developed a new pipeline for calcium imaging data analysis called deCLUTTER2+ (deconvolution of Ca2+ fluorescent patterns) that can be used to discover spontaneous or cue-dependent patterns of Ca2+ transients. Altogether, our protocol enables the characterization of the functional properties of human ventral midbrain patterned astrocytes under physiological conditions and in disease.

Generation of human otic neuronal organoids using pluripotent stem cells.

Otic neurons, also known as spiral ganglion neurons (SGNs) in mammalian cochlea, transmit electrical signals from sensory hair cells to cochlear nuclei of the auditory system. SGNs are sensitive to toxic insults, vulnerable to get irreversible damaged and hardly regenerate after damage, causing persistent sensorineural hearing loss. Yet, to get authentic SGNs for research or therapeutic purpose remains challenging. Here we developed a protocol to generate human otic neuronal organoids (hONOs) from human pluripotent stem cells (hESCs), in which hESCs were step-wisely induced to SGNs of the corresponding stages according to their developmental trajectory. The hONOs were enriched for SGN-like cells at early stage, and for both neurons and astrocytes, Schwann cells or supporting cells thereafter. In these hONOs, we also determined the existence of typical Type I and Type II SGNs. Mature hONOs (at differentiation Day 60) formed neural network, featured by giant depolarizing potential (GDP)-like events and rosette-organized regions-elicited calcium traces. Electrophysiological analysis confirmed the existence of glutamate-responsive neurons in these hONOs. The otic neuronal organoids generated in this study provide an ideal model to study SGNs and related disorders, facilitating therapeutic development for sensorineural hearing loss.

A hardware system for real-time decoding of in vivo calcium imaging data.

Epifluorescence miniature microscopes ('miniscopes') are widely used for in vivo calcium imaging of neural population activity. Imaging data are typically collected during a behavioral task and stored for later offline analysis, but emerging techniques for online imaging can support novel closed-loop experiments in which neural population activity is decoded in real time to trigger neurostimulation or sensory feedback. To achieve short feedback latencies, online imaging systems must be optimally designed to maximize computational speed and efficiency while minimizing errors in population decoding. Here we introduce DeCalciOn, an open-source device for real-time imaging and population decoding of in vivo calcium signals that is hardware compatible with all miniscopes that use the UCLA Data Acquisition (DAQ) interface. DeCalciOn performs online motion stabilization, neural enhancement, calcium trace extraction, and decoding of up to 1024 traces per frame at latencies of <50 ms after fluorescence photons arrive at the miniscope image sensor. We show that DeCalciOn can accurately decode the position of rats (n = 12) running on a linear track from calcium fluorescence in the hippocampal CA1 layer, and can categorically classify behaviors performed by rats (n = 2) during an instrumental task from calcium fluorescence in orbitofrontal cortex. DeCalciOn achieves high decoding accuracy at short latencies using innovations such as field-programmable gate array hardware for real-time image processing and contour-free methods to efficiently extract calcium traces from sensor images. In summary, our system offers an affordable plug-and-play solution for real-time calcium imaging experiments in behaving animals.

A minimal-complexity light-sheet microscope maps network activity in 3D neuronal systems

In vitro systems mimicking brain regions, brain organoids, are revolutionizing the neuroscience field. However, characterization of their electrical activity has remained a challenge as it requires readout at millisecond timescale in 3D at single-neuron resolution. While custom-built microscopes used with genetically encoded sensors are now opening this door, a full 3D characterization of organoid neural activity has not been performed yet, limited by the combined complexity of the optical and the biological system. Here, we introduce an accessible minimalistic light-sheet microscope to the neuroscience community. Designed as an add-on to a standard inverted microscope it can be assembled within one day. In contrast to existing simplistic setups, our platform is suited to record volumetric calcium traces. We successfully extracted 4D calcium traces at high temporal resolution by using a lightweight piezo stage to allow for 5 Hz volumetric scanning combined with a processing pipeline for true 3D neuronal trace segmentation. As a proof of principle, we created a 3D connectivity map of a stem cell derived neuron spheroid by imaging its activity. Our fast, low complexity setup empowers researchers to study the formation of neuronal networks in vitro for fundamental and neurodegeneration research.

Fast, efficient, and accurate neuro-imaging denoising via supervised deep learning

Volumetric functional imaging is widely used for recording neuron activities in vivo, but there exist tradeoffs between the quality of the extracted calcium traces, imaging speed, and laser power. While deep-learning methods have recently been applied to denoise images, their applications to downstream analyses, such as recovering high-SNR calcium traces, have been limited. Further, these methods require temporally-sequential pre-registered data acquired at ultrafast rates. Here, we demonstrate a supervised deep-denoising method to circumvent these tradeoffs for several applications, including whole-brain imaging, large-field-of-view imaging in freely moving animals, and recovering complex neurite structures in C. elegans. Our framework has 30× smaller memory footprint, and is fast in training and inference (50–70 ms); it is highly accurate and generalizable, and further, trained with only small, non-temporally-sequential, independently-acquired training datasets (∼500 pairs of images). We envision that the framework will enable faster and long-term imaging experiments necessary to study neuronal mechanisms of many behaviors.

Biominerals in the Cacteae tribe: Chemical-morphological characterization, distribution and systematic perspectives

• The occurrence of silica bodies in the hypodermis of cacti are diagnostic for all the species of Echinocactus , and the exclusion of E. grusonii of this genus is supported by the lack of silica bodies as well as the occurrence of calcium oxalate druses. • Six biomineral habits were found in the Cacteae species studies, being spherulites and prisms the most common. • Extracellular sandstones occur in six species of Mammillaria , commonly in the outer periclinal wall of the epidermis. • For the first time the structure of the biominerals of seven genera ( Cumarinia, Echinomastus, Escobaria, Obregonia, Sclerocactus , Stenocactus) of Cacteae are characterized. Biominerals precipitate by biological activity and are found in various organisms. In the Cactaceae family, biominerals have been described for numerous genera and species and their contribution to systematics has recently been demonstrated. The aims of this study are to characterize the biominerals in the stem of members of Cacteae by describing their shape, position and mineral composition. Twenty-eight genera and 149 species of Cacteae were studied by bright-field and polarized microscopy. The composition of biominerals was analyzed by scanning electron microscopy and energy-dispersive X-ray spectroscopy in 34 species representing the Cacteae clades. The biominerals of seven genera out of 28 are described for the first time. Only six species of Mammillaria have extracellular biominerals. Sixteen genera and 91 species possess intracellular biominerals in hypodermis, where species of Echinocactus and Ferocactus showed silica bodies. Spherulites, prisms and druses are present in 28 genera, and are distributed in the cortex of 141 species and in the pith of 94 species. Statistical analysis revealed differences between genera for the maximum length of biominerals in the hypodermis and cortex. Notably, Kadenicarpus possesses the smallest biominerals in the cortex and pith (< 35 µm in mean) and the largest mean in the pith for Astrophytum (212 µm). In the Cacteae, calcium oxalates were the most predominant biominerals. Other elements such as magnesium, manganese, and aluminum were also identified. Lophophora is characterized by crystalline aggregates in the cortex of both species with calcium oxalate and traces of silicon and iron, which are not found in other crystalline aggregates of other taxa. We detected a unique combination of biominerals that allowed for us to distinguish the species of some genera, such as Astrophytum and Echinocactus . In conclusion, the occurrence, structure and size of biominerals provide valuable information for systematics at the generic level in Cacteae.

Astrocyte calcium dysfunction causes early network hyperactivity in Alzheimer's disease.

SummaryDysfunctions of network activity and functional connectivity (FC) represent early events in Alzheimer’s disease (AD), but the underlying mechanisms remain unclear. Astrocytes regulate local neuronal activity in the healthy brain, but their involvement in early network hyperactivity in AD is unknown. We show increased FC in the human cingulate cortex several years before amyloid deposition. We find the same early cingulate FC disruption and neuronal hyperactivity in AppNL-F mice. Crucially, these network disruptions are accompanied by decreased astrocyte calcium signaling. Recovery of astrocytic calcium activity normalizes neuronal hyperactivity and FC, as well as seizure susceptibility and day/night behavioral disruptions. In conclusion, we show that astrocytes mediate initial features of AD and drive clinically relevant phenotypes.

Minian, an open-source miniscope analysis pipeline.

Miniature microscopes have gained considerable traction for in vivo calcium imaging in freely behaving animals. However, extracting calcium signals from raw videos is a computationally complex problem and remains a bottleneck for many researchers utilizing single-photon in vivo calcium imaging. Despite the existence of many powerful analysis packages designed to detect and extract calcium dynamics, most have either key parameters that are hard-coded or insufficient step-by-step guidance and validations to help the users choose the best parameters. This makes it difficult to know whether the output is reliable and meets the assumptions necessary for proper analysis. Moreover, large memory demand is often a constraint for setting up these pipelines since it limits the choice of hardware to specialized computers. Given these difficulties, there is a need for a low memory demand, user-friendly tool offering interactive visualizations of how altering parameters at each step of the analysis affects data output. Our open-source analysis pipeline, Minian (miniscope analysis), facilitates the transparency and accessibility of single-photon calcium imaging analysis, permitting users with little computational experience to extract the location of cells and their corresponding calcium traces and deconvolved neural activities. Minian contains interactive visualization tools for every step of the analysis, as well as detailed documentation and tips on parameter exploration. Furthermore, Minian has relatively small memory demands and can be run on a laptop, making it available to labs that do not have access to specialized computational hardware. Minian has been validated to reliably and robustly extract calcium events across different brain regions and from different cell types. In practice, Minian provides an open-source calcium imaging analysis pipeline with user-friendly interactive visualizations to explore parameters and validate results.

Multiscale modeling of presynaptic dynamics from molecular to mesoscale.

Chemical synapses exhibit a diverse array of internal mechanisms that affect the dynamics of transmission efficacy. Many of these processes, such as release of neurotransmitter and vesicle recycling, depend strongly on activity-dependent influx and accumulation of Ca2+. To model how each of these processes may affect the processing of information in neural circuits, and how their dysfunction may lead to disease states, requires a computationally efficient modelling framework, capable of generating accurate phenomenology without incurring a heavy computational cost per synapse. Constructing a phenomenologically realistic model requires the precise characterization of the timing and probability of neurotransmitter release. Difficulties arise in that functional forms of instantaneous release rate can be difficult to extract from noisy data without running many thousands of trials, and in biophysical synapses, facilitation of per-vesicle release probability is confounded by depletion. To overcome this, we obtained traces of free Ca2+ concentration in response to various action potential stimulus trains from a molecular MCell model of a hippocampal Schaffer collateral axon. Ca2+ sensors were placed at varying distance from a voltage-dependent calcium channel (VDCC) cluster, and Ca2+ was buffered by calbindin. Then, using the calcium traces to drive deterministic state vector models of synaptotagmin 1 and 7 (Syt-1/7), which respectively mediate synchronous and asynchronous release in excitatory hippocampal synapses, we obtained high-resolution profiles of instantaneous release rate, to which we applied functional fits. Synchronous vesicle release occurred predominantly within half a micron of the source of spike-evoked Ca2+ influx, while asynchronous release occurred more consistently at all distances. Both fast and slow mechanisms exhibited multi-exponential release rate curves, whose magnitudes decayed exponentially with distance from the Ca2+ source. Profile parameters facilitate on different time scales according to a single, general facilitation function. These functional descriptions lay the groundwork for efficient mesoscale modelling of vesicular release dynamics.

A deep-dive into fictive locomotion - a strategy to probe cellular activity during speed transitions in fictively swimming zebrafish larvae.

ABSTRACTFictive locomotion is frequently used to study locomotor output in paralyzed animals. We have evaluated the character of swim episodes elicited by different strategies in zebrafish. Motor output was measured on both sides of a body segment using electrodes and a pipeline for synchronizing stimulation and recording, denoising data and peak-finding was developed. The optomotor response generated swims most equivalent to spontaneous activity, while electrical stimulation and NMDA application caused various artefacts. Our optimal settings, optomotor stimulation using 5-day-old larvae, were combined with calcium imaging and optogenetics to validate the setup's utility. Expression of GCaMP5G by the mnx1 promoter allowed correlation of calcium traces of dozens of motor neurons to the fictive locomotor output. Activation of motor neurons through channelrhodopsin produced aberrant locomotor episodes. This strategy can be used to investigate novel neuronal populations in a high-throughput manner to reveal their role in shaping motor output. This article has an associated First Person interview with the first author of the paper.

Decontaminate Traces From Fluorescence Calcium Imaging Videos Using Targeted Non-negative Matrix Factorization.

Fluorescence microscopy and genetically encoded calcium indicators help understand brain function by recording large-scale in vivo videos in assorted animal models. Extracting the fluorescent transients that represent active periods of individual neurons is a key step when analyzing imaging videos. Non-specific calcium sources and background adjacent to segmented neurons contaminate the neurons’ temporal traces with false transients. We developed and characterized a novel method, temporal unmixing of calcium traces (TUnCaT), to quickly and accurately unmix the calcium signals of neighboring neurons and background. Our algorithm used background subtraction to remove the false transients caused by background fluctuations, and then applied targeted non-negative matrix factorization to remove the false transients caused by neighboring calcium sources. TUnCaT was more accurate than existing algorithms when processing multiple experimental and simulated datasets. TUnCaT’s speed was faster than or comparable to existing algorithms.

To deconvolve, or not to deconvolve: Inferences of neuronal activities using calcium imaging data

BackgroundWith the increasing popularity of calcium imaging in neuroscience research, choosing the right methods to analyze calcium imaging data is critical to address various scientific questions. Unlike spike trains measured using electrodes, fluorescence intensity traces provide an indirect and noisy measurement of the underlying neuronal activities. The observed calcium traces are either analyzed directly or deconvolved to spike trains to infer neuronal activities. When both approaches are applicable, it is unclear whether deconvolving calcium traces is a necessary step. MethodsIn this article, we compare the performance of using calcium traces or their deconvolved spike trains for three common analyses: clustering, principal component analysis (PCA), and population decoding. ResultsWe found that (1) the two approaches lead to diverging results; (2) estimated spike trains, when smoothed or binned appropriately, usually lead to satisfactory performances, such as more accurate estimation of cluster membership; (3) although estimate spike train produce results more similar to true spike data than trace data, we found that the PCA results from trace data might better reflect the underlying neuronal ensembles (clusters); and (4) for both approaches, decobability can be improved by using denoising or smoothing methods. Comparison with existing methodsOur simulations and applications to real data suggest that estimated spike data outperform trace data in cluster analysis and give comparable results for population decoding. In addition, the decobability of estimated spike data can be slightly better than that of calcium trace data with appropriate filtering / smoothing methods. ConclusionWe conclude that spike detection might be a useful pre-processing step for certain problems such as clustering; however, the continuous nature of calcium imaging data provides a natural smoothness that might be helpful for problems such as dimensional reduction.

Calcium imaging of the nodose ganglion reveals specific cell responses to specific cytokines

Neural reflex circuits regulate the progression and resolution of inflammation. In the inflammatory reflex, sensory responses to injury or infection are relayed via afferent vagus nerve fibers to the brainstem that in turn sends efferent neural signals to spleen, which inhibits inflammation. Prior vagus nerve recording techniques demonstrated that information linked to specific cytokines is carried through the afferent arm of the vagus nerve. However, these electrical recordings cannot observe sensory signaling at the single neuron level. Here, using calcium imaging we demonstrate that individual nodose ganglion neurons respond to specific cytokines. To explore the role of the vagus sensory neurons in reporting specific cytokine signals, we utilized Vglut2-gCaMP6 mice expressing green fluorescent protein in response to intracellular Ca2+as a proxy for neuronal activity. Nodose ganglion was isolated from the brainstem, and placed under a Miniscope, leaving intact connections to the peripheral organs. Using this preparation, approximately 69±16.3 cells per recording were monitored in a plane of focus for individual neuronal activity, continuously for over 1 hour. After baseline imaging, two proinflammatory cytokines, TNF and IL-1β, were administered directly on the nerve in 5 min intervals with saline washes in between cytokines. The viability of the neuronal preparation was confirmed using KCl as a positive control. Analysis of the calcium traces for individual cells using the computational toolbox CaImAn revealed that individual sensory neurons either selectively respond to only one cytokine at a time (responding cells TNF: 23.6±10.4; IL-1β: 19.75±15.7) or with a subset of neurons that respond to both (responding cells TNF+IL-1β: 13±10.3). Interestingly, the peak relative fluorescence (dF/F) values of TNF responsive neurons are significantly higher than the neurons responding to both TNF and IL1β (TNF vs. TNF+IL-1β, p < 0.01). These findings suggest that individual sensory neurons in the nodose ganglion encode information about a specific cytokine and be recruited by multiple cytokines.

Flipping the switch on the hub cell: Islet desynchronization through cell silencing.

Pancreatic β cells, responsible for secreting insulin into the bloodstream and maintaining glucose homeostasis, are organized in the islets of Langerhans as clusters of electrically coupled cells. Gap junctions, connecting neighboring cells, coordinate the behavior of the islet, leading to the synchronized oscillations in the intracellular calcium and insulin secretion in healthy islets. Recent experimental work has shown that silencing special hub cells can lead to a disruption in the coordinated behavior, calling into question the democratic paradigm of islet insulin secretion with more or less equal input from each β cell. Islets were shown to have scale-free functional connectivity and a hub cell whose silencing would lead to a loss of functional connectivity and activity in the islet. A mechanistic model representing the electrical and calcium dynamics of β cells during insulin secretion was applied to a network of cells connected by gap junctions to test the hypothesis of hub cells. Functional connectivity networks were built from the simulated calcium traces, with some networks classified as scale-free, confirming experimental results. Potential hub cells were identified using previously defined centrality measures, but silencing them was unable to desynchronize the islet. Instead, switch cells, which were able to turn off the activity of the islet but were not highly functionally connected, were found via systematically silencing each cell in the network.

Automated Curation of CNMF-E-Extracted ROI Spatial Footprints and Calcium Traces Using Open-Source AutoML Tools.

In vivo 1-photon (1p) calcium imaging is an increasingly prevalent method in behavioral neuroscience. Numerous analysis pipelines have been developed to improve the reliability and scalability of pre-processing and ROI extraction for these large calcium imaging datasets. Despite these advancements in pre-processing methods, manual curation of the extracted spatial footprints and calcium traces of neurons remains important for quality control. Here, we propose an additional semi-automated curation step for sorting spatial footprints and calcium traces from putative neurons extracted using the popular constrained non-negative matrixfactorization for microendoscopic data (CNMF-E) algorithm. We used the automated machine learning (AutoML) tools TPOT and AutoSklearn to generate classifiers to curate the extracted ROIs trained on a subset of human-labeled data. AutoSklearn produced the best performing classifier, achieving an F1 score >92% on the ground truth test dataset. This automated approach is a useful strategy for filtering ROIs with relatively few labeled data points and can be easily added to pre-existing pipelines currently using CNMF-E for ROI extraction.

Drosophila Brain Functional Data Analysis: A Unified Framework.

A unified framework for the analysis of fluorescence data taken by a two-photon imaging system is presented. As in the processing of blood-oxygen-level-dependent signals of functional magnetic resonance imaging, the acquired functional images have to be co-registered with a structural brain atlas before delineating the regions activated by a given stimulus. The voxels whose calcium traces are highly correlated with the predicted responses are demarcated without the need for subjective reasoning. Experimental data acquired while presenting olfactory stimuli are used to demonstrate the efficacy of the proposed schemes. The results indicate that the functional images of a Drosophila individual can be normalized into a standard stereotactic space, and the expected brain regions can be delineated adequately. This framework provides an opportunity to enable the development of a Drosophila functional connectome database.

Chemoscopic, macromorphological and micromorphological evaluation of the leaves of &lt;i&gt;Crescentia cujet&lt;/i&gt;Linn

The leaves of Crescentia cujete Linn belonging to Bignoniaceae family have been reported to exhibit some important medicinal properties such as antioxidant, antimicrobial, anti-tumour and anti-inflammatory activities. This study therefore evaluated the chemoscopic, macro-morphological andmicromorphological attributes of powdered, fresh and anatomical sections of Crescentia cujete Linn leaves using standard methods. The result ofchemoscopic study confirmed presence of calcium oxalate crystals, fat deposits and traces of lignin in numbers on epidermal surfaces. Macro-morphological study revealed that C. cujete leaves are deep green in colour with faint odour, sour taste and smooth-feel with non-granular surfaces. Micromorphological examinations indicated that epidermal cells are irregular, rectangular to polygonal in shape on the abaxial surface but epidermal cells on the adaxial surface were straight, slightly undulating with thick anticlinal cell walls. Paracytic stomata arrangement was found only on the abaxial surfaces. Quantitative leaf microscopy confirmed that epidermal cells had average sizes of 37.52 ± 4.62 – 39.23 ± 4.73 μm in length while cell width was 25.51± 0.86 – 27.76 ± 4.21μm. The stomata length was 15.66 ± 2.04 and 6.29 ±0.93 in width. Organoleptic and other parameters evaluated on C. cujete shows that it has optimum potential for herbal drug development and a baseline for species identification.

In vivo large-scale analysis of Drosophila neuronal calcium traces by automated tracking of single somata

How does the concerted activity of neuronal populations shape behavior? Impediments to address this question are primarily due to critical experimental barriers. An integrated perspective on large scale neural information processing requires an in vivo approach that can combine the advantages of exhaustively observing all neurons dedicated to a given type of stimulus, and simultaneously achieve a resolution that is precise enough to capture individual neuron activity. Current experimental data from in vivo observations are either restricted to a small fraction of the total number of neurons, or are based on larger brain volumes but at a low spatial and temporal resolution. Consequently, fundamental questions as to how sensory information is represented on a population scale remain unanswered. In Drosophila melanogaster, the mushroom body (MB) represents an excellent model to analyze sensory coding and memory plasticity. In this work, we present an experimental setup coupled with a dedicated computational method that provides in vivo measurements of the activity of hundreds of densely packed somata uniformly spread in the MB. We exploit spinning-disk confocal 3D imaging over time of the whole MB cell body layer in vivo while it is exposed to olfactory stimulation. Importantly, to derive individual signal from densely packed somata, we have developed a fully automated image analysis procedure that takes advantage of the specificities of our data. After anisotropy correction, our approach operates a dedicated spot detection and registration over the entire time sequence to transform trajectories to identifiable clusters. This enabled us to discard spurious detections and reconstruct missing ones in a robust way. We demonstrate that this approach outperformed existing methods in this specific context and made possible high-throughput analysis of approximately 500 single somata uniformly spread over the MB in various conditions. Applying this approach, we find that learned experiences change the population code of odor representations in the MB. After long-term memory (LTM) formation, we quantified an increase in responsive somata count and a stable single neuron signal. We predict that this method, which should further enable studying the population pattern of neuronal activity, has the potential to uncover fine details of sensory processing and memory plasticity.