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

Abstract

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.All behavior relies on accurate information processing of sensory signals carried out by the concerted activity of populations of neurons 1,2 . While much is known about the pathways of neuronal transduction, how the integration of information derives from the cooperative action of neuronal activity remains largely elusive. However, for many functions of the brain such as sensory processing or memory plasticity, the important coding might be represented within the neuronal population rather than the individual cell. In animal models, recent developments in the field of in vivo imaging tools have allowed neuroscientists to characterize neuronal activity patte...

Circuit reorganization in theDrosophilamushroom body calyx accompanies memory consolidation

“…In comparison to those data, using genetic and functional identification of PN subsets we reveal here that the structural modifications are specific and limited to the PNs conveying the conditioned odour. Importantly, our in vivo functional imaging data support the view that the circuit reorganization that we describe leads to additional [65]. If we hypothesize that appetitive conditioning could lead to a similar outcome, our data could provide anatomical and functional support to these findings.…”

Circuit reorganization in the Drosophila mushroom body calyx accompanies memory consolidation

“…A recent publication, however, suggests an exciting alternative view. After aversive LTM establishment, the number of KCs responding to the conditioned odor is increased (Delestro et al, 2020). If we hypothesize that appetitive conditioning leads to a similar outcome, our data could provide anatomical and functional support to these findings.…”

The cellular architecture of memory modules inDrosophilasupports stochastic input integration

“…Recent studies have observed an increased representa- tion of stimuli in KCs which was mediated through electrical synapses [49]. Furthermore, conditioning induced a functional decorrelation of calcium traces in KC lobes [6,15]. In short, KCs could be recruited to participate in the representation of a stimulus and increase their synaptic input while on the other hand synaptic modulations can decrease synaptic input at the KC-MBON synapse.…”