1Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy 2Brain Connectivity Center IRCCS Mondino Foundation, Pavia, Italy * Email:dimitri.rodarie@unipv.it
Introduction
We aim to reconstruct and simulate atlas-mappedmousecerebellar regions, capturing the relationship between structure, dynamics, and function. Numerous experiments on rodents and humans show that the declive region (lobule VI) plays a relevant role in many functions including motor, cognitive, emotional, and social tasks [1]. We present here a pipeline to reconstruct the mouse declive, based on the Blue Brain Cell Atlas (BBCA) model [2] and the Brain Scaffold Builder (BSB) tool [3]. With this pipeline, we could estimate the specific densities of each cell type. With the BSB we placed, oriented, and connected the neurons. The output of this pipeline is a circuit that can be simulated and validated against experimental findings.
Methods We built a 3D model of the mouse declive (Fig. 1), based on the BBCA pipeline (Fig. 1DE), which we extended with the Purkinje layer at the boundary between granular and molecular layers (Fig. 1A). We placed cells based on the atlas and regional densities [4,5] and proposed a new strategy to place Purkinje layer cells based on linear density [6] (Fig. 1F). To connect the cells, we computed the orientations and depth [2] of each morphology (Fig. 1BC). These fields are used to bend the cells’ neurites following the declive curvature (Figure 1G). We applied voxel intersection on these bent cells with synaptic in- and out-degree ratios [3]. Finally, we assigned point-neuron electrical parameters to each cell and connection [7]. Results We combined the workflows of the BBCA and the BSB into a single pipeline. This includes tools to align experimental data into an atlas, to reconstruct and to simulate cerebellar circuits. This allowed us to produce the most detailed model of the mouse declive. We obtained new densities for each cell type of the cerebellum. Our model shows cell composition differences between cerebellar regions. We also estimated the impact of the declive shape on its local connectivity, by comparing different sub-part of the region with respect to a cubic canonical circuit. Finally, we simulated our circuit using the BSB interfacing with the NEST simulator [8] in resting state and created a paradigm to reproduce fear conditioning experiments on mice. Discussion By combining the two pipelines to reconstruct our circuit, we are now able to leverage atlas data to estimate the spatial cellular composition in the cerebellum. The atlas registration will also facilitate the embedding of our model into larger brain circuits [9]. We also found that the cerebellum's highly parceled layers, its curved shape and its position within the mouse atlas make our model very sensitive to artifacts in the data (Figure 1DE). The model will be refined as more data become available. We plan to reconstruct different sub regions of the cerebellar cortex to compare their structure and function. Our future work will also involve mapping the different types of Purkinje neurons based on the “zebrin stripes” [10].
Figure 1. Fig 1: Reconstruction pipeline. A. Annotations shown in colors over the Nissl volume. B. Orientation field showing the local axons’ main axis. Colors represent the vectors’ norm. C. Distance to the outside border, following the orientation field. D. E. Neuron and inhibitory neuron density. F. Neuron positions displayed over annotations. G. Scaled and bent Purkinje morphologies over annotations. Acknowledgements Funding: ● European Union's Horizon 2020 research and innovation program - Marie Sklodowska-Curie - grant 956414 Cerebellum and Emotional Networks ● Virtual Brain Twin Project - European Union's Research and Innovation Program Horizon Europe - grant 101137289 ● National Centre for HPC, Big Data and Quantum Computing - CN00000013 PNRR MUR – M4C2 – Fund 1.4 - decree n. 3138 16 december 2021
