Community-based Reconstruction and Simulation of a Full-scale Model of Region CA1 of Rat Hippocampus

Abstract

The CA1 region of the hippocampus is one of the most studied regions of the rodent brain, thought to play an important role in cognitive functions such as memory and spatial navigation. Despite a wealth of experimental data on its structure and function, it can be challenging to reconcile information obtained from diverse experimental approaches. To address this challenge, we present a community-driven, full-scalein silicomodel of the rat CA1 that integrates a broad range of experimental data, from synapse to network, including the reconstruction of its principal afferents, the Schaffer collaterals, and a model of the effects that acetylcholine has on the system. We have tested and validated each model component and the final network model, and made input data, assumptions, and strategies explicit and transparent. The flexibility of the model allows scientists to address a range of scientific questions. In this article, we describe the methods used to set up simulations that reproduce and extendin vitroandin vivoexperiments. Among several applications in the article, we focus on theta rhythm, a prominent hippocampal oscillation associated with various behavioral correlates and use our computer model to reproduce and reconcile experimental findings. Finally, we make data, code and model available through the hippocampushub.eu portal, which also provides an extensive set of analyses of the model and a user-friendly interface to facilitate adoption and usage. This neuroscience community-driven model represents a valuable tool for integrating diverse experimental data and provides a foundation for further research into the complex workings of the hippocampal CA1 region.

Cell-type specific contributions to theta-gamma coupled rhythms in the hippocampus

“…Very detailed network models with explicitly identified and characterized cell types have been developed and can express theta and gamma rhythms (Bezaire et al, 2016; Ecker et al, 2020; Romani et al, 2024). Although it is not possible to parse mechanisms using these models, they can be used to explore biological intricacies such as ion channel complements in different cell types and receptor densities.…”

Hippocampome.org v2.0: a knowledge base enabling data-driven spiking neural network simulations of rodent hippocampal circuits

“…For instance, simulations with Hippocampome.org ’s real-scale model of the dentate gyrus can build on previous network models of epileptogenesis (Dyhrfjeld-Johnsen et al, 2007) by providing further clarity to the roles of all documented neuron types and their corresponding potential connections in seizure initiation and propagation. A real-scale model of CA1 can aim to further the insights into the spatiotemporal dynamics of the circuit during theta oscillations (Bezaire et al, 2016; Navas-Olive et al, 2020; Romani et al, 2023). Furthermore, network models involving multiple subregions can open new vistas on unexplored territories, such as the use of real-scale models of the entorhinal cortex and CA2 to simulate the neuron- and connection-type specific mechanisms of social memory (Lopez-Rojas et al, 2022).…”

Enhancement of brain atlases with laminar coordinate systems: Flatmaps and barrel column annotations

“…For example, hippocampus has a complex geometry where a path following its local depth axis tends to be curved, and different paths can have entirely opposite orientations in the different hippocampal subfields (Strange et al, 2014). Since these properties cannot be accounted for by simple linear or affine transforms of the Cartesian coordinate system, hippocampal geometry has been described in terms of long-axis, proximal-distal and laminar coordinates in human (DeKraker et al, 2018) or longitudinal, transverse and radial coordinates in rat (Romani et al, 2023). Even thalamic nuclei contain functional gradients that can be expressed as axes of a region-specific coordinate system (Sumser et al, 2017).…”