The physiological variability of channel density in hippocampal CA1 pyramidal cells and interneurons explored using a unified data-driven modeling workflow

Every neuron is part of a network, exerting its function by transforming multiple spatiotemporal synaptic input patterns into a single spiking output. This function is specified by the particular shape and passive electrical properties of the neuronal membrane, and the composition and spatial distribution of ion channels across its processes. For a variety of physiological or pathological reasons, the intrinsic input/output function may change during a neuron’s lifetime. This process results in high variability in the peak specific conductance of ion channels in individual neurons. The mechanisms responsible for this variability are not well understood, although there are clear indications from experiment and modeling that degeneracy and correlation among multiple channels may be involved. Here, we studied this issue in biophysical models of hippocampal CA1 pyramidal neurons and interneurons. Using a unified data-driven simulation workflow and starting from a set of experimental recordings and morphological reconstructions obtained from rats, we built and analyzed several ensembles of morphologically and biophysically accurate single cell models with intrinsic electrophysiological properties consistent with experimental findings. The results suggest that the set of conductances expressed in any given hippocampal neuron may be considered as belonging to two groups: one subset is responsible for the major characteristics of the firing behavior in each population and the other responsible for a robust degeneracy. Analysis of the model neurons suggests several experimentally testable predictions related to the combination and relative proportion of the different conductances that should be expressed on the membrane of different types of neurons for them to fulfill their role in the hippocampus circuitry

Data-driven model of the hippocampus using the HBP Brain Simulation Platform

The hippocampus is one of four brain regions being modeled in the ramp-up phase of the Human Brain Project (HBP), testing and guiding the development of the HBP Brain Simulation Platform (BSP) to be released in March 2016. Using preliminary versions of BSP applications developed at the Blue Brain Project, a first draft data-driven model of hippocampus was assembled, integrating data available from HBP and community sources. In brief, the building process started by populating the hippocampal volume, defined by the Allen Brain Atlas, with a series of reconstructions of well-characterized cell types according to experimentally observed densities and proportions. A connectome was generated as previously described [1], constrained by biological values for bouton density and synapses per connection. Single cell electrical models and synapse physiology were constrained by electrophysiological recordings and publicly available data. Further datasets not used as input during model building were used to validate the model. This first draft of the circuit model and the pipeline to build it are to be released with the HBP-BSP in March 2016, and they will be periodically updated. The model represents a resource for the community to integrate data, perform in silico experiments, and test hypotheses. Establishing a community process for the continued refinement of the model is planned for the next phase of the HBP. [1] Reimann, M. et al. An algorithm to predict the connectome of neural microcircuits. Front. Comput. Neurosci. (2015). http://dx.doi.org/10.3389/fncom.2015.0012