Simple models of quantitative firing phenotypes in hippocampal neurons: comprehensive coverage of intrinsic diversity

Abstract

Author Summary: 35The neurons in the hippocampus show enormous diversity in their intrinsic activity patterns. A comprehensive characterization of various intrinsic types using a neuronal modeling system is necessary to simulate biologically realistic networks of brain regions. Morphologically detailed neuronal modeling frameworks often limit the scalability of such network simulations due to the specification of hundreds of rules governing each neuron's intrinsic dynamics. In this work, we 40 have accomplished a comprehensive mapping of experimentally identified intrinsic dynamics in a simple modeling system with only two governing rules. We have created over a hundred pointneuron models that reflect the intrinsic differences among the hippocampal neuron types both qualitatively and quantitatively. In addition, we compactly extended our point-neurons to include up to four compartments, which will allow anatomically finer-grained connections among the 45 neurons in a network. Our compact model representations, which are freely available in Hippocampome.org, will allow future researchers to investigate dynamical interactions among various intrinsic types and emergent integrative properties using scalable, yet biologically realistic network simulations.

Hippocampome.org 2.0 is a knowledge base enabling data-driven spiking neural network simulations of rodent hippocampal circuits

“…The quantifications of firing pattern phenotypes, such as rapid adapting spiking, transient stuttering, and persistent slow-wave bursting, in v1.6 (Komendantov et al, 2019 ; hippocampome.org/firing_patterns) were fitted by dynamical systems modeling (Izhikevich, 2003 ) in v1.7 (Venkadesh et al, 2019 ;hippocampome.org/Izhikevich). Although the above properties were largely measured from slice preparations, v1.9 made available measurements from in vivo recordings (Sanchez-Aguilera et al, 2021 ;hippocampome.org/in-vivo).…”

The structural aspects of neural dynamics and information flow

“…Based on the single-cell level information, we analyze the information processing of the direct and indirect hippocampal pathways consisting of CA1, CA3, and DG cells. This circuit is a computational representation of the biological two-input system of CA1 [46][47][48], where the CA1 pyramidal neuron can take inputs either directly or indirectly. This circuit is the primary information processing unit for match/mismatch calculation between what is encountered and what is expected-this continuous calculation is important for memory encoding and retrieval in the hippocampus [49][50][51].…”

Quantification of neuron types in the rodent hippocampal formation by data mining and numerical optimization

“…Hippocampome.org further annotates every neuron type with its reported connectivity (Rees et al, 2016), electrophysiological (Komendantov et al, 2019), molecular (White et al, 2020), synaptic (Moradi & Ascoli, 2020), morphological (Tecuatl et al, 2021) and functional (Sanchez‐Aguilera et al, 2021) properties, in all cases providing links to the underlying experimental evidence. The ultimate goal of Hippocampome.org is to create biologically plausible computational models of the hippocampus (Venkadesh et al, 2019). Towards this aim, one key piece of information needed is the count of neurons in each type.…”