Hippocampome.org

Hippocampome.org curates a machine-readable knowledge base of synaptic electrophysiology and neuron-type electrophysiological models for the rodent hippocampus to enable quantitative analysis and modeling of neuron-type-specific synaptic interactions.

Key Features:

• Comprehensive Neuronal Characterization: Systematic annotation of 120 neuron types/subtypes in the rodent hippocampus with intrinsic activity patterns documented.
• Intrinsic Electrophysiological Phenotypes: Detailed phenotypes include delayed spiking, frequency adaptation, and bursting spike-pattern classifications.
• Phenomenological Modeling: A set of quantitative models includes point-neuron models and multi-compartment models with up to four compartments to reproduce electrophysiological phenotypes.
• Low-dimensional Model Mapping: Neuron types are mapped to a low-dimensional model space to enable scalable, biologically realistic network simulations with dendritic compartments to capture bursting and non-linearities in frequency-adapting neurons.
• Synaptic Electrophysiology Evidence Extraction: Extraction of experimental measurements of synaptic amplitude, kinetics, and plasticity across 68 different methods covering 88% of potential hippocampal connections.
• Data Structure and Article Linking: Data structures represent variability across experimental modalities while maintaining relationships among entries and link each entry to relevant text or figure excerpts from over 1,200 published journal articles.
• Synapse Type Mapping: Annotated experiments are mapped to synapse types defined as presynaptic–postsynaptic neuron-type pairs via a computational pipeline that translates neuron-type properties into formal queries.

Scientific Applications:

• Network simulation: Build and analyze biologically realistic hippocampal network models using neuron-type-specific phenomenological models.
• Dynamical interaction analysis: Explore dynamical interactions among neuron types and emergent integrative properties at the mesoscopic level.
• Synaptic measurement analysis: Validate expected correlations and covariates among synaptic amplitude, kinetics, and plasticity measurements and identify novel relationships.
• Hypothesis generation: Generate and test hypotheses about general rules governing synaptic signals across neuron-type-defined synapse types.

Methodology:

Computational methods include mapping 120 neuron types to a low-dimensional model space; implementing phenomenological point-neuron and multi-compartment (up to four compartments) models to reproduce electrophysiological phenotypes; extracting synaptic amplitude, kinetics, and plasticity data from the literature across 68 methods and linking entries to text/figure excerpts from >1,200 articles; and mapping annotated experiments to synapse types via a pipeline that translates neuron-type properties into formal queries.