Hippocampome.org: A knowledge base of neuron types in the rodent hippocampus
Abstract
Hippocampome.org is a comprehensive knowledge base of neuron types in the rodent hippocampal formation (dentate gyrus, CA3, CA2, CA1, subiculum, and entorhinal cortex). Although the hippocampal literature is remarkably information-rich, neuron properties are often reported with incompletely defined and notoriously inconsistent terminology, creating a formidable challenge for data integration. Our extensive literature mining and data reconciliation identified 122 neuron types based on neurotransmitter, axonal and dendritic patterns, synaptic specificity, electrophysiology, and molecular biomarkers. All ~3700 annotated properties are individually supported by specific evidence (~14,000 pieces) in peer-reviewed publications. Systematic analysis of this unprecedented amount of machine-readable information reveals novel correlations among neuron types and properties, the potential connectivity of the full hippocampal circuitry, and outstanding knowledge gaps. User-friendly browsing and online querying of Hippocampome.org may aid design and interpretation of both experiments and simulations. This powerful, simple, and extensible neuron classification endeavor is unique in its detail, utility, and completeness.
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© 2015, Wheeler et al.
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Further reading
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During rest and sleep, memory traces replay in the brain. The dialogue between brain regions during replay is thought to stabilize labile memory traces for long-term storage. However, because replay is an internally driven, spontaneous phenomenon, it does not have a ground truth - an external reference that can validate whether a memory has truly been replayed. Instead, replay detection is based on the similarity between the sequential neural activity comprising the replay event and the corresponding template of neural activity generated during active locomotion. If the statistical likelihood of observing such a match by chance is sufficiently low, the candidate replay event is inferred to be replaying that specific memory. However, without the ability to evaluate whether replay detection methods are successfully detecting true events and correctly rejecting non-events, the evaluation and comparison of different replay methods is challenging. To circumvent this problem, we present a new framework for evaluating replay, tested using hippocampal neural recordings from rats exploring two novel linear tracks. Using this two-track paradigm, our framework selects replay events based on their temporal fidelity (sequence-based detection), and evaluates the detection performance using each event’s track discriminability, where sequenceless decoding across both tracks is used to quantify whether the track replaying is also the most likely track being reactivated.
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