Reference library
Generalized leaky integrate-and-fire models classify multiple neuron types.
Paper summary
Fits generalized leaky integrate-and-fire models of increasing complexity to recorded neurons. More complex point models better predict held-out spike timing, and parameter patterns help distinguish broad cell classes.
Relevance to the project
Offers a reduced-model validation example: compare specified observable responses instead of claiming complete biological fidelity. Can inform tests for intrinsic adaptation in F.
Spike prediction under selected stimuli is narrower than general neuronal equivalence.
Source record
- Reference ID
- doi-10-1038-s41467-017-02717-4
- Archived version
- Publisher PDF registered with Crossref
- Summary provenance
- reference-library/papers/doi-10-1038-s41467-017-02717-4/metadata.json · summary
- Review status
- initial orientation summary; not a critical full-paper review
- Reading scope
- Selected abstract/opening and available closing discussion/conclusion passages in the preserved text extract; broader project notes provide context. No reproduction of experiments, exhaustive methods review, or equation/figure audit.