Abstract ↔ claims
run not observed · v1 provisional awaiting approvalWhich claims does the abstract carry, and which does it drop?
for Spatially targeted inhibitory rhythms differentially affect neuronal integration · this layer across all papers · json
Provisional
This layer needs a corpus-scope decision that has not been ruled on yet, so what it produces would change if the decision changed. It waits on claim-format, relation-vocab.
Awaiting approval
Waiting for approval. That is a statement about the record, not about whether anyone has read this: people read the corpus without stamping what they read, and only a stamp leaves a trace. Approval is an operation on a version, not a step of its own — it is recorded against the version it was granted to, so running this layer again does not carry it forward.
What this layer produced
Abstract mapped to claims
The paper's abstract is shown with each sentence linked to the claim(s) it represents in the dependency graph. Hover or click a sentence to highlight the corresponding claim cards. Below: what the graph contains that the abstract leaves out, and vice versa.
1Pyramidal neurons form dense recurrently connected networks with multiple types of inhibitory interneurons. 2A major differentiator between interneuron subtypes is whether they synapse onto perisomatic or dendritic regions. 3They can also engender local inhibitory rhythms, beta (12–35 Hz) and gamma (40–80 Hz). 4The interaction between the rhythmicity of inhibition and its spatial targeting on the neuron may determine how it regulates neuronal integration. 5Thus, we sought to understand how rhythmic perisomatic and distal dendritic inhibition impacted integration in a layer 5 pyramidal neuron model with realistic dendrites supporting Na+, NMDA, and Ca²⁺ spikes. 6We found that inhibition regulated the coupling between dendritic spikes and action potentials in a location and rhythm-dependent manner. 7Perisomatic inhibition principally regulated action potential generation, while distal dendritic inhibition regulated the incidence of dendritic spikes and their temporal coupling with action potentials. 8Perisomatic inhibition was most effective when provided at gamma frequencies, while distal dendritic inhibition functioned best at beta. 9Moreover, beta modulated responsiveness to distal inputs in a phase-dependent manner, while gamma did so for proximal inputs. 10These results may provide a functional interpretation for the reported association of soma-targeting parvalbumin-positive interneurons with gamma and dendrite-targeting somatostatin interneurons with beta.
- naturalistic-drive-parameterization fig1A (inset) The model is driven by ~26,000 excitatory and ~4,500 inhibitory synapses with parameters (release probability, PSC amplitude, temporal kinetics) taken from published experimental measurements, producing a baseline somatic firing rate of approximately 5.3 Hz that matches typical in vivo layer 5 firing rates; no sensitivity analysis over these synaptic parameter choices is presented.
- H1.P4.1 gamma-perisomatic-no-dendritic-spike-change fig5 Gamma-frequency perisomatic rhythms phase-modulate action potential threshold without substantially altering overall dendritic spike rates, demonstrating functional orthogonality between the perisomatic-gamma and distal-beta inhibitory streams.
- E2 burst-effects-emerge-first-cycles fig9 Phase-dependent gating of dendritic spikes and AP timing by oscillatory inhibition kicks in within the first few cycles of a burst — the inhibitory control engages on the same timescale as the rhythm itself.
- E4 ei-lag-sensitivity-firing-rate fig4 E-I coupling lag (4–500 ms) barely changes total firing rate but substantially reshuffles which dendritic compartments drive spiking — timing reorganizes the internal computation without changing the bulk output.
How it is defined
A model answers this layer, so the prompt is the layer. It is reproduced below from the committed file, and it is a declared input — editing it makes every run that used it stale.
The declaration names this path and the repository does not have it. An input that does not exist hashes to nothing, so it cannot make a run stale — the layer is declared to depend on something it is not in fact tracking.
Artifacts
Versions
From the run ledger. There is no changelog beside it to keep in step.
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v1 · 2026-04-19 · unrecorded backfilled from the artifact
backfilled from the artifact on disk
This layer across the corpus
Across the corpus
9 run not observed · 1 stale·a paper links to its own cell, where this layer's output for it is rendered
Inputs and outputs
- Reads, besides its dependencies
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- extract/prompts/abstract-map.md · declared, and not in the repository — it hashes to nothing, so it cannot make a run stale
- Produces
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- site/src/data/abstract-mapping/{paper}.json
One per paper — the table above links each one that exists.
- Views
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- document — rendered above, from the artifact itself
- comparison — on the cell page, two versions aligned by the matcher, wherever the ledger holds more than one
Running it
The command comes from the declaration, so this text and what actually runs cannot
diverge. pipeline.py run also runs the unmet dependencies first.
python3 scripts/pipeline.py run <paper> abstract-map
Underneath, that runs cd extract && python3 -m claim_graphs.cli abstract-map --paper {paper}.