Abstract ↔ claims

run not observed · v1 provisional awaiting approval

Which claims does the abstract carry, and which does it drop?

for Feedback of peripheral saccade targets to early foveal cortex · 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.

Abstract

1Human vision is characterized by frequent eye movements and constant shifts in visual input, yet our perception of the world remains remarkably stable. 2Here, we directly demonstrate image-specific foveal feedback to primary visual cortex in the context of saccadic eye movements. 3To this end, we used a gaze-contingent fMRI paradigm, in which peripheral saccade targets disappeared before they could be fixated. 4Despite no direct foveal stimulation, we were able to decode peripheral saccade targets from foveal retinotopic areas, demonstrating that image-specific feedback during saccade preparation may underlie this effect. 5Decoding was sensitive to shape but not semantic category of natural images, indicating feedback of only low-to-mid-level information. 6Cross-decoding to a control condition with foveal stimulus presentation indicates a shared representational format between foveal feedback and direct stimulation. 7Moreover, eccentricity-dependent analyses showed a U-shaped decoding curve, confirming that these results are not explained by spillover of peripheral activity or large receptive fields. 8Finally, fluctuations in foveal decodability covaried with activity in the intraparietal sulcus, thus providing a candidate region for driving foveal feedback. 9These findings suggest that foveal cortex predicts the features of incoming stimuli through feedback from higher cortical areas, which offers a candidate mechanism underlying stable perception.

[1]
background / framing — not a paper-specific claim
[2]
direct map → E2 · Foveal V1 carries decodable information about peripheral saccade targets even wh
[3]
direct map → M2 · The gaze-contingent display extinguished the peripheral target before it crossed
[4]
direct map → E2 · Foveal V1 carries decodable information about peripheral saccade targets even wh
[5]
combines multiple claims → S1 · Foveal feedback carries low-to-mid-level shape information but not semantic cate, H1.P2.1 · Within foveal V1, cross-category decoding drops significantly under feedback whi
[6]
direct map → H3.P1.1 · Classifiers trained on foveal feedback responses generalize to direct foveal sti
[7]
direct map → H2.P1.1 · Decoding accuracy across V1, V2, and V3 dips at parafoveal eccentricities and ri
[8]
direct map → S2 · Trial-by-trial intraparietal sulcus activity tracks foveal decoding strength mor
[9]
no corresponding claim in the graph
Claims in the graph not surfaced in the abstract
  • M1 preregistered-design-validates-mvpa methods
    The MVPA pipeline, ROI definitions, and statistical tests were preregistered, constraining analytic flexibility for the main decoding results — though the parametric modulation analysis was excluded from the registered plan.
  • Sc2 preregistration-submitted-after-manuscript methods
    The preregistration was uploaded to OSF only after the manuscript was submitted, so its evidentiary weight rests on author-cited website timestamps rather than on a public deposit predating data collection.
  • E1 foveal-feedback-below-direct-stimulation fig2A
    The feedback signal in foveal V1 is reliably weaker than the response to direct foveal stimulation, consistent with a low-bandwidth top-down channel rather than a fully reinstated sensory representation.
  • H1.P1.1 lo-shows-reversed-specificity fig3B
    Lateral occipital cortex shows the inverse profile to foveal V1 — cross-shape decoding drops while cross-category decoding survives — yielding a double dissociation that rules out a generic sensitivity argument for the V1 result.
  • H1.P2.2 v2-v3-generalize-shape-not-category fig3-figure-supplement-1
    The shape-sensitive, category-insensitive feedback profile extends to foveal V2 and V3, locating the effect in early visual cortex broadly rather than in V1 alone.
  • Sc1 parametric-modulation-exploratory-not-preregistered methods
    The parametric modulation analysis identifying IPS as a feedback driver was explicitly exploratory and outside the preregistered plan, so it carries the weight of a hypothesis-generating result rather than a confirmatory test.
  • C1 fef-lo-nonsignificant-after-correction fig4B
    Neither FEF nor LO survives Bonferroni correction in the parametric modulation analysis, leaving IPS as the only ROI specifically coupled to foveal decoding rather than a global brain-state effect.
  • C2 ips-foveal-effect-reverses-in-control fig4-figure-supplement-1
    Under direct foveal stimulation the IPS–foveal-decoding correlation reverses sign, confirming that the positive coupling seen during feedback is context-specific and not a generic effect of attention or arousal.
Abstract assertions without corresponding claims in the graph
  • [9] These findings suggest that foveal cortex predicts the features of incoming stimuli through feedback from higher cortical areas, which offers a candidate mechanism underlying stable perception.

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.

extract/prompts/abstract-map.mdthe prompt it runs undernot in the repository

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.

  1. 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

PaperStateVersionLast runOutputCell
A three-dimensional immunofluorescence atlas of the …backfilled from the artifact on diskrun not observedv12026-04-20artiushin-2026-spider-atlas.jsonjson
Distinct representational properties of cues and con…backfilled from the artifact on diskrun not observedv12026-04-20bouyeure-2026-fear-rsa.jsonjson
Computational modelling identifies key determinants …backfilled from the artifact on diskrun not observedv12026-04-20ejdrup-2026-dopamine.jsonjson
Contributions of insula and superior temporal sulcus…re-run for the current treestalev52026-09-12gadeke-2026-guilt-insula.jsonjson
Spatially targeted inhibitory rhythms differentially…backfilled from the artifact on diskrun not observedv12026-04-19headley-2026-inhibitory-rhythms.jsonjson
Feedback of peripheral saccade targets to early fove…backfilled from the artifact on diskrun not observedv12026-04-19kammer-2026-foveal-feedback.jsonjson
iGABASnFR2 is an improved genetically encoded protei…backfilled from the artifact on diskrun not observedv12026-04-20kolb-2026-igabasnfr2.jsonjson
A deep learning pipeline for mapping in situ network…backfilled from the artifact on diskrun not observedv12026-04-20rozak-2026-neurovascular-dl.jsonjson
Self-association enhances early attentional selectio…backfilled from the artifact on diskrun not observedv12026-04-20scheller-2026-self-prioritization.jsonjson
Impaired excitability of fast-spiking neurons in a n…backfilled from the artifact on diskrun not observedv12026-04-20wengert-2026-kcnc1.jsonjson

Inputs and outputs

Reads, besides its dependencies
Produces
  • site/src/data/abstract-mapping/{paper}.json

One per paper — the table above links each one that exists.

Views
  • 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}.