Coverage

blocked upstream · v3 provisional awaiting approval

What does the paper assert that no claim represents?

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 it produced22 spans.orphans

Read from coverage/kammer-2026-foveal-feedback.json · 8 KB. claims 24panels.pct 45.5statistics.total 31statistics.pct 74.2spans.segmented 212spans.obligations 60spans.textual 152spans.accounted 38spans.pct 63.3

#	uid	section	text	stats	panels
1	results-003	results	To maximise statistical power, we implemented the paradigm using a block design ( Figure 1A ).	`[]`	`["fig1a"]`
2	results-013	results	( A ) Illustration of one block of the experimental and control conditions, respectively.	`[]`	`["fig1a"]`
3	results-017	results	( B ) Depiction of the four stimuli used in the experiment, which were matched in either visual shape (horizontal/vertical) or semantic category (animal/instrument).	`[]`	`["fig1b"]`
4	results-021	results	To compare the experimental condition to activation elicited by direct foveal input, we included a control condition in which participants were instructed to fixate a point at the center of the screen…	`[]`	`["fig1a"]`
5	results-023	results	To elucidate the content of the stimulus information fed back to foveal retinotopic areas, we used four different natural stimuli (one stimulus per block) allowing us to disentangle the nature of the …	`[]`	`["fig1b"]`
6	results-044	results	Foveal feedback is sensitive to stimulus shape, not semantic category Our use of natural stimuli allowed us to test the effects of shape and category on decoding accuracy to better understand the natu…	`[]`	`["fig3a"]`
7	results-048	results	( A ) Schematic depiction of comparisons to assess the information content of the neural representations.	`[]`	`["fig3a"]`
8	results-055	results	Figure 3—figure supplement 1. Decoding stimulus content from all early foveal areas.	`[]`	`["fig3s1"]`
9	results-070	results	We focused on three regions that have consistently been associated with eye movements and object representations: Frontal eye fields (FEF) ( Paus, 1996 ; Vernet et al., 2014 ), intraparietal sulcus (I…	`[]`	`["fig4a","fig3s1f","fig3s1e"]`
10	results-077	results	In contrast, we found no significant association between peripheral decoding and any of the ROIs (FEF: t(27) = 0.49, p =1.0; IPS: t(27) = 1.35, p =0.56; LO: t(27) = 2.43, p =0.07).	`["t(27) = 0.49","p =1.0","t(27) = 1.35","p =0.56","t(27) = 2.43","p =0.07"]`	`[]`
11	results-078	results	These findings confirm that our main effects were not simply explained by global brain fluctuations or signal-to-noise ratio, since under those conditions, we would have expected a similar relationshi…	`[]`	`["fig4s1"]`
12	results-080	results	( A ) Cortical masks used in the ROI analyses.	`[]`	`["fig4a"]`
13	results-084	results	Figure 4—figure supplement 1. Parametric modulation analysis in the control condition.	`[]`	`["fig4s1"]`
14	results-085	results	We conducted the same parametric modulation analysis on the control condition (n=28).	`["n=28"]`	`[]`
15	results-088	results	Peripheral decoding was not associated with significant changes in any of the region of interests (ROIs) (FEF: t(27) = 0.49, p =1.0; IPS: t(27) = 1.35, p =0.56; LO: t(27) = 2.43, p =0.07).	`["t(27) = 0.49","p =1.0","t(27) = 1.35","p =0.56","t(27) = 2.43","p =0.07"]`	`[]`
16	discussion-025	discussion	This explanation does not apply to the effect observed in the present study, since there never was a stimulus presented in the fovea, so remapping of spatial attention to the fovea (as in Rolfs et al.…	`[]`	`["fig5"]`
17	captions-020	captions	( B ) Decoding accuracies for all comparisons using data from foveal regions of V1 and from the lateral occipital area (LO) (n=28).	`["n=28"]`	`[]`
18	captions-023	captions	[panels detected: a, b] === Figure 3s1 === Figure 3—figure supplement 1. Decoding stimulus content from all early foveal areas.	`[]`	`["fig3s1"]`
19	captions-029	captions	( B ) Results of the ROI analyses comparing neural activation as a function of foveal and peripheral decoding in three key areas related to eye movements (n=28).	`["n=28"]`	`[]`
20	captions-031	captions	[panels detected: a, b] === Figure 4s1 === Figure 4—figure supplement 1. Parametric modulation analysis in the control condition.	`[]`	`["fig4s1"]`
21	captions-032	captions	We conducted the same parametric modulation analysis on the control condition (n=28).	`["n=28"]`	`[]`
22	captions-035	captions	Peripheral decoding was not associated with significant changes in any of the region of interests (ROIs) (FEF: t(27) = 0.49, p =1.0; IPS: t(27) = 1.35, p =0.56; LO: t(27) = 2.43, p =0.07).	`["t(27) = 0.49","p =1.0","t(27) = 1.35","p =0.56","t(27) = 2.43","p =0.07"]`	`[]`

Artifacts

coverage/kammer-2026-foveal-feedback.json

Versions

From the run ledger. There is no changelog beside it to keep in step.

v3 · 2026-09-13 · scripts/pipeline.py run

ran via scripts/pipeline.py

cd extract && python3 -m elife_extract.cli coverage --paper kammer-2026-foveal-feedback --json ../coverage/kammer-2026-foveal-feedback.json
v2 · 2026-09-12 · scripts/pipeline.py run

re-run after prepare v2

cd extract && python3 -m elife_extract.cli coverage --paper kammer-2026-foveal-feedback --json ../coverage/kammer-2026-foveal-feedback.json
v1 · 2026-09-11 · scripts/pipeline.py run

coverage for the nine papers that had none

cd extract && python3 -m elife_extract.cli coverage --paper kammer-2026-foveal-feedback --json ../coverage/kammer-2026-foveal-feedback.json

This layer across the corpus

Across the corpus

4 blocked upstream · 6 stale·a paper links to its own cell, where this layer's output for it is rendered

Paper	State	Version	Last run	Output	Cell
A three-dimensional immunofluorescence atlas of the …ran via scripts/pipeline.py	blocked upstream	v3	2026-09-13	artiushin-2026-spider-atlas.json	json
Distinct representational properties of cues and con…ran via scripts/pipeline.py	stale	v4	2026-09-13	bouyeure-2026-fear-rsa.json	json
Computational modelling identifies key determinants …ran via scripts/pipeline.py	stale	v3	2026-09-13	ejdrup-2026-dopamine.json	json
Contributions of insula and superior temporal sulcus…rebuild after edge completion pass	stale	v7	2026-09-13	gadeke-2026-guilt-insula.json	json
Spatially targeted inhibitory rhythms differentially…ran via scripts/pipeline.py	stale	v3	2026-09-13	headley-2026-inhibitory-rhythms.json	json
Feedback of peripheral saccade targets to early fove…ran via scripts/pipeline.py	blocked upstream	v3	2026-09-13	kammer-2026-foveal-feedback.json	json
iGABASnFR2 is an improved genetically encoded protei…ran via scripts/pipeline.py	blocked upstream	v5	2026-09-13	kolb-2026-igabasnfr2.json	json
A deep learning pipeline for mapping in situ network…ran via scripts/pipeline.py	blocked upstream	v5	2026-09-13	rozak-2026-neurovascular-dl.json	json
Self-association enhances early attentional selectio…ran via scripts/pipeline.py	stale	v3	2026-09-13	scheller-2026-self-prioritization.json	json
Impaired excitability of fast-spiking neurons in a n…ran via scripts/pipeline.py	stale	v5	2026-09-13	wengert-2026-kcnc1.json	json

Inputs and outputs

Produces: coverage/{paper}.json

One per paper — the table above links each one that exists.
Views: document — declared, and this artifact is not the shape this view needs
table — rendered above, over the 128 spans.orphans in the artifact

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> coverage

Underneath, that runs cd extract && python3 -m claim_graphs.cli coverage --paper {paper} --json ../coverage/{paper}.json.