Evidence map›Paper›PMID 41378281›Full record

ArticleFrontiers in neuroimaging2025

Strategies for automatic generation of information processing pathway maps.

Anirudh Lakra, Cai Wingfield, Chao Zhang, Andrew Thwaites

Abstract read
In one paragraph

Article in Frontiers in neuroimaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Anirudh LakraDepartment of Computer Science, University College London, London, United Kingdom.
Cai WingfieldMRC Cognition and Brain Sciences Unit, Cambridge, United Kingdom.
Chao ZhangDepartment for Speech Hearing and Phonetic Sciences, University College London, London, United Kingdom.
Andrew ThwaitesMRC Cognition and Brain Sciences Unit, Cambridge, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Information Processing Pathway Maps (IPPMs) are a concise way to represent the evidence for the transformation of information as it travels around the brain. However, their construction currently relies on hand-drawn maps from electrophysical recordings such as magnetoencephalography (MEG) and electroencephalography (EEG). This is both inefficient and contains an element of subjectivity. A better approach would be to automatically generate IPPMs from the data and objectively evaluate their accuracy. In this work, we propose a range of possible strategies and compare them to select the best. To this end, we (a) provide a test dataset against which automatic IPPM creation procedures can be evaluated; (b) suggest two novel evaluation metrics-

Indexed as

auditory processingelectroencaphlographyinformation processing pathway mapsmagnetoencepalographymotion processing

Identifiers

PMID41378281
PMCPMC12687749

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.