Evidence map›Paper›PMID 34859213›Full record

ArticleBrain communications2021

A novel stroke lesion network mapping approach: improved accuracy yet still low deficit prediction.

Lorenzo Pini, Alessandro Salvalaggio, Michele De Filippo De Grazia, Marco Zorzi, Michel Thiebaut de Schotten, Maurizio Corbetta

Abstract read
In one paragraph

Article in Brain communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
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

6 authors.

Lorenzo PiniPadova Neuroscience Center (PNC), University of Padova, Padova, 35100 Italy.ORCID https://orcid.org/0000-0002-9305-3376
Alessandro SalvalaggioPadova Neuroscience Center (PNC), University of Padova, Padova, 35100 Italy.ORCID https://orcid.org/0000-0002-1273-7566
Michele De Filippo De GraziaIRCCS San Camillo Hospital, Venice, 30126 Italy.ORCID https://orcid.org/0000-0003-3682-8582
Marco ZorziIRCCS San Camillo Hospital, Venice, 30126 Italy.ORCID https://orcid.org/0000-0002-4651-6390
Michel Thiebaut de SchottenBrain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, 75006 France.ORCID https://orcid.org/0000-0002-0329-1814
Maurizio CorbettaPadova Neuroscience Center (PNC), University of Padova, Padova, 35100 Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lesion network mapping estimates functional network abnormalities caused by a focal brain lesion. The method requires embedding the volume of the lesion into a normative functional connectome and using the average functional magnetic resonance imaging signal from that volume to compute the temporal correlation with all other brain locations. Lesion network mapping yields a map of potentially functionally disconnected regions. Although promising, this approach does not predict behavioural deficits well. We modified lesion network mapping by using the first principal component of the functional magnetic resonance imaging signal computed from the voxels within the lesioned area for temporal correlation. We measured potential improvements in connectivity strength, anatomical specificity of the lesioned network and behavioural prediction in a large cohort of first-time stroke patients at 2-weeks post-injury (

Indexed as

behaviourfunctional connectivityresting-state networksstroke

Identifiers

PMID34859213
PMCPMC8633453

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.