Evidence map›Paper›PMID 35964357›Full record

ArticleCortex; a journal devoted to the study of the nervous system and behavior2022

Preserved anatomical bypasses predict variance in language functions after stroke.

B A Erickson, B Kim, B L Deck, D Pustina, A T DeMarco, J V Dickens, A S Kelkar, P E Turkeltaub, J D Medaglia

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cortex; a journal devoted to the study of the nervous system and behavior, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

9 authors.

B A EricksonDepartment of Psychology, Drexel University, Philadelphia, PA, USA. Electronic address: bae25@drexel.edu.
B KimDepartment of Psychology, Drexel University, Philadelphia, PA, USA.
B L DeckDepartment of Psychology, Drexel University, Philadelphia, PA, USA.
D PustinaCHDI Foundation, Princeton, NJ, USA.
A T DeMarcoDepartment of Rehabilitation Medicine, Georgetown University, Washington, DC, USA.
J V DickensDepartment of Neurology, Georgetown University, Washington, DC, USA.
A S KelkarDepartment of Psychology, Drexel University, Philadelphia, PA, USA.
P E TurkeltaubDepartment of Rehabilitation Medicine, Georgetown University, Washington, DC, USA; Department of Neurology, Georgetown University, Washington, DC, USA; MedStar National Rehabilitation Hospital, Washington, DC, USA.
J D MedagliaDepartment of Psychology, Drexel University, Philadelphia, PA, USA; Department of Neurology, Drexel University, Philadelphia, PA, USA; Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA.

Funding

Contributions of spared brain structures and connections to aphasia recoveryR01DC014960 · NIDCD · GEORGETOWN UNIVERSITY · PI TURKELTAUB, PETER ETHAN · 2017 to 2021
$4.0M
Treating primary progressive aphasia and elucidating neurodegeneration in the language network using transcranial direct current stimulationR01AG059763 · NIA · UNIVERSITY OF PENNSYLVANIA · PI HAMILTON, ROY H · 2019 to 2024
$3.7M
Transcranial Magnetic Stimulation for Aphasia: Efficacy and Neural BasisR01DC016800 · NIDCD · UNIVERSITY OF PENNSYLVANIA · PI COSLETT, H BRANCH · 2018 to 2022
$3.3M
Validating MXene Electrodes for Next-Generation ElectroencephalographyR01NS121219 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI MEDAGLIA, JOHN, VITALE, FLAVIA · 2021 to 2025
$2.3M
NIA NIH HHS R01 AG059763NIDCD NIH HHS R01 DC014960NIDCD NIH HHS R01 DC016800NINDS NIH HHS R01 NS121219
6 · The paper itself

Abstract

The severity of post-stroke aphasia is related to damage to white matter connections. However, neural signaling can route not only through direct connections, but also along multi-step network paths. When brain networks are damaged by stroke, paths can bypass around the damage to restore communication. The shortest network paths between regions could be the most efficient routes for mediating bypasses. We examined how shortest-path bypasses after left hemisphere strokes were related to language performance. Regions within and outside of the canonical language network could be important in aphasia recovery. Therefore, we innovated methods to measure the influence of bypasses in the whole brain. Distinguishing bypasses from all residual shortest paths is difficult without pre-stroke imaging. We identified bypasses by finding shortest paths in subjects with stroke that were longer than the most reliably observed connections in age-matched control networks. We tested whether features of those bypasses predicted scores in four orthogonal dimensions of language performance derived from a principal components analysis of a battery of language tasks. The features were the length of each bypass in steps, and how many bypasses overlapped on each individual direct connection. We related these bypass features to language factors using support vector regression, a technique that extracts robust relationships in high-dimensional data analysis. The support vector regression parameters were tuned using grid-search cross-validation. We discovered that the length of bypasses reliably predicted variance in lexical production (R

Indexed as

AphasiaStrokeBrainBrain MappingHumansLanguageMagnetic Resonance ImagingAphasiaGraph theoryLanguageNetwork neurosciencePath length

Identifiers

PMID35964357
PMCPMC11697986

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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.