Evidence map›Paper›PMID 29454932›Full record

ArticleNeuroImage2019

Preserved canonicality of the BOLD hemodynamic response reflects healthy cognition: Insights into the healthy brain through the window of Multiple Sclerosis.

Monroe P Turner, Nicholas A Hubbard, Dinesh K Sivakolundu, Lyndahl M Himes, Joanna L Hutchison, John Hart, Jeffrey S Spence, Elliot M Frohman, Teresa C Frohman, Darin T Okuda and 1 more

Abstract read
In one paragraph

Article in NeuroImage, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Towards whole brain mapping of the hemodynamic response function.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2025
    Article
  4. Article
  5. Article
  6. 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

11 authors.

Monroe P TurnerSchool of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX, USA.
Nicholas A HubbardMcGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
Dinesh K SivakolunduSchool of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX, USA.
Lyndahl M HimesSchool of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX, USA.
Joanna L HutchisonSchool of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX, USA.
John HartSchool of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX, USA; Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Jeffrey S SpenceSchool of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX, USA.
Elliot M FrohmanDepartment of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Teresa C FrohmanDepartment of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Darin T OkudaDepartment of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Bart RypmaSchool of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX, USA; Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA. Electronic address: bart.rypma@utdallas.edu.

Funding

BOLD and its discontents: age-differences in the neurophysiology of fMRI signalR01AG047972 · NIA · UT SOUTHWESTERN MEDICAL CENTER · PI LU, HANZHANG, RYPMA, BART · 2015 to 2019
$1.7M
Physiological, neural and cognitive bases of age-related working memory changeR01AG029523 · NIA · UNIVERSITY OF TEXAS DALLAS · PI RYPMA, BART · 2007 to 2010
$1.2M
NIA NIH HHS R01 AG029523NIA NIH HHS R01 AG047972
6 · The paper itself

Abstract

The hemodynamic response function (HRF), a model of brain blood-flow changes in response to neural activity, reflects communication between neurons and the vasculature that supplies these neurons in part by means of glial cell intermediaries (e.g., astrocytes). Intact neural-vascular communication might play a central role in optimal cognitive performance. This hypothesis can be tested by comparing healthy individuals to those with known white-matter damage and impaired performance, as seen in Multiple Sclerosis (MS). Glial cell intermediaries facilitate the ability of neurons to adequately convey metabolic needs to cerebral vasculature for sufficient oxygen and nutrient perfusion. In this study, we isolated measurements of the HRF that could quantify the extent to which white-matter affects neural-vascular coupling and cognitive performance. HRFs were modeled from multiple brain regions during multiple cognitive tasks using piecewise cubic spline functions, an approach that minimized assumptions regarding HRF shape that may not be valid for diseased populations, and were characterized using two shape metrics (peak amplitude and time-to-peak). Peak amplitude was reduced, and time-to-peak was longer, in MS patients relative to healthy controls. Faster time-to-peak was predicted by faster reaction time, suggesting an important role for vasodilatory speed in the physiology underlying processing speed. These results support the hypothesis that intact neural-glial-vascular communication underlies optimal neural and cognitive functioning.

Indexed as

AdultBrainCognitionCognitive DysfunctionFemaleFunctional NeuroimagingHemodynamicsHumansMagnetic Resonance ImagingMaleMiddle AgedMultiple SclerosisNeurovascular CouplingPsychomotor Performance

Identifiers

PMID29454932
PMCPMC6093806

What OpenQuestion holds

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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.