Evidence map›Paper›PMID 30690157›Full record

ArticleNeuroImage2019

Intracortical smoothing of small-voxel fMRI data can provide increased detection power without spatial resolution losses compared to conventional large-voxel fMRI data.

Anna I Blazejewska, Bruce Fischl, Lawrence L Wald, Jonathan R Polimeni

Open access · greenAbstract 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 40 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 1 pooled it
4.4field-weighted citation impact, top 5% of its field
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

40 citing papers in PubMed, 1 synthesis or guideline pooled it, 69 citations in OpenAlex.

  1. Pooled it
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  7. Differential Impacts of Strabismic and Anisometropic Amblyopia on the Mesoscale Functional Organization of the Human Visual Cortex.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025
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  13. Selective Functional Connectivity between Ocular Dominance Columns in the Primary Visual Cortex.Ophthalmic medical image analysis : 11th International Workshop, OMIA 2024, held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings. OMIA (Workshop) (11th : 2024 : Marrakech, Morocco) · 2025
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  17. Closed-loop fMRI at the mesoscopic scale of columns and layers: Can we do it and why would we want to?Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
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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 at 1 institution in 1 country.

Anna I BlazejewskaAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA. Electronic address: ABLAZEJEWSKA@mgh.harvard.edu.
Bruce FischlAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
Lawrence L WaldAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.
Jonathan R PolimeniAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Boston, MA, USA; Department of Radiology, Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.
Athinoula A. Martinos Center for Biomedical Imaging · US

Funding

EPIDEMIOLOGY OF DEMENTIA IN THE FRAMINGHAM STUDYR01AG008122 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI AU, RHODA, SESHADRI, SUDHA · 1989 to 2015
$14.4M
MRI, Genetics &Cognitive Precursors of AD &DementiaR01AG016495 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI AU, RHODA · 1999 to 2016
$12.5M
The Human Connectome Project (HCP)U01MH093765 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI ROSEN, BRUCE R · 2010 to 2014
$12.1M
Project 4P41EB015896 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI ROSEN, BRUCE R · 2012 to 2018
$9.8M
Neuropathology of CTE and Delayed Effects of TBI: Toward In-Vivo DiagnosticsU01NS086625 · NINDS · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI DAMS-O'CONNOR, KRISTEN · 2014 to 2017
$6.1M
FreeSurfer Development, Maintenance, and HardeningR01EB023281 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI Bruce Fischl, Douglas Nowlin Greve · 2016 to 2026
$5.6M
fMRI Technologies for Imaging at the Limit of Biological Spatiotemporal Resolution: Administrative SupplementR01EB019437 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI POLIMENI, JONATHAN RIZZO, SETSOMPOP, KAWIN · 2015 to 2024
$5.5M
Resting state connectivity: Biophysical basis for and improved fMRI measurementsR01MH111438 · NIMH · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI KLEINFELD, DAVID, ROSEN, BRUCE R · 2016 to 2020
$5.2M
Improving Human fMRI through Modeling and Imaging Microvascular Dynamics: Administrative SupplementR01MH111419 · NIMH · MASSACHUSETTS GENERAL HOSPITAL · PI POLIMENI, JONATHAN RIZZO · 2016 to 2020
$4.9M
A Longitudinal Analysis Stream for FreeSurferR01NS083534 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI Bruce Fischl · 2014 to 2026
$4.6M
Tools for Analyzing Cortical Structure and ConnectivityR01NS052585 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI FISCHL, BRUCE · 2006 to 2010
$2.5M
Algorithms for MR and OCT-based Architectonic and Laminar SegmentationR01EB019956 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI FISCHL, BRUCE · 2015 to 2018
$2.4M
NCRR NIH HHS S10 RR019307NCRR NIH HHS S10 RR020948NCRR NIH HHS S10 RR023043NCRR NIH HHS S10 RR023401NIA NIH HHS R01 AG008122NIA NIH HHS R01 AG016495NIBIB NIH HHS P41 EB015896NIBIB NIH HHS R01 EB006758NIBIB NIH HHS R01 EB019437NIBIB NIH HHS R01 EB019956NIBIB NIH HHS R01 EB023281NIBIB NIH HHS R21 EB018907NIDDK NIH HHS R21 DK108277NIMH NIH HHS K99 MH120054NIMH NIH HHS R01 MH111419NIMH NIH HHS R01 MH111438NIMH NIH HHS U01 MH093765NINDS NIH HHS R01 NS052585NINDS NIH HHS R01 NS070963NINDS NIH HHS R01 NS083534NINDS NIH HHS R21 NS072652NINDS NIH HHS U01 NS086625
6 · The paper itself

Abstract

Continued improvement in MRI acquisition technology has made functional MRI (fMRI) with small isotropic voxel sizes down to 1 mm and below more commonly available. Although many conventional fMRI studies seek to investigate regional patterns of cortical activation for which conventional voxel sizes of 3 mm and larger provide sufficient spatial resolution, smaller voxels can help avoid contamination from adjacent white matter (WM) and cerebrospinal fluid (CSF), and thereby increase the specificity of fMRI to signal changes within the gray matter. Unfortunately, temporal signal-to-noise ratio (tSNR), a metric of fMRI sensitivity, is reduced in high-resolution acquisitions, which offsets the benefits of small voxels. Here we introduce a framework that combines small, isotropic fMRI voxels acquired at 7 T field strength with a novel anatomically-informed, surface mesh-navigated spatial smoothing that can provide both higher detection power and higher resolution than conventional voxel sizes. Our smoothing approach uses a family of intracortical surface meshes and allows for kernels of various shapes and sizes, including curved 3D kernels that adapt to and track the cortical folding pattern. Our goal is to restrict smoothing to the cortical gray matter ribbon and avoid noise contamination from CSF and signal dilution from WM via partial volume effects. We found that the intracortical kernel that maximizes tSNR does not maximize percent signal change (ΔS/S), and therefore the kernel configuration that optimizes detection power cannot be determined from tSNR considerations alone. However, several kernel configurations provided a favorable balance between boosting tSNR and ΔS/S, and allowed a 1.1-mm isotropic fMRI acquisition to have higher performance after smoothing (in terms of both detection power and spatial resolution) compared to an unsmoothed 3.0-mm isotropic fMRI acquisition. Overall, the results of this study support the strategy of acquiring voxels smaller than the cortical thickness, even for studies not requiring high spatial resolution, and smoothing them down within the cortical ribbon with a kernel of an appropriate shape to achieve the best performance-thus decoupling the choice of fMRI voxel size from the spatial resolution requirements of the particular study. The improvement of this new intracortical smoothing approach over conventional surface-based smoothing is expected to be modest for conventional resolutions, however the improvement is expected to increase with higher resolutions. This framework can also be applied to anatomically-informed intracortical smoothing of higher-resolution data (e.g. along columns and layers) in studies with prior information about the spatial structure of activation.

Indexed as

AdultCerebral CortexFemaleFunctional NeuroimagingHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleYoung AdultColumnar fMRICortical depth analysisfMRI analysisHigh-resolution fMRILaminar fMRIPhysiological noiseSpatial smoothingSurface-based analysis

Identifiers

PMID30690157
PMCPMC6668026
OpenAlexW2912544111

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.