Evidence map›Paper›PMID 25451480›Full record

ArticleNeuroImage2015

A voxel-wise encoding model for early visual areas decodes mental images of remembered scenes.

Thomas Naselaris, Cheryl A Olman, Dustin E Stansbury, Kamil Ugurbil, Jack L Gallant

Abstract read
In one paragraph

Article in NeuroImage, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 101 papers.

0numbers the graph read from it
0cells of the map it votes in
101citing 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

101 citing papers in PubMed.

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  14. Hippocampal-guided reconstruction of an event's prior temporal context.bioRxiv : the preprint server for biology · 2025
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  15. Article
  16. A transformation from vision to imagery in the human brain.bioRxiv : the preprint server for biology · 2025
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41 more citing papers are in PubMed but not listed here.

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

5 authors.

Thomas NaselarisDepartment of Neurosciences, Medical University of South Carolina, SC, USA. Electronic address: tnaselar@musc.edu.
Cheryl A OlmanDepartment of Psychology, University of Minnesota, MN, USA; Center for Magnetic Resonance Research, University of Minnesota, MN, USA.
Dustin E StansburyVision Science Group, University of California, Berkeley, CA, USA.
Kamil UgurbilCenter for Magnetic Resonance Research, University of Minnesota, MN, USA.
Jack L GallantVision Science Group, University of California, Berkeley, CA, USA; Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA; Department of Psychology, University of California, Berkeley, CA, USA.

Funding

Visual TestingP30EY011374 · NEI · UNIVERSITY OF MINNESOTA TWIN CITIES · PI NEWMAN, ERIC A · 1996 to 2019
$8.8M
NMR Imaging and SpectroscopyP41EB015894 · NIBIB · UNIVERSITY OF MINNESOTA · PI UGURBIL, KAMIL · 2012 to 2017
$8.4M
Institutional Center Cores for Advanced NeuroimagingP30NS076408 · NINDS · UNIVERSITY OF MINNESOTA · PI UGURBIL, KAMIL · 2012 to 2020
$4.2M
Seen and mental images in visual cortexR01EY023384 · NEI · UNIVERSITY OF MINNESOTA · PI HERMES, DORA, NASELARIS, THOMAS P · 2014 to 2025
$3.4M
Visual Representation and AttentionR01EY019684 · NEI · UNIVERSITY OF CALIFORNIA BERKELEY · PI GALLANT, JACK L · 2010 to 2018
$2.9M
NEI NIH HHS NEI R01-EY019684NEI NIH HHS NEI R01-EY023384NEI NIH HHS P30 EY011374NEI NIH HHS R01 EY019684NEI NIH HHS R01 EY023384NIBIB NIH HHS P41 EB015894NINDS NIH HHS P30 NS076408
6 · The paper itself

Abstract

Recent multi-voxel pattern classification (MVPC) studies have shown that in early visual cortex patterns of brain activity generated during mental imagery are similar to patterns of activity generated during perception. This finding implies that low-level visual features (e.g., space, spatial frequency, and orientation) are encoded during mental imagery. However, the specific hypothesis that low-level visual features are encoded during mental imagery is difficult to directly test using MVPC. The difficulty is especially acute when considering the representation of complex, multi-object scenes that can evoke multiple sources of variation that are distinct from low-level visual features. Therefore, we used a voxel-wise modeling and decoding approach to directly test the hypothesis that low-level visual features are encoded in activity generated during mental imagery of complex scenes. Using fMRI measurements of cortical activity evoked by viewing photographs, we constructed voxel-wise encoding models of tuning to low-level visual features. We also measured activity as subjects imagined previously memorized works of art. We then used the encoding models to determine if putative low-level visual features encoded in this activity could pick out the imagined artwork from among thousands of other randomly selected images. We show that mental images can be accurately identified in this way; moreover, mental image identification accuracy depends upon the degree of tuning to low-level visual features in the voxels selected for decoding. These results directly confirm the hypothesis that low-level visual features are encoded during mental imagery of complex scenes. Our work also points to novel forms of brain-machine interaction: we provide a proof-of-concept demonstration of an internet image search guided by mental imagery.

Indexed as

AdultBrain MappingHumansImaginationMagnetic Resonance ImagingPattern Recognition, VisualVisual CortexDecodingfMRIMental imageryPerceptionVisionVoxel-wise encoding models

Identifiers

PMID25451480
PMCPMC4364759

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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.