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Record W4410632917 · doi:10.1101/2025.05.23.25328072

Visual Mental Imagery and Aphantasia Lesions Map onto a Convergent Brain Network

2025· preprint· en· W4410632917 on OpenAlexaff
Julian Kutsche, Calvin Howard, William Drew, Matthias Michel, Alexander L. Cohen, Michael Fox, Isaiah Kletenik

Bibliographic record

VenuemedRxiv · 2025
Typepreprint
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsColumbia College
Fundersnot available
KeywordsMental imagePsychologyCartographyArtificial intelligenceCognitive psychologyNeuroscienceComputer scienceGeographyCognition

Abstract

fetched live from OpenAlex

Abstract Background Visual mental imagery, the ability to volitionally form perceptual representations without corresponding external stimuli, allows reliving of past events, solving problems and imagining the future. The absence of visual mental imagery, called aphantasia, has recently been recognized to occur in about 1% of the general population but the cause is uncertain. By studying rare cases of acquired aphantasia we can identify regions that when injured cause loss of visual mental imagery. Methods We analyzed aphantasia lesions, identified from case reports by systematic review, and previously studied control lesions causing other neuropsychiatric symptoms (n=887). The network of brain regions connected to each lesion location was computed using resting-state functional connectivity from healthy subjects (n=1000). First, we tested the connectivity of aphantasia lesions and controls to the fusiform imagery node , a region in the ventral visual pathway which is active during visual mental imagery tasks. Then, we performed a data-driven analysis assessing whole brain lesion connectivity that was sensitive (100% overlap) and specific (family-wise error p<0.05) for aphantasia. Finally, we compared our aphantasia lesion network to activations previously associated with visual mental imagery tasks. Results We identified 12 cases of lesion-induced aphantasia which occurred in multiple different brain regions. However, 100% of these lesion locations were functionally connected to a region in the left fusiform gyrus, recently termed the fusiform imagery node . Connectivity to this region was both sensitive (100% overlap) and specific (family-wise error p<0.05) for aphantasia. The aphantasia lesion network aligned with functional connections previously associated with visual mental imagery tasks. Conclusions and Relevance Lesions causing aphantasia are located in many different brain regions but are all functionally connected to a specific location in the left fusiform gyrus. These findings support the hypothesis that the fusiform imagery node is a key brain region involved in visual mental imagery and offers clinical insight into which locations of brain injury are likely to cause aphantasia.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.046
GPT teacher head0.330
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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