Article

Hyperface: a naturalistic fMRI dataset for investigating human face processing

2026-03-13

Abstract excerpt

Faces convey information that guides social behavior, yet neuroimaging studies investigating human face processing typically use static images with small sets of identities under artificial conditions. Controlled designs limit our ability to characterize human face processing under naturalistic conditions or test whether computational models generalize beyond the laboratory. To address this gap, here we release h...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: ef94eb84-4507-5d65-9dc9-d1b6ae99bdfd
DOI: 10.64898/2026.03.11.711073

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Hyperface: a naturalistic fMRI dataset for investigating human face processingDOI 10.64898/2026.03.11.711073Read

Multi-Task Faces (MTF) Data Set: A Legally and Ethically Compliant Collection of Face Images for Various Classification TasksSemantic proximity Read

A novel 4D fMRI clustering technique to examine event-related spatiotemporal dynamics of face processing in naturalistic stimuliSemantic proximity Read

Diffusion-based stimulus optimization reveals functional organization across higher visual cortexSemantic proximity Read

View, engage, predict: enhancing brain-behavior mapping with naturalistic movie-watching fMRISemantic proximity Read

Task demands dynamically structure feature selection, routing, and integration in the human brainSemantic proximity Read

Deep learning algorithms reveal a new visual-semantic representation of familiar faces in human perception and memorySemantic proximity Read

Adjudicating between face-coding models with individual-face fMRI responsesSemantic proximity Read

Video-evoked fMRI BOLD responses are highly consistent across different data acquisition sitesSemantic proximity Read

Diverse Visual Experience Promotes Integrated and Human-Aligned Face Representations in Deep Neural NetworksSemantic proximity Read

Face recognition depends on specialized mechanisms tuned to view-invariant facial features: Insights from deep neural networks optimized for face or object recognitionSemantic proximity Read

Humans and marmosets share similar face recognition signatures in shape-based visual face discrimination behaviorSemantic proximity Read

Similarity judgments and cortical visual responses reflect different properties of object and scene categories in naturalistic imagesSemantic proximity Read