Proceedings of the National Academy of SciencesNeurosciencePeer-reviewed journal article
Sculpting New Visual Categories into the Human Brain
Coraline Rinn IordaniD, Victoria J. H. Ritvo, Kenneth A. NormaniD, Nicholas B. Turk‐BrowneiD, Jonathan D. CoheniD
Abstract
Learning requires changing the brain. This typically occurs through experience, study, or instruction. We report a proof-of-concept for a new way for humans to acquire visual knowledge by directly sculpting activity patterns in the human brain that mirror those expected to arise through learning. We used a non-invasive technique (closed-loop real-time functional magnetic resonance imaging neurofeedback) to create new categories of visual objects in the brain, without the participants explicit awareness. After neural sculpting, participants exhibited behavioral and neural biases for the sculpted, but not for the control categories. The ability to sculpt new perceptual distinctions in the human brain offers a new paradigm for human fMRI research that allows for non-invasive, causal testing of the link between neural representations and behavior. As such, beyond its current application to perception, our work potentially has broad relevance to other domains of cognition such as decision-making, memory, and motor control. Significance StatementObjects that belong to the same category tend to elicit similar patterns of brain activity. Here we reverse this mapping and ask whether neural similarity is sufficient to induce increased perceptual discrimination and categorical perception. We do this by using real-time fMRI to modify neural representations of objects in high-level visual cortex. Participants viewed an object and received closed-loop neurofeedback that pushed them to represent the object more similarly to a brain activity pattern we chose for that category. After successfully self-modulating their brain activity, participants began to perceive objects assigned to the same brain pattern as more categorically distinct from those assigned to a different brain pattern. These findings open a new avenue for understanding and accelerating human learning.
- Citations
- 11
- FWCI
- 2.18
- Field percentile
- top 12%
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