High-dimensional structure underlying individual differences in naturalistic visual experience
How do different brains create unique visual experiences from identical sensory input? While neural representations vary across individuals, the fundamental architecture underlying these differences remains poorly understood. Here, we reveal that individual visual experience emerges from a high-dimensional neural geometry across the visual cortical hierarchy. Using spectral decomposition of fMRI responses during naturalistic movie viewing, we find that idiosyncratic neural patterns persist across multiple orders of magnitude of latent dimensions. Remarkably, each dimensional range encodes qualitatively distinct aspects of individual processing, and this multidimensional neural geometry predicts subsequent behavioral differences in memory recall. These fine-grained patterns of inter-individual variability cannot be reduced to those detected by conventional intersubject correlation measures. Our findings demonstrate that subjective visual experience arises from information integrated across an expansive multidimensional manifold. This geometric framework offers a powerful new lens for understanding how diverse brains construct unique perceptual worlds from shared experiences.
Code (1)
Similar Papers 제목 키워드 기반
Disentangled behavioural representations
Individual characteristics in human decision-making are often quantified by fitting a parametric cognitive model to subjects' behavior and then studying differences between them in the associated parameter space. …
Decision MakingScalable Multi-Task Gaussian Process Tensor Regression for Normative Modeling of Structured Variation in Neuroimaging Data
Most brain disorders are very heterogeneous in terms of their underlying biology and developing analysis methods to model such heterogeneity is a major challenge. A promising approach is to use probabilistic regression m…
Anomaly DetectionMulti-Task LearningData-driven brain network models predict individual variability in behavior
The relationship between brain structure and function has been probed using a variety of approaches, but how the underlying structural connectivity of the human brain drives behavior is far from understood. To investigat…
Human Preference-Based Learning for High-dimensional Optimization of Exoskeleton Walking Gaits
Optimizing lower-body exoskeleton walking gaits for user comfort requires understanding users' preferences over a high-dimensional gait parameter space. However, existing preference-based learning methods have only explo…
VA-Adapter: Adapting Ultrasound Foundation Model to Echocardiography Probe Guidance
Echocardiography is a critical tool for detecting heart diseases, yet its steep operational difficulty causes a shortage of skilled personnel. Probe guidance systems, which assist in acquiring high-quality images, offer …