Universal scale-free representations in human visual cortex
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Abstract (arXiv)
How does the human brain encode complex visual information? While previous research has characterized individual dimensions of visual representation in cortex, we still lack a comprehensive understanding of how visual information is organized across the full range of neural population activity. Here, analyzing fMRI responses to natural scenes across multiple individuals, we discover that neural representations in human visual cortex follow a remarkably consistent scale-free organization -- their variance systematically decays as a power law, detected across four orders of magnitude of latent dimensions. This scale-free structure appears consistently across multiple visual regions and across individuals, suggesting it reflects a fundamental organizing principle of visual processing. Critically, when we align neural responses across individuals using hyperalignment, we find that these representational dimensions are largely shared between people, revealing a universal high-dimensional spectrum of visual information that emerges despite individual differences in brain anatomy and visual experience. Traditional analysis approaches in cognitive neuroscience have focused primarily on a small number of high-variance dimensions, potentially missing crucial aspects of visual representation. Our results demonstrate that visual information is distributed across the full dimensionality of cortical activity in a systematic way, suggesting we need to move beyond low-dimensional characterizations to fully understand how the brain represents the visual world. This work reveals a new fundamental principle of neural coding in human visual cortex and highlights the importance of examining neural representations across their full dimensionality.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 Sep 2024.
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Citing papers per year: 2025: 3; 2026: 2.
5 papers.
- 2025Spectral Analysis of Representational Similarity with Limited Neuronscited by 2
- 2025Noninvasive precision modulation of high-level neural population activity via natural vision perturbationscited by 1
- 2025Why all roads don't lead to Rome: Representation geometry varies across the human visual cortical hierarchycited by 0
- 2026Computation-Aware Kalman Filtering with Model Selection for Neural Dynamicscited by 0
- 2026Learning reshapes power-law anisotropy in internal representationscited by 0
- 2026Learning reshapes power-law anisotropy in internal representations15 Aug 2026
- 2026Computation-Aware Kalman Filtering with Model Selection for Neural Dynamics31 May 2026
- 2025Why all roads don't lead to Rome: Representation geometry varies across the human visual cortical hierarchy16 Sep 2025
- 2025Noninvasive precision modulation of high-level neural population activity via natural vision perturbations5 Jun 2025
- 2025Spectral Analysis of Representational Similarity with Limited Neurons27 Feb 2025