A new study published on arXiv analyzes sex-based differences in brain connectomes using the Krakencoder framework. Researchers examined structural and functional connectomes from 702 participants in the Human Connectome Project, assessing the impact of removing individual Yeo-7 functional networks. The Default Mode Network caused the largest perturbations, while the Somatomotor network had the smallest effect. While sex-specific information in predicted connectomes was subtle, full predicted connectomes retained significantly more sex-discriminative information (up to 84.76% accuracy) compared to perturbation-derived signatures alone (66.09% accuracy). AI
RANK_REASON The cluster contains a research paper published on arXiv detailing a novel analysis method and findings.
- default mode network
- Frobenius norm
- Human Connectome Project
- Krakencoder
- Kullback–Leibler divergence
- Somatomotor network
- Wasserstein metric
- Yeo-7 functional networks
AI-generated summary · Google Gemini · from 2 sources. How we write summaries →
