paper-with-me

홈 › Papers

The Graph of Our Mind

2020-03-17

Graph theory in the last two decades penetrated sociology, molecular biology, genetics, chemistry, computer engineering, and numerous other fields of science. One of the more recent areas of its applications is the study of the connections of the human brain. By the development of diffusion magnetic resonance imaging (diffusion MRI), it is possible today to map the connections between the 1-1.5 cm$^2$ regions of the gray matter of the human brain. These connections can be viewed as a graph: the vertices are the anatomically identified regions of the gray matter, and two vertices are connected by an edge if the diffusion MRI-based workflow finds neuronal fiber tracts between these areas. This way we can compute 1015-vertex graphs with tens of thousands of edges. In a previous work, we have analyzed the male and female braingraphs graph-theoretically, and we have found statistically significant differences in numerous parameters between the sexes: the female braingraphs are better expanders, have more edges, larger bipartition widths, and larger vertex cover than the braingraphs of the male subjects. Our previous study has applied the data of 96 subjects; here we present a much larger study of 426 subjects. Our data source is an NIH-founded project, the "Human Connectome Project (HCP)" public data release. As a service to the community, we have also made all of the braingraphs computed by us from the HCP data publicly available at the \url{http://braingraph.org} for independent validation and further investigations.

📄 PDF Abstract BibTeX arXiv:1603.00904

Code (0)

등록된 구현이 없습니다.

Tasks

Diffusion MRISociology

Similar Papers 제목 키워드 기반

Efficient Mind-Map Generation via Sequence-to-Graph and Reinforced Graph Refinement

2021-09-06 · EMNLP 2021 11 · Mengting Hu, Honglei Guo, Shiwan Zhao, Hang Gao 외

A mind-map is a diagram that represents the central concept and key ideas in a hierarchical way. Converting plain text into a mind-map will reveal its key semantic structure and be easier to understand. Given a document,…

Sentence

GraphMind: Interactive Novelty Assessment System for Accelerating Scientific Discovery

2025-10-17 · Italo Luis da Silva, Hanqi Yan, Lin Gui, Yulan He arxiv

Large Language Models (LLMs) show strong reasoning and text generation capabilities, prompting their use in scientific literature analysis, including novelty assessment. While evaluating novelty of scientific papers is c…

Information RetrievalText Generation

RAGAT-Mind: A Multi-Granular Modeling Approach for Rumor Detection Based on MindSpore

2025-04-24 · Zhenkai Qin, Guifang Yang, Dongze Wu

As false information continues to proliferate across social media platforms, effective rumor detection has emerged as a pressing challenge in natural language processing. This paper proposes RAGAT-Mind, a multi-granular …

Mind Artist: Creating Artistic Snapshots with Human Thought

2024-01-01 · CVPR 2024 1 · Jiaxuan Chen, Yu Qi, Yueming Wang, Gang Pan

We introduce Mind Artist (MindArt) a novel and efficient neural decoding architecture to snap artistic photographs from our mind in a controllable manner. Recently progress has been made in image reconstruction with …

Graph MatchingImage ReconstructionRepresentation Learning

DGSG-Mind: Dynamic 3D Gaussian Scene Graphs for Long-Term Scene Understanding and Grounding

2026-05-28 · Luzhou Ge, Xiangyu Zhu, Jinyan Liu, Xuesong Li arxiv

Integrating open-vocabulary semantic information into dynamic 3D scene representations is essential for long-term embodied scene understanding. However, existing methods often suffer from fragile instance association due…

Semantic SegmentationMultimodal ReasoningScene UnderstandingSpatial Reasoning