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相关论文: Graph Theoretical Analysis Reveals: Women's Brains…

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In our previous study we have shown that the female connectomes have significantly better, deep graph-theoretical parameters, related to superior "connectivity", than the connectome of the males. Since the average female brain is smaller…

神经元与认知 · 定量生物学 2015-12-04 Balázs Szalkai , Bálint Varga , Vince Grolmusz

Deep, classical graph-theoretical parameters, like the size of the minimum vertex cover, the chromatic number, or the eigengap of the adjacency matrix of the graph were studied widely by mathematicians in the last century. Most researchers…

神经元与认知 · 定量生物学 2017-09-18 Balazs Szalkai , Balint Varga , Vince Grolmusz

In mapping the human structural connectome, we are in a very fortunate situation: one can compute and compare graphs, describing the cerebral connections between the very same, anatomically identified small regions of the gray matter among…

神经元与认知 · 定量生物学 2017-12-01 Mate Fellner , Balint Varga , Vince Grolmusz

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…

神经元与认知 · 定量生物学 2020-03-19 Balázs Szalkai , Bálint Varga , Vince Grolmusz

While it is still not possible to describe the neural-level connections of the human brain, we can map the human connectome with several hundred vertices, by the application of diffusion-MRI based techniques. In these graphs, the nodes…

神经元与认知 · 定量生物学 2020-09-09 Mate Fellner , Balint Varga , Vince Grolmusz

Determining important vertices in large graphs (e.g., Google's PageRank in the case of the graph of the World Wide Web) facilitated the construction of excellent web search engines, returning the most important hits corresponding to the…

神经元与认知 · 定量生物学 2021-07-06 Laszlo Keresztes , Evelin Szogi , Balint Varga , Vince Grolmusz

In the study of the human connectome, the vertices and the edges of the network of the human brain are analyzed: the vertices of the graphs are the anatomically identified gray matter areas of the subjects; this set is exactly the same for…

神经元与认知 · 定量生物学 2018-11-26 Mate Fellner , Balint Varga , Vince Grolmusz

For more than a decade now, we can discover and study thousands of cerebral connections with the application of diffusion magnetic resonance imaging (dMRI) techniques and the accompanying algorithmic workflow. While numerous connectomical…

神经元与认知 · 定量生物学 2019-12-06 Laszlo Keresztes , Evelin Szogi , Balint Varga , Vince Grolmusz

Human braingraphs or connectomes are widely studied in the last decade to understand the structural and functional properties of our brain. In the last several years our research group has computed and deposited thousands of human…

神经元与认知 · 定量生物学 2024-12-03 Balint Varga , Vince Grolmusz

The human brain is the most complex object of study we encounter today. Mapping the neuronal-level connections between the more than 80 billion neurons in the brain is a hopeless task for science. By the recent advancement of magnetic…

神经元与认知 · 定量生物学 2020-09-01 Balint Varga , Vince Grolmusz

The connectome, a map of the structural and/or functional connections in the brain, provides a complex representation of the neurobiological phenotypes on which it supervenes. This information-rich data modality has the potential to…

Mapping the brain imaging data to networks, where each node represents a specific area of the brain, has enabled an objective graph-theoretic analysis of human connectome. However, the latent structure on higher-order connections remains…

神经元与认知 · 定量生物学 2019-04-09 Bosiljka Tadic , Miroslav Andjelkovic , Roderick Melnik

The human braingraph, or connectome is a description of the connections of the brain: the nodes of the graph correspond to small areas of the gray matter, and two nodes are connected by an edge if a diffusion MRI-based workflow finds fibers…

神经元与认知 · 定量生物学 2015-07-02 Csaba Kerepesi , Balázs Szalkai , Bálint Varga , Vince Grolmusz

Understanding the common topological characteristics of the human brain network across a population is central to understanding brain functions. The abstraction of human connectome as a graph has been pivotal in gaining insights on the…

定量方法 · 定量生物学 2023-04-26 Soumya Das , D. Vijay Anand , Moo K. Chung

There has been huge interest in studying human brain connectomes inferred from different imaging modalities and exploring their relationship with human traits, such as cognition. Brain connectomes are usually represented as networks, with…

机器学习 · 统计学 2021-09-14 Meimei Liu , Zhengwu Zhang , David B. Dunson

Based on the data of the NIH-funded Human Connectome Project, we have computed structural connectomes of 426 human subjects in five different resolutions of 83, 129, 234, 463 and 1015 nodes and several edge weights. The graphs are given in…

神经元与认知 · 定量生物学 2016-10-07 Csaba Kerepesi , Balazs Szalkai , Balint Varga , Vince Grolmusz

The human brain is a complex system, and understanding its mechanisms has been a long-standing challenge in neuroscience. The study of the functional connectome, which maps the functional connections between different brain regions, has…

神经与进化计算 · 计算机科学 2025-04-14 Tananun Songdechakraiwut , Yutong Wu

The characterisation of the brain as a "connectome", in which the connections are represented by correlational values across timeseries and as summary measures derived from graph theory analyses, has been very popular in the last years.…

机器学习 · 计算机科学 2020-03-13 Tiago Azevedo , Luca Passamonti , Pietro Liò , Nicola Toschi

Graphs are quickly emerging as a leading abstraction for the representation of data. One important application domain originates from an emerging discipline called "connectomics". Connectomics studies the brain as a graph; vertices…

The average human brain volume of the males is larger than that of the females. Several MRI voxel-based morphometry studies show that the gray matter/white matter ratio is larger in females. Here we have analyzed the recent public release…

神经元与认知 · 定量生物学 2016-04-21 Balázs Szalkai , Vince Grolmusz
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