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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…

Neurons and Cognition · Quantitative Biology 2020-09-01 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…

Neurons and Cognition · Quantitative Biology 2024-12-03 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…

Neurons and Cognition · Quantitative Biology 2019-12-06 Laszlo Keresztes , Evelin Szogi , 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…

Neurons and Cognition · Quantitative Biology 2017-12-01 Mate Fellner , Balint Varga , Vince Grolmusz

The connectomes of different human brains are pairwise distinct: we cannot talk about an abstract "graph of the brain". Two typical connectomes, however, have quite a few common graph edges that may describe the same connections between the…

Neurons and Cognition · Quantitative Biology 2015-01-07 Balazs Szalkai , Csaba Kerepesi , Balint 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…

Neurons and Cognition · Quantitative Biology 2020-09-09 Mate Fellner , Balint Varga , Vince Grolmusz

Connections of the living human brain, on a macroscopic scale, can be mapped by a diffusion MR imaging based workflow. Since the same anatomic regions can be corresponded between distinct brains, one can compare the presence or the absence…

Neurons and Cognition · Quantitative Biology 2016-02-16 Balázs Szalkai , Csaba Kerepesi , Bálint Varga , Vince Grolmusz

Here we show a method of directing the edges of the connectomes, prepared from diffusion tensor imaging (DTI) datasets from the human brain. Before the present work, no high-definition directed braingraphs (or connectomes) were published,…

Neurons and Cognition · Quantitative Biology 2016-09-29 Balázs Szalkai , Csaba Kerepesi , Bálint Varga , Vince Grolmusz

Deep graph-theoretic ideas in the context with the graph of the World Wide Web led to the definition of Google's PageRank and the subsequent rise of the most-popular search engine to date. Brain graphs, or connectomes, are being widely…

Neurons and Cognition · Quantitative Biology 2016-02-17 Balazs Szalkai , Balint Varga , Vince Grolmusz

Currently, connectomes (e.g., functional or structural brain graphs) can be estimated in humans at $\approx 1~mm^3$ scale using a combination of diffusion weighted magnetic resonance imaging, functional magnetic resonance imaging and…

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…

The human connectome has become the very frequent subject of study of brain-scientists, psychologists, and imaging experts in the last decade. With diffusion magnetic resonance imaging techniques, unified with advanced data processing…

Neurons and Cognition · Quantitative Biology 2019-07-24 Mate Fellner , Balint Varga , Vince Grolmusz

The underlying anatomical structure is fundamental to the study of brain networks, but the role of brainstem from a structural perspective is not very well understood. We conduct a computational and graph-theoretical study of the human…

Neurons and Cognition · Quantitative Biology 2023-04-26 Salma Salhi , Youssef Kora , Gisu Ham , Hadi Zadeh Haghighi , Christoph Simon

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…

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…

Neurons and Cognition · Quantitative Biology 2020-03-19 Balázs Szalkai , Bálint Varga , Vince Grolmusz

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…

Neurons and Cognition · Quantitative Biology 2015-07-02 Csaba Kerepesi , 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…

Neurons and Cognition · Quantitative Biology 2017-09-18 Balazs Szalkai , Balint Varga , Vince Grolmusz

Human brain connectome studies aim at extracting and analyzing relevant features associated to pathologies of interest. Usually this consists in modeling the brain connectome as a graph and in using graph metrics as features. A fine brain…

Neurons and Cognition · Quantitative Biology 2020-05-04 Félix Renard , Christian Heinrich , Marine Bouthillon , Maleka Schenck , Francis Schneider , Stéphane Kremer , Sophie Achard

The human brain is a complex network comprised of functionally and anatomically interconnected brain regions. A growing number of studies have suggested that empirical estimates of brain networks may be useful for discovery of biomarkers of…

Neurons and Cognition · Quantitative Biology 2022-11-15 Andrew Hannum , Mario A. Lopez , Saúl A. Blanco , Richard F. Betzel

We tackle classification based on brain connectivity derived from diffusion magnetic resonance images. We propose a machine-learning model inspired by graph convolutional networks (GCNs), which takes a brain connectivity input graph and…

Neurons and Cognition · Quantitative Biology 2023-09-21 Anees Kazi , Jocelyn Mora , Bruce Fischl , Adrian V. Dalca , Iman Aganj
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