TY  - JOUR
AU  - Anđelković, Miroslav
AU  - Tadić, Bosiljka
AU  - Melnik, Roderick
PY  - 2020
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/9677
AB  - Higher-order connectivity in complex systems described by simplexes of different orders provides a geometry for simplex-based dynamical variables and interactions. Simplicial complexes that constitute a functional geometry of the human connectome can be crucial for the brain complex dynamics. In this context, the best-connected brain areas, designated as hub nodes, play a central role in supporting integrated brain function. Here, we study the structure of simplicial complexes attached to eight global hubs in the female and male connectomes and identify the core networks among the affected brain regions. These eight hubs (Putamen, Caudate, Hippocampus and Thalamus-Proper in the left and right cerebral hemisphere) are the highest-ranking according to their topological dimension, defined as the number of simplexes of all orders in which the node participates. Furthermore, we analyse the weight-dependent heterogeneity of simplexes. We demonstrate changes in the structure of identified core networks and topological entropy when the threshold weight is gradually increased. These results highlight the role of higher-order interactions in human brain networks and provide additional evidence for (dis)similarity between the female and male connectomes.
T2  - Scientific Reports
T1  - The topology of higher-order complexes associated with brain hubs in human connectomes
VL  - 10
IS  - 1
SP  - 17320
DO  - 10.1038/s41598-020-74392-3
ER  - 

@article{
author = "Anđelković, Miroslav and Tadić, Bosiljka and Melnik, Roderick",
year = "2020",
abstract = "Higher-order connectivity in complex systems described by simplexes of different orders provides a geometry for simplex-based dynamical variables and interactions. Simplicial complexes that constitute a functional geometry of the human connectome can be crucial for the brain complex dynamics. In this context, the best-connected brain areas, designated as hub nodes, play a central role in supporting integrated brain function. Here, we study the structure of simplicial complexes attached to eight global hubs in the female and male connectomes and identify the core networks among the affected brain regions. These eight hubs (Putamen, Caudate, Hippocampus and Thalamus-Proper in the left and right cerebral hemisphere) are the highest-ranking according to their topological dimension, defined as the number of simplexes of all orders in which the node participates. Furthermore, we analyse the weight-dependent heterogeneity of simplexes. We demonstrate changes in the structure of identified core networks and topological entropy when the threshold weight is gradually increased. These results highlight the role of higher-order interactions in human brain networks and provide additional evidence for (dis)similarity between the female and male connectomes.",
journal = "Scientific Reports",
title = "The topology of higher-order complexes associated with brain hubs in human connectomes",
volume = "10",
number = "1",
pages = "17320",
doi = "10.1038/s41598-020-74392-3"
}

Anđelković, M., Tadić, B.,& Melnik, R.. (2020). The topology of higher-order complexes associated with brain hubs in human connectomes. in Scientific Reports, 10(1), 17320.
https://doi.org/10.1038/s41598-020-74392-3

Anđelković M, Tadić B, Melnik R. The topology of higher-order complexes associated with brain hubs in human connectomes. in Scientific Reports. 2020;10(1):17320.
doi:10.1038/s41598-020-74392-3 .

Anđelković, Miroslav, Tadić, Bosiljka, Melnik, Roderick, "The topology of higher-order complexes associated with brain hubs in human connectomes" in Scientific Reports, 10, no. 1 (2020):17320,
https://doi.org/10.1038/s41598-020-74392-3 . .

TY  - JOUR
AU  - Tadić, Bosiljka
AU  - Anđelković, Miroslav
AU  - Melnik, Roderick
PY  - 2019
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/8451
AB  - Mapping the brain imaging data to networks, where nodes represent anatomical brain regions and edges indicate the occurrence of fiber tracts between them, has enabled an objective graph-theoretic analysis of human connectomes. However, the latent structure on higher-order interactions remains unexplored, where many brain regions act in synergy to perform complex functions. Here we use the simplicial complexes description of human connectome, where the shared simplexes encode higher-order relationships between groups of nodes. We study consensus connectome of 100 female (F-connectome) and of 100 male (M-connectome) subjects that we generated from the Budapest Reference Connectome Server v3.0 based on data from the Human Connectome Project. Our analysis reveals that the functional geometry of the common F&M-connectome coincides with the M-connectome and is characterized by a complex architecture of simplexes to the 14th order, which is built in six anatomical communities, and linked by short cycles. The F-connectome has additional edges that involve different brain regions, thereby increasing the size of simplexes and introducing new cycles. Both connectomes contain characteristic subjacent graphs that make them 3/2-hyperbolic. These results shed new light on the functional architecture of the brain, suggesting that insightful differences among connectomes are hidden in their higher-order connectivity. © 2019, The Author(s).
T2  - Scientific Reports
T1  - Functional Geometry of Human Connectomes
VL  - 9
IS  - 1
SP  - 12060
DO  - 10.1038/s41598-019-48568-5
ER  - 

@article{
author = "Tadić, Bosiljka and Anđelković, Miroslav and Melnik, Roderick",
year = "2019",
abstract = "Mapping the brain imaging data to networks, where nodes represent anatomical brain regions and edges indicate the occurrence of fiber tracts between them, has enabled an objective graph-theoretic analysis of human connectomes. However, the latent structure on higher-order interactions remains unexplored, where many brain regions act in synergy to perform complex functions. Here we use the simplicial complexes description of human connectome, where the shared simplexes encode higher-order relationships between groups of nodes. We study consensus connectome of 100 female (F-connectome) and of 100 male (M-connectome) subjects that we generated from the Budapest Reference Connectome Server v3.0 based on data from the Human Connectome Project. Our analysis reveals that the functional geometry of the common F&M-connectome coincides with the M-connectome and is characterized by a complex architecture of simplexes to the 14th order, which is built in six anatomical communities, and linked by short cycles. The F-connectome has additional edges that involve different brain regions, thereby increasing the size of simplexes and introducing new cycles. Both connectomes contain characteristic subjacent graphs that make them 3/2-hyperbolic. These results shed new light on the functional architecture of the brain, suggesting that insightful differences among connectomes are hidden in their higher-order connectivity. © 2019, The Author(s).",
journal = "Scientific Reports",
title = "Functional Geometry of Human Connectomes",
volume = "9",
number = "1",
pages = "12060",
doi = "10.1038/s41598-019-48568-5"
}

Tadić, B., Anđelković, M.,& Melnik, R.. (2019). Functional Geometry of Human Connectomes. in Scientific Reports, 9(1), 12060.
https://doi.org/10.1038/s41598-019-48568-5

Tadić B, Anđelković M, Melnik R. Functional Geometry of Human Connectomes. in Scientific Reports. 2019;9(1):12060.
doi:10.1038/s41598-019-48568-5 .

Tadić, Bosiljka, Anđelković, Miroslav, Melnik, Roderick, "Functional Geometry of Human Connectomes" in Scientific Reports, 9, no. 1 (2019):12060,
https://doi.org/10.1038/s41598-019-48568-5 . .

TY  - JOUR
AU  - Anđelković, Miroslav
AU  - Tadić, Bosiljka
AU  - Mitrović Dankulov, Marija
AU  - Rajković, Milan
AU  - Melnik, Roderick
PY  - 2016
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/1085
AB  - The communication processes of knowledge creation represent a particular class of human dynamics where the expertise of individuals plays a substantial role, thus offering a unique possibility to study the structure of knowledge networks from online data. Here, we use the empirical evidence from questions-and-answers in mathematics to analyse the emergence of the network of knowledge contents (or tags) as the individual experts use them in the process. After removing extra edges from the network-associated graph, we apply the methods of algebraic topology of graphs to examine the structure of higher-order combinatorial spaces in networks for four consecutive time intervals. We find that the ranking distributions of the suitably scaled topological dimensions of nodes fall into a unique curve for all time intervals and filtering levels, suggesting a robust architecture of knowledge networks. Moreover, these networks preserve the logical structure of knowledge within emergent communities of nodes, labeled according to a standard mathematical classification scheme. Further, we investigate the appearance of new contents over time and their innovative combinations, which expand the knowledge network. In each network, we identify an innovation channel as a subgraph of triangles and larger simplices to which new tags attach. Our results show that the increasing topological complexity of the innovation channels contributes to networks architecture over different time periods, and is consistent with temporal correlations of the occurrence of new tags. The methodology applies to a wide class of data with the suitable temporal resolution and clearly identified knowledge-content units.
T2  - PLOS One
T1  - Topology of Innovation Spaces in the Knowledge Networks Emerging through Questions-And-Answers
VL  - 11
IS  - 5
DO  - 10.1371/journal.pone.0154655
ER  - 

@article{
author = "Anđelković, Miroslav and Tadić, Bosiljka and Mitrović Dankulov, Marija and Rajković, Milan and Melnik, Roderick",
year = "2016",
abstract = "The communication processes of knowledge creation represent a particular class of human dynamics where the expertise of individuals plays a substantial role, thus offering a unique possibility to study the structure of knowledge networks from online data. Here, we use the empirical evidence from questions-and-answers in mathematics to analyse the emergence of the network of knowledge contents (or tags) as the individual experts use them in the process. After removing extra edges from the network-associated graph, we apply the methods of algebraic topology of graphs to examine the structure of higher-order combinatorial spaces in networks for four consecutive time intervals. We find that the ranking distributions of the suitably scaled topological dimensions of nodes fall into a unique curve for all time intervals and filtering levels, suggesting a robust architecture of knowledge networks. Moreover, these networks preserve the logical structure of knowledge within emergent communities of nodes, labeled according to a standard mathematical classification scheme. Further, we investigate the appearance of new contents over time and their innovative combinations, which expand the knowledge network. In each network, we identify an innovation channel as a subgraph of triangles and larger simplices to which new tags attach. Our results show that the increasing topological complexity of the innovation channels contributes to networks architecture over different time periods, and is consistent with temporal correlations of the occurrence of new tags. The methodology applies to a wide class of data with the suitable temporal resolution and clearly identified knowledge-content units.",
journal = "PLOS One",
title = "Topology of Innovation Spaces in the Knowledge Networks Emerging through Questions-And-Answers",
volume = "11",
number = "5",
doi = "10.1371/journal.pone.0154655"
}

Anđelković, M., Tadić, B., Mitrović Dankulov, M., Rajković, M.,& Melnik, R.. (2016). Topology of Innovation Spaces in the Knowledge Networks Emerging through Questions-And-Answers. in PLOS One, 11(5).
https://doi.org/10.1371/journal.pone.0154655

Anđelković M, Tadić B, Mitrović Dankulov M, Rajković M, Melnik R. Topology of Innovation Spaces in the Knowledge Networks Emerging through Questions-And-Answers. in PLOS One. 2016;11(5).
doi:10.1371/journal.pone.0154655 .

Anđelković, Miroslav, Tadić, Bosiljka, Mitrović Dankulov, Marija, Rajković, Milan, Melnik, Roderick, "Topology of Innovation Spaces in the Knowledge Networks Emerging through Questions-And-Answers" in PLOS One, 11, no. 5 (2016),
https://doi.org/10.1371/journal.pone.0154655 . .

TY  - DATA
AU  - Anđelković, Miroslav
AU  - Tadić, Bosiljka
AU  - Mitrović Dankulov, Marija
AU  - Rajković, Milan
AU  - Melnik, Roderick
PY  - 2016
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/9420
AB  - Names of the first twenty tags ordered according to their topological dimension in the network of tags before filtering and after filtering at the indicated confidence level p has been performed.
T2  - PLOS One
T1  - Names of the first twenty tags ordered according to their topological dimension in the network of tags before filtering and after filtering at the indicated confidence level p has been performed
DO  - 10.1371/journal.pone.0154655.t002
ER  - 

@misc{
author = "Anđelković, Miroslav and Tadić, Bosiljka and Mitrović Dankulov, Marija and Rajković, Milan and Melnik, Roderick",
year = "2016",
abstract = "Names of the first twenty tags ordered according to their topological dimension in the network of tags before filtering and after filtering at the indicated confidence level p has been performed.",
journal = "PLOS One",
title = "Names of the first twenty tags ordered according to their topological dimension in the network of tags before filtering and after filtering at the indicated confidence level p has been performed",
doi = "10.1371/journal.pone.0154655.t002"
}

Anđelković, M., Tadić, B., Mitrović Dankulov, M., Rajković, M.,& Melnik, R.. (2016). Names of the first twenty tags ordered according to their topological dimension in the network of tags before filtering and after filtering at the indicated confidence level p has been performed. in PLOS One.
https://doi.org/10.1371/journal.pone.0154655.t002

Anđelković M, Tadić B, Mitrović Dankulov M, Rajković M, Melnik R. Names of the first twenty tags ordered according to their topological dimension in the network of tags before filtering and after filtering at the indicated confidence level p has been performed. in PLOS One. 2016;.
doi:10.1371/journal.pone.0154655.t002 .

Anđelković, Miroslav, Tadić, Bosiljka, Mitrović Dankulov, Marija, Rajković, Milan, Melnik, Roderick, "Names of the first twenty tags ordered according to their topological dimension in the network of tags before filtering and after filtering at the indicated confidence level p has been performed" in PLOS One (2016),
https://doi.org/10.1371/journal.pone.0154655.t002 . .

TY  - DATA
AU  - Anđelković, Miroslav
AU  - Tadić, Bosiljka
AU  - Mitrović Dankulov, Marija
AU  - Rajković, Milan
AU  - Melnik, Roderick
PY  - 2016
UR  - https://vinar.vin.bg.ac.rs/handle/123456789/9421
AB  - The graph-level measures for tags networks for four consecutive periods, filtered at confidence p = 0.1
T2  - PLOS One
T1  - The graph-level measures for tags networks for four consecutive periods, filtered at confidence p = 0.1
DO  - 10.1371/journal.pone.0154655.t001
ER  - 

@misc{
author = "Anđelković, Miroslav and Tadić, Bosiljka and Mitrović Dankulov, Marija and Rajković, Milan and Melnik, Roderick",
year = "2016",
abstract = "The graph-level measures for tags networks for four consecutive periods, filtered at confidence p = 0.1",
journal = "PLOS One",
title = "The graph-level measures for tags networks for four consecutive periods, filtered at confidence p = 0.1",
doi = "10.1371/journal.pone.0154655.t001"
}

Anđelković, M., Tadić, B., Mitrović Dankulov, M., Rajković, M.,& Melnik, R.. (2016). The graph-level measures for tags networks for four consecutive periods, filtered at confidence p = 0.1. in PLOS One.
https://doi.org/10.1371/journal.pone.0154655.t001

Anđelković M, Tadić B, Mitrović Dankulov M, Rajković M, Melnik R. The graph-level measures for tags networks for four consecutive periods, filtered at confidence p = 0.1. in PLOS One. 2016;.
doi:10.1371/journal.pone.0154655.t001 .

Anđelković, Miroslav, Tadić, Bosiljka, Mitrović Dankulov, Marija, Rajković, Milan, Melnik, Roderick, "The graph-level measures for tags networks for four consecutive periods, filtered at confidence p = 0.1" in PLOS One (2016),
https://doi.org/10.1371/journal.pone.0154655.t001 . .