?
Blurred Magnitude Homology of Functional Connectome for ASD Diagnosis
Frontiers in Psychiatry. 2026. Vol. 16. Article 1677282.
Autism spectrum disorder (ASD) is one of the most common neurodevelopmental disorders. Existing studies show that adults with ASD may experience accelerated or altered neurocognitive aging. Consequently, cognitive decline in people with ASD can be delayed if timely measures are taken to treat this disorder. This study focuses on the development of a new algorithm for the early prediction of ASD from fMRI images. Autism spectrum disorder alters functional connectivity between brain regions. Therefore, it is important to develop methods for diagnosing this condition based on the analysis of a brain network. Functional brain networks are usually studied using undirected correlations, while functional connections in the brain are inherently directed. Blurred magnitude homology is an algebro-topological tool that enables the analysis of directed graphs, including directed functional connectomes. The method proposed in this work is based on applying a fully connected neural network to blurred magnitude homology-based features of a directed functional connectivity network. Experiments on empirically derived connectomes from fMRI images show that blurred magnitude homology is a useful invariant for distinguishing directed brain networks of individuals with ASD and typically developing individuals.
Language:
English
Pilé I., Shchur L., Deng Y., Physical Review B: Condensed Matter and Materials Physics 2026 Vol. 114 Article 014101
We investigate the spatial overlap of successive spin configurations in Markov chain Monte Carlo simulations using the local Metropolis algorithm and the Swendsen-Wang and Wolff cluster algorithms. We examine the dynamics of these algorithms for models in different universality classes: Ising model, Potts model with three components, and four-state Potts model. The overlap of two ...
Added: July 6, 2026
Irkutsk: ISDCT SB RAS, 2026.
We study a model problem on the filtration of a conducting fluid through a
porous layer. A porous medium is presented as an assemblage of identical spherical
cells. Each cell consists of a porous core and liquid shell. We derive apriori estimates
for flow characteristics which show the specific behavior of the fluid. Our estimates
are validated numerically. ...
Added: July 5, 2026
М.: Наука и технологии, 2026.
«Телекоммуникации» ежемесячный рецензируемый производственный, информационно-аналитический и учебно-методический журнал выходит в свет с июля 2000 г.
Для руководителей и работников промышленности, научно-исследовательских и проектно-конструкторских институтов, высших учебных заведений, аспирантов и студентов, а также для специалистов, разрабатывающих, выпускающих и эксплуатирующих средства телекоммуникаций.
Новости разработок и производства, прогнозы развития, защита информации, Нормативные, справочные, аналитические и учебно-методические материалы.
Переход к глобальному информационному ...
Added: July 4, 2026
МФТИ, 2025.
абота редакции научного журнала «Труды Московского физико-технического института» (кратко «Труды МФТИ»), редакционной коллегии и редакционного совета осуществляется в соответствии с Положением, утвержденным ректором института. В состав редакционной коллегии входят руководители института, факультетов, институтских и факультетских кафедр. Главный редактор журнала —президент МФТИ, член-корр. РАН Кудрявцев Н.Н.
Журнал «Труды МФТИ» входит в базу данных РИНЦ (Российский Индекс Научного Цитирования) и доступен в электронной ...
Added: July 4, 2026
Hualin M., Jie Z., Jerome Y. et al., Journal of Internet Technology 2026 Vol. 27 No. 3 P. 367–382
In open, interference-prone scenarios, the scarcity of precisely annotated signal samples limits the application of deep learning–based modulation identification, which generally relies on extensive labeled data for stability. Relation Networks, as an emerging class of deep learning models, exhibit rapid convergence in few-shot learning tasks. Motivated by the fast convergence property of relation-based learning and ...
Added: July 3, 2026
Osipov D., Информационно-управляющие системы 2026 № 3 С. 49–62
Introduction: In many communication systems under construction and those to be created power control and channel estimation techniques developed for the previous generation communication systems fail to provide desired precision. One way to solve this problem is to use order-statistics-based reception techniques that do not need channel estimation or power control. To ensure the desired ...
Added: July 3, 2026
Springer, 2026.
This book presents established and new research on the close connections between graph games and systems of logic, particularly existing and newly designed modal logics. The volume utilizes two graph games – the sabotage game and the hide-and-seek game – to demonstrate the natural interplay between designing new graph games and exploring new kinds of ...
Added: June 30, 2026
Pochinka O., Barinova M., Journal of Geometry and Physics 2026 Vol. 228 P. 1–8
In the present paper we consider an Ω-stable 3-diffeomorphism with a solid or thickened surfaced non-trivial basic set. Such basic sets include, for instance, all one-dimensional expanding attractors and those two-dimensional basic sets that are not expanding. We prove that the chain recurrent set of every such a diffeomorphism necessarily contains at least two non-trivial ...
Added: June 30, 2026
German O., Illarionov A., Известия РАН. Серия математическая 2026 Т. 90 № 3 С. 3–18
Пусть симплекс с целочисленными вершинами - содержащий ровно одну целочисленную точку, отличную от своих вершин. В работе доказывается, что если точка находится во внутренности симплекса или в относительной внутренности некоторой гиперграни симплекса, то объем симплекса ограничен величиной, зависящей только от размерности, в противном случае объем симплекса может быть сколь угодно большим. Этот результат применяется для вывода асимптотической формулы для среднего числа вершин полиэдров ...
Added: June 29, 2026
Netherlands: ScienceDirect, 2025.
No ...
Added: June 28, 2026
Vasilii A. Gromov, Dang Q. N., Asel S. Erbolova, Complexity 2025 Vol. 2025 No. 1 Article 9659172
The present paper employs topological data analysis methods to reveal ‘holes’ (stable persistent homologies) in the semantic spaces of words, bigrams, and trigrams of the English and Russian languages, and to ascertain their boundaries. Furthermore, the paper selects those holes that belong to the large‐scale (coarse‐grained) structure of the language that are not just local ...
Added: November 11, 2025
Абрамов А. С., Chernyshev V. L., Mikhaylets E. et al., / Series Social Science Research Network "Social Science Research Network". 2025.
Computer vision is one of the most relevant modern research areas with broad practical applications. However, traditional solutions based on deep learning have signicant limitations and can be misleading. Topological data analysis, on the other hand, is a modern approach to solving similar problems using mathematically deterministic methods of algebraic topology that reduce the risk ...
Added: September 23, 2025
Vallverdú J., Alshanskaia E., BioNanoScience 2025 Vol. 15 Article 406
Artificial intelligence (AI) systems have predominantly mirrored neurotypical brain architectures (NBA), optimizing for efficiency, predictability, and standardized cognitive patterns. However, non-neurotypical brains (NNB) exhibit unique neurochemical, hormonal, and functional mechanisms that underpin divergent thinking, creativity, and alternative problem-solving strategies. Drawing from evolutionary biology, we emphasize how neurodiversity serves as a critical mechanism for adaptability, survival, ...
Added: June 14, 2025
Kudrjashov S., Karpik O., Klyshinskiy E., , in: Analysis of Images, Social Networks and Texts, 12th International Conference, AIST 2024, Bishkek, Kyrgyzstan, October 17–19, 2024, Revised Selected PapersVol. 15419.: Springer, 2024. P. 120–130.
Added: May 29, 2025
Sergei Kudriashov, Veronika Zykova, Stepanova A. et al., , in: Advances in Neural Computation, Machine Learning, and Cognitive Research VIII, Selected Papers from the XXVI International Conference on Neuroinformatics, October 21-25, 2024, Moscow, RussiaVol. VIII.: Cham: Springer, 2024. P. 13–22.
The interpretation of deep learning models is a rapidly growing field,
with particular interest in language models. There are various approaches to this
task, including training simpler models to replicate neural network predictions and
analyzing the latent space of the model. The latter method allows us to not only
identify patterns in the model’s decision-making process, but also understand ...
Added: October 24, 2024
Vasilii A. Gromov, Nikita S. Borodin, Asel S. Yerbolova, Complexity 2024 Vol. 2024 No. 1 Article 8863360
Te present paper introduces a novel object of study, a language fractal structure; we hypothesize that a set of embeddings of all n-grams of a natural language constitutes a representative sample of this fractal set. (We use the term Hailonakea to refer to the sum total of all language fractal structures, over all n). Te ...
Added: June 29, 2024
Cherniavskii D., Tulchinskii E., Mikhailov V. et al., , in: Findings of the Association for Computational Linguistics: EMNLP 2022.: Association for Computational Linguistics, 2022. Ch. 7 P. 88–107.
Added: February 17, 2023
Sorokin K., Ayzenberg A., Анохин К. В. et al., / Series Computer Science "arxiv.org". 2022.
In present paper we test different approaches to reconstructing the topology of the physical space from neural activity data in A1 fields of mice brains, in particular, having a Cognitome-focused approach in mind. Animals were placed in different new environments and discovered them while their physical and neural activity was recorded. We discuss possible approaches ...
Added: November 17, 2022
Magai German, Ayzenberg A., / Series CS "https://arxiv.org/". 2022.
Despite significant advances in the field of deep learning in applications to various fields, explaining the inner processes of deep learning models remains an important and open question. The purpose of this article is to describe and substantiate the geometric and topological view of the learning process of neural networks. Our attention is focused on ...
Added: November 14, 2022
Frontiers Media S.A., 2022.
We are excited to present the proceedings of the 6th Human Brain Project Student Conference on Interdisciplinary Brain Research, an open forum for exchange of knowledge within and across the various research fields addressed by the Human Brain Project (HBP). The conference was organized by young researchers for young researchers, as a virtual meeting for ...
Added: September 30, 2022
Sorokin K., Ayzenberg A., / Series arXiv "math". 2022.
In this paper we prove that there exists an asymptotical diagonalization algorithm for a class of sparse Hermitian (or real symmetric) matrices if and only if the matrices become Hessenberg matrices after some permutation of rows and columns. The proof is based on Morse theory, Roberts’ theorem on indifference graphs, toric topology, and computer-based homological ...
Added: September 22, 2022
Society of Photo-Optical Instrumentation Engineers, 2020.
The paper will provide examples of computer vision tasks in which topological data analysis gave new effective solutions. Ideas underlying topological data analysis and its basic methods will be briefly described and illustrated with examples of computer vision problems. No prior knowledge in topological data analysis and computational geometry is assumed, a brief introduction to ...
Added: October 14, 2021
IEEE, 2021.
The increasing use of eye tracking in modern cognitive and clinical psychology, neuroscience, and ophthalmology requires new methods of objective quantitative analysis of complex eye movement data. In the current work, topological data analysis (TDA) is used to extract a new type of features of eye movements to differentiate between two eye movements groups, obtained ...
Added: October 14, 2021