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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
Herbert A., Cherednichenko O., Lybrand T. et al., International Journal of Molecular Sciences 2025 Vol. 26 No. 6 Article 2422
The double-stranded RNA editing enzyme ADAR1 connects two forms of genetic programming, one based on codons and the other on flipons. ADAR1 recodes codons in pre-mRNA by deaminating adenosine to form inosine, which is translated as guanosine. ADAR1 also plays essential roles in the immune defense against viruses and cancers by recognizing left-handed Z-DNA and ...
Added: June 22, 2026
Калужский печатный двор, 2026.
Conference Proceedings INTERNATIONAL CONFERENCE
“Mathematical Ideas of Academician
P.L. Chebyshev, Their Applications in Natural
Sciences and Artificial Intelligence Technologies”
dedicated to the 205th anniversary of his birth ...
Added: June 20, 2026
Джанбекова А. Р., Shvedov A. S., Математическое моделирование 2026 Т. 38 № 3 С. 159–176
Boundary value problems for the Black–Scholes partial differential equation, which describes the value of a financial instrument, may contain a free boundary condition if the financial instrument allows for early exercise. This article considers free boundary value problems for the Black–Scholes equation and the convection diffusion equation. For the convection diffusion equation, a finite difference ...
Added: June 20, 2026
Stognieva O., Чеснокова Н. Е., Отечественная и зарубежная педагогика 2026 Т. 1 № 3 (115) С. 123–131
Integration of generative artificial intelligence tools into educational practice highlights the need for pedagogically grounded approaches to their use in the creation of educational video content, which is increasingly applied in language and professionally oriented instruction.
The purpose of this article is to conduct a comparative analysis of educational video content created using generative AI tools ...
Added: June 20, 2026
Buryak A., Tessler R., Troshkin M., Journal of Geometry and Physics 2026 Vol. 223 Article 105783
We give a natural definition of open Hurwitz numbers, where the weight of each ramified covering includes an integer parameter N taken to the power that is equal to the number of boundary components of a Riemann surface with boundary mapping to . We prove that the resulting sequence of partition functions, depending on , is a tau-sequence of ...
Added: June 19, 2026
Buryak A., Rossi P., Communications in Mathematical Physics 2025 Vol. 406 Article 205
Of the two approaches to integrable systems associated to semisimple cohomological field theories (CohFTs), the one suggested by Dubrovin and Zhang and the more recent one using the geometry of the double ramification (DR) cycle, the second has the advantage of being very explicit. The Poisson operator of the DR hierarchy is , where is the metric ...
Added: June 19, 2026
Cherednichenko O., Herbert A., Poptsova M., Computational and Structural Biotechnology Journal 2025 Vol. 27 P. 992–1000
Large language models (LLMs) in genomics have successfully predicted various functional genomic elements. While their performance is typically evaluated using genomic benchmark datasets, it remains unclear which LLM is best suited for specific downstream tasks, particularly for generating whole-genome annotations. Current LLMs in genomics fall into three main categories: transformer-based models, long convolution-based models, and state-space models ...
Added: June 19, 2026
Poptsova M., Briefings in Bioinformatics 2025 Vol. 26 No. 2 P. 1–11
Kolmogorov–Arnold networks (KANs) emerged as a promising alternative for multilayer perceptrons (MLPs) in dense fully connected networks. Multiple attempts have been made to integrate KANs into various deep learning architectures in the domains of computer vision and natural language processing. Integrating KANs into deep learning models for genomic tasks has not been explored. Here, we ...
Added: June 19, 2026
Анненков А. Н., Nesterov R., Моделирование и анализ информационных систем 2026 Т. 33 № 2 С. 176–205
Declarative process models are widely used in process mining to describe flexible process behavior through sets of constraints. However, models discovered automatically from event logs may contain inconsistent constraints, which can make them difficult to interpret and unusable for execution, conformance checking, or further analysis. Existing methods for consistency analysis either rely on automata-based constructions ...
Added: June 18, 2026
Cham: Springer Publishing Company, 2026.
The four-volume set LNCS 16483-16486 constitutes the refereed conference proceedings of the 48th European Conference on Information Retrieval, ECIR 2026, held in Delft, The Netherlands, during March 29–April 2, 2026.
The 46 full papers and 37 short papers presented together with 10 findings papers, 9 reproducibility papers, 17 resource papers, 11 workshop papers, 7 tutorial papers, ...
Added: June 18, 2026
Poddiakov A., Троицкий вариант. Наука 2026 № 12 С. 24–25
В научно-популярной заметке представлен обзор содержания поста филдсовского медалиста Тимоти Гауэрса о возможностях ИИ в математике и содержания комментариев под постом. Обзор сделан в основном чат-ботом DeepSeek. В заключение обсуждается возможность не только решения задач искусственным интеллектом, но и их постановки. ...
Added: June 18, 2026
Minnigulova A., Dragoy O., Arutiunian V., European Child and Adolescent Psychiatry 2026
Communication deficits in Autism Spectrum Disorder (ASD) involve impairments in both verbal and nonverbal domains, potentially associated with altered brain network connectivity related to language, attention, and social cognition systems. This study investigated functional connectivity patterns among the Default Mode Network (DMN), Salience Network (SN), Dorsal Attention Network (DAN), and Language Network (LN) in male children ...
Added: June 18, 2026
Beznosikov A., Kormakov G., Grigorievskiy A. et al., Journal of Optimization Theory and Applications 2026 Vol. 209 Article 18
The objective of Vertical Federated Learning (VFL) is to collectively train a model using features available on different devices while sharing the same users. This paper focuses on the saddle point reformulation of the VFL problem via the classical Lagrangian function. We first demonstrate how this formulation can be solved using deterministic methods.More importantly, we explore various stochastic modifications to ...
Added: June 17, 2026
Garzón J., Mora Rodríguez J., Moreno-Franco H. A., Applied Mathematics and Optimization 2026 Vol. 94 No. 10 P. 1–43
We study an optimal extraction problem where the agent’s actions in the spot market exert an additive proportional negative impact on the commodity price. The commodity price dynamics, prior to any activity by the agent, evolve according to a drifted Brownian motion with jumps. The agent’s primary aim is to identify an optimal extraction strategy ...
Added: June 17, 2026
Chertenkov V. I., Shchur L., Lobachevskii Journal of Mathematics 2026 Vol. 47 No. 2 P. 720–727
Supervised machine learning is successfully applied to the study of critical phenomena and allows us to obtain a numerical estimate of the phase transition temperature and the correlation length exponent. We discuss the influence of possible systematic errors, as well as statistical errors, on the accuracy of such numerical estimates. Errors in the training and ...
Added: June 16, 2026
Deeb B., Andrey V. Savchenko, Makarov I., IEEE Access 2026 Vol. 13 P. 56283–56295
Speech Emotion Recognition has gained considerable attention in speech processing and machine learning due to its potential applications in human-computer interaction, mental health monitoring, and customer service. However, state-of-the-art models for speech emotion recognition use many parameters, which leads to computational complexity. In this paper, we introduce a novel deep-learning model to enhance the accuracy ...
Added: June 16, 2026
Makarov N., Savchenko A., Zemtsova I. et al., Scientific Reports 2025 Vol. 15 Article 26641
The grey wolf (Canis lupus) is a pivotal species for ecological studies. As a key participant in ecosystem
processes, it also serves as a model for investigating social structure formation and ecological
adaptation. However, the species’ complex social behavior, spatial dynamics, and expansive habitats
make monitoring and population assessments across large areas particularly challenging. In recent
years, audio traps ...
Added: June 16, 2026
Vasilev R., Savchenko A., Blinov P. et al., Frontiers in Medicine 2026 Vol. 13
Automated disease screening systems face challenges when applied to multi-class medical image analysis, particularly under severe class imbalance inherent in clinical datasets. Retinal fundus imaging enables non-invasive screening for multiple ocular and systemic diseases simultaneously, yet current automated systems typically assess risk for only a single pathology or a limited disease range. We developed a ...
Added: June 16, 2026
Novopoltsev M., Tulenkov A., Murtazin R. et al., IEEE Access 2025 Vol. 13 P. 188170–188181
Video-based Isolated Sign Language Recognition (ISLR) problem presents significant challenges in scaling across diverse languages due to data scarcity and the computational costs associated with training of language-specific models. In this paper, we introduce a novel training pipeline that leverages self-supervised learning on a large-scale sign language dataset. To obtain the foundation model, we utilize ...
Added: June 16, 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