Research Article
Characterizing Epilepsy-Related EEG Frequency Patterns Using Self-Organizing Maps
Hazem Doufesh*
Issue:
Volume 14, Issue 3, September 2026
Pages:
60-67
Received:
29 June 2026
Accepted:
10 July 2026
Published:
28 July 2026
Abstract: Understanding the effects of epilepsy on oscillatory dynamics in the human brain is essential to improve the neurophysiological characterization of epileptic disorders. Self-Organizing Map (SOM) is an unsupervised artificial neural network technique that provides a powerful tool to visualize and explore complex high-dimensional EEG data without the need for predefined diagnostic labels. Thirty patients with confirmed epilepsy underwent continuous EEG recording using a computer-based data acquisition system (Nicolet NicVue). Electrode data were recorded from four scalp locations frontal (F3), central (C3), parietal (P3), and occipital (O1). Power spectral density was calculated using Fast Fourier Transform to extract the five canonical EEG frequency bands: delta, theta, alpha, beta, and gamma. Four SOM maps were trained and optimized, and correlation patterns between epileptic brain activity and each frequency band were identified through U-matrix visualization and component plane analysis. The visualized results indicated that the theta band showed the strongest positive correlation with epileptic activity, while the delta band exhibited the weakest association. Notably, no significant correlation with epilepsy was found for the alpha, beta and gamma bands at any of the recorded electrode sites. The SOM based analysis offers an interpretable and computationally efficient framework for exploring associations of EEG frequency bands in epilepsy. Consistent increase in theta-band activity across cortical regions supports its role as a candidate neurophysiological marker of epileptic brain states.
Abstract: Understanding the effects of epilepsy on oscillatory dynamics in the human brain is essential to improve the neurophysiological characterization of epileptic disorders. Self-Organizing Map (SOM) is an unsupervised artificial neural network technique that provides a powerful tool to visualize and explore complex high-dimensional EEG data without the...
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Research Article
Systematic Genome-wide Identification and Analysis of Alternative Splicing in the Pathogenic Fungus Talaromyces marneffei
Xiangjia Min*,
Tanya Pai Dhungat,
Theoni Kasamias,
Chester Cooper
Issue:
Volume 14, Issue 3, September 2026
Pages:
68-77
Received:
27 June 2026
Accepted:
24 July 2026
Published:
26 August 2026
DOI:
10.11648/j.ijbse.20261403.12
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Abstract: Talaromyces marneffei, a thermally dimorphic saprophytic fungus, causes talaromycosis in immunocompromised patients. Differential gene expressions determine the morphology of this species at different growing temperatures. It is known that alternative splicing (AS) is common in eukaryotes, including fungal species, however, there is not a systematic AS analysis yet in T. marneffei. We collected over 2.3 billion paired RNA-sequencing reads and mapped these reads to the reference genome. A total of 36,769 AS events, including 3,512 alternative acceptor sites, 2,216 alternative donor site, 219 exon skipping, 12,442 intron retention, and 18,380 other events were identified by the genome-wide mapping analysis. These AS events were identified from 1,734 protein-coding gene models and 752 newly identified genomic loci, including 46 genes encoding carbohydrate active enzymes. The AS rate was estimated to be ~19.8%. A total of 46,249 unique RNA transcripts were assembled and 45,296 polypeptides were predicted and functionally annotated. Preliminary analysis using data collected from samples grown at 25°C and 37°C or in dimorphic transitions by switching temperatures identified treatment specific events, suggesting that AS may play some roles in establishing specific morphological characteristics in this species. The data collected in the work, including RNA-seq data mapping information, assembled RNA transcripts, identified AS events, and new genomic loci, provide a solid resource for further investigation of the gene regulations in the dimorphism of T. marneffei.
Abstract: Talaromyces marneffei, a thermally dimorphic saprophytic fungus, causes talaromycosis in immunocompromised patients. Differential gene expressions determine the morphology of this species at different growing temperatures. It is known that alternative splicing (AS) is common in eukaryotes, including fungal species, however, there is not a systemati...
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