Biology subjects

Aksenov, A.

Publications and source records attributed to Aksenov, A..

7 recordsLinked to original sources

bioRxiv2023

Cortical Adaptation Mechanism in the Delta Band of Post-Stroke Aphasic subjects during Naming Task

AO_SCPLOWBSTRACTC_SCPLOWThis study explores differences in spatiotemporal cortical dynamics between five people with chronic post-stroke aphasia and five healthy subjects. Electroencephalography was recorded during picture naming in both groups. Frequency-specific Global Field Power (GFP) results showed that the delta band has higher power to discriminate between healthy subjects and people with aphasia (PWA) than theta and alpha bands. EEG topologies computed at the time of GFP peaks in the delta band revealed strong activation oscillating between posterior and anterior areas in PWA. On the other hand, EEG topologies from healthy subjects were variable. Then, Spatial ERP (S-ERP) were developed to add spatial resolution to classical ERP analysis. S-ERP and associated analyses confirmed the previously observed oscillatory pattern in the delta frequency band among PWA during picture naming. This oscillating pattern was alternating between occipital and prefrontal areas with almost opposite phases, a characteristic not observed in healthy subjects. In addition, all PWA performed well on the picture naming task, suggesting that this oscillating pattern may be a cortical adaptation mechanism enabling them to succeed. The observation of large-scale oscillating delta activity across the scalp in all post-stroke subjects who have substantially recovered from aphasia holds the potential to inspire innovative rehabilitation methods employing non-invasive brain stimulation techniques such as transcranial alternating current stimulation (tACS).

neuroscience↗

bioRxiv2023

Investigating Spatiotemporal Dynamics of Cortical Activity During Language Production in the Healthy and Lesioned Brain

Efficient language production requires rapid interactions between different brain areas. These interactions can be severely affected by brain lesions. However, the neurophysiological correlates of the spatiotemporal dynamics during language production are not well understood. The current pilot study explores differences in spatiotemporal cortical dynamics between five subjects with post-stroke aphasia and five control subjects. Electroencephalography was recorded during picture naming in both groups. Average-based analyses (event-related potential (ERP), frequency-specific Global Field Power (GFP)), reveal a strong synchronization of cortical oscillations, especially within the first 600ms post-stimulus, with a time shift between participants with aphasia and control subjects. ERPs and the corresponding brain microstates indicate coordinated brain activity alternating mainly between frontal and occipital zones. This behavior can be described as standing waves between two main sources. At the single-trial scale, traveling waves (TW) were identified from both phase and amplitude analyses. The spatiotemporal distribution of amplitude TW reveals subject-specific organization of several interconnected hubs. In patients with aphasia this spatial organization of TW reveals zones with no TW notably in the vicinity of stroke lesions. The present results provide important hints for the hypothesis that TW contribute to the synchronization and communication between different brain areas especially by interconnecting cortical hubs. Moreover, our findings show that cortical dynamics is affected by brain lesions. Contribution to the FieldO_LISpatiotemporal cortical dynamics of individual trials reveals the presence of phase and amplitude traveling waves. C_LIO_LIExploration of traveling waves on the 2D cortical surface reveals the presence of interconnected epicenters or hubs in all subjects. C_LIO_LIThe spatiotemporal distribution of traveling waves shows a higher density in the prefrontal area for people with aphasia than for healthy subjects. C_LIO_LIFor subjects with aphasia, a sparser density of traveling waves is observed in the approximated lesion area. C_LIO_LIEvent-related potential analyses reveal a consistent alternating activity between the frontal and occipital regions. C_LIO_LISubjects with aphasia present a larger and/or delayed contribution in the delta range in the GFP patterns compared to control subjects. C_LI

neuroscience↗

bioRxiv2022

Characterization of spatiotemporal dynamics in EEG data during picture naming with optical flow patterns

We present an analysis of the spatiotemporal dynamics of the oscillations in the electric potential that arises from neural activity. Depending on the frequency and phase of oscillations, these dynamics can be characterized as standing waves or as out-of-phase and modulated waves, which represent a combination of standing and moving waves. We characterize these dynamics as optical flow patterns, in terms of sources, sinks, spirals and saddles. Analytical and numerical solutions are compared with real EEG data acquired during a picture-naming task. Analytical approximation of standing waves allows us to establish some properties of pattern location and number. Namely, sources and sinks have mainly the same location, while saddles are located between them. The number of saddles correlates with the sum of all the other patterns. These properties are confirmed in both the simulated and real EEG data.

neuroscience↗

bioRxiv2020

Algorithmic Learning for Auto-deconvolution of GC-MS Data to Enable Molecular Networking within GNPS.

Gas chromatography-mass spectrometry (GC-MS) represents an analytical technique with significant practical societal impact. Spectral deconvolution is an essential step for interpreting GC-MS data. No public GC-MS repositories that also enable repository-scale analysis exist, in part because deconvolution requires significant user input. We therefore engineered a scalable machine learning workflow for the Global Natural Product Social Molecular Networking (GNPS) analysis platform to enable the mass spectrometry community to store, process, share, annotate, compare, and perform molecular networking of GC-MS data. The workflow performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization, using a Fast Fourier Transform-based strategy to overcome scalability limitations. We introduce a "balance score" that quantifies the reproducibility of fragmentation patterns across all samples. We demonstrate the utility of the platform with breathomics analysis applied to the early detection of oesophago-gastric cancer, and by creating the first molecular spatial map of the human volatilome.

bioinformatics↗

bioRxiv2019

Revisiting microbe-metabolite interactions: doing better than random

I.Recently, Quinn and Erb et al [1] made the case that when used correctly, correlation and proportionality can outperform MMvec when identifying microbe-metabolite interactions. We revisit this comparison and show that the proposed correlation and proportionality are outperformed by MMvec on real data due to their inability to deal with sparsity commonly observed in microbiome and metabolome datasets.

bioinformatics↗

bioRxiv2019

Feature-based Molecular Networking in the GNPS Analysis Environment

Molecular networking has become a key method used to visualize and annotate the chemical space in non-targeted mass spectrometry-based experiments. However, distinguishing isomeric compounds and quantitative interpretation are currently limited. Therefore, we created Feature-based Molecular Networking (FBMN) as a new analysis method in the Global Natural Products Social Molecular Networking (GNPS) infrastructure. FBMN leverages feature detection and alignment tools to enhance quantitative analyses and isomer distinction, including from ion-mobility spectrometry experiments, in molecular networks.

bioinformatics↗

bioRxiv2019

The Molecular and Microbial Microenvironments in Chronically Diseased Lungs

To visualize the personalized distributions of pathogens, chemical environments including microbial metabolites, pharmaceuticals, and their metabolic products within and between human lungs afflicted with cystic fibrosis, we generated 3D microbiome and metabolome maps of six explanted lungs from three cystic fibrosis patients. These 3D spatial maps revealed that the chemical environments are variable between patients and within the lungs of each patient. Although the patients microbial ecosystems were defined by the dominant pathogen, their chemical diversity was not. Additionally, the chemical diversity between locales in lungs of the same individual sometimes exceeded inter-individual variation. Thus, the chemistry and microbiome of the explanted lungs appear to be not only personalized but also regiospecific. Previously undescribed analogs of microbial quinolones and antibiotic metabolites were also detected. Furthermore, mapping the chemical and microbial distributions allowed visualization of microbial community interactions, such as increased production of quorum sensing quinolones in locations where Pseudomonas was in contact with Staphylococcus and Granulicatella, consistent with in vitro observations of bacteria isolated from these patients. Visualization of microbe-metabolite associations within a host organ in early-stage CF disease in animal models will help elucidate a complex interplay between the presence of a given microbial structure, antibiotics, metabolism of antibiotics, microbial virulence factors, and host responses.\n\nImportanceMicrobial infections are now recognized to be polymicrobial and personalized in nature. A comprehensive analysis and understanding of the factors underlying the polymicrobial and personalized nature of infections remains limited, especially in the context of the host. By visualizing microbiomes and metabolomes of diseased human lungs, we describe how different the chemical environments are between hosts that are dominated by the same pathogen and how community interactions shape the chemical environment, or vice versa. We highlight that three-dimensional organ mapping are hypothesis building tools that allow us to design mechanistic studies aimed at addressing microbial responses to other microbes, the host, and pharmaceutical drugs.

microbiology↗