Biology subjects

Lebedev, M.

Publications and source records attributed to Lebedev, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Neuronal avalanches in awake macaque V1 and V4

Neuronal avalanches are cascades of synchronised activity whose sizes follow power law. Analyses of avalanches shed light on cortical dynamics operating near a critical point. In awake monkeys, avalanches were found in motor and premotor cortex, where they are invariant to temporal binning, detection threshold and the number of electrodes employed. Whether awake primate early visual cortex, which receives strong structured afferent drive, shares these properties has not been tested. We analyzed a public 1,024-channel resting-state dataset from V1 and V4 of two macaques. In both animals avalanche sizes followed power laws over more than 10-fold range, the exponent scaled with bin width as alpha proportional to delta-t to the power beta (beta = -0.045 and -0.031), and the distributions ended at a cutoff proportional to the number of electrodes analysed. Raising the detection threshold from 1.5 to 4.5 standard deviations (SDs) removed over 99% of events but changed alpha by only 0.02-0.05 per SD, whereas randomly removing the same events destroyed the power law. Per-electrode shuffling abolished all heavy tails. Eye closure shifted alpha, beta and the branching ratio by less than predefined equivalence bounds, far below the reproducible differences between recording sites. Avalanche organisation therefore extends to awake early visual cortex.

neuroscience↗

bioRxiv2026

FastaLake selects compact metaproteomic databases from large sequence reservoirs by de novo peptide lookup

Metaproteomics analyses require protein sequence databases, yet the microbial proteins present in complex communities are not known in advance. Searching reference catalogs containing hundreds of millions of candidate sequences reduces identification sensitivity, while generating sample-specific databases through metagenomic sequencing adds time and cost. We introduce FastaLake, a computational workflow that uses full-length de novo peptide predictions by AlphaNovo to retrieve complete proteins from broad sequence resources and selects compact databases for conventional searching. In a defined eight-member community, FastaLake approached reference-search peptide yields without knowing its members. Using public sequence catalogs, FastaLake identified about as many peptides as matched metagenomic databases in two stool cohorts and 20-35% more in intestinal fluid at the same nominal 1% peptide false discovery rate. The resulting proteomes reveal personal functional profiles that persist across intestinal regions despite differences in leading species between intestinal fluid and stool. DNA, RNA and protein profiles agreed on broad differences between patients but only weakly on individual functions. All 726 acquisition-specific databases were smaller than the human reference proteome. Compact databases allowed non-specific searches of all 347 CapScan acquisitions, revealing histidine enrichment at peptide C termini in intestinal fluid. FastaLake enables metaproteomics analysis without matched metagenomic sequencing by constructing search databases from sequence resources and de novo peptide sequencing.

bioinformatics↗

bioRxiv2026

DualMyo: Multi-Channel Dual-Stream Transformer Architecture for EMG-to-Digit Classification

Surface electromyography (sEMG) is a robust non-invasive modality for human-machine interaction, yet its application remains largely limited to coarse motor tasks such as grasping or rotation. The decoding of fine motor skills, specifically handwriting, remains a challenging problem with potential relevance for prosthetic control and natural communication interfaces. In this work, we explore a Transformer-based alternative to classical signal-processing pipelines that treats multi-channel sEMG signals as complex time series. We introduce DualMyo, a specialized model integrating Patch Embeddings and Rotary Positional Embeddings (RoPE) to capture the intricate spatio-temporal dynamics of myoelectric activity. Our experimental results show strong intra-session performance. Furthermore, we address the inherent challenges of signal drift and sensor displacement in cross-session applications. We show that a lightweight fine-tuning strategy of 10 epochs enables DualMyo to effectively adapt to session variability, achieving approximately 91\% accuracy with two examples per digit. These findings provide a promising step toward adaptive sEMG-based handwriting interfaces, although further validation is required for real-time and multi-subject deployment and neuromuscular control.

neuroscience↗

bioRxiv2026

Data aggregation strategies for a P300 speller: decoding models, epoch averaging, cross-subject ensembles, and multi-channel models

Accurate detection of P300 event-related potentials from electroencephalography (EEG) re-mains challenging for small numbers of trials due to low signal-to-noise ratios and substantial inter-subject variability. This study presents a systematic comparison of data aggregation strate-gies for improving P300 classification, evaluated on a 10-subject dataset using two convolutional neural network architectures (EEGNet and BaseCNN) and a support vector machine (SVM). We compared: (1) subject-specific and pooled general models for single trials; (2) epoch aver-aging with 5 and 10 stimuli repetitions; (3) multi-channel models where subjects corresponded to different input channels; (4) cross-subject averaging; (5) mixed (uncontrolled) averaging; (6) a combined approach with K trials per subject across all participants; and (7) time-shifted channels from extended single-trial epochs. Decoding performance was quantified using the Information Transfer Rate (ITR), computed for binary classification accuracy. We found that single-trial ITR was unpractical (0.15-0.64 bits/trial), whereas controlled aggregation improved the performance. The combined cross-subject approach with K = 3 trials per participant (30 channels) achieves the highest ITR with multi-channel EEGNet: 0.95 bits/aggregated decision in the no-aperture recordings and 0.97 bits/aggregated decision on Aperture data, approaching the theoretical binary-classification limit for the aggregated decision. Controlled cross-subject averaging consistently outperformed random trial mixing, and multi-channel architectures out-performed simple averaging when inter-subject structure was preserved. These findings con-tribute to improving P300 decoding and implementing multi-subject brain-computer interfaces (BCIs).

neuroscience↗

bioRxiv2025

Motor Imagery Affects both Cortical and Spinal Circuitry: A Transcranial and Transspinal Magnetic Stimulation Study.

Motor imagery (MI), the mental rehearsal of movement without physical execution, is a key technique in brain-computer interfaces (BCIs) for voluntarily eliciting cortical modulations. Beyond cortical effects, MI could also modulate spinal cord processing, which offers additional potential for neurorehabilitation in conditions like spinal cord injury (SCI) and stroke, where BCIs are used for therapy. To investigate the interactions of MI with both the cortex and the spinal cord, we employed both transcranial magnetic stimulation (TMS) and trans-spinal magnetic stimulation (TSMS). With proper coil orientation, TSMS elicited short- and long-latency motor evoked potentials (MEPs) in forearm muscles and lateralized evoked potentials in the cortex. MI modulated both TMS-induced and TSMS-induced cortical responses and MEPs. This demonstration of MI affecting both cortical and spinal circuitry underscores its potential as a powerful strategy for BCI-driven neurorehabilitation, including pairing MI with magnetic stimulation.

neuroscience↗

bioRxiv2025

Connecting a P300 speller to a large language model

The advent of large-language models (LLMs) offers a transformative approach for improving the performance of brain-computer interface (BCI) spellers. We propose a novel framework that leverages the contextual understanding of LLMs to compensate for imperfect BCI decoding. Using existing P300 speller data, we simulated a system where users select letters to form words, generating text with characteristic spelling errors. This output is then processed by an LLM, which corrects the errors - a task that becomes more effective when the model considers full-sentence context. Our findings suggest that this synergy can accelerate communication rates by relaxing the need for high single-character accuracy. Beyond speed, integrating an LLM transforms the BCI into an intelligent agent, capable of acting as a discussant and assistant, thereby enriching the user experience.

neuroscience↗

bioRxiv2024

Scents Modulate Anxiety Levels, but Electroencephalographic and Electrocardiographic Assessments Could Diverge from Subjective Reports

Scents could modulate anxiety levels, such as anxiety in a medical office. Here we investigated the impact of two scents on the subjective and physiological anxiety markers in the dental office environment, utilizing self-reported anxiety assessments alongside physiological assessment with electroencephalographic (EEG) and electrocardiographic (ECG) measurements. Lavender was the first tested scent with the previously reported calming effect. African stone was the second stimulus with a musky scent. Twenty healthy participants took part in scent exposure sessions. Anxiety levels were assessed using the State-Trait Anxiety Inventory (STAI), EEG-based theta, alpha, and beta power ratios, and heart rate variability (HRV) indices derived from ECG data. Lavender exposure significantly decreased self-reported anxiety whereas African stone reduced physiological indicators of anxiety. Namely, African stone exposure led to decreased theta and increased alpha power in the parietal-occipital EEG signals. Additionally, decreases were observed in low-frequency (LF) HRV power and total HRV power, reflecting lowered autonomic arousal. These findings support the potential effectiveness for olfactory interventions to aid in anxiety management within clinical environments, but draw attention to the issue of proper evaluation of anxiety. In particular, the difference between the subjective reports and traditional EEG and HRV markers indicates that anxiety involves a complexity of factors, which makes its treatment by scents challenging.

neuroscience↗

bioRxiv2024

The proteomic landscape of proteotoxic stress in a fibrogenic liver disease

Protein misfolding diseases, including alpha-1 antitrypsin deficiency (AATD), pose significant health challenges, with their cellular progression still poorly understood1-3. We utilize spatial proteomics by mass spectrometry and machine learning to map AATD in human liver tissue. Combining Deep Visual Proteomics (DVP) with single-cell analysis4,5, we probe intact patient biopsies to resolve molecular events during hepatocyte stress in pseudo-time across fibrosis stages. We achieve unprecedented proteome depth of up to 3,800 proteins from a third of a single cell in formalin-fixed, paraffin-embedded (FFPE) tissue. This dataset revealed a potentially clinically actionable peroxisomal upregulation that precedes the canonical unfolded protein response. Our single-cell proteomics data show alpha-1 antitrypsin accumulation is largely cell-intrinsic, with minimal stress propagation between hepatocytes. We integrated proteomic data with AI-guided image-based phenotyping across multiple disease stages, revealing a terminal hepatocyte state characterized by globular protein aggregates and distinct proteomic signatures, notably including elevated TNFSF10/TRAIL expression. This phenotype may represent a critical disease progression stage. Our study offers novel insights into AATD pathogenesis and introduces a powerful methodology for high-resolution, in situ proteomic analysis of complex tissues. This approach holds potential to unravel molecular mechanisms in various protein misfolding disorders, setting a new standard for understanding disease progression at the single-cell level in human tissue.

cell biology↗

bioRxiv2024

AlphaDIA enables End-to-End Transfer Learning for Feature-Free Proteomics

Mass spectrometry (MS)-based proteomics continues to evolve rapidly, opening more and more application areas. The scale of data generated on novel instrumentation and acquisition strategies pose a challenge to bioinformatic analysis. Search engines need to make optimal use of the data for biological discoveries while remaining statistically rigorous, transparent and performant. Here we present alphaDIA, a modular open-source search framework for data independent acquisition (DIA) proteomics. We developed a feature-free identification algorithm particularly suited for detecting patterns in data produced by sensitive time-of-flight instruments. It naturally adapts to novel, more eTicient scan modes that are not yet accessible to previous algorithms. Rigorous benchmarking demonstrates competitive identification and quantification performance. While supporting empirical spectral libraries, we propose a new search strategy named end-to-end transfer learning using fully predicted libraries. This entails continuously optimizing a deep neural network for predicting machine and experiment specific properties, enabling the generic DIA analysis of any post-translational modification (PTM). AlphaDIA provides a high performance and accessible framework running locally or in the cloud, opening DIA analysis to the community.

bioinformatics↗

bioRxiv2023

Peptide-mimetic treatment of Pseudomonas aeruginosa in a mouse model of respiratory infection

The rise of drug resistance has become a global crisis, with >1 million deaths due to resistant bacterial infections each year. Pseudomonas aeruginosa, in particular, remains a serious problem with limited solutions due to complex resistance mechanisms that now lead to more than 32,000 multidrug-resistant (MDR) infections and over 2,000 deaths annually. While the emergence of resistant bacteria has become concerningly common, identification of useful new drug classes has been limited over the past 40+ years. We found that a potential novel therapeutic, the peptide-mimetic TM5, is effective at killing P. aeruginosa and displays sufficiently low toxicity for mammalian cells to allow for use in treatment of infections. Interestingly, TM5 kills P. aeruginosa more rapidly than traditional antibiotics, within 30-60 minutes in vitro, and is effective against a range of clinical isolates. In vivo, TM5 significantly reduced bacterial load in the lungs within 24 hours compared to untreated mice and demonstrated few adverse effects. Taken together, these observations suggest that TM5 shows promise as an alternative therapy for MDR P. aeruginosa respiratory infections.

microbiology↗

bioRxiv2023

Tactile vs Motor Imagery: the Effects on Corticospinal Excitability Assessed with single-pulse TMS

Tactile Imagery (TI) remains a fairly understudied phenomenon despite an increased attention to this topic in recent years. Here we investigated the effects of TI on corticospinal excitability by measuring motor evoked potentials (MEPs) induced by single-pulse transcranial magnetic stimulation (TMS). The effects of TI were compared with those of tactile stimulation (TS) and kinesthetic motor imagery (kMI). Twenty-two participants performed three tasks in randomly assigned order: imagine finger tapping (kMI); experience vibratory sensations in the middle finger (TS); and mentally reproduce the sensation of vibration (TI). MEPs increased during both kMI and TI, with a stronger increase for kMI. No statistically significant change in MEP was observed during TS. The demonstrated differential effects of kMI, TI and TS on corticospinal excitability have practical implications for the development of imagery-based and TS-based brain-computer interfaces (BCIs), particularly the ones intended to improve neurorehabilitation by evoking plastic changes in sensorimotor circuitry. Significance StatementWhile it is known that tactile imagery (TI) engages the primary somatosensory cortex similarly to physical tactile perceptions, it is not well understood how TI affects neural processing in the primary motor cortex (M1), the area that controls voluntary movements while receiving somatosensory feedback. This study employed transcranial magnetic stimulation (TMS) to examine the responsiveness of M1 to different types of somatosensory imagery in response to TMS. TI facilitated the responses in the forearm and hand muscles but to a significantly lesser extent compared to kinesthetic motor imagery (kMI). This demonstration of the distinct effects of TI and kMI on corticospinal excitability highlights the importance of selecting an imagery strategy when using imagery to modulate cortical representation of the body. These findings have practical implications for the development of imagery-based brain-computer interfaces (BCIs) intended for rehabilitation of sensorimotor impairments.

neuroscience↗

bioRxiv2023

Unveiling Rotational Structure in Neural Data

Spatiotemporal properties of the activity of neuronal populations in cortical motor areas have been the subject of many experimental and theoretical investigations, which generated numerous inter-pretations regarding the mechanisms of preparing and executing limb movements. Two competing models, namely representational and dynamical models, strive to explain the temporal course of neuronal activity and its relationship to different parameters of movements. One proposed dynamical model employs the jPCA method, a dimensionality reduction technique, to holistically characterize oscillatory activity in a population of neurons by maximizing rotational dynamics that are present in the data. Different interpretations have been proposed for the rotational dynamics revealed with jPCA approach in various brain areas. Yet, the nature of such dynamics remains poorly understood. Here we conducted a comprehensive analysis of several neuronal-population datasets. We found that rotational dynamics were consistently accounted for by a travelling wave pattern. To quantify the rotation strength, we developed a complex-valued measure termed the gyration number. Additionally, we identified the parameters influencing the extent of rotation in the data. Overall, our findings suggest that rotational dynamics and travelling waves are the same phenomena, which requires reevaluation of the previous interpretations where they were considered as separate entities.

neuroscience↗

bioRxiv2023

Resting-state EEG recorded with gel-based versus consumer dry electrodes: spectral characteristics and across-device correlations

Recordings of electroencephalographic (EEG) rhythms and their analyses have been instrumental in basic Neuroscience, clinical diagnostics, and the field of brain-computer interfaces (BCIs). While in the past such measurements have been conducted mostly in laboratory settings, recent advancements in dry electrode technology pave way to a broader range of consumer and medical application because of their greater convenience compared to gel-based electrodes. Here we conducted resting-state EEG recordings in two groups of healthy participants using three dry-electrode devices, the Neiry Headband, the Neiry Headphones and the Muse Headband, and one standard gel electrode-based system, the NVX. We examined signal quality for various spatial and spectral ranges which are essential for cognitive monitoring and consumer applications. Distinctive characteristics of signal quality were found, with the Neiry Headband showing sensitivity in low-frequency ranges and replicating the modulations of delta, theta and alpha power corresponding to the eyes-open and eyes-closed conditions, and the NVX system performing well in capturing high-frequency oscillations. The Neiry Headphones were more prone to low-frequency artifacts compared to the Neiry Headband, yet recorded modulations in alpha power and had a strong alignment with the NVX at higher frequencies. The Muse Headband had several limitations in signal quality. We suggest that while dry-electrode technology appears to be appropriate for the EEG rhythm-based applications the potential benefits of these technologies in terms of ease of use and accessibility should be carefully weighted against the capacity of each concrete system.

neuroscience↗

bioRxiv2023

Tactile Imagery Affects Cortical Responses to Vibrotactile Stimulation of the Fingertip

Although imagery of tactile sensations is not so well studied compared to other types of mental imagery, it is potentially very useful for brain computer interfaces (BCIs) where it could produce neural modulations needed for BCI operations. Here we assessed neural modulations associated with tactile imagery (TI) by comparing its effects on cortical responses to the effects of actual vibrotactile stimulation of the fingertip. We found that both TI and vibrostimulation evoked event-related frequency changes of the electroencephalographic (EEG) activity. Moreover, TI affected somatosensory evoked potentials (SEPs) evoked by short pulses of vibration. EEG data were collected in 29 participants trained to perform tactile imagery task. Responses to vibratory pulses were measured with and without TI. These SEPs consisted of three prominent components: a P100 response in the centro-parietal regions, a P200 response in the frontal region, and a P300 response in the central regions. The TI consistently resulted in an increase in ipsilateral P100, ipsi- and contralateral P300 and frontal P200. Moreover, TI strengthened the {theta}-band ERS in the frontal region that occurred in response to vibration. These findings suggest that TI not only modulates EEG patterns by itself but also affects cortical processing of physical somatosensory stimuli. Such conjoint processing of both real and imagined somatic sensations could be utilized in BCIs, particularly in clinically relevant BCI that strive to restore somatosensory processing by combining centrally-induced and peripheral activities. Significance StatementWhile it is known that tactile imagery (TI) engages the same cortical areas that are active during the processing of real tactile inputs, neural mechanisms of such shared representation are not well understood. This study employed EEG recordings to examine the interaction between real and imagined somatic sensations. It was found that TI both changes EEG oscillatory activity and facilitates cortical responses to real tactile stimuli. Therefore combining TI with tactile stimulation could be useful for tactile-based brain-computer interfaces (BCIs), particularly the ones of clinical utility for neurorehabilitation and sensory substitution.

neuroscience↗

bioRxiv2023

Lateralized Sensorimotor Evoked Potentials during Visuomotor Transformation in Real and Imagined Movements

The neural mechanisms underlying motor preparation have attracted much attention, particularly because of the assertion that they are similar to the mechanisms of motor imagery (MI), a technique widely used in motor rehabilitation and brain-computer interfaces (BCIs). Here we clarified the process of visuomotor transformation for the real and imagined movements by analyzing EEG responses that were time locked to the appearance of visual targets and movement onsets. The experimental task required responding to target stimuli with button presses or imagined button presses while ignoring distractors. We examined how different components of movement-related potentials (MRPs) varied depending on the reaction time (RT) and interpreted the findings in terms of the motor noise accumulation hypothesis. Furthermore, we compared MRPs and event-related desynchronization (ERD) for overt motor actions versus motor imagery. For the MRPs, we distinguished lateralized readiness potentials (LRPs) and reafferent potentials (RAPs). While MRPs were similar for the real and imagined movements, imagery-related potentials were not lateralized. The amplitude of the late potentials that developed during motor imagery at the same time RAPs occurred during real movements was correlated with the amplitude of {beta}-ERD. As such they could have represented sensorimotor activation triggered by the imagery. LRPs that occurred during real movements lasted longer for longer RTs, which is consistent with activity accumulation in the motor cortex prior to overt action onset. LRPs occurred for non-target stimuli, as well, but they were small and short lived. We interpret these results in terms of a visuomotor transformation, where information flows from visual to motor areas and results in a movement, a decision not to move and/or a mental image of a movement. The amplitude of the late positive peak that developed during MI was correlated with the amplitude of the {beta}-ERD. Since the latency of this component was consistent with the timing of RAP, we suggest that it is a non-lateralized RAP-like component associated with sensorimotor activation during kinesthetic MI.

neuroscience↗

bioRxiv2022

Anillin forms linear structures and facilitates furrow ingression after septin and formin depletion

During cytokinesis a contractile ring consisting of unbranched filamentous actin (F-actin) and myosin II filaments assembles and constricts at the cell equator. Unbranched F-actin is de novo generated by formin and without formin cleavage furrow ingression fails. In C. elegans depletion of septin restores cleavage furrow ingression in formin (CYK-1) mutants. How the cleavage furrow ingresses without a detectable unbranched F-actin ring is not known. We report, that in this setting anillin (ANI-1) is essential for furrow ingression and forms a meshwork of linear structures, which circumferentially align around the cell equator. Although equatorial ANI-1 recruitment is facilitated by septins, the formation of linear ANI-1 structures is septin independent. Analysis of ANI-1 deletion mutants reveals that its disordered linker region is required for linear structure formation and furrow ingression. We also found that myosin II (NMY-2) decorates linear ANI-1 structures and promotes their circumferential alignment. NMY-2 also interacts with various lipids and forms membrane localized clusters in absence of F-actin and anillin binding. This suggests that NMY-2 represents an independent link between the F-actin / ANI-1 network and the plasma membrane. Collectively, our data reveals a compensatory mechanism, mediated by ANI-1 linear structures and membrane-bound NMY-2, that promotes furrow formation and ingression when formins are depleted and therefore unbranched F-actin polymerization is compromised.

cell biology↗

bioRxiv2022

EEG Changes during Odor Perception and Discrimination

Brain-Computer Interfaces (BCIs) are devices designed for communication between the central nervous system and a computer. The communication can occur through different sensory modalities, and most commonly visual and auditory systems are used. We suggest that BCIs can be expanded by the incorporation of olfactory modality. To probe the modulation of EEG activity by odorants, we implemented two olfactory tasks: one that required attention to perception of odors, and the second one where participants discriminated consecutively presented odors. EEG recordings were conducted in 13 healthy participants while they performed the tasks following computer-generated verbal instructions. Respiratory activity was recorded to relate EEG modulations to the breath cycle. Theta activity responses were observed over the frontal EEG leads approximately 2 s after the inhalation. This theta activity was different depending on whether or not the inhaled air contained an odorant, and cognitive load also had an effect. We conclude that the frontal theta rhythm is reflective of the neural processing of odors. As such, it could be incorporated in the olfactory-based BCIs which take odors either as inputs or outputs. These BCIs could improve olfactory training needed for conditions like anosmia and hyposmia, and mild cognitive impairment.

neuroscience↗

bioRxiv2022

Event-Related Desynchronization induced by Tactile Imagery: an EEG Study

It is well known that both the movement of the hand itself and the mental representation of it lead to event-related desynchronization (ERD) of EEG recorded over the corresponding motor areas of the cerebral cortex. Similarly, in somatosensory cortical areas, ERD occurs upon tactile stimulation of the hand, but whether this effect is caused by mental representation of sensations from tactile stimulation remains poorly understood. In the present study, the effects on the EEG of imaginary vibrotactile sensations on the right hand were compared with the effects of real vibrotactile stimulation. Both actual vibrotactile stimulation and mental representation of it have been found to elicit contralateral ERD patterns, particularly prominent in the -band and most pronounced in the C3 region. The paper discusses tactile imagery as a part of the complex sensorimotor mental image and its prospects for using EEG patterns of imagery-induced tactile sensations as control signals in BCI circuits independently and when combined with ERD based on movement imagination to improve the efficiency of neurointerface technologies in rehabilitation medicine, in particular, to restore movements after a stroke and neurotrauma.

neuroscience↗