Mikhail Lebedev

The paper investigates neuronal avalanches in awake macaques' V1 and V4, finding power law distributions and robustness to detection parameters.

This paper develops a compact CNN-Transformer model for decoding handwritten digits from sEMG signals, showing improved performance with few-shot adaptation.

This study investigates how the Jendrassik maneuver and motor imagery affect the H-reflex and EEG activity, finding that MI reduces the H-reflex and both JM and MI modulate cortical activity.

This paper connects a P300 speller to a large language model to improve text generation accuracy and communication speed by leveraging contextual error correction.

The paper examines EEG activity in anesthetized rats to identify neurophysiological markers of acute pain under urethane-induced anesthesia.

This paper introduces a second-order Poincare plot to analyze heart rate variability, revealing respiratory effects through serial dependencies in RR intervals.

This paper investigates how tactile imagery affects cortical responses to vibrotactile stimulation, finding that it modulates EEG patterns and enhances cortical processing of real tactile stimuli.

This study examines how lavender and African stone scents affect subjective and physiological anxiety markers in a dental office, finding lavender reduces self-reported anxiety while African stone affects physiological indicators.

This study compares the effects of tactile imagery, tactile stimulation, and kinesthetic motor imagery on corticospinal excitability using TMS, finding greater increases during kinesthetic motor imagery than tactile imagery.

The paper analyzes neuronal population data to show that rotational dynamics are equivalent to travelling waves, introducing a measure to quantify rotation strength.

This study develops an olfactory-based neurofeedback system using EEG alpha rhythm, showing increased alpha power in true NFB groups compared to a mock group.

This study compares EEG patterns from real and imagined vibrotactile sensations on the right hand, finding similar ERD patterns in motor and somatosensory areas.

The paper analyzes EEG responses during real and imagined movements to understand visuomotor transformation, finding differences in lateralized readiness potentials and sensorimotor activation patterns.

This study investigates EEG changes during odor perception and discrimination, finding that frontal theta rhythms reflect odor processing and could be used in olfactory-based BCIs.

This study identifies EEG correlates of olfactory processing during an instructed-delay task, finding specific spatio-spectral patterns associated with odor processing.

This study trains primates and rats to detect and discriminate spinal cord stimulation patterns, finding that sensory discrimination follows Weber's law and varies with stimulation parameters.

This paper investigates reducing the visual field in a P300 speller to improve performance by minimizing non-target stimulus contributions.

This study shows that short-latency visual neurofeedback of parietal alpha activity enhances training effectiveness, with longer delays reducing sustained changes in alpha rhythm.

The paper extends previous findings on neuronal population dynamics by showing that both consistent and heterogeneous responses contribute to rotational patterns observed with jPCA, and suggests users consider these contributions when interpreting results.

The paper develops a method to localize epileptic seizure origins using MEG data by modeling spike propagation as traveling waves.

This paper develops algorithms to reduce feedback delay in brain rhythm-contingent paradigms using EEG data from human subjects.

This study demonstrates that intracortical microstimulation can convey texture information through active tactile exploration in monkeys, following Weber's law, suggesting potential for neuroprosthetic texture sensing.

The paper evaluates Churchland's claim that rotational dynamics represent a fundamental neuronal processing mechanism, finding that such patterns can arise from simple temporal shifts in firing rates and arbitrary simulations, suggesting they may not reflect meaningful neurophysiological structures.

This paper proposes an algorithm to reduce neurofeedback latency in EEG by optimizing FIR filter weights and analytic signal reconstruction, enabling predictive feedback with maintained accuracy.

The paper identifies flaws in the use of information transfer rate (ITR) to evaluate brain-machine interfaces (BMIs) and discusses the limitations of ITR as a metric for BMI performance.