Biology subjects

Rusinova, A.

Publications and source records attributed to Rusinova, A..

4 recordsLinked to original sources

bioRxiv2025

Interoceptive training enhances emotional awareness and body image perception: evidence from improved heartbeat detection and psychological outcomes

The conscious integration of interoceptive signals, such as heartbeats and breathing, is essential for emotional regulation, self-awareness, and stress resilience. We conducted a controlled trial implementing a 5-day biofeedback-guided interoceptive training program to assess its impact on interoceptive accuracy (IAc) and psychological dimensions of bodily and mental perception. The experimental group showed significant improvements in IAc compared to controls, reflecting enhanced detection of heartbeats. Training increased scores on two MAIA subscales: "Awareness of Negative Emotional States" and "Not Distracting". These outcomes suggest the intervention enhanced participants capacity to acknowledge and engage with unpleasant bodily sensations without resorting to avoidance or distraction strategies. A trend toward improved body image perception emerged in the experimental group, with gains correlating with reductions in depressive symptoms, underscoring the interplay between bodily awareness and emotional well-being. These findings underscore that targeted interoceptive training represents a powerful tool for refining awareness of internal states, enhancing attentional control, and optimizing emotional processing. By bridging bodily signals and affective experiences, this approach offers a pathway for innovative, evidence-based therapies to bolster emotional resilience and address conditions rooted in dysregulated emotional states, such as anxiety, depression, and stress-related disorders.

physiology↗

bioRxiv2025

Qualitative and Quantitative Comparative Analysis of Common Normal Variants and Physiological Artifacts in MEG and EEG

AbstractMagnetoencephalography (MEG) and electroencephalography (EEG) provide complementary insights into brain activity, yet their distinct biophysical principles influence how normal neurophysiological patterns and artifacts are represented. This study presents a comprehensive qualitative and quantitative analysis of common physiological variants and artifacts in simultaneously recorded MEG and EEG data. We systematically examined patterns such as alpha spindles, sensorimotor rhythms, sleep-related waveforms (vertex waves, K-complexes, sleep spindles, and posterior slow waves of youth), as well as common artifacts including eye blinks, chewing, and movement-related interferences. By applying time-domain, time-frequency, and source- space analyses, we identified modality-specific differences in signal representation, source localization, and artifact susceptibility. Our results demonstrate that MEG provides a more spatially focal representation of physiological patterns, whereas EEG captures broader, radially oriented cortical activity. Mutual information analysis indicated that MEG-derived independent components exhibited greater topographical variability and higher information content for neurophysiological activity, while EEG components were more homogeneous. Signal-to-noise ratio (SNR) analysis confirmed that MEG gradiometers capture the highest total information, followed by magnetometers and then EEG. Notably, physiological signals such as vertex waves and K-complexes exhibited significantly higher total information in MEG, whereas EEG was more sensitive to high-amplitude artifacts, including swallowing and muscle activity. These findings highlight the distinct strengths and limitations of MEG and EEG, reinforcing the necessity of multimodal approaches in clinical and research applications to improve the accuracy of neurophysiological assessments.

neuroscience↗

bioRxiv2024

Body dissatisfaction shapes time perception and interoception interplay

This study explores the relationship between emotions, physiological responses, interoception, and time perception. We also aimed to understand how body dissatisfaction influences this interplay. Participants (N = 40) watched videos designed to evoke positive, neutral, and negative emotions while their heart rate was monitored via electrocardiography. Our findings indicate that video duration perception varied depending on emotional content. Negative and neutral videos were perceived as shorter, while positive videos were estimated more accurately. Negative emotions were linked to a decrease in heart rate, suggesting a "freeze response," while positive and neutral content did not significantly affect heart rate. A significant correlation between heart rate and time perception was observed in participants with a normal body image, indicating that heart rate might serve as an internal clock. However, this correlation was absent in those with body image dissatisfaction, implying a weakened link between physiological states and time perception. Additionally, a strong negative correlation between heart rate and interoceptive accuracy was found in participants with body image dissatisfaction. The results suggest that body image dissatisfaction disrupts the integration of emotional and physiological signals, affecting how we perceive and understand our internal bodily sensations and emotions.

physiology↗

bioRxiv2023

Short-Term Meditation Training Alters Brain Activity and Sympathetic Responses at Rest, but not during the meditation

Numerous studies have shown that meditation has a number of positive effects on the physical and psychological well-being of practitioners. As a result, meditation has become widely practiced not only as a religious practice but also as a self-regulation technique to achieve specific measurable goals. This raises the question of how quickly physiological changes can be noticed in individuals for whom meditation is not the main focus of their lives but rather a wellbeing keeping technique. Another question is whether it is possible to observe changes occurring directly during meditation and use bio- or neuro-feedback to enhance such meditation training and achieve tangible results. In our study, the experimental group of individuals with no previous meditation experience underwent eight weeks of training in Taoist meditation (2 sessions lasting 1 hour each week), under the guidance of a certified instructor. Participants in the control group attended offline group meetings during the same period, where they listened to audio books. All participants performed meditation testing before and after the intervention, following audio instructions. During the meditation practice, participants EEG, photoplethysmogram, respiratory rate, and skin conductance were recorded. The meditation training, but not the control group activity, resulted in topically organized changes of the resting state brain activity and heart rate variability. Specifically, we observed an increase in EEG power in multiple frequency bands (delta, theta, alpha, beta) and changes in the heart rate variability indicators associated with sympathetic system activation. However, no significant changes were observed when we compared the physiological indicators during the actual meditation process performed prior and post the 8-week training. We interpret these changes as signs of increased alertness and possibly accelerated resting metabolic rate. Importantly, these changes were observed after only 16 hours of meditation training performed during the 8-week period of time. The absence of difference in the band-specific power profiles between the experimental and control groups during the process of meditation conceptually complicates the development of assistive devices aimed at "guiding" the novice meditators during the actual meditation. Our results suggest that the focus in creating such digital assistants should rather be shifted towards monitoring neurophysiological activity during the time intervals outside of the actual meditation. The apparent changes occur not only in the EEG derived parameters but are also detectable based on the markers of autonomous nervous system activity that can be readily registered with a range of wearable gadgets which renders hope for a rapid translation of our results into practical applications.

neuroscience↗