Morozova Marina
Junior researcher
2026
3.
Morozova, Marina; Yakovlev, Lev; Syrov, Nikolay; Lebedev, Mikhail; Kaplan, Alexander (2026). Using a TMS Navigation System for High-Precision Digitization of Sensor Locations to Improve Source Localization. Journal of Visualized Experiments, 227(e69508). https://doi.org/10.3791/69508
@article{Morozova2026,
title = {Using a TMS Navigation System for High-Precision Digitization of Sensor Locations to Improve Source Localization},
author = {Marina Morozova and Lev Yakovlev and Nikolay Syrov and Mikhail Lebedev and Alexander Kaplan},
doi = {10.3791/69508},
issn = {1940-087X},
year = {2026},
date = {2026-01-23},
urldate = {2026-01-23},
journal = {Journal of Visualized Experiments},
volume = {227},
number = {e69508},
publisher = {MyJove Corporation},
abstract = {Summary
We present a reproducible method for digitizing high-density electroencephalography (EEG) sensor locations using instruments of a Navigated Brain Stimulation (NBS) system. This approach does not require any additional software extensions, only standard NBS tools. Integrated with MNE-Python pipelines, this approach improves source localization accuracy without additional hardware.
Abstract
Source localization is a technique used to estimate the sources of brain activity based on signals recorded from the scalp. Accurate source localization critically depends on the precise spatial digitization of sensor locations. In this protocol, we present a practical and reliable method for digitizing sensor locations using the Navigated Brain Stimulation (NBS) system. NBS is a component of Transcranial Magnetic Stimulation (TMS) equipment commonly available in TMS laboratories, but rarely utilized for sensor digitization of electroencephalography (EEG) or functional near-infrared spectroscopy (fNIRS) systems. This approach allows researchers to leverage existing infrastructure to significantly improve the spatial accuracy of source modeling, without investing in dedicated digitization equipment.
We guide viewers through the full workflow: (1) digitizing EEG electrode locations using default tools of the Nexstim NBS system; (2) exporting coordinate data in compatible formats; (3) integrating this data into EEG preprocessing and source localization pipelines using the MNE-Python package. The protocol also includes tips for aligning digitized data with MRI images and optimizing coregistration accuracy. To illustrate the method's practical utility, we apply it to analyze data from a tactile stimulation experiment.
Custom Python scripts for coordinate processing and coregistration are provided to ensure reproducibility and ease of adoption. The results show that incorporating digitized electrode positions remarkably improves the anatomical accuracy and interpretability of cortical source estimates compared to default electrode montages.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Summary
We present a reproducible method for digitizing high-density electroencephalography (EEG) sensor locations using instruments of a Navigated Brain Stimulation (NBS) system. This approach does not require any additional software extensions, only standard NBS tools. Integrated with MNE-Python pipelines, this approach improves source localization accuracy without additional hardware.
Abstract
Source localization is a technique used to estimate the sources of brain activity based on signals recorded from the scalp. Accurate source localization critically depends on the precise spatial digitization of sensor locations. In this protocol, we present a practical and reliable method for digitizing sensor locations using the Navigated Brain Stimulation (NBS) system. NBS is a component of Transcranial Magnetic Stimulation (TMS) equipment commonly available in TMS laboratories, but rarely utilized for sensor digitization of electroencephalography (EEG) or functional near-infrared spectroscopy (fNIRS) systems. This approach allows researchers to leverage existing infrastructure to significantly improve the spatial accuracy of source modeling, without investing in dedicated digitization equipment.
We guide viewers through the full workflow: (1) digitizing EEG electrode locations using default tools of the Nexstim NBS system; (2) exporting coordinate data in compatible formats; (3) integrating this data into EEG preprocessing and source localization pipelines using the MNE-Python package. The protocol also includes tips for aligning digitized data with MRI images and optimizing coregistration accuracy. To illustrate the method's practical utility, we apply it to analyze data from a tactile stimulation experiment.
Custom Python scripts for coordinate processing and coregistration are provided to ensure reproducibility and ease of adoption. The results show that incorporating digitized electrode positions remarkably improves the anatomical accuracy and interpretability of cortical source estimates compared to default electrode montages.
We present a reproducible method for digitizing high-density electroencephalography (EEG) sensor locations using instruments of a Navigated Brain Stimulation (NBS) system. This approach does not require any additional software extensions, only standard NBS tools. Integrated with MNE-Python pipelines, this approach improves source localization accuracy without additional hardware.
Abstract
Source localization is a technique used to estimate the sources of brain activity based on signals recorded from the scalp. Accurate source localization critically depends on the precise spatial digitization of sensor locations. In this protocol, we present a practical and reliable method for digitizing sensor locations using the Navigated Brain Stimulation (NBS) system. NBS is a component of Transcranial Magnetic Stimulation (TMS) equipment commonly available in TMS laboratories, but rarely utilized for sensor digitization of electroencephalography (EEG) or functional near-infrared spectroscopy (fNIRS) systems. This approach allows researchers to leverage existing infrastructure to significantly improve the spatial accuracy of source modeling, without investing in dedicated digitization equipment.
We guide viewers through the full workflow: (1) digitizing EEG electrode locations using default tools of the Nexstim NBS system; (2) exporting coordinate data in compatible formats; (3) integrating this data into EEG preprocessing and source localization pipelines using the MNE-Python package. The protocol also includes tips for aligning digitized data with MRI images and optimizing coregistration accuracy. To illustrate the method's practical utility, we apply it to analyze data from a tactile stimulation experiment.
Custom Python scripts for coordinate processing and coregistration are provided to ensure reproducibility and ease of adoption. The results show that incorporating digitized electrode positions remarkably improves the anatomical accuracy and interpretability of cortical source estimates compared to default electrode montages.
2025
2.
Morozova, Marina; Yakovlev, Lev; Syrov, Nikolay; Lebedev, Mikhail; Kaplan, Alexander (2025). Cortical responses to tactile imagery: a high-density EEG study of the μ-rhythm event-related desynchronization and somatosensory evoked potentials. NeuroImage, 319(121440). https://doi.org/10.1016/j.neuroimage.2025.121440
@article{Morozova2025b,
title = {Cortical responses to tactile imagery: a high-density EEG study of the μ-rhythm event-related desynchronization and somatosensory evoked potentials},
author = {Marina Morozova and Lev Yakovlev and Nikolay Syrov and Mikhail Lebedev and Alexander Kaplan},
url = {https://megmoscow.ru/wp-content/uploads/pubs/10.1016_j.neuroimage.2025.121440.pdf},
doi = {10.1016/j.neuroimage.2025.121440},
issn = {1053-8119},
year = {2025},
date = {2025-10-00},
urldate = {2025-10-00},
journal = {NeuroImage},
volume = {319},
number = {121440},
publisher = {Elsevier BV},
abstract = {Scents can influence anxiety, including that experienced in clinical environments. This study examined the effects of two distinct aromas: lavender, a fragrance widely recognized for its calming properties, and African stone, a musky and relatively unfamiliar scent. Twenty healthy participants underwent alternating periods of rest and scent inhalation in a dental office environment while anxiety was assessed using the State–Trait Anxiety Inventory (STAI), electroencephalographic (EEG) measures of theta, alpha, and beta power ratios, and electrocardiographic (ECG) measures of heart rate variability (HRV). Lavender inhalation significantly reduced self-reported state anxiety scores but did not produce measurable changes in EEG or HRV indices, possibly due to the short (5 min) exposure duration. African stone, in contrast, did not alter self-reported anxiety but induced significant physiological effects, including reduced theta and, increased alpha power in parieto-occipital regions, and decreased high-frequency (HF) and total HRV power. While the EEG changes are consistent with a more relaxed state, the HRV reductions could indicate a heightened autonomic arousal, suggesting that African stone could have triggered increased attention and physiological activation rather than merely relaxation. These findings demonstrate a divergence between subjective and physiological responses to scent exposure. Lavender appears to primarily reduce perceived anxiety, while African stone influences physiological arousal. We suggest that a multimodal approach be applied in aromatherapy research.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Scents can influence anxiety, including that experienced in clinical environments. This study examined the effects of two distinct aromas: lavender, a fragrance widely recognized for its calming properties, and African stone, a musky and relatively unfamiliar scent. Twenty healthy participants underwent alternating periods of rest and scent inhalation in a dental office environment while anxiety was assessed using the State–Trait Anxiety Inventory (STAI), electroencephalographic (EEG) measures of theta, alpha, and beta power ratios, and electrocardiographic (ECG) measures of heart rate variability (HRV). Lavender inhalation significantly reduced self-reported state anxiety scores but did not produce measurable changes in EEG or HRV indices, possibly due to the short (5 min) exposure duration. African stone, in contrast, did not alter self-reported anxiety but induced significant physiological effects, including reduced theta and, increased alpha power in parieto-occipital regions, and decreased high-frequency (HF) and total HRV power. While the EEG changes are consistent with a more relaxed state, the HRV reductions could indicate a heightened autonomic arousal, suggesting that African stone could have triggered increased attention and physiological activation rather than merely relaxation. These findings demonstrate a divergence between subjective and physiological responses to scent exposure. Lavender appears to primarily reduce perceived anxiety, while African stone influences physiological arousal. We suggest that a multimodal approach be applied in aromatherapy research.
1.
Morozova, Marina; Gabrielyan, Irina; Kleeva, Daria; Efimova, Victoria; Lebedev, Mikhail (2025). Scents modulate anxiety levels, but electroencephalographic and electrocardiographic assessments could diverge from subjective reports: a pilot study. Front. Behav. Neurosci., 19(1534716). https://doi.org/10.3389/fnbeh.2025.1534716
@article{Morozova2025,
title = {Scents modulate anxiety levels, but electroencephalographic and electrocardiographic assessments could diverge from subjective reports: a pilot study},
author = {Marina Morozova and Irina Gabrielyan and Daria Kleeva and Victoria Efimova and Mikhail Lebedev},
url = {https://megmoscow.ru/wp-content/uploads/pubs/10.3389_fnbeh.2025.1534716.pdf},
doi = {10.3389/fnbeh.2025.1534716},
issn = {1662-5153},
year = {2025},
date = {2025-09-16},
urldate = {2025-09-16},
journal = {Front. Behav. Neurosci.},
volume = {19},
number = {1534716},
publisher = {Frontiers Media SA},
abstract = {Scents can influence anxiety, including that experienced in clinical environments. This study examined the effects of two distinct aromas: lavender, a fragrance widely recognized for its calming properties, and African stone, a musky and relatively unfamiliar scent. Twenty healthy participants underwent alternating periods of rest and scent inhalation in a dental office environment while anxiety was assessed using the State–Trait Anxiety Inventory (STAI), electroencephalographic (EEG) measures of theta, alpha, and beta power ratios, and electrocardiographic (ECG) measures of heart rate variability (HRV). Lavender inhalation significantly reduced self-reported state anxiety scores but did not produce measurable changes in EEG or HRV indices, possibly due to the short (5 min) exposure duration. African stone, in contrast, did not alter self-reported anxiety but induced significant physiological effects, including reduced theta and, increased alpha power in parieto-occipital regions, and decreased high-frequency (HF) and total HRV power. While the EEG changes are consistent with a more relaxed state, the HRV reductions could indicate a heightened autonomic arousal, suggesting that African stone could have triggered increased attention and physiological activation rather than merely relaxation. These findings demonstrate a divergence between subjective and physiological responses to scent exposure. Lavender appears to primarily reduce perceived anxiety, while African stone influences physiological arousal. We suggest that a multimodal approach be applied in aromatherapy research.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Scents can influence anxiety, including that experienced in clinical environments. This study examined the effects of two distinct aromas: lavender, a fragrance widely recognized for its calming properties, and African stone, a musky and relatively unfamiliar scent. Twenty healthy participants underwent alternating periods of rest and scent inhalation in a dental office environment while anxiety was assessed using the State–Trait Anxiety Inventory (STAI), electroencephalographic (EEG) measures of theta, alpha, and beta power ratios, and electrocardiographic (ECG) measures of heart rate variability (HRV). Lavender inhalation significantly reduced self-reported state anxiety scores but did not produce measurable changes in EEG or HRV indices, possibly due to the short (5 min) exposure duration. African stone, in contrast, did not alter self-reported anxiety but induced significant physiological effects, including reduced theta and, increased alpha power in parieto-occipital regions, and decreased high-frequency (HF) and total HRV power. While the EEG changes are consistent with a more relaxed state, the HRV reductions could indicate a heightened autonomic arousal, suggesting that African stone could have triggered increased attention and physiological activation rather than merely relaxation. These findings demonstrate a divergence between subjective and physiological responses to scent exposure. Lavender appears to primarily reduce perceived anxiety, while African stone influences physiological arousal. We suggest that a multimodal approach be applied in aromatherapy research.