Biology subjects

Jun, S. C.

Publications and source records attributed to Jun, S. C..

4 recordsLinked to original sources

bioRxiv2023

Exploring connectivity of resting-state EEG between BCI-literate and -illiterate groups

Although Motor Imagery-based Brain-Computer Interface (MI-BCI) holds significant potential, its practical application faces challenges attributable to the phenomenon known as BCI-illiteracy. BCI researchers have attempted to predict BCI-illiteracy to mitigate this issue. As connectivitys significance in neuroscience has grown, BCI researchers have applied connectivity to predict BCI-illiteracy with resting-state data. However, connectivity metrics use and interpretation of the results can be challenging for several reasons. Firstly, there are various connectivity metrics, each with its own advantages and disadvantages based on their underlying hypotheses and perspectives. These pros and cons are shaped by several factors, increasing the complexity of their application and interpretation. Secondly, it is unclear whether they are as acceptable as their developers have claimed. Thirdly, it is not evident which factor may influence the estimation of connectivity and which metric is suitable for this research. Therefore, this study conducted an empirical test to provide BCI researchers with a better understanding of connectivity. We analyzed three large public datasets using three functional connectivity (FC) and three effective connectivity (EC) metrics. Additionally, the structural difference in the resting-state network between BCI-literate and illiterate groups was examined. Our analysis revealed that the appropriate frequency range to measure connectivity varies depending upon the metric used. The alpha range was found to be suitable for FC, while the alpha, alpha + theta, and beta ranges were found to be appropriate for EC. Further, the results of estimating connectivity varied depending upon the dataset and metric used. Although we observed that BCI-literacy had stronger connections between nodes, no other significant structural differences were found between the two groups. However, BCI-literacys resting-state network displayed higher network efficiency compared to BCI-illiteracy, regardless of the metrics and dataset used. Therefore, it seems reasonable to use resting-state connectivity to predict BCI-illiteracy. Our conclusion is that each metric has its own specific hypothesis and perspective to measure connectivity under certain conditions.

neuroscience↗

bioRxiv2021

Key Factors in the Cortical Response to Transcranial Electrical Stimulations--A Multi-Scale Modeling Study

Transcranial electrode stimulation (tES), one of the techniques used to apply non-invasive brain stimulation (NIBS), modulates cortical activities by delivering weak electric currents through scalp-attached electrodes. This emerging technique has gained increasing attention recently; however, the results of tES vary greatly depending upon subjects and the stimulation paradigm, and its cellular mechanism remains uncertain. In particular, there is a controversy over the factors that determine the cortical response to tES. Some studies have reported that the electric fields (EF) orientation is the determining factor, while others have demonstrated that the EF magnitude itself is the crucial factor. In this work, we conducted an in-depth investigation of cortical activity in two types of electrode montages used widely--the conventional (C)-tES and high-definition (HD)-tES--as well as two stimulation waveforms--direct current (DC) and alternating current (AC). To do so, we constructed a multi-scale model by coupling an anatomically realistic human head model and morphologically realistic multi-compartmental models of three types of cortical neurons (layer 2/3 pyramidal neuron, layer 4 basket cell, layer 5 pyramidal neuron). Then, we quantified the neuronal response to the C-/HD-tDCS/tACS and explored the relation between the electric field (EF) and the radial fields (RF: radial component of EF) magnitude and the cortical neurons threshold. The EF tES induced depended upon the electrode montage, and the neuronal responses were correlated with the EF rather than the RFs magnitude. The electrode montages and stimulation waveforms caused a small difference in threshold, but the higher correlation between the EFs magnitude and the threshold was consistent. Further, we observed that the neurons morphological features affected the degree of the correlation highly. Thus, the EF magnitude was a key factor in the responses of neurons with arborized axons. Our results demonstrate that the crucial factor in neuronal excitability depends upon the neuron models morphological and biophysical properties. Hence, to predict the cellular targets of NIBS precisely, it is necessary to adopt more advanced neuron models that mimic realistic morphological and biophysical features of actual human cells.

neuroscience↗

bioRxiv2021

Revealing the Physiological Origin of Event-Related Potentials using Electrocorticography in Humans

The scientific and clinical value of event-related potentials (ERPs) depends on understanding the contributions to them of three possible mechanisms: (1) additivity of time-locked voltage changes; (2) phase resetting of ongoing oscillations; (3) asymmetrical oscillatory activity. Their relative contributions are currently uncertain. This study uses analysis of human electrocorticographic activity to quantify the origins of movement-related potentials (MRPs) and auditory evoked potentials (AEPs). The results show that MRPs are generated primarily by endogenous additivity (88%). In contrast, P1 and N1 components of AEPs are generated almost entirely by exogenous phase reset (93%). Oscillatory asymmetry contributes very little. By clarifying ERP mechanisms, these results enable creation of ERP models; and they enhance the value of ERPs for understanding the genesis of normal and abnormal auditory or sensorimotor behaviors.

neuroscience↗

bioRxiv2019

Effect of sinusoidal electrical cortical stimulation on brain cells

BackgroundElectrical cortical stimulation is often used in patients with neurological disorders but it is unclear how it modulates different types of brain cells. ObjectiveThe aim of this study was to determine the effect of sinusoidal electrical brain stimulation (SEBS) on different types of brain cells and to identify the exact types of brain cells that are stimulated. MethodsThe study subjects were 40 male Sprague Dawley rats (weight 300-350 g; age 9 weeks). SEBS was delivered continuously at frequencies of 20, 40, 60, or 100 Hz to the sensory parietal cortex using epidurally placed electrodes for 1 week. Transverse rat brain tissue sections were immunolabeled with calmodulin-dependent protein kinase II and parvalbumin (PV) antibodies and with c-Fos for counting of activated excitatory and inhibitory neurons. Computer simulation was performed to cross-validate the frequency-specific cell stimulation results. ResultsInhibitory neurons were more excited than excitatory neurons after epidural EBS. Most excitatory neural activity was evoked at 40 Hz (p<0.05) and most inhibitory neuronal activity was evoked at 20 Hz (p<0.01). The contralateral sensory cortex was activated significantly more at 40 Hz (p<0.05) and the corticothalamic circuit at 20 Hz (p<0.001). Stimulation-induced excitatory and inhibitory neuronal activation was widest at 20 Hz. ConclusionsEpidural electrical stimulation targets both excitatory and inhibitory neurons and the related neural circuits. Further exploration is needed to identify circuits that promote the plasticity needed for recovery in patients with specific neurological diseases. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=90 SRC="FIGDIR/small/855395v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@3fbad8org.highwire.dtl.DTLVardef@3dad5org.highwire.dtl.DTLVardef@113fbe9org.highwire.dtl.DTLVardef@ffa066_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗