Standardized Low-resolution Brain Electromagnetic Tomography Research Articles

Decoding the Preparation Stage of Target Shooting under Audiovisual Restricted Conditions: Investigating Neural Mechanisms Using Microstate Analysis.

Shooting is a fine sport that is greatly influenced by mental state, and the neural activity of brain in the preparation stage of shooting has a direct influence on the level of shooting. In order to explore the brain neural mechanism in the preparation stage of pistol shooting under audiovisual restricted conditions, and to reveal the intrinsic relationship between brain activity and shooting behavior indicators, the electroencephalography (EEG) signals and seven shooting behaviors including shooting performance, gun holding stability, and firing stability, were experimentally captured from 30 shooters, these shooters performed pistol shooting under three conditions, normal, dim, and noisy. Using EEG microstates combined with standardized low-resolution brain electromagnetic tomography (sLORETA) traceability analysis method, we investigated the difference between the microstates characteristics under audiovisual restricted conditions and normal condition, the relationship between the microstates characteristics and the behavioral indicators during the shooting preparation stage under different conditions. The experimental results showed that microstate 1 corresponded to microstate A, microstate 2 corresponded to microstate B, and microstate 4 corresponded to microstate D; Microstate 3 was a unique template, which was localized in the occipital lobe, its function was to generate the "vision for action"; The dim condition significantly reduced the shooter's performance, whereas the noisy condition had less effect on the shooter's performance; In audiovisual restricted conditions, the microstate characteristics were significantly different from those in the normal condition. Microstate 4' parameters decreased significantly while microstate 3' parameters increased significantly under restricted visual and auditory conditions; Dim condition required more shooting skills from the shooter; There was a significant relationship between characteristics of microstates and indicators of shooting behavior; It was concluded that in order to obtain good shooting performance, shooters should improve attention and concentrate on the adjustment of collimator and target's center leveling relation, but the focus was slightly different in the three conditions; Microstates that are more important for accomplishing the task have less variation in their characteristics over time; Similar conclusions to previous studies were obtained at the same time, i.e., increased visual attention prior to shooting is detrimental to shooting performance, and there is a high positive correlation with microstate D for task completion. The experimental results further reveal the brain neural mechanism in the shooting preparation stage, and the extracted neural markers can be used as effective functional indicators for monitoring the brain state in the shooting preparation stage of pistols.

The neurological effects of acute physical exhaustion on inhibitory function

ObjectiveWe aimed to investigate the neural mechanisms underlying the inhibitory function performance of maritime Search and Rescue (SAR) personnel in states of physical exhaustion. BackgroundSAR missions pose serious challenges to the cognitive function of SAR personnel, especially in extreme environments and physical exhaustion. It is important to understand SAR personnel's cognitive performance and neural activity under exhaustion to improve the efficiency of task execution and ensure work safety. MethodTwenty-six maritime SAR personnel were recruited to simulate boat operations until they reached a self-imposed state of exhaustion. The exhaustion state was monitored by maximum heart rate and subjective fatigue scale. Two event-related potentials, N200 and P300, were measured during a Go-Nogo task before and after a session of acute exhaustive tasks. ResultsAfter exhaustion, a marked reduction in accuracy, a notable increase in N200 amplitude, and a substantial decline in P300 amplitude under the Nogo condition were observed compared to the baseline phase. Pre- and post-exhaustion comparisons using standardized low-resolution brain electromagnetic tomography revealed reduced activations in the right middle temporal gyrus's N200 component after exhaustion in SAR personnel during the Nogo condition. ConclusionThe results suggest that acute physical exhaustion significantly impacts the inhibition ability of SAR personnel, prolonging the conflict monitoring phase and weakening the response inhibition phase. These findings provide valuable insights into how physical exhaustion affects cognitive functions critical to the safety and effectiveness of SAR operations, and can inform strategies to improve training and equipment to enhance performance under extreme conditions.

Effects of transcranial direct current stimulation on brain activity and cortical functional connectivity in children with autism spectrum disorders.

Transcranial direct current stimulation (tDCS) has emerged as a therapeutic option to mitigate symptoms in individuals with autism spectrum disorder (ASD). Our study investigated the effects of a two-week regimen of tDCS targeting the left dorsolateral prefrontal cortex (DLPFC) in children with ASD, examining changes in rhythmic brain activity and alterations in functional connectivity within key neural networks: the default mode network (DMN), sensorimotor network (SMN), and dorsal attention network (DAN). We enrolled twenty-six children with ASD and assigned them randomly to either an active stimulation group (n=13) or a sham stimulation group (n=13). The active group received tDCS at an intensity of 1mA to the left DLPFC for a combined duration of 10 days. Differences in electrical brain activity were pinpointed using standardized low-resolution brain electromagnetic tomography (sLORETA), while functional connectivity was assessed via lagged phase synchronization. Compared to the typically developing children, children with ASD exhibited lower current source density across all frequency bands. Post-treatment, the active stimulation group demonstrated a significant increase in both current source density and resting state network connectivity. Such changes were not observed in the sham stimulation group. tDCS targeting the DLPFC may bolster brain functional connectivity in patients with ASD, offering a substantive groundwork for potential clinical applications.

Semiautomated electric source imaging determines epileptogenicity of encephaloceles in temporal lobe epilepsy.

We aimed to assess the ability of semiautomated electric source imaging (ESI) from long-term video-electroencephalographic (EEG) monitoring (LTM) to determine the epileptogenicity of temporopolar encephaloceles (TEs) in patients with temporal lobe epilepsy. We conducted a retrospective study involving 32 temporal lobe epilepsy patients with TEs as potentially epileptogenic lesions in structural magnetic resonance imaging scans. Findings were validated through invasive intracerebral stereo-EEG in six of 32 patients and postsurgical outcome after tailored resection of the TE in 17 of 32 patients. LTM (mean duration = 6 days) was performed using the 10/20 system with additional T1/T2 for all patients and sphenoidal electrodes in 23 of 32 patients. Semiautomated detection and clustering of interictal epileptiform discharges (IEDs) were carried out to create IED types. ESI was performed on the averages of the two most frequent IED types per patient, utilizing individual head models, and two independent inverse methods (sLORETA [standardized low-resolution brain electromagnetic tomography], MUSIC [multiple signal classification]). ESI maxima concordance and propagation in spatial relation to TEs were quantified for sources with good signal quality (signal-to-noise ratio > 2, explained signal > 60%). ESI maxima correctly colocalized with a TE in 20 of 32 patients (62.5%) either at the onset or half-rising flank of at least one IED type per patient. ESI maxima showed propagation from the temporal pole to other temporal or extratemporal regions in 14 of 32 patients (44%), confirming propagation originating in the area of the TE. The findings from both inverse methods validated each other in 14 of 20 patients (70%), and sphenoidal electrodes exhibited the highest signal amplitudes in 17 of 23 patients (74%). The concordance of ESI with the TE predicted a seizure-free postsurgical outcome (Engel I vs. >I) with a diagnostic odds ratio of 2.1. Semiautomated ESI from LTM often successfully identifies the epileptogenicity of TEs and the IED onset zone within the area of the TEs. Additionally, it shows potential predictive power for postsurgical outcomes in these patients.

Sensory Gating Networks in Normal-Hearing Adults With Minimal Tinnitus.

The goal of this study was to observe sensory gating-related networks underlying cortical auditory evoked potential (CAEP) peak components in individuals with and without minimal tinnitus, as measured using the Tinnitus Handicap Inventory (THI). This analysis was performed on previously published sensory gating responses in normal-hearing adults with and without minimal tinnitus. Independent component analysis was performed for each individual CAEP gating component (Pa, P50, N1, and P2). Significant components were retained for source localization analyses within the following groups: no tinnitus, tinnitus with a THI score ≤ 6, and tinnitus with a THI score > 6. Brain source localization was performed on the gating difference wave for each component using standardized low-resolution brain electromagnetic tomography. Gating-related networks were identified within each group. Different regional sources were observed between groups, with parietal sources underlying the Pa and P50 components as tinnitus severity increased. A larger prefrontal regional activation was also shown for the N1 gating component as tinnitus severity increased. These results expand upon the functional gating responses via CAEP waveforms in a previously published study. The auditory gating response, as measured via CAEPs, has previously been shown to significantly correlate with an increase in tinnitus severity in adults with normal hearing. The corresponding changes in the gating response appear to be supported by different cortical regions in those without tinnitus, those with a THI score ≤ 6, and those with a THI score > 6. Next, functional differences between localized cortical regions should be tested.

EEG Source Localization in Temporal Encephaloceles: Concordance With Surgical Resection and Clinical Outcomes.

Temporal encephaloceles are a cause of drug-resistant temporal lobe epilepsy; however, their relationship with epileptogenesis is unclear, and optimal surgical resection is uncertain. EEG source localization (ESL) may guide surgical decision-making. We reviewed patients at Mayo Clinic Rochester with drug-resistant temporal lobe epilepsy and temporal encephaloceles, who underwent limited resection and had 1-year outcomes. EEG source localization was performed using standard density scalp EEG of ictal and interictal activity. Distance from dipole and standardized low-resolution brain electromagnetic tomography (sLORETA) solutions to the encephalocele were measured. Concordance of ESL with encephalocele and surgical resection was compared with 1-year surgical outcomes. Seventeen patients met criteria. The mean distances from ESL results to encephalocele center for dipole and sLORETA analyses were 23 mm (SD 9) and 22 mm (SD 11), respectively. Ten patients (55.6%) had Engel I outcomes at 1 year. Dipole-encephalocele distance and sLORETA-encephalocele distance were significantly longer in patients with Engel I outcome and patients whose encephalocele was contained by sLORETA had worse outcome as well; however, multiple logistic regression analysis found that only containment of encephalocele by the sLORETA current density was significant (P < 0.05), odds ratio 0.12 (95% confidence interval [0.021, 0.71]). EEG source localization of scalp EEG localizes near encephaloceles, however, typically not in the encephalocele itself; this may be due to scalp EEG sampling propagated activity or alternatively that the seizure onset zone extends beyond the herniated cortex. Surprisingly, we observed increased ESL to encephalocele distances in patients with excellent surgical outcomes. Larger cohort studies including intracranial EEG data are needed to further explore this finding.

Effects of Robot-Assisted Activity Using a Communication Robot on Neurological Activity in Older Adults with and without Cognitive Decline.

Robot-assisted activity (RAA) using a communication robot (RAA-CR) has been proposed as a tool for alleviating behavioral and psychological symptoms accompanying dementia (BPSD) in patients with cognitive decline. This study aimed to clarify the effects of differences in cognitive function among older adults on changes in active brain areas induced by RAA-CR. Twenty-nine older adults were divided into a cognitive decline group (n = 11) and a control group (n = 18). The participants individually received a 5-minute RAA session, and their resting EEG activity was measured before and after the session. Brain spatial analysis was performed on recorded EEG data using standardized low-resolution brain electromagnetic tomography. In addition, statistical comparisons of neural activity in the brain were made before and after RAA-CR and between the cognitively impaired and control groups. These results suggest that RAA-CR stimulates neural activity in the region centered on the posterior cingulate gyrus and precuneus in cognitively healthy older adults but does not significantly alter brain neural activity in cognitively impaired older adults. Therefore, modifications to the implementation methods may be necessary to effectively implement RAA-CR in cognitively impaired individuals.

Source Aware Deep Learning Framework for Hand Kinematic Reconstruction Using EEG Signal.

The ability to reconstruct the kinematic parameters of hand movement using noninvasive electroencephalography (EEG) is essential for strength and endurance augmentation using exoskeleton/exosuit. For system development, the conventional classification-based brain-computer interface (BCI) controls external devices by providing discrete control signals to the actuator. A continuous kinematic reconstruction from EEG signal is better suited for practical BCI applications. The state-of-the-art multivariable linear regression (mLR) method provides a continuous estimate of hand kinematics, achieving a maximum correlation of up to 0.67 between the measured and the estimated hand trajectory. In this work, three novel source aware deep learning models are proposed for motion trajectory prediction (MTP). In particular, multilayer perceptron (MLP), convolutional neural network-long short-term memory (CNN-LSTM), and wavelet packet decomposition (WPD) for CNN-LSTM are presented. In addition, novelty in the work includes the utilization of brain source localization (BSL) [using standardized low-resolution brain electromagnetic tomography (sLORETA)] for the reliable decoding of motor intention. The information is utilized for channel selection and accurate EEG time segment selection. The performance of the proposed models is compared with the traditionally utilized mLR technique on the reach, grasp, and lift (GAL) dataset. The effectiveness of the proposed framework is established using the Pearson correlation coefficient (PCC) and trajectory analysis. A significant improvement in the correlation coefficient is observed when compared with the state-of-the-art mLR model. Our work bridges the gap between the control and the actuator block, enabling real-time BCI implementation.

Relationship between Loudness Dependence of Auditory-evoked Potentials and Suicidality.

: Serotonin concentration is associated with suicide in patients with major depressive disorder. Loudness dependence of auditory-evoked potentials (LDAEPs), a representative neurophysiological indicator, is related to serotonin activity. Therefore, this study aimed to investigate the relationship between LDAEPs and suicidal ideation, suicide attempts, and the severity of depression. : We evaluated the scalp N1, P2, and N1/P2 LDAEPs along with standardized low-resolution brain electromagnetic tomography (sLORETA)-localized N1, P2, and N1/P2 LDAEPs of 221 patients with major depressive disorder. The demographic and clinical data of the patients, including data on suicidal ideation and previous suicide attempts, were obtained from clinical interviews and medical records. The severity of depression was assessed using the Beck Depression Inventory and Hamilton Depression Rating Scale, whereas suicidal ideation was evaluated using the Beck Scale for Suicidal Ideation (BSS). : The total BSS score was associated with low N1/P2 LDAEP (p = 0.045), whereas P2 sLORETA-LDAEP was associated with lower previous suicide attempts (p = 0.043). In addition, suicide attempt was correlated with an elevated P2 left sLORETA-LDAEP (coefficient = 4.638, p = 0.038). : These findings suggest that suicidal ideation is associated with decreased LDAEP, whereas suicide attempt is associated with increased LDAEP.

In silico study of the effects of cerebral circulation on source localization using a dynamical anatomical atlas of the human head

Objective. This study focuses on the effects of dynamical vascular modeling on source localization errors in electroencephalography (EEG). Our aim of this in silico study is to (a) find out the effects of cerebral circulation on the accuracy of EEG source localization estimates, and (b) evaluate its relevance with respect to measurement noise and interpatient variation. Approach. We employ a four-dimensional (3D + T) statistical atlas of the electrical properties of the human head with a cerebral circulation model to generate virtual patients with different cerebral circulatory conditions for EEG source localization analysis. As source reconstruction techniques, we use the linearly constraint minimum variance (LCMV) beamformer, standardized low-resolution brain electromagnetic tomography (sLORETA), and the dipole scan (DS). Main results. Results indicate that arterial blood flow affects source localization at different depths and with varying significance. The average flow rate plays an important role in source localization performance, while the pulsatility effects are very small. In cases where a personalized model of the head is available, blood circulation mismodeling causes localization errors, especially in the deep structures of the brain where the main cerebral arteries are located. When interpatient variations are considered, the results show differences up to 15 mm for sLORETA and LCMV beamformer and 10 mm for DS in the brainstem and entorhinal cortices regions. In regions far from the main arteries vessels, the discrepancies are smaller than 3 mm. When measurement noise is added and interpatient differences are considered in a deep dipolar source, the results indicate that the effects of conductivity mismatch are detectable even for moderate measurement noise. The signal-to-noise ratio limit for sLORETA and LCMV beamformer is 15 dB, while the limit is under 30 dB for DS. Significance. Localization of the brain activity via EEG constitutes an ill-posed inverse problem, where any modeling uncertainty, e.g. a slight amount of noise in the data or material parameter discrepancies, can lead to a significant deviation of the estimated activity, especially in the deep structures of the brain. Proper modeling of the conductivity distribution is necessary in order to obtain an appropriate source localization. In this study, we show that the conductivity of the deep brain structures is particularly impacted by blood flow-induced changes in conductivity because large arteries and veins access the brain through that region.

Is Functional Connectivity after a First Unprovoked Seizure Different Based on Subsequent Seizures and Future Diagnosis of Epilepsy?

There are no highly sensitive biomarkers for epilepsy to date. Recently, promising results regarding functional connectivity analysis have been obtained, which may improve epilepsy diagnosis even in the absence of visible abnormality in electroencephalography. We aimed to investigate the differences in functional connectivity after a first unprovoked seizure between patients diagnosed with epilepsy within 1 year due to subsequent seizures and those who were not. We compared quantitative electroencephalography power spectra and functional connectivity between 12 patients who were diagnosed with epilepsy (two or more unprovoked seizures) within 1 year and 17 controls (those not diagnosed within 1 year) using iSyncBrain® (iMediSync Inc., Suwon, Korea; https://isyncbrain.com/). In the source-level analysis, the current distribution across the brain was assessed using the standardized low-resolution brain electromagnetic tomography technique, to compare relative power values in 68 regions of interest and connectivity (the imaginary part of coherency) between regions of interest. In the epilepsy group, quantitative electroencephalography showed lower alpha2 band power in left frontal, central, superior temporal, and parietal regions and higher beta2 power in both frontal, central, temporal, occipital, and left parietal regions compared with the control group. Additionally, epilepsy patients had significantly lower connectivity in alpha2 and beta2 bands than the controls. Patients experiencing their first unprovoked seizure presented different brain function according to whether they have subsequent seizures and future epilepsy. Our results propose the potential clinical ability to diagnose epilepsy after the first unprovoked seizure in the absence of interictal epileptiform discharges.

Is Functional Connectivity after a First Unprovoked Seizure Different Based on Subsequent Seizures and Future Diagnosis of Epilepsy?

Background and Purpose: There are no highly sensitive biomarkers for epilepsy to date. Recently, promising results regarding functional connectivity analysis have been obtained, which may improve epilepsy diagnosis even in the absence of visible abnormality in electroencephalography. We aimed to investigate the differences in functional connectivity after a first unprovoked seizure between patients diagnosed with epilepsy within 1 year due to subsequent seizures and those who were not.Methods: We compared quantitative electroencephalography power spectra and functional connectivity between 12 patients who were diagnosed with epilepsy (two or more unprovoked seizures) within 1 year and 17 controls (those not diagnosed within 1 year) using iSyncBrain&lt;sup&gt;®&lt;/sup&gt; (iMediSync Inc., Suwon, Korea; https://isyncbrain.com/). In the source-level analysis, the current distribution across the brain was assessed using the standardized low-resolution brain electromagnetic tomography technique, to compare relative power values in 68 regions of interest and connectivity (the imaginary part of coherency) between regions of interest.Results: In the epilepsy group, quantitative electroencephalography showed lower alpha2 band power in left frontal, central, superior temporal, and parietal regions and higher beta2 power in both frontal, central, temporal, occipital, and left parietal regions compared with the control group. Additionally, epilepsy patients had significantly lower connectivity in alpha2 and beta2 bands than the controls.Conclusions: Patients experiencing their first unprovoked seizure presented different brain function according to whether they have subsequent seizures and future epilepsy. Our results propose the potential clinical ability to diagnose epilepsy after the first unprovoked seizure in the absence of interictal epileptiform discharges.

Sensory Inhibition and Speech Perception-in-Noise Performance in Children With Normal Hearing.

This study investigated whether sensory inhibition in children may be associated with speech perception-in-noise performance. Additionally, gating networks associated with sensory inhibition were identified via standardized low-resolution brain electromagnetic tomography (sLORETA), and the detectability of the cortical auditory evoked potential (CAEP) N1 response was enhanced using a 4- to 30-Hz bandpass filter. CAEP gating responses, reflective of inhibition, were evoked via click pairs and recorded using high-density electroencephalography in neurotypical 5- to 8-year-olds and 22- to 24-year-olds. Amplitude gating indices were calculated and correlated with speech perception in noise. Gating generators were estimated using sLORETA. A 4- to 30-Hz filter was applied to detect the N1 gating component. Preliminary findings indicate children showed reduced gating, but there was a correlational trend between better speech perception and decreased N2 gating. Commensurate with decreased gating, children presented with incomplete compensatory gating networks. The 4- to 30-Hz filter identified the N1 response in a subset of children. There was a tenuous relationship between children's speech perception and sensory inhibition. This may suggest that sensory inhibition is only implicated in atypically poor speech perception. Finally, the 4- to 30-Hz filter settings are critical in N1 detectability. Gating may help evaluate reduced sensory inhibition in children with clinically poor speech perception using the appropriate methodology. Cortical gating generators in typically developing children are also newly identified.

Functional brain changes using electroencephalography after a 24-week multidomain intervention program to prevent dementia.

Quantitative electroencephalography (QEEG) has proven useful in predicting the response to various treatments, but, until now, no study has investigated changes in functional connectivity using QEEG following a lifestyle intervention program. We aimed to investigate neurophysiological changes in QEEG after a 24-week multidomain lifestyle intervention program in the SoUth Korean study to PrEvent cognitive impaiRment and protect BRAIN health through lifestyle intervention in at-risk elderly people (SUPERBRAIN). Participants without dementia and with at least one modifiable dementia risk factor, aged 60–79 years, were randomly assigned to the facility-based multidomain intervention (FMI) (n = 51), the home-based multidomain intervention (HMI) (n = 51), and the control group (n = 50). The analysis of this study included data from 44, 49, and 34 participants who underwent EEG at baseline and at the end of the study in the FMI, HMI, and control groups, respectively. The spectrum power and power ratio of EEG were calculated. Source cortical current density and functional connectivity were estimated by standardized low-resolution brain electromagnetic tomography. Participants who received the intervention showed increases in the power of the beta1 and beta3 bands and in the imaginary part of coherence of the alpha1 band compared to the control group. Decreases in the characteristic path lengths of the alpha1 band in the right supramarginal gyrus and right rostral middle frontal cortex were observed in those who received the intervention. This study showed positive biological changes, including increased functional connectivity and higher global efficiency in QEEG after a multidomain lifestyle intervention.Clinical trial registration[https://clinicaltrials.gov/ct2/show/NCT03980392] identifier [NCT03980392].

Improvement in magnetic nanoparticle tomography estimation accuracy by combining sLORETA and non-negative least squares methods

Imaging methods that can detect biofunctionalized magnetic nanoparticles (MNPs) accumulated at cancerous tumor sites are expected to be part of the in vivo cancer diagnostic techniques. An imaging technique called magnetic nanoparticle tomography (MNT), which uses a magnetic sensor array, has been proposed. High sensitivity and spatial resolution were achieved using the non-negative least-squares (NNLS) inverse solution in MNT. However, owing to the presence of measurement noise, the concentration and position of certain MNPs were estimated inaccurately, i.e., artifacts were generated. To overcome this issue, this study first applied standardized low-resolution brain electromagnetic tomography (sLORETA), a spatial filter method with no location bias, to approximate the position of MNPs. The region of analysis was restricted to where the estimated value exceeded the threshold. Subsequently, the NNLS method was applied to estimate the concentration and position of MNPs in the restricted region. In the experiment, two Resovist MNP samples (300 or 500 μgFe) were arranged at a distance of 25–502 mm, and the concentration and position estimation were performed. The estimation results demonstrated that the proposed method successfully suppresses artifacts and adequately estimates the concentration and position of MNPs within a position error of 10 mm and a concentration error of 20 %.

EEG resting-state functional connectivity: evidence for an imbalance of external/internal information integration in autism

BackgroundAutism spectrum disorder (ASD) is associated with atypical neural activity in resting state. Most of the studies have focused on abnormalities in alpha frequency as a marker of ASD dysfunctions. However, few have explored alpha synchronization within a specific interest in resting-state networks, namely the default mode network (DMN), the sensorimotor network (SMN), and the dorsal attention network (DAN). These functional connectivity analyses provide relevant insight into the neurophysiological correlates of multimodal integration in ASD.MethodsUsing high temporal resolution EEG, the present study investigates the functional connectivity in the alpha band within and between the DMN, SMN, and the DAN. We examined eyes-closed EEG alpha lagged phase synchronization, using standardized low-resolution brain electromagnetic tomography (sLORETA) in 29 participants with ASD and 38 developing (TD) controls (age, sex, and IQ matched).ResultsWe observed reduced functional connectivity in the ASD group relative to TD controls, within and between the DMN, the SMN, and the DAN. We identified three hubs of dysconnectivity in ASD: the posterior cingulate cortex, the precuneus, and the medial frontal gyrus. These three regions also presented decreased current source density in the alpha band.ConclusionThese results shed light on possible multimodal integration impairments affecting the communication between bottom-up and top-down information. The observed hypoconnectivity between the DMN, SMN, and DAN could also be related to difficulties in switching between externally oriented attention and internally oriented thoughts.

Attachment style dimensions are associated with neural activation during projection of mental states.

The aim of the present study was to investigate the association between attachment dimensions and neural correlates in response to the Rorschach inkblots. Twenty-seven healthy volunteers were recruited for the electroencephalographic registration during a visual presentation of the Rorschach inkblots and polygonal shapes. The Attachment Style Questionnaire (ASQ) was administered to participants. Correlations between the ASQ scores and standardized low-resolution brain electromagnetic tomography (sLORETA) intensities were performed. The Rorschach inkblots elicited several projective responses greater than the polygonal shapes (distortions, human and total movements, and embellishments). Only during the Rorschach inkblots presentation, discomfort with closeness and relationships as secondary subscales were negatively correlated with the activation of right hippocampus, parahippocampus, amygdala, and insula; need for approval subscale was negatively correlated with the activation of orbital and prefrontal cortex and left hippocampus. Moreover, the correlations between attachment dimensions and neural activation during the Rorschach inkblots were significantly higher compared to the same correlations in response to polygonal shapes. These findings suggest that attachment style can modulate brain activation during the projective activity of the Rorschach inkblots.

Research on Top Archer’s EEG Microstates and Source Analysis in Different States

The electroencephalograph (EEG) microstate is a method used to describe the characteristics of the EEG signal through the brain scalp electrode potential’s spatial distribution; as such, it reflects the changes in the brain’s functional state. The EEGs of 13 elite archers from China’s national archery team and 13 expert archers from China’s provincial archery team were recorded under the alpha rhythm during the resting state (with closed eyes) and during archery aiming. By analyzing the differences between the EEG microstate parameters and the correlation between these parameters with archery performance, as well as by combining our findings through standardized low-resolution brain electromagnetic tomography source analysis (sLORETA), we explored the changes in the neural activity of professional archers of different levels, under different states. The results of the resting state study demonstrated that the duration, occurrence, and coverage in microstate D of elite archers were significantly higher than those of expert archers and that their other microstates had the greatest probability of transferring to microstate D. During the archery aiming state, the average transition probability of the other microstates transferring to microstate in the left temporal region was the highest observed in the two groups of archers. Moreover, there was a significant negative correlation between the duration and coverage of microstates in the frontal region of elite archers and their archery performance. Our findings indicate that elite archers are more active in the dorsal attention system and demonstrate a higher neural efficiency during the resting state. When aiming, professional archers experience an activation of brain regions associated with archery by suppressing brain regions unrelated to archery tasks. These findings provide a novel theoretical basis for the study of EEG microstate dynamics in archery and related cognitive motor tasks, particularly from the perspective of the subject’s mental state.

Abnormal brain oscillations and activation of patients with heroin use disorder during emotion regulation: The role of delta- and theta-band power

BackgroundEmotion dysregulation is a crucial component of substance use disorders in predisposition, maintenance, and relapse. Emotional regulation strategies are an important factor in emotion dysregulation. However, studies on heroin use disorder (HUD) patients' ability to use emotion regulation strategies are scarce. MethodsTime-frequency-based analyses were used to compare the power of 33 patients with HUD and 28 healthy controls to elucidate whether patients with HUD have abnormal neural oscillations during passive viewing and emotion regulation strategies. Using the standardized low-resolution brain electromagnetic tomography algorithm (sLORETA), we estimated the possible sources of the anomalous band power. ResultsCompared to patients with HUD, healthy controls showed a stronger decrease in the power of the delta/theta band across all task conditions. The effect peaked at approximately 1300–1900 ms after stimulus onset and varied by task condition. The estimation of sLORETA suggested the frontal, parietal, and limbic lobes as possible generators. LimitationsWe cannot exclude the potential influence of additional factors, such as sex, depression and anxiety levels, and polysubstance use, on the results. ConclusionsPatients with HUD have blunted arousal and impaired ability to use emotion regulation strategies. The abnormal patterns described above may be the underlying neurophysiological basis for this dysfunction. Future studies could combine different approaches to improve emotion dysregulation in patients with HUD to promote treatment outcomes.

A clinical trial of a patient-customized virtual reality intervention for tinnitus

Virtual reality (VR) has recently been used as a clinical treatment because it can efficiently simulate situations that are difficult to control in real-world settings. In our study, we assessed the potential of VR in patients with chronic subjective tinnitus. An evaluation of its clinical benefits was performed based on analyses of patient electroencephalograms (EEGs) and by questionnaire responses after 6–8 weeks of patient involvement in our VR-based alleviation program. Clinical trials were performed at a tertiary academic hospital. Nineteen patients (aged 33–64 years) who visited our hospital with chronic subjective tinnitus over 3 months were enrolled in the study. The intervention consisted of trashing the tinnitus avatar in VR. We expected that the patients would have the subjective feeling of controlling tinnitus through our intervention. The VR environment comprised four different sessions in four different settings: a bedroom, a living room, a restaurant, and a city street. We analyzed changes in the source activities of the prefrontal regions related to tinnitus in these patients using standardized low-resolution brain electromagnetic tomography. The Tinnitus Handicap Inventory (THI), the total score (from 50.11 to 44.21, P = 0.046) and the grade (from 3.16 to 2.79, P = 0.035) were significantly improved after the VR-based tinnitus treatment program (P < 0.05). The Pittsburgh Sleep Quality Index also showed improved outcomes (P = 0.025). On the other hand, a Tinnitus Handicap Questionnaire, Quality of Life Assessment (WHO-QOL), Hospital Anxiety and Depression Scale, Profile of Mood States revealed no significant change after the intervention. The baseline EEG data showed that brain activity in the orbitofrontal cortex significantly increased in the alpha and theta frequency bands. Furthermore, patients who showed a THI score improvement after the intervention showed specific increases in brain activity for the theta and high beta bands in the orbitofrontal cortex. Our findings suggest that the virtual reality-based program, as in parts of cognitive behavioral treatment, may help to alleviate tinnitus-related distress in patients with chronic subjective tinnitus.