Brain Topography最新文献

Transcutaneous auricular vagus nerve stimulation (taVNS), a non-invasive form of electrical brain stimulation, has shown potent therapeutic potential for a wide spectrum of conditions. How taVNS influences the characterization of motion sickness - a long mysterious syndrome with a polysymptomatic onset - remains unclear. Here, to examine taVNS-induced effects on brain function in response to motion-induced nausea, 64-channel electroencephalography (EEG) recordings from 42 healthy participants were analyzed; collected during nauseogenic visual stimulation concurrent with taVNS administration, in a crossover randomized sham-controlled study. Cortical neuronal generators were estimated from the obtained EEG using exact low-resolution brain electromagnetic tomography (eLORETA). While both sham and taVNS increased insula activation during electrical stimulation, compared to baseline, taVNS additionally augmented middle frontal gyrus neuronal activity. Following taVNS, brain regions including the supramarginal, parahippocampal, and precentral gyri were activated. Contrasting sham, taVNS markedly increased activity in the middle occipital gyrus during stimulation. A repeated-measures ANOVA showed that taVNS reduced motion sickness symptoms. This reduction in symptoms correlated with taVNS-induced neural activation. Our findings provide new insights into taVNS-induced brain changes, during and after nauseogenic stimuli exposure, including accompanying behavioral response. Together, these findings suggest that taVNS has promise as an effective neurostimulation tool for motion sickness management.

White matter dissection (WMD) involves isolating bundles of myelinated axons in the brain and serves to gain insights into brain function and neural mechanisms underlying neurological disorders. While effective, cadaveric brain dissections pose certain challenges mainly due to availability of resources. Technological advancements, such as photogrammetry, have the potential to overcome these limitations by creating detailed three-dimensional (3D) models for immersive learning experiences in neuroanatomy. This study aimed to provide a detailed step-by-step WMD captured using two-dimensional (2D) images and 3D models (via photogrammetry) to serve as a comprehensive guide for studying white matter tracts of the brain. One formalin-fixed brain specimen was utilized to perform the WMD. The brain was divided in a sagittal plane and both cerebral hemispheres were stored in a freezer at -20 °C for 10 days, then thawed under running water at room temperature. Micro-instruments under an operating microscope were used to perform a systematic lateral-to-medial and medial-to-lateral dissection, while 2D images were captured and 3D models were created through photogrammetry during each stage of the dissection. Dissection was performed with comprehensive examination of the location, main landmarks, connections, and functions of the white matter tracts of the brain. Furthermore, high-quality 3D models of the dissections were created and housed on SketchFab^®, allowing for accessible and free of charge viewing for educational and research purposes. Our comprehensive dissection and 3D models have the potential to increase understanding of the intricate white matter anatomy and could provide an accessible platform for the teaching of neuroanatomy.

Semantic verbal fluency (SVF) impairment is present in several neurological disorders. Although activation in SVF-related areas has been reported, how these regions are connected and their functional roles in the network remain divergent. We assessed SVF static and dynamic functional connectivity (FC) and effective connectivity in healthy participants using functional magnetic resonance imaging. We observed activation in the inferior frontal (IFG), middle temporal (pMTG) and angular gyri (AG), anterior cingulate (AC), insular cortex, and regions of the superior, middle, and medial frontal gyri (SFG, MFG, MidFG). Our static FC analysis showed a highly interconnected task and resting state network. Increased connectivity of AC with the pMTG and AG was observed for the task. The dynamic FC analysis provided circuits with connections similarly modulated across time and regions related to category identification, language comprehension, word selection and recovery, word generation, inhibition of speaking, speech planning, and articulatory planning of orofacial movements. Finally, the effective connectivity analysis provided a network that best explained our data, starting at the AG and going to the pMTG, from which there was a division between the ventral and dorsal streams. The SFG and MFG regions were connected and modulated by the MidFG, while the inferior regions formed the ventral stream. Therefore, we successfully assessed the SVF network, exploring regions associated with the entire processing, from category identification to word generation. The methodological approach can be helpful for further investigation of the SVF network in neurological disorders.

Microstates are transient scalp configurations of brain activity measured by electroencephalography (EEG). The application of microstate analysis in magnetoencephalography (MEG) data remains challenging. In one MEG dataset (N = 113), we aimed to identify MEG microstates at rest, explore their brain sources, and relate them to changes in brain activity during open-eyes (ROE) or closed-eyes resting state (RCE) and an auditory Mismatch Negativity (MMN) task. In another dataset of simultaneously recorded EEG-MEG data (N = 21), we investigated the association between MEG and EEG microstates. Six MEG microstates (mMS) provided the best clustering of resting-state activity, each linked to different brain sources: mMS 1-2: left/right occipito-parietal; mMS 3: fronto-temporal; mMS 4: centro-medial; mMS 5-6: left/right fronto-parietal. Increases in occipital alpha power in RCE relative to ROE correlated with greater mMS 1-2 time coverage (τ_bs < 0.20, ps > .002), while the lateralization of deviance detection in MMN was associated with mMS 5-6 time coverage (τ_bs < 0.16, ps > .012). No temporal correlation was found between EEG and MEG microstates (ps > .05), despite some overlap in brain sources and global explained variance between mMS 2-3 and EEG microstates B-C (rs > 0.60, ps < .002). Hence, the MEG signal can be decomposed into microstates, but mMS brain activity clustering captures phenomena different from EEG microstates. Source reconstruction and task-related modulations link mMS to large-scale networks and localized activities. Thus, mMSs offer insights into brain dynamics and task-specific processes, complementing EEG microstates in studying physiological and dysfunctional brain activity.

Methamphetamine (MA) is a neurological drug, which is harmful to the overall brain cognitive function when abused. Based on this property of MA, people can be divided into those with MA abuse and healthy people. However, few studies to date have investigated automatic detection of MA abusers based on the neural activity. For this reason, the purpose of this research was to investigate the difference in the neural activity between MA abusers and healthy persons and accordingly discriminate MA abusers. First, we performed event-related potential (ERP) analysis to determine the time range of P300. Then, the wavelet coefficients of the P300 component were extracted as the main features, along with the time and frequency domain features within the selected P300 range to classify. To optimize the feature set, F_score was used to remove features below the average score. Finally, a Bidirectional Long Short-term Memory (BiLSTM) network was performed for classification. The experimental result showed that the detection accuracy of BiLSTM could reach 83.85%. In conclusion, the P300 component of EEG signals of MA abusers is different from that in normal persons. Based on this difference, this study proposes a novel way for the prevention and diagnosis of MA abuse.

Functional near-infrared spectroscopy (fNIRS), a non-invasive optical neuroimaging technique that is portable and acoustically silent, has become a promising tool for evaluating auditory brain functions in hearing-vulnerable individuals. This study, for the first time, used fNIRS to evaluate neuroplasticity of speech-in-noise processing in older adults. Ten older adults, most of whom had moderate-to-mild hearing loss, participated in a 4-week speech-in-noise training. Their speech-in-noise performances and fNIRS brain responses to speech (auditory sentences in noise), non-speech (spectrally-rotated speech in noise) and visual (flashing chequerboards) stimuli were evaluated pre- (T0) and post-training (immediately after training, T1; and after a 4-week retention, T2). Behaviourally, speech-in-noise performances were improved after retention (T2 vs. T0) but not immediately after training (T1 vs. T0). Neurally, we intriguingly found brain responses to speech vs. non-speech decreased significantly in the left auditory cortex after retention (T2 vs. T0 and T2 vs. T1) for which we interpret as suppressed processing of background noise during speech listening alongside the significant behavioural improvements. Meanwhile, functional connectivity within and between multiple regions of temporal, parietal and frontal lobes was significantly enhanced in the speech condition after retention (T2 vs. T0). We also found neural changes before the emergence of significant behavioural improvements. Compared to pre-training, responses to speech vs. non-speech in the left frontal/prefrontal cortex were decreased significantly both immediately after training (T1 vs. T0) and retention (T2 vs. T0), reflecting possible alleviation of listening efforts. Finally, connectivity was significantly decreased between auditory and higher-level non-auditory (parietal and frontal) cortices in response to visual stimuli immediately after training (T1 vs. T0), indicating decreased cross-modal takeover of speech-related regions during visual processing. The results thus showed that neuroplasticity can be observed not only at the same time with, but also before, behavioural changes in speech-in-noise perception. To our knowledge, this is the first fNIRS study to evaluate speech-based auditory neuroplasticity in older adults. It thus provides important implications for current research by illustrating the promises of detecting neuroplasticity using fNIRS in hearing-vulnerable individuals.

Changes in brain oscillatory activity are commonly used as biomarkers both in cognitive neuroscience and in neuropsychiatric conditions. However, little is known about how its profile changes across maturation. Here we use regression models to characterize magnetoencephalography power changes within classical frequency bands in a sample of 792 healthy participants, covering the range 13 to 80 years old. Our findings unveil complex, non-linear power trajectories that defy the traditional linear paradigm, with notable cortical region variations. Interestingly, slow wave activity increases correlate with improved cognitive performance throughout life and larger gray matter volume in the elderly. Conversely, fast wave activity diminishes in adulthood. Elevated low-frequency activity during aging, traditionally seen as compensatory, may also signify neural deterioration. This dual interpretation, highlighted by our study, reveals the intricate dynamics between brain oscillations, cognitive performance, and aging. It advances our understanding of neurodevelopment and aging by emphasizing the regional specificity and complexity of brain rhythm changes, with implications for cognitive and structural integrity.

The ability to comprehend the intention conveyed through human body movements is crucial for effective interpersonal interactions. If people can't understand the intention behind other individuals' isolated or interactive actions, their actions will become meaningless. Psychologists have investigated the cognitive processes and neural representations involved in understanding action intention, yet a cohesive theoretical explanation remains elusive. Hence, we mainly review existing literature related to neural correlates of action intention, and primarily propose a putative Three-stage Dynamic Brain-cognitive Model of understanding action intention, which involves body perception, action identification and intention understanding. Specifically, at the first stage, body parts/shapes are processed by those brain regions such as extrastriate and fusiform body areas; During the second stage, differentiating observed actions relies on configuring relationships between body parts, facilitated by the activation of the Mirror Neuron System; The last stage involves identifying various intention categories, utilizing the Mentalizing System for recruitment, and different activation patterns concerning the nature of the intentions participants dealing with. Finally, we delves into the clinical practice, like intervention training based on a theoretical model for individuals with autism spectrum disorders who encounter difficulties in interpersonal communication.

Most Event Related Potential studies investigating the time course of visual processing have focused mainly on the N170 component. Stimulus orientation affects the N170 amplitude for faces but not for objects, a finding interpreted as reflecting holistic/configural processing for faces and featural processing for objects. Furthermore, while recent studies suggest where on the face people fixate impacts the N170, fixation location effects have not been investigated in objects. A data-driven mass univariate analysis (all time points and electrodes) was used to investigate the time course of inversion and fixation location effects on the neural processing of faces and houses. Strong and widespread orientation effects were found for both faces and houses, from 100-350ms post-stimulus onset, including P1 and N170 components, and later, a finding arguing against a lack of holistic processing for houses. While no clear fixation effect was found for houses, fixation location strongly impacted face processing early, reflecting retinotopic mapping around the C2 and P1 components, and during the N170-P2 interval. Face inversion effects were also largest for nasion fixation around 120ms. The results support the view that facial feature integration (1) depends on which feature is being fixated and where the other features are situated in the visual field, (2) occurs maximally during the P1-N170 interval when fixation is on the nasion and (3) continues past 200ms, suggesting the N170 peak, where weak effects were found, might be an inflexion point between processes rather than the end of a feature integration into a whole process.

Fatigue affects approximately 80% of people with Multiple Sclerosis (PwMS) and can impact several domains of daily life. However, the neural underpinnings of fatigue in MS are still not completely clear. The aim of our study was to investigate the spontaneous large-scale networks functioning associated with fatigue in PwMS using the EEG microstate approach with a spectral decomposition. Forty-three relapsing-remitting MS patients and twenty-four healthy controls (HCs) were recruited. All participants underwent an administration of Modified Fatigue Impact scale (MFIS) and a 15-min resting-state high-density EEG recording. We compared the microstates of healthy subjects, fatigued (F-MS) and non-fatigued (nF-MS) patients with MS; correlations with clinical and behavioral fatigue scores were also analyzed. Microstates analysis showed six templates across groups and frequencies. We found that in the F-MS emerged a significant decrease of microstate F, associated to the salience network, in the broadband and in the beta band. Moreover, the microstate B, associated to the visual network, showed a significant increase in fatigued patients than healthy subjects in broadband and beta bands. The multiple linear regression showed that the high cognitive fatigue was predicted by both an increase and decrease, respectively, in delta band microstate B and beta band microstate F. On the other hand, higher physical fatigue was predicted with lower occurrence microstate F in beta band. The current findings suggest that in MS the higher level of fatigue might be related to a maladaptive functioning of the salience and visual network.