Brain Topography最新文献

Numerous studies utilizing magnetic resonance imaging (MRI) have observed sex and interhemispheric disparities in sulcal morphology, which could potentially underpin certain functional disparities in the human brain. Most of the existing research examines the precentral sulcus comprehensively, with a rare focus on its subsections. To explore the morphology, asymmetry, and sex disparities within the inferior precentral sulcus (IPCS), we acquired 3.0T magnetic resonance images from 92 right-handed Chinese adolescents. Brainvisa was used to reconstruct the IPCS structure and calculate its mean depth (MD). Based on the morphological patterns of IPCS, it was categorized into five distinct types. Additionally, we analyzed four different types of spatial relationships between IPCS and inferior frontal sulcus (IFS). There was a statistically significant sex disparity in the MD of IPCS, primarily observed in the right hemisphere. Females exhibited significantly greater asymmetry in the MD of IPCS compared to males. No statistically significant sex or hemispheric variations were identified in sulcal patterns. Our findings expand the comprehension of inconsistencies in sulcal structure, while also delivering an anatomical foundation for the study of related regions' function.

Long-term musical training induces adaptive changes in the functional representation of the motor cortex. It is unknown if the maladaptive plasticity associated with chronic pain, frequently affecting trained musicians, may alter the use-dependent plasticity in the motor cortex. This study investigated the interaction between adaptive and maladaptive plasticity in the motor pathways, in particular how chronic pain influences long-term use-dependent plasticity. Using transcranial magnetic stimulation (TMS), corticospinal excitability was assessed by measuring the amplitude of the motor-evoked potential (MEP), area of the motor map, volume, and center of gravity of the first dorsal interosseous muscle in 19 pain-free musicians, 17 upper limb/neck pain chronic pain musicians, and 19 pain-free non-musicians as controls. Motor map volume and MEP amplitude were smaller for both pain-free and chronic pain musicians compared to pain-free controls (P < 0.011). No significant differences were found between musicians with and without chronic pain. These findings confirm that long-term musical training can lead to focalized and specialized functional organization of the primary motor cortex. Moreover, the adaptive use-dependent plasticity acquired through fine-motor skill acquisition is not significantly compromised by the maladaptive plasticity typically associated with chronic pain, highlighting the potential of long-term sensorimotor training to counteract the effects of chronic pain in the motor system.

Purpose: Identify the presence of a dysfunctional electroencephalographic (EEG) pattern in individuals with sickle cell disease (SCD) and hip osteonecrosis, and assess its potential associations with depression, anxiety, pain severity, and serum levels of brain-derived neurotrophic factor (BDNF).

Methods: In this cross-sectional investigation, 24 SCD patients with hip osteonecrosis and chronic pain were matched by age and sex with 19 healthy controls. Resting-state EEG data were recorded using 32 electrodes for both groups. Power spectral density (PSD) and peak alpha frequency (PAF) were computed for each electrode across Delta, Theta, Alpha, and Beta frequency bands. Current Source Density (CSD) measures were performed utilizing the built-in Statistical nonparametric Mapping Method of the LORETA-KEY software.

Results: Our findings demonstrated that SCD individuals exhibited higher PSD in delta and theta frequency bands when compared to healthy controls. Moreover, SCD individuals displayed increased CSD in delta and theta frequencies, coupled with decreased CSD in the alpha frequency within brain regions linked to pain processing, motor function, emotion, and attention. In comparison to the control group, depression symptoms, and pain intensity during hip abduction were positively correlated with PSD and CSD in the delta frequency within the parietal region. Depression symptoms also exhibited a positive association with PSD and CSD in the theta frequency within the same region, while serum BDNF levels showed a negative correlation with CSD in the alpha frequency within the left insula.

Conclusion: This study indicates that individuals with SCD experiencing hip osteonecrosis and chronic pain manifest a dysfunctional EEG pattern characterized by the persistence of low-frequency PSD during a resting state. This dysfunctional EEG pattern may be linked to clinical and biochemical outcomes, including depression symptoms, pain severity during movement, and serum BDNF levels.

Social norms and altruistic punitive behaviours are both based on the integration of information from multiple contexts. Individual behavioural performance can be altered by loss and gain contexts, which produce different mental states and subjective perceptions. In this study, we used event-related potential and time-frequency techniques to examine performance on a third-party punishment task and to explore the neural mechanisms underlying context-dependent differences in punishment decisions. The results indicated that individuals were more likely to reject unfairness in the context of loss (vs. gain) and to increase punishment as unfairness increased. In contrast, fairness appeared to cause an early increase in cognitive control signal enhancement, as indicated by the P2 amplitude and theta oscillations, and a later increase in emotional and motivational salience during decision-making in gain vs. loss contexts, as indicated by the medial frontal negativity and beta oscillations. In summary, individuals were more willing to sanction violations of social norms in the loss context than in the gain context and rejecting unfair losses induced more equity-related cognitive conflict than accepting unfair gains, highlighting the importance of context (i.e., gain vs. loss) in equity-related social decision-making processes.

Epilepsia partialis continua (EPC) is a rare type of focal motor status epilepticus that causes continuous muscle jerking in a specific part of the body. Experiencing this type of seizure, along with other seizure types, such as focal motor seizures and focal to bilateral tonic-clonic seizures, can result in a disabling situation. Non-invasive brain stimulation methods like transcranial direct current stimulation (tDCS) show promise in reducing seizure frequency (SF) when medications are ineffective. However, research on tDCS for EPC and related seizures is limited. We evaluated personalized multichannel tDCS in drug-resistant EPC of diverse etiologies for long-term clinical efficacy We report three EPC patients undergoing a long-term protocol of multichannel tDCS. The patients received several cycles (11, 9, and 3) of five consecutive days of stimulation at 2 mA for 2 × 20 min, targeting the epileptogenic zone (EZ), including the central motor cortex with cathodal electrodes. The primary measurement was SF changes. In three cases, EPC was due to Rasmussen's Encephalitis (case 1), focal cortical dysplasia (case 2), or remained unknown (case 3). tDCS cycles were administered over 6 to 22 months. The outcomes comprised a reduction of at least 75% in seizure frequency for two patients, and in one case, a complete cessation of severe motor seizures. However, tDCS had no substantial impact on the continuous myoclonus characterizing EPC. No serious side effects were reported. Long-term application of tDCS cycles is well tolerated and can lead to a considerable reduction in disabling seizures in patients with various forms of epilepsy with EPC.

I-wave periodicity repetitive paired-pulse transcranial magnetic stimulation (iTMS) can modify acquisition of a novel motor skill, but the associated neurophysiological effects remain unclear. The current study therefore used combined TMS-electroencephalography (TMS-EEG) to investigate the neurophysiological effects of iTMS on subsequent visuomotor training (VT). Sixteen young adults (26.1 ± 5.1 years) participated in three sessions including real iTMS and VT (iTMS + VT), control iTMS and VT (iTMS_Control + VT), or iTMS alone. Motor-evoked potentials (MEPs) and TMS-evoked potentials (TEPs) were measured before and after iTMS, and again after VT, to assess neuroplastic changes. Irrespective of the intervention, MEP amplitude was not changed after iTMS or VT. Motor skill was improved compared with baseline, but no differences were found between stimulus conditions. In contrast, the P30 peak was altered by VT when preceded by control iTMS (P < 0.05), but this effect was not apparent when VT was preceded by iTMS or following iTMS alone (all P > 0.15). In contrast to expectations, iTMS was unable to modulate MEP amplitude or influence motor learning. Despite this, changes in P30 amplitude suggested that motor learning was associated with altered cortical reactivity. Furthermore, this effect was abolished by priming with iTMS, suggesting an influence of priming that failed to impact learning.

Developing motor and cognitive skills is needed to achieve expert (motor) performance or functional recovery from a neurological condition, e.g., after stroke. While extensive practice plays an essential role in the acquisition of good motor performance, it is still unknown whether certain person-specific traits may predetermine the rate of motor learning. In particular, learners' functional brain organisation might play an important role in appropriately performing motor tasks. In this paper, we aimed to study how two critical cognitive brain networks-the Attention Network (AN) and the Default Mode Network (DMN)-affect the posterior motor performance in a complex visuomotor task: virtual surfing. We hypothesised that the preactivation of the AN would affect how participants divert their attention towards external stimuli, resulting in robust motor performance. Conversely, the excessive involvement of the DMN-linked to internally diverted attention and mind-wandering-would be detrimental for posterior motor performance. We extracted seven widely accepted microstates-representing participants mind states at rest-out of the Electroencephalography (EEG) resting-state recordings of 36 healthy volunteers, prior to execution of the virtual surfing task. By correlating neural biomarkers (microstates) and motor behavioural metrics, we confirmed that the preactivation of the posterior DMN was correlated with poor posterior performance in the motor task. However, we only found a non-significant association between AN preactivation and the posterior motor performance. In this EEG study, we propose the preactivation of the posterior DMN-imaged using EEG microstates-as a neural trait related to poor posterior motor performance. Our findings suggest that the role of the executive control system is to preserve an homeostasis between the AN and the DMN. Therefore, neurofeedback-based downregulation of DMN preactivation could help optimise motor training.

More than 10% of births are preterm, and the long-term consequences on sensory and semantic processing of non-linguistic information remain poorly understood. 17 very preterm-born children (born at < 33 weeks gestational age) and 15 full-term controls were tested at 10 years old with an auditory object recognition task, while 64-channel auditory evoked potentials (AEPs) were recorded. Sounds consisted of living (animal and human vocalizations) and manmade objects (e.g. household objects, instruments, and tools). Despite similar recognition behavior, AEPs strikingly differed between full-term and preterm children. Starting at 50ms post-stimulus onset, AEPs from preterm children differed topographically from their full-term counterparts. Over the 108-224ms post-stimulus period, full-term children showed stronger AEPs in response to living objects, whereas preterm born children showed the reverse pattern; i.e. stronger AEPs in response to manmade objects. Differential brain activity between semantic categories could reliably classify children according to their preterm status. Moreover, this opposing pattern of differential responses to semantic categories of sounds was also observed in source estimations within a network of occipital, temporal and frontal regions. This study highlights how early life experience in terms of preterm birth shapes sensory and object processing later on in life.

Microstate analysis is a multivariate method that enables investigations of the temporal dynamics of large-scale neural networks in EEG recordings of human brain activity. To meet the enormously increasing interest in this approach, we provide a thoroughly updated version of the first open source EEGLAB toolbox for the standardized identification, visualization, and quantification of microstates in resting-state EEG data. The toolbox allows scientists to (i) identify individual, mean, and grand mean microstate maps using topographical clustering approaches, (ii) check data quality and detect outlier maps, (iii) visualize, sort, and label individual, mean, and grand mean microstate maps according to published maps, (iv) compare topographical similarities of group and grand mean microstate maps and quantify shared variances, (v) obtain the temporal dynamics of the microstate classes in individual EEGs, (vi) export quantifications of these temporal dynamics of the microstates for statistical tests, and finally, (vii) test for topographical differences between groups and conditions using topographic analysis of variance (TANOVA). Here, we introduce the toolbox in a step-by-step tutorial, using a sample dataset of 34 resting-state EEG recordings that are publicly available to follow along with this tutorial. The goals of this manuscript are (a) to provide a standardized, freely available toolbox for resting-state microstate analysis to the scientific community, (b) to allow researchers to use best practices for microstate analysis by following a step-by-step tutorial, and (c) to improve the methodological standards of microstate research by providing previously unavailable functions and recommendations on critical decisions required in microstate analyses.

Microstate analysis of resting-state EEG is a unique data-driven method for identifying patterns of scalp potential topographies, or microstates, that reflect stable but transient periods of synchronized neural activity evolving dynamically over time. During infancy - a critical period of rapid brain development and plasticity - microstate analysis offers a unique opportunity for characterizing the spatial and temporal dynamics of brain activity. However, whether measurements derived from this approach (e.g., temporal properties, transition probabilities, neural sources) show strong psychometric properties (i.e., reliability) during infancy is unknown and key information for advancing our understanding of how microstates are shaped by early life experiences and whether they relate to individual differences in infant abilities. A lack of methodological resources for performing microstate analysis of infant EEG has further hindered adoption of this cutting-edge approach by infant researchers. As a result, in the current study, we systematically addressed these knowledge gaps and report that most microstate-based measurements of brain organization and functioning except for transition probabilities were stable with four minutes of video-watching resting-state data and highly internally consistent with just one minute. In addition to these results, we provide a step-by-step tutorial, accompanying website, and open-access data for performing microstate analysis using a free, user-friendly software called Cartool. Taken together, the current study supports the reliability and feasibility of using EEG microstate analysis to study infant brain development and increases the accessibility of this approach for the field of developmental neuroscience.