Brain Topography最新文献

Ischemic stroke is a vascular disease that may cause cognitive and behavioral abnormalities. This study aims to assess abnormal brain function in ischemic stroke patients using the percent amplitude of fluctuation (PerAF) method and further explore the feasibility of PerAF as an imaging biomarker for investigating ischemic stroke pathophysiology mechanisms. Sixteen ischemic stroke patients and 22 healthy controls (HCs) underwent resting state functional magnetic resonance imaging (rs-fMRI) scanning, and the resulting data were analyzed using PerAF. Then a correlation analysis was conducted between PerAF values and Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores. Finally, the abnormal PerAF values were extracted and defined as features for support vector machine (SVM) analysis. Compared with HCs, ischemic stroke patients showed decreased PerAF in the bilateral cuneus, left middle frontal gyrus, precuneus and right inferior temporal gyrus, and increased PerAF in the bilateral orbital part of middle frontal gyrus and right orbital part of superior frontal gyrus. Correlation analyses revealed that PerAF values in the left orbital part of middle frontal gyrus was negatively correlated with the MoCA scores. The SVM classification of the PerAF values achieved an area under the curve (AUC) of 0.98 and an accuracy of 94.74%. Abnormal brain function has been found among ischemic stroke patients, which may be correlated with visual impairment, attention deficits, and dysregulation of negative emotions following a stroke. Our findings may support the potential of PerAF as a sensitive biomarker for investigating the underlying mechanisms of ischemic stroke.

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 purpose of this study is to evaluate the efficacy of repetitive transcranial magnetic stimulation (rTMS) combined with body weight-support treadmill training (BWSTT) for improving walking function of individuals with chronic incomplete spinal cord injury (iSCI). A 4-week, double-blinded, randomized, sham-controlled pilot study involved 12 sessions of real (10 Hz, 1800 pulses) or sham rTMS combined with BWSTT (15-20 min, moderate intensity). Walking independence was assessed using the Walking Index for Spinal Cord Injury II (WISCI-II). Lower extremity motor function (lower extremity motor score [LEMS]) and spasticity, sensory function, functional independence (Spinal Cord Injury Measure III [SCIM-III]), and quality of life were also assessed. Walking independence (WISCI-II) after the 6th session was higher in the BWSTT/rTMS real (n = 7) (median change (IQR): 3 (1.5 to 3.5)) than in the sham group (n = 8) (median change (IQR): 0 (0 to 0.25), but there was no difference between groups after 12th session (BWSTT/rTMS real median change (IQR): 4 (2 to 5); BWSSTT/rTMS sham median change (IQR): 0 (0 to 3.25). Compared to baseline, LEMS and SCIM-III mobility scores were increased after 12 sessions in the BWSTT/rTMS real but not in the sham group. Within- and between-group sensory function, functional independence, and quality of life remained similar. This preliminary result suggests that combining BWSTT with rTMS could lead to earlier gait improvement in patients with chronic iSCI.

In event-related potential (ERP) analysis, it is commonly assumed that individual trials from a subject share similar properties and originate from comparable neural sources, allowing reliable interpretation of group-averages. Nevertheless, traditional group-level ERP analysis methods, including cluster analysis, often overlook critical information about individual subjects' neural processes due to using fixed measurement intervals derived from averaging. We developed a multi-set consensus clustering pipeline to examine cognitive processes at the individual subject level. Initially, consensus clustering from diverse methods was applied to single-trial EEG epochs of individual subjects. Subsequently, a second level of consensus clustering was performed across the trials of each subject. A newly modified time window determination method was then employed to identify individual subjects' ERP(s) of interest. We validated our method with simulated data for ERP components N2 and P3, and real data from a visual oddball task to confirm the P3 component. Our findings revealed that estimated time windows for individual subjects provide precise ERP identification compared to fixed time windows across all subjects. Additionally, Monte Carlo simulations with synthetic single-trial data demonstrated stable scores for the N2 and P3 components, confirming the reliability of our method. The proposed method enhances the examination of brain-evoked responses at the individual subject level by considering single-trial EEG data, thereby extracting mutual information relevant to the neural process. This approach offers a significant improvement over conventional ERP analysis, which relies on the averaging mechanism and fixed measurement interval.

Inhibitory control refers to the ability to suppress cognitive or motor processes. Current neurocognitive models indicate that this function mainly involves the anterior cingulate cortex and the inferior frontal cortex. However, how the communication between these areas influence inhibitory control performance and their functional response remains unknown. We addressed this question by injecting behavioral and electrophysiological markers of inhibitory control recorded during a Go/NoGo task as the 'symptoms' in a connectome-based lesion-symptom mapping approach in a sample of 96 first unilateral stroke patients. This approach enables us to identify the white matter tracts whose disruption by the lesions causally influences brain functional activity during inhibitory control. We found a central role of left frontotemporal and frontobasal intrahemispheric connections, as well as of the connections between the left temporoparietal and right temporal areas in inhibitory control performance. We also found that connections between the left temporal and right superior parietal areas modulate the conflict-related N2 event-related potential component and between the left temporal parietal area and right temporal and occipital areas for the inhibition P3 component. Our study supports the role of a distributed bilateral network in inhibitory control and reveals that combining lesion-symptom mapping approaches with functional indices of cognitive processes could shed new light on post-stroke functional reorganization. It may further help to refine the interpretation of classical electrophysiological markers of executive control in stroke patients.

Primary angle-closure glaucoma (PACG) is a sight-threatening eye condition that leads to irreversible blindness. While past neuroimaging research has identified abnormal brain function in PACG patients, the relationship between PACG and alterations in brain functional networks has yet to be explored. This study seeks to examine the influence of PACG on brain networks, aiming to advance knowledge of its neurobiological processes for better diagnostic and therapeutic approaches utilizing graph theory analysis. A cohort of 44 primary angle-closure glaucoma (PACG) patients and 44 healthy controls participated in this study. Functional brain networks were constructed using fMRI data and the Automated Anatomical Labeling 90 template. Subsequently, graph theory analysis was employed to evaluate global metrics, nodal metrics, modular organization, and network-based statistics (NBS), enabling a comparative analysis between PACG patients and the control group. The analysis of global metrics, including small-worldness and network efficiency, did not exhibit significant differences between the two groups. However, PACG patients displayed elevated nodal metrics, such as centrality and efficiency, in the left frontal superior medial, right frontal superior medial, and right posterior central brain regions, along with reduced values in the right temporal superior gyrus region compared to healthy controls. Furthermore, Module 5 showed notable disparities in intra-module connectivity, while Module 1 demonstrated substantial differences in inter-module connectivity with both Module 7 and Module 8. Noteworthy, the NBS analysis unveiled a significantly altered network when comparing the PACG and healthy control groups. The study proposes that PACG patients demonstrate variations in nodal metrics and modularity within functional brain networks, particularly affecting the prefrontal, occipital, and temporal lobes, along with cerebellar regions. However, an analysis of global metrics suggests that the overall connectivity patterns of the entire brain network remain unaltered in PACG patients. These results have the potential to serve as early diagnostic and differential markers for PACG, and interventions focusing on brain regions with high degree centrality and nodal efficiency could aid in optimizing therapeutic approaches.

The cortical generators of the pure tone MMN and P300 have been thoroughly studied. Their nature and interaction with respect to phoneme perception, however, is poorly understood. Accordingly, the cortical sources and functional connections that underlie the MMN and P300 in relation to passive and active speech sound perception were identified. An inattentive and attentive phonemic oddball paradigm, eliciting a MMN and P300 respectively, were administered in 60 healthy adults during simultaneous high-density EEG recording. For both the MMN and P300, eLORETA source reconstruction was performed. The maximal cross-correlation was calculated between ROI-pairs to investigate inter-regional functional connectivity specific to passive and active deviant processing. MMN activation clusters were identified in the temporal (insula, superior temporal gyrus and temporal pole), frontal (rostral middle frontal and pars opercularis) and parietal (postcentral and supramarginal gyrus) cortex. Passive discrimination of deviant phonemes was aided by a network connecting right temporoparietal cortices to left frontal areas. For the P300, clusters with significantly higher activity were found in the frontal (caudal middle frontal and precentral), parietal (precuneus) and cingulate (posterior and isthmus) cortex. Significant intra- and interhemispheric connections between parietal, cingulate and occipital regions constituted the network governing active phonemic target detection. A predominantly bilateral network was found to underly both the MMN and P300. While passive phoneme discrimination is aided by a fronto-temporo-parietal network, active categorization calls on a network entailing fronto-parieto-cingulate cortices. Neural processing of phonemic contrasts, as reflected by the MMN and P300, does not appear to show pronounced lateralization to the language-dominant hemisphere.

Aperiodic activity is derived from the electroencephalography (EEG) power spectrum and reflects changes in the slope and shifts of the broadband spectrum. Studies have shown inconsistent test-retest reliability of the aperiodic components. This study systematically measured how the test-retest reliability of the aperiodic components was affected by data duration (1, 2, 3, 4, and 5 min), states (resting with eyes closed, resting with eyes open, performing mental arithmetic, recalling the events of the day, and mentally singing songs), and methods (the Fitting Oscillations and One-Over-F (FOOOF) and Linear Mixed-Effects Regression (LMER)) at both short (90-min) and long (one-month) intervals. The results showed that aperiodic components had fair, good, or excellent test-retest reliability (ranging from 0.53 to 0.91) at both short and long intervals. It is recommended that better reliability of the aperiodic components be obtained using data durations longer than 3 min, the resting state with eyes closed, the mental arithmetic task state, and the LMER method.

To date, it is largely unknown how frequency range of neural oscillations measured with EEG is related to functional connectivity. To address this question, we investigated frequency-dependent directed functional connectivity among the structures of mesial and anterior temporal network including amygdala, hippocampus, temporal pole and parahippocampal gyrus in the living human brain. Intracranial EEG recording was obtained from 19 consecutive epilepsy patients with normal anterior mesial temporal MR imaging undergoing intracranial presurgical epilepsy diagnostics with multiple depth electrodes. We assessed intratemporal bidirectional functional connectivity using several causality measures such as Granger causality (GC), directed transfer function (DTF) and partial directed coherence (PDC) in a frequency-specific way. In order to verify the obtained results, we compared the spontaneous functional networks with intratemporal effective connectivity evaluated by means of SPES (single pulse electrical stimulation) method. The overlap with the evoked network was found for the functional connectivity assessed by the GC method, most prominent in the higher frequency bands (alpha, beta and low gamma), yet vanishing in the lower frequencies. Functional connectivity assessed by means of DTF and PCD obtained a similar directionality pattern with the exception of connectivity between hippocampus and parahippocampal gyrus which showed opposite directionality of predominant information flow. Whereas previous connectivity studies reported significant divergence between spontaneous and evoked networks, our data show the role of frequency bands for the consistency of functional and evoked intratemporal directed connectivity. This has implications for the suitability of functional connectivity methods in characterizing local brain circuits.

Chronotype is an inherent physiological trait reflecting an individual's subjective preference for their sleep awakening time, exerting a substantial influence on both physical and mental well-being. While existing research has established a close relationship between chronotype and individual brain structure, prior studies have predominantly focused on individual measurements of brain structural scales, thereby limiting the exploration of the underlying mechanisms of structural changes. This study seeks to validate previous research findings and enhance our understanding of the correlation between circadian rhythm preference and diverse cortical indicators in healthy young individuals. Magnetic resonance imaging (MRI) scans and chronotype assessments were conducted once for all participants, comprising 49 late chronotype (LC) young adults and 49 matched early chronotype young adults. The Chronotype Questionnaire was utilized to assess morningness and eveningness preferences. Surface-based analysis of structural MRI data revealed that LC young adults exhibited thinner cortical thickness of left pars orbitalis and lower cortical mean curve of right paracentral gyrus. Overall, this study represents a significant advancement in elucidating the connection between brain structure and function within the context of chronotypes.