Brain Topography最新文献

Inhibitory control (IC) develops in stages from infancy through adolescence and is associated with numerous developmental disorders and learning outcomes. This study examined how neural architecture - in particular myelination - underlies brain activation patterns observed during IC tasks in a sample of 28 children aged 4-10 years old. IC was observed using reaction times during go/no-go and flanker IC tasks. Myelination was measured using quantitative longitudinal relaxation rate (R1) mapping obtained from selected white matter regions of interest (ROIs). Brain activation was defined as task-related changes in hemoglobin oxygenation as measured by functional near-infrared spectroscopy (fNIRS) averaged within ROIs. Results indicated that myelination in ROIs was higher in older children and fNIRS activation in frontal channels was significantly and positively associated with go/no-go mean reaction time. Myelination in the corona radiata and superior longitudinal fasciculus was positively associated with frontal fNIRS activation, while myelination was negatively associated with go/no-go and flanker mean reaction times across white matter ROIs. Overall, significance level notably varied across models. Independently of inhibitory control constructs, these regions may be of interest in future structure-function studies across development.

We explore cerebral reorganization in patients with spinal cord injury (SCI) using structural and functional magnetic resonance imaging (fMRI) to investigate regions relative to the prognosis of sensory-motor ability within SCI patients. Thirty right-handed SCI patients and 30 gender- and age-matched healthy controls (HCs) were included. Gray matter volume (GMV) changes in SCI patients were observed and the amplitude of low-frequency fluctuations (ALFF) values within regions with significant differences in GMV were calculated. These altered gray matter regions were used as regions of interest (ROIs) for functional connectivity (FC) analysis to detect related functional changes. Additionally, the Granger causality analysis (GCA) was used to study alterations in effective connectivity (EC) within the brain. The potential association between all the above MRI values with the International Standards for Neurological Classification of Spinal Cord Injury (ISNCSCI) scores was investigated through partial correlation analysis. SCI patients showed reduced GMV in bilateral putamen compared to the HCs. Meanwhile, significant lower FC were found between the bilateral putamen and the right superior parietal gyrus, whereas significant higher FC were found between the right putamen and the bilateral precuneus in patients with SCI. GCA revealed enhanced EC from the left precuneus to the right putamen. The degree of functional alterations with the putamen might hint at the level of sensory-motor function of patients following SCI. When multisensory integration was decreased due to disease, the increased connection between the precuneus and the putamen might serve a role in SCI recovery by increasing visuospatial integration.

Increasing evidence suggests that brain areas outside of the auditory pathway may be involved in the development and maintenance of tinnitus. We hypothesized that repetitive transcranial magnetic stimulation (rTMS) to those areas in patients with comorbid psychiatric and neurocognitive disorder may reduce tinnitus distress. This is a case series of patients treated with off-label accelerated continuous or intermittent theta burst rTMS for medically refractory tinnitus. Target selections for each patient were performed using a personalized brain atlas based on resting state functional MRI (rsMRI) that identified regions of anomalous connectivity by comparing resting state functional connectivity to a normal cohort. Nine patients were treated with personalized, parcel-guided rTMS (Sydney, Australia) from 2018 to 2023, inclusive. Four patients had Major Depressive Disorder (MDD) of which three had comorbid anxiety, three patients had traumatic brain injury, and one patient had migraines. All patients had targets identified outside of the auditory network, including central executive network (CEN), default mode network (DMN), and salience network (SN). Clinically significant improvements in tinnitus symptoms were reported in 75% and 100% of patients based on TRQ and THI, respectively. No major adverse safety events occurred. rTMS with target selection using a personalized, agile approach is safe and may provide durable symptomatic relief rTMS with target selection using a personalized, agile approach is safe and may provide durable symptomatic relief for patients with chronic tinnitus, including those with comorbid psychiatric and neurocognitive conditions.

Functional brain network (FBN) derived from functional Magnetic Resonance Imaging (fMRI) has promising prospects in clinical research, but fMRI is not a routine acquisition data, which limits its popularity in clinical applications. Therefore, it is imperative to generate FBN based on routine clinical structural MRI brain network. In this study, a BrainNet-GAN model was proposed for generating FBN from radiomics-based morphological brain network (radMBN) derived from routinely acquired T1-weighted image (T1WI). BrainNet-GAN integrated two Multi-Channel Multi-Scale Adaptive (Multi²Ada) generators and two (Local_to_Global) discriminators. In the generator, Graph Convolutional Network (GCN) was used inside each channel to aggregate multi-scale information between direct or indirect neighbors of nodes, and the output of each channel was adaptively fused through several sets of learnable coefficients; In the discriminator, Multi-channel GCN was used to aggregate local nodes information, and a feature selection module was designed to establish correlations between feature maps at different channels. Additionally, a Multi-Angle Multi-Constraint (MAMC) loss function was proposed, which could guide the learning process of the model from different aspects. Experiments with 2116 subjects in two publicly available datasets showed that BrainNet-GAN model exhibited promising performance on the task of generating FBN. Meanwhile, the individual-level brain network visualization was displayed with high consistency in generated FBN and target FBN. Further, the Top 10 brain regions identified by four graph-theory analysis metrics also exhibited with consistency. The proposed BrainNet-GAN model demonstrated superior performance in generating FBN based on radMBN, which could facilitate the application of FBN in clinical practice.

Developmental dyslexia (DD) is a common reading disorder with neurological underpinnings; however, it remains unclear whether Chinese children with DD exhibit spectral power or network topology abnormalities. This study investigated spectral power and brain network topology abnormalities using electroencephalography (EEG) during resting states and a one-back Chinese-Korean character task in 85 Hong Kong Chinese children with DD and 51 typically developing peers (ages 7-11). EEG signals were transformed using the Fast Fourier Transform to estimate spectral power. Functional connectivity matrices were derived using the phase-lag index, and network topology was assessed via minimum spanning tree (MST) analysis. The results suggested that children with DD showed reduced alpha power over central, frontal, temporal, parietal, and occipital scalp areas at rest, and over central and frontal areas during the task. MST results revealed decreased beta band integration at rest but increased alpha band integration during the one-back task. Familiar Chinese stimuli elicited greater alpha and beta power and lower beta band integration compared to unfamiliar Korean stimuli. Moreover, resting-state beta band integration correlated positively with reading fluency in children with DD. These findings point to inhibitory control deficits and cortical hyperactivation in Chinese DD, reflected in disrupted large-scale network topology, and highlight the alpha band as a potential biomarker. They also demonstrate that language familiarity modulates neural efficiency and recruits compensatory networks. Overall, the study provides new insights into the neural basis of reading difficulties in Chinese children with DD.

Apathy is a cognitive, behavioral, and emotional disorder marked by a decrease in goal-directed activities as well as affective flattening. This multifaceted disorder has been described in Parkinson's disease as a highly common neuropsychiatric feature. The pathophysiology that underlies apathy, however, is still not entirely understood. The major goal of this study was to determine the microstate correlations of apathy in Parkinson's disease. This study involved patients with the diagnosis of idiopathic Parkinson's disease. Based on the Apathy Evaluation Scale criteria, Parkinson's disease groups were divided into two main groups- apathetic and non-apathetic. Patients underwent clinical, motor, and demographic characteristics as well as neuropsychometric evaluations. Spontaneous EEG brain activity was recorded, and a microstate analysis was conducted. The clinical and motor functions of the apathetic and non-apathetic groups did not differ significantly; nevertheless, the apathetic group performed worse on several executive function and memory tests. A comparison of EEG microstates between the apathetic and non-apathetic groups found that the apathetic group had an increase in the duration and coverage of microstates B and E, whereas the frequency of Microstate D decreased. Additionally, in patients with apathy, an increased transition was observed from Microstate A > B, C > E and C > G. Our findings suggest that the increased transitions from Microstate A to B and from C to E and G, along with an increase in Microstates E and B and a decrease in Microstate D, may reflect changes in the activity or functional connectivity of several large-scale brain circuits in Parkinsonian apathy. On the other hand, Microstate E could be the fundamental microstate reflecting changes associated with the Default Mode Network in Parkinsonian apathy.

Interoception, the process of sensing and interpreting internal bodily signals, plays a crucial role in emotional regulation, decision-making, and overall well-being. This study aimed to investigate the relationship between self-reported interoceptive processes, assessed through the Body Perception Questionnaire (BPQ), and psychophysiological measures of interoception, including cardiac autonomic markers (HF-HRV and RMSSD), cortical processing of cardiac signals (heartbeat-evoked potentials, HEPs), and EEG microstates. We recorded EEG and ECG from 64 healthy volunteers during open-eyed resting state. A positive association was found between the Subdiaphragmatic Reactivity subscale of the BPQ and the coverage of microstate A, a spatial configuration linked to the activation of temporal brain regions, arousal, and sensory processing. No associations were observed between BPQ scores and cardiac measures or HEP amplitudes, suggesting that subjective reports may not align with psychophysiological indices of interoception. Associations were found between HEP amplitudes and microstates A and B, as well as between HRV measures and microstate D, highlighting potential links between autonomic functioning and brain activity during resting state. Although the BPQ is a widely used tool to assess interoceptive sensibility, it may not fully capture the complexity of this construct. These findings provide insight into the complex interplay between self-reported interoception and psychophysiological markers, while emphasizing the need for further research to clarify these relationships and their implications for emotional and cognitive processing.

The ability to maintain our body's balance and stability in space is crucial for performing daily activities. Effective postural control (PC) strategies rely on integrating visual, vestibular, and proprioceptive sensory inputs. While neuroimaging has revealed key areas involved in PC-including brainstem, cerebellum, and cortical networks-the rapid neural mechanisms underlying dynamic postural tasks remain less understood. Therefore, we used EEG microstate analysis within the BioVRSea experiment to explore the temporal brain dynamics that support PC. This complex paradigm simulates maintaining an upright posture on a moving platform, integrated with virtual reality (VR), to replicate the sensation of balancing on a boat. Data were acquired from 266 healthy subjects using a 64-channel EEG system. Using a modified k-means method, five EEG microstate maps were identified to best model the paradigm. Differences in each microstate maps feature (occurrence, duration, and coverage) between experimental phases were analyzed using a linear mixed model, revealing significant differences between microstates within the experiment phases. The temporal parameters of microstate C showed significantly higher levels in all experimental phases compared to other microstate maps, whereas microstate B displayed an opposite pattern, consistently showing lower levels. This study marks the first attempt to use microstate analysis during a dynamic task, demonstrating the decisive role of microstate C and, conversely, microstate B in differentiating the PC phases. These results demonstrate the utility of microstate technique in studying temporal brain dynamics during PC, with potential applications in the early detection of neurodegenerative diseases.

There is growing interest in the neural network of pragmatic language and its potential overlap with the Theory of Mind (ToM) network. However, no Spanish-adapted fMRI tasks were used for studying sarcasm, the subtype of pragmatic language most related to ToM. Furthermore, stimuli used in prior studies often impose high cognitive demands, confounding its sarcasm brain representation with the executive network. We investigate the neural correlates of sarcasm in Spanish using a novel experimental paradigm designed to minimize cognitive load and enhance ecological validity. Eighteen healthy, right-handed participants underwent a 3T fMRI session with a sarcasm comprehension task. Brain activations analysed with SPM12 were calculated for sarcasm vs. literal contrast. Sarcasm activated the left temporo-parietal junction, Medial Prefrontal Cortex (BA 10), Left Inferior Frontal Gyrus (BA 45), Left Medial and Superior Temporal Gyrus (BA 21 & 22), and Left Temporal Pole (BA 38). Sarcasm comprehension involves an extensive fronto-temporal-parietal network, with prominent activation of ToM-related areas. These findings suggest an overlap between sarcasm and ToM networks, emphasizing the role of the medial prefrontal cortex in pragmatic language, the left inferior frontal gyrus in semantic integration, and the role of a left-lateralized frontotemporal network for sarcasm processing.

Type 1 Diabetes Mellitus (T1DM) progression has a direct impact on brain microstructural integrity and typical functional organization from the early stages of neurodevelopment. Diffusion Tensor Imaging (DTI) is a neuroimaging method that has proven sensitive to changes in white matter microstructure. Using diffusion-weighted probabilistic tractography methods, we aim to evaluate the white matter integrity and anatomical relationships within the Default Mode Network (DMN) brain regions, which have been proven to be particularly affected by T1DM in a group of eighteen carefully selected clinically well-controlled young T1DM patients versus eighteen healthy matched controls according to sex, age, and education level. Results showed no relevant differences in the anatomical distribution of DMN between the groups. However, the transitivity graph metric was significantly lower in T1DM patients, who also showed weaker connectivity between the left ventral prefrontal cortex and the left medial temporal gyrus, representing the anatomical trajectory of the arcuate fasciculus. Considering that neural myelination is affected by language input and the critical role of language-related structures on brain development, the current findings denote early ill-driven brain modifications to better adapt to the increasing daily demands.