Resting-state Activity Research Articles

Intermodal Consistency of Whole-Brain Connectivity and Signal Propagation Delays.

Measuring propagation of perturbations across the human brain and their transmission delays is critical for network neuroscience, but it is a challenging problem that still requires advancement. Here, we compare results from a recently introduced, noninvasive technique of functional delays estimation from source-reconstructed electro/magnetoencephalography, to the corresponding findings from a large dataset of cortico-cortical evoked potentials estimated from intracerebral stimulations of patients suffering from pharmaco-resistant epilepsies. The two methods yield significantly similar probabilistic connectivity maps and signal propagation delays, in both cases characterized with Pearson correlations greater than 0.5 (when grouping by stimulated parcel is applied for delays). This similarity suggests a correspondence between the mechanisms underpinning the propagation of spontaneously generated scale-free perturbations (i.e., neuronal avalanches observed in resting state activity studied using magnetoencephalography) and the spreading of cortico-cortical evoked potentials. This manuscript provides evidence for the accuracy of the estimate of functional delays obtained noninvasively from reconstructed sources. Conversely, our findings show that estimates obtained from externally induced perturbations in patients capture physiological activities in healthy subjects. In conclusion, this manuscript constitutes a mutual validation between two modalities, broadening their scope of applicability and interpretation. Importantly, the capability to measure delays noninvasively (as per MEG) paves the way for the inclusion of functional delays in personalized large-scale brain models as well as in diagnostic and prognostic algorithms.

Dynamical models reveal anatomically reliable attractor landscapes embedded in resting-state brain networks

Abstract Analyses of functional connectivity (FC) in resting-state brain networks (RSNs) have generated many insights into cognition. However, the mechanistic underpinnings of FC and RSNs are still not well-understood. It remains debated whether resting-state activity is best characterized as reflecting noise-driven fluctuations around a single stable state, or instead, as a nonlinear dynamical system with nontrivial attractors embedded in the RSNs. Here, we provide evidence for the latter, by constructing whole-brain dynamical systems models from individual resting-state fMRI (rfMRI) recordings, using the Mesoscale Individualized NeuroDynamic (MINDy) framework. The MINDy models consist of hundreds of neural masses representing brain parcels, connected by fully trainable, individualized weights. We found that our models manifested a diverse taxonomy of nontrivial attractor landscapes including multiple equilibria and limit cycles. However, when projected into anatomical space, these attractors mapped onto a limited set of canonical RSNs, including the default mode network (DMN) and frontoparietal control network (FPN), which were reliable at the individual level. Further, by creating convex combinations of models, bifurcations were induced that recapitulated the full spectrum of dynamics found via fitting. These findings suggest that the resting brain traverses a diverse set of dynamics, which generate several distinct but anatomically overlapping attractor landscapes. Treating rfMRI as a unimodal stationary process (i.e., conventional FC) may miss critical attractor properties and structure within the resting brain. Instead, these may be better captured through neural dynamical modeling and analytic approaches. The results provide new insights into the generative mechanisms and intrinsic spatiotemporal organization of brain networks.

Association between resting-state synaptic activity and overall performance in a cognitive visuoconstructive task as revealed by magnetoencephalography (MEG).

Performance of a task involves the engagement of various brain areas, as evidenced by the effects of lesions of particular brain areas and the results of functional neuroimaging and neurophysiological studies. Here we tested the hypothesis that overall task performance would depend on the level of ongoing, resting-state change in synaptic activity of participating areas, such that the degree of success of the outcome would be higher, the higher the resting-state activation. For that purpose, we used 248-sensor magnetoencephalography (MEG) in healthy people to obtain estimates of resting-state synaptic activity in various areas and then correlated those estimates to the average performance score in three visuospatial tasks assessed outside the MEG session using the Montreal Cognitive Assessment (MoCA), namely the Trails, Cube, and Clock Drawing (TCCD) tasks. We found that the average success score in these tasks covaried positively with the level of resting-state neural activity of 3 broad area clusters, namely (a) right cerebellum, occipital, and parietal cortical regions (strongest association), (b) right inferior frontal, middle and posterior temporal regions, and (c) left middle frontal region. The dependence of the outcome of task performance on the activation state of areas in the absence of action, i.e. in resting-state, points to a priming role in facilitating task performance.

Resting-state functional near-infrared spectroscopy in neurodegenerative diseases - A systematic review.

To systematically review and summarize alterations found in resting-state activity as measured via functional near-infrared spectroscopy (fNIRS) in neurodegenerative diseases. fNIRS is a novel and emerging neuroimaging method suitable for a variety of study designs. Resting-state is the measure of brain activity in the absence of a task, which has been investigated for yielding information about neurodegenerative diseases, mainly using magnetic resonance imaging. We aimed to systematically review the usage of resting-state fNIRS (rsfNIRS) in neurodegenerative diseases. Studies investigating people diagnosed with a neurodegenerative disease and resting-state activity obtained with fNIRS using at least two channels. We searched three databases for publications. After the screening, 16 studies were included in the systematic review. The quality of the studies was assessed, and data were extracted. Data were qualitatively synthesized and in the case of at least 10 similar studies, a meta-analysis was planned. Most studies investigated Mild cognitive impairment (50%), followed by Alzheimer's disease (25%). Other neurodegenerative diseases encompassed Parkinson's disease, Multiple sclerosis, and Amyotrophic lateral sclerosis. All studies reported oxygenated hemoglobin. Still, studies were heterogeneous in terms of study design, measurement duration, fNIRS device, montage, pre-processing, and analyses. A meta-analysis was not considered possible due to this heterogeneity. rsfNIRS shows promise in neurodegenerative disease, as most studies have observed resting-state alterations when compared to healthy controls. However, inconsistencies across studies limit data comparison and meta-analysis. Hence, we strongly advocate the application of fNIRS reporting guidelines and the establishment of rsfNIRS-specific guidelines. This will ensure reliable and comparable results in future research.

Aging disrupts the link between network centrality and functional properties of prefrontal neurons during memory-guided behavior

The prefrontal cortex (PFC) is vital for higher cognitive functions and displays neuronal heterogeneity, with neuronal activity varying significantly across individual neurons. Using calcium imaging in the medial PFC (mPFC) of mice, we investigate whether differences in degree centrality—a measure of connectivity strength within local circuits—could explain this neuronal diversity and its functional implications. In young adults, neurons with high degree centrality, inferred from resting-state activity, exhibit reliable and stable action-plan selectivity during memory-guided tasks, suggesting that connectivity strength is closely linked to functional heterogeneity. This relationship, however, deteriorates in middle-aged and older mice. A computational model simulating age-related declines in synaptic plasticity reproduces these results. In young adults, degree centrality also predicts cross-modal action-plan selectivity, but this predictive power diminishes with age. Furthermore, neurons with high action-plan selectivity are spatially clustered, a pattern that fades with aging. These findings reveal the significant aging impact on the network properties in parallel with the functional and spatial organization of the mPFC.

Theta/Beta Ratio Neurofeedback Effects on Resting and Task-Related Theta Activity in Children with ADHD.

The EEG theta band displays distinct roles in resting and task states. Low resting theta and transient increases in frontal-midline (fm) theta power during tasks are associated with better cognitive control, such as error monitoring. ADHD can disrupt this balance, resulting in high resting theta linked to drowsiness and low fm-theta activity associated with reduced cognitive abilities. Theta/beta ratio (TBR) neurofeedback aims to normalize resting state activity by downregulating theta, which could potentially unfavorably affect task-related fm-theta. This study examines the TBR neurofeedback's impact on both resting and fm-theta activity, hypothesizing that remission depends on these effects. We analyzed data from a multi-center, double-blind randomized controlled trial with 142 children with ADHD and high TBR (ICAN study). Participants were randomized into experimental or sham NF groups. EEG measurements were taken at rest and during an Oddball task before and after neurofeedback, assessing global electrodes for resting theta and fm electrodes during error dynamics. Post-intervention changes were calculated as differences, and ANOVAs were conducted on GROUP, REMISSION, and CONDITION variables. Final analysis included fewer participants for all analyses. Resting state analysis showed no significant effects on global or fm-theta after TBR neurofeedback. Error dynamics analysis was inconclusive for global and fm-theta in both remitters and non-remitters. Results suggest that the current TBR neurofeedback protocol did not reduce aberrant resting state theta, and emphasize the need for refined protocols targeting specific theta-band networks to reduce resting-state theta without affecting fm-theta related to cognitive control.

The Resting-State Activities of the Angular Gyrus and the Micturition Desire-Awakening Function in Children With and Without Enuresis.

Micturition desire-awakening (MDA) function plays a pivotal role in the development of primary nocturnal enuresis (PNE); however, its neural correlates remain largely unexplored. Consequently, this study aimed to identify specific brain regional activities associated with MDA function. Neuroimaging data were collected from 173 children with varying MDA functional grade scores at the Department of Developmental and Behavioral Pediatrics, Shanghai Children's Medical Center, from July 2018 to November 2022. Resting-state images were analyzed using whole-brain correlation techniques and AlphaSim correction to identify brain regional activities and resting-state functional connectivity (RSFC) associated with MDA functional grade scores. Whole-brain correlation analysis demonstrated that the fractional amplitude of low-frequency fluctuations in the right angular gyrus (AG) exhibited a negative correlation with MDA functional grade scores (rs = -0.336, p < 0.001), indicating reduced neural activity in this region with MDA dysfunction. Conversely, RSFC between the right middle frontal gyrus and the right AG was positively correlated with MDA functional grade scores (rs = 0.274, p < 0.001), suggesting increased connectivity in these areasassociated with worse MDA functionality. These findings provide preliminary insights into the neural underpinnings of MDA functionality.

The effects of deep TMS on purpose in life, quantitative EEG and event-related potentials in major depressive disorder

Background: Perceived purpose in life (PIL) is linked with many vital health outcomes, including Major Depressive Disorder (MDD). Methods: In this study, biomarkers associated with depression and PIL were investigated using Brain Network Activation (BNA) based quantitative electroencephalography (QEEG) and event-related potential (ERP) measures in a sample of individuals with MDD. Data were analyzed before and after a 36-session, Deep transcranial magnetic stimulation (TMS) program. Results: At baseline, the study observed that increased slow-frequency resting-state activity in the frontal and temporal regions correlated with higher levels of depression and reduced PIL. Additionally, a reduced P3b amplitude was found to predict elevated depressive symptoms. However, with the application of Deep TMS treatment notable improvements were observed in both depression (p < .001. d = 2.15) and PIL (p < .001, d = 1.59) levels. The treatment also successfully regulated resting-state QEEG (delta/beta) and ERP characteristics (P200 latency), bringing them closer to healthy levels. Conclusions: This attenuation of brain activity patterns relating to depression is encouraging as it suggests that effects were robust and are more likely to be sustained over time. This study represents the first exploration of the effects of Deep TMS on PIL and relevant QEEG and ERP biomarkers. The initial evidence suggests that Deep TMS holds promise in enhancing both PIL and neurophysiological health. Future investigations should continue exploring the utility of Deep TMS in targeting a wide range of neuropsychological and physical health conditions, leveraging objective biomarkers such as QEEG and ERP.

Rest2Task: Modeling task-specific components in resting-state functional connectivity and applications

The networks observed in the brain during resting-state activity are not entirely “task-free.” Instead, they hint at a hierarchical structure prepared for adaptive cognitive functions. Recent studies have increasingly demonstrated the potential of resting-state fMRI to predict local activations or global connectomes during task performance. However, uncertainties remain regarding the unique and shared task-specific components within resting-state brain networks, elucidating local activations and global connectome patterns. A coherent framework is also required to integrate these task-specific components to predict local activations and global connectome patterns. In this work, we introduce the Rest2Task model based on the partial least squares-based multivariate regression algorithm, which effectively integrates mappings from resting-state connectivity to local activations and global connectome patterns. By analyzing the coefficients of the regression model, we extracted task-specific resting-state components corresponding to brain local activation or global connectome of various tasks and applied them to the brain lateralization prediction and psychiatric disorders diagnostic. Our model effectively substitutes traditional whole-brain functional connectivity (FC) in predicting functional lateralization and diagnosing brain disorders. Our research represents the inaugural effort to quantify the contribution of patterns (components) within resting-state FC to different tasks, endowing these components with specific task-related contextual information. The task-specific resting-state components offer new insights into brain lateralization processing and disease diagnosis, potentially providing fresh perspectives on the adaptive transformation of brain networks in response to tasks.

Resting-state brain networks alterations in adolescents with Internet Gaming Disorder associate with cognitive control impairments.

Research indicates that cognitive control is compromised in individuals with internet gaming disorder (IGD). However, the neural mechanisms behind it are still unclear. This study aims to investigate alterations in resting-state brain networks in adolescents with IGD and the potential neurobiological mechanisms underlying cognitive dysfunction. A total of 44 adolescent IGD subjects (male/female: 38/6) and 50 healthy controls (male/female: 40/10) were enrolled. Participants underwent demographic assessments, Young's Internet Addiction Scale, Barratt Impulsiveness Scale 11 Chinese Revised Version, the Chinese Adolescents' Maladaptive Cognitions Scale, exploratory eye movement tests, and functional magnetic resonance imaging (fMRI). FMRI data were analyzed using the GIFT software for independent component analysis, focusing on functional connectivity within and between resting-state brain networks. In comparison to the control group, impulsivity in adolescent IGD subjects showed a positive correlation with the severity of IGD (r=0.6350, p < 0.001), linked to impairments in the Executive Control Network (ECN) and a decrease in functional connectivity between the Salience Network (SN) and ECN (r=0.4307, p=0.0021; r=-0.5147, p=0.0034). Decreased resting state activity of the dorsal attention network (DAN) was associated with attentional dysregulation of IGD in adolescents (r=0.4071, p=0.0017), and ECN increased functional connectivity with DAN. The degree of IGD was positively correlated with enhanced functional connectivity between the ECN and DAN (r=0.4283, p=0.0037). This research demonstrates that changes in the ECN and DAN correlate with heightened impulsivity and attentional deficits in adolescents with IGD. The interaction between cognitive control disorders and resting-state brain networks in adolescent IGD is related.

Daily Dynamics of Resting-State Electroencephalographic Theta and Gamma Fluctuations Are Associated With Cognitive Performance in Healthy Aging.

Healthy age-related cognitive changes are highly heterogeneous across individuals. This variability is increasingly explained through the lens of spontaneous fluctuations of brain activity, now considered a powerful index of age-related changes. However, brain activity is a biological process modulated by circadian rhythms, and how these fluctuations evolve throughout the day is under investigation. We analyzed data from 101 healthy late middle-aged participants from the Cognitive Fitness in Aging study (68 women and 33 men; aged 50-69 years). Participants completed 5 electroencephalographic (EEG) recordings of spontaneous resting-state activity on the same day. We used weighted phase-lag index (wPLI) analyses as an index of the functional synchrony between brain regions couplings, and we computed daily global PLI fluctuation rates of the 5 recordings to assess the association with cognitive performance and β-amyloid and tau/neuroinflammation pathological markers. We found that theta and gamma daily fluctuations in the salience-control executive internetwork (SN-CEN) are associated with distinct mechanisms underlying cognitive heterogeneity in aging. Higher levels of SN-CEN theta daily fluctuations appear to be deleterious for memory performance and were associated with higher tau/neuroinflammation rates. In contrast, higher levels of gamma daily fluctuations are positively associated with executive performance and were associated with lower rate of β-amyloid deposition. Thus, accounting for daily EEG fluctuations of brain activity contributes to a better understanding of subtle brain changes underlying individuals' cognitive performance in healthy aging. Results also provide arguments for considering the time of day when assessing cognition for old adults in a clinical context.

Induction and stabilization of delta frequency brain oscillations by phase-synchronized rTMS and tACS

BackgroundBrain oscillations in the delta frequency band have been linked with deep sleep and consolidation of declarative memory during sleep. However, the causal relationship of these associations remains not competely clarified, primarily due to constraints by technical limitations of brain stimulation approaches suited to induce and stabilize respective oscillatory activity in the human brain. The objective of this study was to establish a non-invasive brain stimulation protocol capable of reliably inducing, and stabilizing respective oscillatory activity in the delta frequency range. HypothesisWe aimed to develop an efficient non-invasive brain stimulation (NIBS) protocol for delta frequency induction and stabilization via concurrent, phase-locked repetitive transcranial magnetic stimulation (rTMS) and transcranial alternating current stimulation (tACS). We hypothesized that rTMS induces oscillatory resting-state activity in the delta frequency and that tACS stabilizes this effect, as has been shown before for alpha and theta frequencies. Methods19 healthy participants took part in a repeated-measures experimental protocol. We applied rTMS pulses synchronized with the peak or trough phase of 0.75Hz tACS over the bilateral prefrontal cortex. Resting state EEG in eyes-open (EO) and eyes-closed (EC) conditions was recorded before, immediately after and every 10 min for up to 1 h after intervention. ResultsrTMS phase-synchronized to the trough of the tACS waveform significantly increased delta frequency activity for up to 60 min in both EO and EC conditions after stimulation. The effects extended from frontal to temporal regions and this enhancement of oscillatory activity was shown to be specific for the delta frequency range. ConclusionConcurrent, trough-synchronized 0.75 Hz rTMS combined with tACS may be a reliable protocol to induce long-lasting oscillatory activity in the delta frequency range. The results of the current study might perspectively be relevant for clinical treatment of sleep disturbances which are accompanied by pathologically altered brain oscillations, and enhancement of memory consolidation.

The reliability and validity of rapid transcranial magnetic stimulation mapping for muscles under active contraction

Rapid mapping is a transcranial magnetic stimulation (TMS) mapping method which can significantly reduce data collection time compared to traditional approaches. However, its validity and reliability has only been established for upper-limb muscles during resting-state activity. Here, we determined the validity and reliability of rapid mapping for non-upper limb muscles that require active contraction during TMS: the masseter and quadriceps muscles. Eleven healthy participants attended two sessions, spaced two hours apart, each involving rapid and ‘traditional’ mapping of the masseter muscle and three quadriceps muscles (rectus femoris, vastus medialis, vastus lateralis). Map parameters included map volume, map area and centre of gravity (CoG) in the medial-lateral and anterior-posterior directions. Low to moderate measurement errors (%SEMeas = 10–32) were observed across muscles. Relative reliability varied from good-to-excellent (ICC = 0.63–0.99) for map volume, poor-to-excellent (ICC = 0.11–0.86) for map area, and fair-to-excellent for CoG (ICC = 0.25–0.8) across muscles. There was Bayesian evidence of equivalence (BF’s > 3) in most map outcomes between rapid and traditional maps across all muscles, supporting the validity of the rapid mapping method. Overall, rapid TMS mapping produced similar estimates of map parameters to the traditional method, however the reliability results were mixed. As mapping of non-upper limb muscles is relatively challenging, rapid mapping is a promising substitute for traditional mapping, however further work is required to refine this method.

MEG Microstates: An Investigation of Underlying Brain Sources and Potential Neurophysiological Processes

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 (τbs < 0.20, ps > .002), while the lateralization of deviance detection in MMN was associated with mMS 5–6 time coverage (τbs < 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.

A visual representation of the hand in the resting somatomotor regions of the human brain

Hand visibility affects motor control, perception, and attention, as visual information is integrated into an internal model of somatomotor control. Spontaneous brain activity, i.e., at rest, in the absence of an active task, is correlated among somatomotor regions that are jointly activated during motor tasks. Recent studies suggest that spontaneous activity patterns not only replay task activation patterns but also maintain a model of the body's and environment's statistical regularities (priors), which may be used to predict upcoming behavior. Here, we test whether spontaneous activity in the human somatomotor cortex as measured using fMRI is modulated by visual stimuli that display hands vs. non-hand stimuli and by the use/action they represent. A multivariate pattern analysis was performed to examine the similarity between spontaneous activity patterns and task-evoked patterns to the presentation of natural hands, robot hands, gloves, or control stimuli (food). In the left somatomotor cortex, we observed a stronger (multivoxel) spatial correlation between resting state activity and natural hand picture patterns compared to other stimuli. No task-rest similarity was found in the visual cortex. Spontaneous activity patterns in somatomotor brain regions code for the visual representation of human hands and their use.

Development of the basic architecture of neocortical circuitry in the human fetus as revealed by the coupling spatiotemporal pattern of synaptogenesis along with microstructure and macroscale in vivo MR imaging

In humans, a quantifiable number of cortical synapses appears early in fetal life. In this paper, we present a bridge across different scales of resolution and the distribution of synapses across the transient cytoarchitectonic compartments: marginal zone (MZ), cortical plate (CP), subplate (SP), and in vivo MR images. The tissue of somatosensory cortex (7–26 postconceptional weeks (PCW)) was prepared for electron microscopy, and classified synapses with a determined subpial depth were used for creating histograms matched to the histological sections immunoreacted for synaptic markers and aligned to in vivo MR images (1.5 T) of corresponding fetal ages (maternal indication). Two time periods and laminar patterns of synaptogenesis were identified: an early and midfetal two-compartmental distribution (MZ and SP) and a late fetal three-compartmental distribution (CP synaptogenesis). During both periods, a voluminous, synapse-rich SP was visualized on the in vivo MR. Another novel finding concerns the phase of secondary expansion of the SP (13 PCW), where a quantifiable number of synapses appears in the upper SP. This lamina shows a T2 intermediate signal intensity below the low signal CP. In conclusion, the early fetal appearance of synapses shows early differentiation of putative genetic mechanisms underlying the synthesis, transport and assembly of synaptic proteins. “Pioneering” synapses are likely to play a morphogenetic role in constructing of fundamental circuitry architecture due to interaction between neurons. They underlie spontaneous, evoked, and resting state activity prior to ex utero experience. Synapses can also mediate genetic and environmental triggers, adversely altering the development of cortical circuitry and leading to neurodevelopmental disorders.

FTO variant is associated with changes in BMI, ghrelin, and brain function following bariatric surgery.

BACKGROUNDA polymorphism in the fat mass and obesity-associated gene (FTO) is linked to enhanced neural sensitivity to food cues and attenuated ghrelin suppression. Risk allele carriers regain more weight than noncarriers after bariatric surgery. It remains unclear how FTO variation affects brain function and ghrelin following surgery.METHODSResting-state functional magnetic resonance imaging and cue-reactivity functional magnetic resonance imaging with high-/low-caloric food cues were performed before surgery and at 1, 6, and 12 months after surgery to examine brain function in 16 carriers with 1 copy of the rs9939609 A allele (AT) and 26 noncarriers (TT). Behavioral assessments up to 5 years after surgery were also conducted.RESULTSThe AT group relative to the TT group had smaller BMI loss at 12-60 months after surgery and lower resting-state activity in posterior cingulate cortex following laparoscopic sleeve gastrectomy (group-by-time interaction effects). Meanwhile, the AT group relative to the TT group showed greater food cue responses in dorsolateral prefrontal cortex (DLPFC), dorsomedial prefrontal cortex (DMPFC), and insula (group effects). There were negative associations of weight loss with ghrelin and greater activation in DLPFC, DMPFC and insula in the AT but not the TT group.CONCLUSIONThese findings indicate that FTO variation is associated with the evolution of ghrelin signaling and brain function after bariatric surgery, which might hinder weight loss.TRIAL REGISTRATIONChinese Clinical Trial Registry Center, ChiCTR-OOB-15006346.FUNDINGThis work was supported by the National Natural Science Foundation of China (grant nos. 82172023, 82202252, 82302292); National Key R&D Program of China (no. 2022YFC3500603); Natural Science Basic Research Program of Shaanxi (grant nos. 2022JC-44, 2022JQ-622, 2023-JC-QN-0922, 2023-ZDLSF-07); Fundamental Research Funds for the Central Universities (grant nos. ZYTS23188, XJSJ23190, XJS221201, QTZX23093); and the Intramural Research Program of the National Institute on Alcoholism and Alcohol Abuse (grant no. Y1AA3009).

Abnormal functional connectivity of the putamen in obsessive-compulsive disorder

The putamen has been proposed to play a critical role in the development of obsessive-compulsive disorder (OCD). The primary objective of this study was to examine the resting-state regional activity and functional connectivity patterns of the putamen in individuals diagnosed with OCD. To achieve this, we employed resting-state functional magnetic resonance imaging (rs-fMRI) to collect data from a sample of 45 OCD patients and 53 healthy control participants. We aimed to use the regional amplitude of low-frequency fluctuation (ALFF) analysis to generate the ROI masks of the putamen and then conduct the whole brain functional connectivity of the putamen in individuals with OCD. Compared to controls, the OCD group demonstrated decreased ALFF in bilateral putamen. The right putamen also displayed decreased FC with the left putamen extending to the inferior frontal gyrus (IFG), bilateral precuneus extending to calcarine, the right middle occipital cortex extending to the right middle temporal cortex, and the left middle occipital gyrus. The decreased connectivity between the right putamen and the left IFG was negatively correlated with Yale-Brown Obsessive Compulsive scale (Y-BOCS) Obsession Scores. This study aimed to reveal the putamen changes in resting-state activity and connectivity in OCD patients, highlighting the significance of aberrant ALFF/FC of the putamen is a key characteristic of OCD.

Changes on Cognition and Brain Network Temporal Variability After Pediatric Neurosurgery.

Pediatric intracranial space-occupying lesions are common, with prognoses improving markedly in recent years, significantly extending survival. As such, there is an imperative to pay increased attention to the postoperative cognitive functions and brain network alterations in these children because these factors significantly influence their quality of life. Temporal variability (TV) analysis of brain networks captures the full extent of resting-state activities, reflecting cognitive functions and rehabilitation potential. However, previous research rarely uses TV analyses and most focus on adults or children after multidisciplinary treatments, not reflecting the combined effect caused by neurosurgery only and self-repair. This study gives our insights into this field from a holistic perspective. We studied 35 children with intracranial space-occupying lesions, analyzing pre- and postsurgery MRI and cognitive tests. We used TV analysis to assess changes and correlated imaging indicators with cognitive performance. We observed a tendency for cognitive recovery after about 3 months postsurgery, primarily in the domains of social cognition and nonverbal reasoning. TV analysis of brain networks indicated increased nodal variability within systems such as the visual and sensorimotor networks, which are integral to external interactions. Correlative analysis showed that alterations in certain occipital regions were associated with changes in social cognition and nonverbal reasoning. These findings suggest significant intrinsic repair in cognitive functions and brain networks at around 3 months postneurosurgery in children. This study not only enriches our comprehension of postoperative cognitive and brain network self-repair processes in children but also furnishes potential therapeutic targets for rehabilitation interventions and establishes a theoretical foundation for proactive surgical interventions.

Adaptive Strategies of Single-Sided Deaf Cochlear-Implant Users Revealed Through Resting State Activity: an Auditory PET Brain Imaging Study

Brain plasticity refers to the brain's ability to reorganize its structure or function in response to experiences, learning, and environmental influences. This phenomenon is particularly significant in individuals with deafness, as the brain adapts to compensate for the lack of auditory stimulation. The aim of this study is to investigate whether cochlear implantation can restore a normal pattern of brain activation following auditory stimulation in cases of asymmetric hearing loss. We used a PET-scan technique to assess brain activity after cochlear implantation, specifically during an auditory voice/non-voice discrimination task. The results indicated a nearly normal pattern of brain activity during the auditory discrimination task, except for increased activation in areas related to attentional processes compared to controls. Additionally, brain activity at rest showed significant changes in implanted participants, including cross modal visuo-auditory processing. Therefore, cochlear implants can restore the brain's activation pattern through long-term adaptive adjustments in intrinsic brain activity.