Anatomical and functional coupling between the dorsal and ventral attention networks

Machine Learning Classification Based on Individual Whole-Brain Functional Connectivity in Male OSA Patients

Purpose

Previous studies have shown altered paired brain functional connectivity (FC) in obstructive sleep apnea (OSA) patients, linked to cognitive impairment. This study utilized individual FC analysis to investigate the distinctive FC characteristics in OSA and evaluate their classification efficiency.

Methods

We included 82 moderate to severe OSA patients [41 OSA with normal cognition (OSA-NC), 41 OSA with mild cognitive impairments (OSA-MCI)] and 84 healthy control (HC). Resting-state fMRI data and clinical scale data were collected. Individual FC was derived using multi-task learning-based sparse convex alternating structure optimization, with feature selection via the least absolute shrinkage and selection operator. Support vector machine classifiers were used for OSA vs HC and OSA-NC vs OSA-MCI classification. The top 10 FC features contributing to classification were analyzed for group differences. A significance level of p < 0.05 was considered statistically significant.

Results

The study results showed that individual FC achieved higher classification accuracy than traditional Pearson-based FC (OSA vs HC: 91.8% vs 79.5%; OSA-NC vs OSA-MCI: 81.3% vs 63.8%). The top 10 individual-specific FC networks contributing to classification were mainly located in the default mode network, attention network, showing significant inter-group differences in connectivity strength between the two groups.

Conclusion

This study identified static individualized FC characteristics in OSA patients with varying cognitive impairments. Based on individual FC, the classification accuracy of OSA-NC and OSA-MCI was significantly improved, the individual FC may serve as a potential neuroimaging marker for predicting OSA-MCI, providing an individual clinical diagnosis and treatment evaluation.

Connections Between the Middle Frontal Gyrus and the Dorsoventral Attention Network Are Associated With the Development of Attentional Symptoms

BACKGROUND

The right middle frontal gyrus (MFG) has been proposed as a convergence site for the dorsal attention network (DAN) and ventral attention network (VAN), regulating both networks and enabling flexible modulation of attention. However, it is unclear whether the connections between the right MFG and these networks can predict changes in attention-deficit/hyperactivity disorder (ADHD) symptoms.

METHODS

This study used data from the Children School Functions and Brain Development project (N = 713, 56.2% boys). Resting-state functional magnetic resonance imaging was employed to analyze the connections of the right MFG with the DAN/VAN; connectome-based predictive modeling was applied for longitudinal prediction, and ADHD polygenic risk scores were used for genetic analysis.

RESULTS

ADHD symptoms were associated with the connections between the right MFG and DAN subregion, including the frontal eye field, as well as the VAN subregions, namely the inferior parietal lobule and inferior frontal gyrus. Furthermore, these connections of the right MFG with the frontal eye field, the inferior parietal lobule, and the inferior frontal gyrus could significantly predict changes in ADHD symptoms over 1 year and mediate the prediction of ADHD symptom changes by polygenic risk scores for ADHD. Finally, the validation samples confirmed that the functional connectivity between the right MFG and the frontal eye field/inferior parietal lobule in patients with ADHD was significantly weaker than that in typically developing control participants, and this difference disappeared after medication.

CONCLUSIONS

The connection of the right MFG with the DAN and VAN can serve as a predictive indicator for changes in ADHD symptoms over the following year, while also mediating the prediction of ADHD symptom changes by a polygenic risk score for ADHD. These findings hold promise as potential biomarkers for early identification of children who are at risk of developing ADHD.

Dissociative experiences alter resting state functional connectivity after childhood abuse

Dissociative experiences commonly occur alongside adverse childhood experiences (ACE), yet research on their neurofunctional biomarkers has overlooked their unique association with dimensions of childhood abuse and neglect. We investigated interactions between dissociative experiences and childhood abuse, anticipating anti-correlations between the right-lateralized anterior middle frontal gyrus (raMFG) and the medial temporal lobe, as well as the temporal gyri. Examining resting-state functional connectivity in 91 participants with a history of ACE, we employed seed-to-voxel analyses seeding the raMFG. Multiple linear regression and post-hoc moderation/mediation models explored interactions and individual effects of dissociation and dimensions of ACE. The Dissociative Experiences Scale (DES) and Childhood Trauma Questionnaire (CTQ) quantified dissociation and dimensions of ACE. A DES by CTQ-A (childhood abuse) interaction predicted an anti-correlation between the raMFG and right hippocampus, moderated by CTQ-A. The CTQ revealed negative connectivity between the raMFG and right anterior cingulate cortex. CTQ-N (childhood neglect) indicated that both the right supplementary motor area and right insula related positively to the raMFG. Our findings underscore a distinct neural signature of childhood abuse-related dissociative experiences, potentially linked to dissociated memories.

Anchoring functional connectivity to individual sulcal morphology yields insights in a pediatric study of reasoning

A salient neuroanatomical feature of the human brain is its pronounced cortical folding, and there is mounting evidence that sulcal morphology is relevant to functional brain architecture and cognition. However, our understanding of the relationships between sulcal anatomy, brain activity, and behavior is still in its infancy. We previously found the depth of three small, shallow sulci in lateral prefrontal cortex (LPFC) was linked to reasoning performance in childhood and adolescence (Voorhies et al., 2021). These findings beg the question: what is the linking mechanism between sulcal morphology and cognition? To shed light on this question, we investigated functional connectivity among sulci in LPFC and lateral parietal cortex (LPC). We leveraged manual parcellations (21 sulci/hemisphere, total of 1806) and functional magnetic resonance (fMRI) data from a reasoning task from 43 participants aged 7-18 years (20 female). We conducted clustering and classification analyses of individual-level functional connectivity among sulci. Broadly, we found that 1) the connectivity patterns of individual sulci could be differentiated - and more accurately than rotated sulcal labels equated for size and shape; 2) sulcal connectivity did not consistently correspond with that of probabilistic labels or large-scale networks; 3) sulci clustered together into groups with similar patterns, not dictated by spatial proximity; and 4) across individuals, greater depth was associated with higher network centrality for several sulci under investigation. These results highlight that functional connectivity can be meaningfully anchored to individual sulcal anatomy, and demonstrate that functional network centrality can vary as a function of sulcal depth.

Altered Static and Dynamic Functional Network Connectivity and Combined Machine Learning in Stroke

Stroke is a condition characterized by damage to the cerebral vasculature from various causes, resulting in focal or widespread brain tissue damage. Prior neuroimaging research has demonstrated that individuals with stroke present structural and functional brain abnormalities, evident through disruptions in motor, cognitive, and other vital functions. Nevertheless, there is a lack of studies on alterations in static and dynamic functional network connectivity in the brains of stroke patients. Fifty stroke patients and 50 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning. Initially, the independent component analysis (ICA) method was utilized to extract the resting-state network (RSN). Subsequently, the disparities in static functional network connectivity both within and between networks among the two groups were computed and juxtaposed. Following this, five consistent and robust dynamic functional network connectivity (dFNC) states were derived by integrating the sliding time window method with k-means cluster analysis, and the distinctions in dFNC between the groups across different states, along with the intergroup variations in three dynamic temporal metrics, were assessed. Finally, a support vector machine (SVM) approach was employed to discriminate stroke patients from HCs using FC and FNC as classification features. Comparing the stroke group to the healthy control (HC) group, the stroke group exhibited reduced intra-network functional connectivity (FC) in the right superior temporal gyrus of the ventral attention network (VAN), the left calcarine of the visual network (VN), and the left precuneus of the default mode network (DMN). Regarding static functional network connectivity (FNC), we identified increased connectivity between the executive control network (ECN) and dorsal attention network (DAN), salience network (SN) and DMN, SN-ECN, and VN-ECN, along with decreased connectivity between DAN-DAN, ECN-SN, SN-SN, and DAN-VN between the two groups. Noteworthy differences in dynamic FNC (dFNC) were observed between the groups in states 3 to 5. Moreover, stroke patients demonstrated a significantly higher proportion of time and longer mean dwell time in state 4, alongside a decreased proportion of time in state 5 compared to HC. Finally, utilizing FC and FNC as features, stroke patients could be distinguished from HC with an accuracy exceeding 70% and an area under the curve ranging from 0.8284 to 0.9364. In conclusion, our study reveals static and dynamic changes in large-scale brain networks in stroke patients, potentially linked to abnormalities in visual, cognitive, and motor functions. This investigation offers valuable insights into the neural mechanisms underpinning the functional deficits observed in stroke, thereby aiding in the diagnosis and development of targeted therapeutic interventions for affected individuals.

A meta-analysis of cognitive flexibility in aging: Perspective from functional network and lateralization

Cognitive flexibility, the ability to switch between mental processes to generate appropriate behavioral responses, is reduced with typical aging. Previous studies have found that age-related declines in cognitive flexibility are often accompanied by variations in the activation of multiple regions. However, no meta-analyses have examined the relationship between cognitive flexibility in aging and age-related variations in activation within large-scale networks. Here, we conducted a meta-analysis employing multilevel kernel density analysis to identify regions with different activity patterns between age groups, and determined how these regions fall into functional networks. We also employed lateralization analysis to explore the spatial distribution of regions exhibiting group differences in activation. The permutation tests based on Monte Carlo simulation were used to determine the significance of the activation and lateralization results. The results showed that cognitive flexibility in aging was associated with both decreased and increased activation in several functional networks. Compared to young adults, older adults exhibited increased activation in the default mode, dorsal attention, ventral attention, and somatomotor networks, while displayed decreased activation in the visual network. Moreover, we found a global-level left lateralization for regions with decreased activation, but no lateralization for regions with higher activation in older adults. At the network level, the regions with decreased activation were left-lateralized, while the regions with increased activation showed varying lateralization patterns within different networks. To sum up, we found that networks that support various mental functions contribute to age-related variations in cognitive flexibility. Additionally, the aging brain exhibited network-dependent activation and lateralization patterns in response to tasks involving cognitive flexibility. We highlighted that the comprehensive meta-analysis in this study offered new insights into understanding cognitive flexibility in aging from a network perspective.

Detection of neurophysiological markers of cognitive reserve: an EEG study

Background and objectives

Cognitive reserve (CR) is a property of the brain that allows for better-than-expected cognitive performance relative to the degree of brain change over the course of life. However, neurophysiological markers of CR remain under-investigated. Electroencephalography (EEG) features may function as suitable neurophysiological markers of CR. To assess this, we investigated whether the dorsal attention network (DAN) and ventral attention network (VAN) activities, as measured during resting-state EEG, moderate the relationship between hippocampal volume and episodic memory.

Methods

Participants were recruited as part of the National Center for Geriatrics and Gerontology-Study of Geriatric Syndromes. Hippocampal volume was determined using magnetic MRI, and episodic memory was measured using word lists. After testing the effect of hippocampal volume on memory performance using multiple regression analysis, we evaluated the interactions between hippocampal volume and DAN and VAN network activities. We further used the Johnson-Neyman technique to quantify the moderating effects of DAN and VAN network activities on the relationship between hippocampal volume and word list memory, as well as to identify specific ranges of DAN and VAN network activity with significant hippocampal-memory association.

Results

A total of 449 participants were included in this study. Our analysis revealed significant moderation of DAN with a slope of β = -0.00012 (95% CI: -0.00024; -0.00001, p = 0.040), and VAN with a slope of β = 0.00014 (95% CI: 0.00001; 0.00026, p = 0.031). Further, we found that a larger hippocampal volume was associated with improved memory performance, and that this association became stronger as the DAN activity decreased until a limit of DAN activity of 944.9, after which the hippocampal volume was no longer significantly related to word-list memory performance. For the VAN, we found that a higher hippocampal volume was more strongly associated with better memory performance when VAN activity was higher. However, when VAN activity extended beyond -914.6, the hippocampal volume was no longer significantly associated with word-list memory.

Discussion

Our results suggest that attentional networks help to maintain memory performance in the face of age-related structural decline, meeting the criteria for the neural implementation of cognitive reserve.

Differences in brain functional connectivity between tinnitus with or without hearing loss

To explore the differences in brain imaging in tinnitus with or without hearing loss (HL). We acquired functional MRI scans from 26 tinnitus patients with HL (tinnitus-HL), 24 tinnitus patients with no HL (tinnitus-NHL), and 26 healthy controls (HCs) matched by age and sex. The left and right thalamus were selected as seeds to study the endogenous functional connectivity (FC) of the whole brain, and its correlation with clinical indices was analyzed. Brain regions showing FC differences among the three groups included the Heschl gyrus (HES), right Hippocampus (HIP), right Amygdala (AMYG), left Calcarine fissure and surrounding cortex (CAL). Post hoc analysis showed that the thalamus-HIP connection and thalamus-lingual gyrus (LING) connection were enhanced in the tinnitus-NHL group, as compared to tinnitus-HL. Compared with HCs, the tinnitus-NHL group showed an enhanced connection between the thalamus and the left Inferior occipital gyrus, left CAL and LING. While in the tinnitus-HL group, the connection between the thalamus and several brain regions (right HES, right AMYG, etc) was weakened. In the tinnitus-HL group, the tinnitus handicap inventory scores were positively correlated with the FC of the left thalamus and right HES, right thalamus and right Rolandic operculum. The duration of tinnitus was negatively correlated with the FC of the right thalamus and right HIP. Abnormal FC in the thalamus may play an important role in the pathogenesis of tinnitus. Tinnitus-NHL and tinnitus-HL show different connection patterns, indicating that there are some differences in their pathogenesis.

A diffusion MRI tractography atlas for concurrent white matter mapping across Eastern and Western populations

The study of brain differences across Eastern and Western populations provides vital insights for understanding potential cultural and genetic influences on cognition and mental health. Diffusion MRI (dMRI) tractography is an important tool in assessing white matter (WM) connectivity and brain tissue microstructure across different populations. However, a comprehensive investigation into WM fiber tracts between Eastern and Western populations is challenged due to the lack of a cross-population WM atlas and the large site-specific variability of dMRI data. This study presents a dMRI tractography atlas, namely the East-West WM Atlas, for concurrent WM mapping between Eastern and Western populations and creates a large, harmonized dMRI dataset (n=306) based on the Human Connectome Project and the Chinese Human Connectome Project. The curated WM atlas, as well as subject-specific data including the harmonized dMRI data, the whole brain tractography data, and parcellated WM fiber tracts and their diffusion measures, are publicly released. This resource is a valuable addition to facilitating the exploration of brain commonalities and differences across diverse cultural backgrounds.

The neural and genetic underpinnings of different developmental trajectories of Attention-Deficit/Hyperactivity Symptoms in children and adolescents

BACKGROUND

The trajectory of attention-deficit hyperactivity disorder (ADHD) symptoms in children and adolescents, encompassing descending, stable, and ascending patterns, delineates their ADHD status as remission, persistence or late onset. However, the neural and genetic underpinnings governing the trajectory of ADHD remain inadequately elucidated.

METHODS

In this study, we employed neuroimaging techniques, behavioral assessments, and genetic analyses on a cohort of 487 children aged 6-15 from the Children School Functions and Brain Development project at baseline and two follow-up tests for 1 year each (interval 1: 1.14 ± 0.32 years; interval 2: 1.14 ± 0.30 years). We applied a Latent class mixed model (LCMM) to identify the developmental trajectory of ADHD symptoms in children and adolescents, while investigating the neural correlates through gray matter volume (GMV) analysis and exploring the genetic underpinnings using polygenic risk scores (PRS).

RESULTS

This study identified three distinct trajectories (ascending-high, stable-low, and descending-medium) of ADHD symptoms from childhood through adolescence. Utilizing the linear mixed-effects (LME) model, we discovered that attention hub regions served as the neural basis for these three developmental trajectories. These regions encompassed the left anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC), responsible for inhibitory control; the right inferior parietal lobule (IPL), which facilitated conscious focus on exogenous stimuli; and the bilateral middle frontal gyrus/precentral gyrus (MFG/PCG), accountable for regulating both dorsal and ventral attention networks while playing a crucial role in flexible modulation of endogenous and extrinsic attention. Furthermore, our findings revealed that individuals in the ascending-high group exhibited the highest PRS for ADHD, followed by those in the descending-medium group, with individuals in the stable-low group displaying the lowest PRS. Notably, both ascending-high and descending-medium groups had significantly higher PRS compared to the stable-low group.

CONCLUSIONS

The developmental trajectory of ADHD symptoms in the general population throughout childhood and adolescence can be reliably classified into ascending-high, stable-low, and descending-medium groups. The bilateral MFG/PCG, left ACC/mPFC, and right IPL may serve as crucial brain regions involved in attention processing, potentially determining these trajectories. Furthermore, the ascending-high pattern of ADHD symptoms exhibited the highest PRS for ADHD.

Aberrant auditory metabolite levels and topological properties are associated with cognitive decline in presbycusis patients

Presbycusis has been reported as related to cognitive decline, but its underlying neurophysiological mechanism is still unclear. This study aimed to investigate the relationship between metabolite levels, cognitive function, and node characteristics in presbycusis based on graph theory methods. Eighty-four elderly individuals with presbycusis and 63 age-matched normal hearing controls underwent magnetic resonance spectroscopy, functional magnetic resonance imaging scans, audiological assessment, and cognitive assessment. Compared with the normal hearing group, presbycusis patients exhibited reduced gamma-aminobutyric acid and glutamate levels in the auditory region, increased nodal characteristics in the temporal lobe and precuneus, as well as decreased nodal characteristics in the superior occipital gyrus and medial orbital. The right gamma-aminobutyric acid levels were negatively correlated with the degree centrality in the right precuneus and the executive function. Degree centrality in the right precuneus exhibited significant correlations with information processing speed and executive function, while degree centrality in the left medial orbital demonstrated a negative association with speech recognition ability. The degree centrality and node efficiency in the superior occipital gyrus exhibited a negative association with hearing loss and speech recognition ability, respectively. These observed changes indicate alterations in metabolite levels and reorganization patterns at the brain network level after auditory deprivation.

Attention Please! Unravelling the Link Between Brain Network Connectivity and Cognitive Attention Following Acquired Brain Injury: A Systematic Review of Structural and Functional Measures

Traumatic brain injury (TBI) and stroke are the most common causes of acquired brain injury (ABI), annually affecting 69 million and 15 million people, respectively. Following ABI, the relationship between brain network disruption and common cognitive issues including attention dysfunction is heterogenous. Using PRISMA guidelines, we systematically reviewed 43 studies published by February 2023 that reported correlations between attention and connectivity. Across all ages and stages of recovery, following TBI, greater attention was associated with greater structural efficiency within/between executive control network (ECN), salience network (SN), and default mode network (DMN) and greater functional connectivity (fc) within/between ECN and DMN, indicating DMN interference. Following stroke, greater attention was associated with greater structural connectivity (sc) within ECN; or greater fc within the dorsal attention network (DAN). In childhood ABI populations, decreases in structural network segregation were associated with greater attention. Longitudinal recovery from TBI was associated with normalization of DMN activity, and in stroke, normalization of DMN and DAN activity. Results improve clinical understanding of attention-related connectivity changes after ABI. Recommendations for future research include increased use of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to measure connectivity at the point of care, standardized attention and connectivity outcome measures and analysis pipelines, detailed reporting of patient symptomatology, and casual analysis of attention-related connectivity using brain stimulation.

rTMS concurrent with cognitive training rewires AD brain by enhancing GM-WM functional connectivity: a preliminary study

Repetitive transcranial magnetic stimulation (rTMS) and cognitive training for patients with Alzheimer's disease (AD) can change functional connectivity (FC) within gray matter (GM). However, the role of white matter (WM) and changes of GM-WM FC under these therapies are still unclear. To clarify this problem, we applied 40 Hz rTMS over angular gyrus (AG) concurrent with cognitive training to 15 mild-moderate AD patients and analyzed the resting-state functional magnetic resonance imaging before and after treatment. Through AG-based FC analysis, corona radiata and superior longitudinal fasciculus (SLF) were identified as activated WM tracts. Compared with the GM results with AG as seed, more GM regions were found with activated WM tracts as seeds. The averaged FC, fractional amplitude of low-frequency fluctuation (fALFF), and regional homogeneity (ReHo) of the above GM regions had stronger clinical correlations (r/P = 0.363/0.048 vs 0.299/0.108, 0.351/0.057 vs 0.267/0.153, 0.420/0.021 vs 0.408/0.025, for FC/fALFF/ReHo, respectively) and better classification performance to distinguish pre-/post-treatment groups (AUC = 0.91 vs 0.88, 0.65 vs 0.63, 0.87 vs 0.82, for FC/fALFF/ReHo, respectively). Our results indicated that rTMS concurrent with cognitive training could rewire brain network by enhancing GM-WM FC in AD, and corona radiata and SLF played an important role in this process.

Multilayer network analysis of dynamic network reconfiguration in patients with moderate-to-severe obstructive sleep apnea and its association with neurocognitive function

BACKGROUND

Brain functional network disruption and neurocognitive dysfunction have been reported in obstructive sleep apnea (OSA) patients. Nevertheless, most research studies static networks, while brain evolution continues dynamically.

PURPOSE

To investigate the characteristics of dynamical networks in moderate-to-severe OSA patients using multilayer network analysis of dynamic networks and compare their association with neurocognitive function.

METHODS

Twenty-seven moderate-to-severe OSA patients and twenty-five matched healthy controls (HCs) who completed the examination of the Epworth sleepiness scale (ESS), neurocognitive function, polysomnography, and functional magnetic resonance imaging (fMRI) were prospectively included. The dynamic variations of resting-state functional networks in both groups were described via network switching rate. Switching rates and their correlation with clinical parameters were analyzed.

RESULTS

At the global level, network switching rates were notably lower in the OSA group than in the HCs group (p = 0.002). More specifically, the differences include the default mode network (DMN), auditory network, and ventral attention network at the subnetwork level, and the right rolandic operculum, left middle temporal gyrus, and right precentral gyrus at the nodal level. Furthermore, these altered switching rates have a close correlation with ESS, sleep parameters, and neurocognitive function.

CONCLUSION

Patients with moderate-to-severe OSA showed lower network switching rates, especially in the DMN, auditory network, and ventral attention network. The disruption of dynamic functional networks may be a potentially crucial mechanism of neurocognitive dysfunction in moderate-to-severe OSA patients.

Aberrant dynamic and static functional connectivity of the striatum across specific low-frequency bands in patients with autism spectrum disorder

BACKGROUND

Dysfunctions of the striatum have been repeatedly observed in autism spectrum disorder (ASD). However, previous studies have explored the static functional connectivity (sFC) of the striatum in a single frequency band, ignoring the dynamics and frequency specificity of brain FC. Therefore, we investigated the dynamic FC (dFC) and sFC of the striatum in the slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) frequency bands.

METHODS

Data of 47 ASD patients and 47 typically developing (TD) controls were obtained from the Autism Brain Imaging Data Exchange (ABIDE) database. A seed-based approach was used to compute the dFC and sFC. Then, a two-sample t-test was performed. For regions showing abnormal sFC and dFC, we performed clinical correlation analysis and constructed support vector machine (SVM) models.

RESULTS

The middle frontal gyrus (MFG), precuneus, and medial superior frontal gyrus (mPFC) showed both dynamic and static alterations. The reduced striatal dFC in the right MFG was associated with autism symptoms. The dynamic‒static FC model had a great performance in ASD classification, with 95.83 % accuracy.

CONCLUSIONS

The striatal dFC and sFC were altered in ASD, which were frequency specific. Examining brain activity using dynamic and static FC provides a comprehensive view of brain activity.

Aberrant functional connectivity within and between brain networks in patients with early-onset bipolar disorder

OBJECTIVE

This study used independent component analysis (ICA) to investigate the connectivity patterns of resting-state functional large-scale brain networks in patients with early-onset bipolar disorder (BD).

METHODS

ICA was used to extract brain functional network components from 43 early-onset BD patients and 21 healthy controls (HCs). Then, the functional connectivity (FC) and functional network connectivity (FNC) within and between the independent brain networks was calculated, and the correlation between the connectivity changes and neuropsychological scale was evaluated.

RESULTS

Compared with HCs, FC increased in the right hippocampus and inferior temporal gyrus, and left triangular inferior frontal gyrus of the anterior default mode network (aDMN); right median cingulate and paracingulate gyri, and inferior parietal lobule of the posterior DMN (pDMN); and right precentral and postcentral gyrus of the sensorimotor network (SMN) in early-onset BD patients. However, FC decreased in the left superior frontal gyrus of the aDMN, left paracentral lobule of the SMN, and left lingual gyrus and calcarine of the visual network in early-onset BD patients. There was no significant correlation between FC values of differential brain regions within resting-state networks (RSNs) and neuropsychological scores (uncorrected p > 0.05). In addition, the FNC among the pDMN-auditory network, pDMN-visual network, left frontoparietal network (lFPN)-visual network, lFPN-aDMN and dorsal attention network-ventral attention network (DAN-VAN) were increased in early-onset BD patients. The zFNC of the pDMN-visual network was positively correlated with the anxiety/somatization score (r = 0.5833, p < 0.0001) and sleep disorders (r = 0.6150, p < 0.0001). The zFNC of the lFPN-aDMN was positively correlated with despair (r = 0.4505, p = 0.004 × 10 < 0.05 after Bonferroni correction). The zFNC of the DAN-VAN was positively correlated with cognitive impairment (r = 0.4598, p = 0.0032 × 10 < 0.05 after Bonferroni correction). The zFNC of the DAN-VAN showed a positive correlation trend with the Hamilton Depression Scale (HAMD) total score (r = 0.4404, p = 0.005 × 10 = 0.05 after Bonferroni correction).

CONCLUSIONS

Patients with early-onset BD showed changes in a wide range of neural functional networks, involving changes in executive control, attention, perceptual regulation, cognition and other neural networks, which may provide new imaging evidence for understanding the pathogenesis of early-onset BD and for therapeutic intervention targets.

Examining resting-state network connectivity in children exposed to perinatal maternal adversity using anatomically weighted functional connectivity (awFC) analyses; A preliminary report

Introduction

Environmental perturbations during critical periods can have pervasive, organizational effects on neurodevelopment. To date, the literature examining the long-term impact of early life adversity has largely investigated structural and functional imaging data outcomes independently. However, emerging research points to a relationship between functional connectivity and the brain’s underlying structural architecture. For instance, functional connectivity can be mediated by the presence of direct or indirect anatomical pathways. Such evidence warrants the use of structural and functional imaging in tandem to study network maturation. Accordingly, this study examines the impact of poor maternal mental health and socioeconomic context during the perinatal period on network connectivity in middle childhood using an anatomically weighted functional connectivity (awFC) approach. awFC is a statistical model that identifies neural networks by incorporating information from both structural and functional imaging data.

Methods

Resting-state fMRI and DTI scans were acquired from children aged 7–9 years old.

Results

Our results indicate that maternal adversity during the perinatal period can affect offspring’s resting-state network connectivity during middle childhood. Specifically, in comparison to controls, children of mothers who had poor perinatal maternal mental health and/or low socioeconomic status exhibited greater awFC in the ventral attention network.

Discussion

These group differences were discussed in terms of the role this network plays in attention processing and maturational changes that may accompany the consolidation of a more adult-like functional cortical organization. Furthermore, our results suggest that there is value in using an awFC approach as it may be more sensitive in highlighting connectivity differences in developmental networks associated with higher-order cognitive and emotional processing, as compared to stand-alone FC or SC analyses.

Learning to read may help promote attention by increasing the volume of the left middle frontal gyrus and enhancing its connectivity to the ventral attention network

Attention and reading are essential skills for successful schooling and in adult life. While previous studies have documented that attention development supports reading acquisition, whether and how learning to read may improve attention among school-age children and the brain structural and functional development that may be involved remain unknown. In this prospective longitudinal study, we examined bidirectional and longitudinal predictions between attention and reading development and the neural mediators of attention and reading development among school-age children using cross-lagged panel modeling. The results showed that better baseline reading performance significantly predicted better attention performance one year later after controlling for baseline attention performance. In contrast, after controlling for baseline reading performance, attention did not significantly predict reading performance one year later, while more attention problems also significantly predicted worse reading performance. Both the increasing gray matter volume of the left middle frontal gyrus and the increasing connectivity between the left middle frontal gyrus and the ventral attention network mediated the above significant longitudinal predictions. This study, directly revealed that reading skills may predict the development of important cognitive functions, such as attention, in school-age children. Therefore, learning to read is not only a challenge for school-age children but is also an important way to optimize attention and brain development.

The impact of aging on morphometric changes in the cerebellum: A voxel-based morphometry study

Introduction

Aging influences the morphology of the central nervous system. While several previous studies focused on morphometric changes of the supratentorial parts, investigations on age-related cerebellar changes are rare. The literature concerning the morphological changes in the cerebellum is heterogenous depending (i) on the methods used (cerebellar analysis in the context of a whole brain analysis or specific methods for a cerebellar analysis), (ii) the life span that was investigated, and (iii) the analytic approach (i.e., using linear or non-linear methods).

Methods

We fill this research gap by investigating age-dependent cerebellar changes in the aging process occurring before the age of 70 in healthy participants, using non-linear methods and the spatially unbiased infratentorial template (SUIT) toolbox which is specifically developed to examine the cerebellum. Furthermore, to derive an overview of the possible behavioral correlates, we relate our findings to functional maps of the cerebellum. Twenty-four older participants (mean age 64.42 years, SD ± 4.8) and 25 younger participants (mean age 24.6 years, SD ± 2.14) were scanned using a 3 T-MRI, and the resulting data were processed using a SUIT.

Results

Gray matter (GM) volume loss was found in older participants in three clusters in the right cerebellar region, namely crus I/II and lobule VI related to the frontoparietal network, with crus I being functionally related to the default-mode network and lobule VI extending into vermis VIIa related to the ventral-attention-network.

Discussion

Our results underline an age-related decline in GM volume in the right cerebellar regions that are functionally predominantly related to non-motor networks and cognitive tasks regions of the cerebellum before the age of 70.

Alternative strategy for driving voltage-oscillator in neocortex of rats

Information integration in the brain requires functional connectivity between local neural networks. Here, we investigated the interregional coupling mechanism from the viewpoint of oscillations using optical recording methods. Low-frequency electrical stimulation of rat neocortical slices in a caffeine-containing medium induced oscillatory activity between the primary visual cortex (Oc1) and medial secondary visual cortex (Oc2M), in which the oscillation generator was located in the Oc2M and was triggered by a feedforward signal. During to-and-fro oscillatory activity, neural excitation was marked in layer II/III. When the upper layer was disrupted between Oc1 and Oc2M, feedforward signals could propagate through the deep layer and switch on the oscillator in the Oc2M. When the lower layer was disrupted between Oc1 and Oc2M, feedforward signals could propagate through the upper layer and switch on the oscillator in the Oc2M. In the backward direction, neither the upper layer cut nor the lower layer cut disrupted the propagation of the oscillations. In all cases, the horizontal and vertical pathways were used as needed. Fluctuations in the oscillatory waveforms of the local field potential at the upper and lower layers in the Oc2M were reversed, suggesting that the oscillation originated between the two layers. Thus, the neocortex may work as a safety device for interregional communications in an alternative way to drive voltage oscillators in the neocortex.

Functional connectivity across dorsal and ventral attention networks in response to task difficulty and experimental pain

The dorsal and ventral attention networks (DAN & VAN) provide a framework for studying attentional modulation of pain. It has been argued that cognitive demand distracts attention from painful stimuli via top-down reinforcement of task goals (DAN), whereas pain exerts an interruptive effect on cognitive performance via bottom-up pathways (VAN). The current study explores this explanatory framework by manipulating pain and task demand in combination with functional near-infrared spectroscopy (fNIRS) and Granger Causal Connectivity Analyses (GCCA). Twenty-one participants played a racing game at low and high difficulty levels with or without experimental pain (administered via a cold pressor test). Six channels of fNIRS were collected from bilateral frontal eye fields and intraparietal sulci (DAN), with right-lateralised channels at the inferior frontal gyrus and temporoparietal junction (VAN). Our first analysis revealed increased G-causality from bottom-up pathways (VAN) during the cold pressor test. However, an equivalent experience of experimental pain during gameplay increased G-causality in top-down (DAN) pathways, with the left intraparietal sulcus serving a hub of connectivity. High game difficulty increased G-causality via top-down pathways and implicated the right inferior frontal gyrus as an interhemispheric hub. Our results are discussed with reference to existing models of both networks and attentional modulation of pain.

Systems-level decoding reveals the cognitive and behavioral profile of the human intraparietal sulcus

INTRODUCTION

The human intraparietal sulcus (IPS) covers large portions of the posterior cortical surface and has been implicated in a variety of cognitive functions. It is, however, unclear how cognitive functions dissociate between the IPS's heterogeneous subdivisions, particularly in perspective to their connectivity profile.

METHODS

We applied a neuroinformatics driven system-level decoding on three cytoarchitectural distinct subdivisions (hIP1, hIP2, hIP3) per hemisphere, with the aim to disentangle the cognitive profile of the IPS in conjunction with functionally connected cortical regions.

RESULTS

The system-level decoding revealed nine functional systems based on meta-analytical associations of IPS subdivisions and their cortical coactivations: Two systems-working memory and numeric cognition-which are centered on all IPS subdivisions, and seven systems-attention, language, grasping, recognition memory, rotation, detection of motions/shapes and navigation-with varying degrees of dissociation across subdivisions and hemispheres. By probing the spatial overlap between systems-level co-activations of the IPS and seven canonical intrinsic resting state networks, we observed a trend toward more co-activation between hIP1 and the front parietal network, between hIP2 and hIP3 and the dorsal attention network, and between hIP3 and the visual and somatomotor network.

DISCUSSION

Our results confirm previous findings on the IPS's role in cognition but also point to previously unknown differentiation along the IPS, which present viable starting points for future work. We also present the systems-level decoding as promising approach toward functional decoding of the human connectome.

A low-dimensional cognitive-network space in Alzheimer's disease and frontotemporal dementia

BACKGROUND

Alzheimer's disease (AD) and frontotemporal dementia (FTD) show network dysfunctions linked with cognitive deficits. Within this framework, network abnormalities between AD and FTD show both convergent and divergent patterns. However, these functional patterns are far from being established and their relevance to cognitive processes remains to be elucidated.

METHODS

We investigated the relationship between cognition and functional connectivity of major cognitive networks in these diseases. Twenty-three bvFTD (age: 71±10), 22 AD (age: 72±6), and 20 controls (age: 72±6) underwent cognitive evaluation and resting-state functional MRI. Principal component analysis was used to describe cognitive variance across participants. Brain network connectivity was estimated with connectome analysis. Connectivity matrices were created assessing correlations between parcels within each functional network. The following cognitive networks were considered: default mode (DMN), dorsal attention (DAN), ventral attention (VAN), and frontoparietal (FPN) networks. The relationship between cognition and connectivity was assessed using a bootstrapping correlation and interaction analyses.

RESULTS

Three principal cognitive components explained more than 80% of the cognitive variance: the first component (cogPC1) loaded on memory, the second component (cogPC2) loaded on emotion and language, and the third component (cogPC3) loaded on the visuo-spatial and attentional domains. Compared to HC, AD and bvFTD showed impairment in all cogPCs (p<0.002), and bvFTD scored worse than AD in cogPC2 (p=0.031). At the network level, the DMN showed a significant association in the whole group with cogPC1 and cogPC2 and the VAN with cogPC2. By contrast, DAN and FPN showed a divergent pattern between diagnosis and connectivity for cogPC2. We confirmed these results by means of a multivariate analysis (canonical correlation).

CONCLUSIONS

A low-dimensional representation can account for a large variance in cognitive scores in the continuum from normal to pathological aging. Moreover, cognitive components showed both convergent and divergent patterns with connectivity across AD and bvFTD. The convergent pattern was observed across the networks primarily involved in these diseases (i.e., the DMN and VAN), while a divergent FC-cognitive pattern was mainly observed between attention/executive networks and the language/emotion cognitive component, suggesting the co-existence of compensatory and detrimental mechanisms underlying these components.

A comparative study of the superior longitudinal fasciculus subdivisions between neonates and young adults

The superior longitudinal fasciculus (SLF) is a complex associative tract comprising three distinct subdivisions in the frontoparietal cortex, each of which has its own anatomical connectivity and functional roles. However, many studies on white matter development, hampered by limitations of data quality and tractography methods, treated the SLF as a single entity. The exact anatomical trajectory and developmental status of each sub-bundle of the human SLF in neonates remain poorly understood. Here, we compared the morphological and microstructural characteristics of each branch of the SLF at two ages using diffusion MRI data from 40 healthy neonates and 40 adults. A multi-shell multi-tissue constrained spherical deconvolution (MSMT-CSD) algorithm was used to ensure the successful separation of the three SLF branches (SLF I, SLF II and SLF III). Then, between-group differences in the diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) metrics were investigated in all the SLF branches. Meanwhile, Mahalanobis distances based on all the diffusion metrics were computed to quantify the maturation of neonatal SLF branches, considering the adult brain as the reference. The SLF branches, excluding SLF II, had similar fibre morphology and connectivity between the neonatal and adult groups. The Mahalanobis distance values further supported the notion of heterogeneous maturation among SLF branches. The greatest Mahalanobis distance was observed in SLF II, possibly indicating that it was the least mature. Our findings provide a new anatomical basis for the early diagnosis and treatment of diseases caused by abnormal neonatal SLF development.

Understanding cognitive control in aging: A brain network perspective

Cognitive control decline is a major manifestation of brain aging that severely impairs the goal-directed abilities of older adults. Magnetic resonance imaging evidence suggests that cognitive control during aging is associated with altered activation in a range of brain regions, including the frontal, parietal, and occipital lobes. However, focusing on specific regions, while ignoring the structural and functional connectivity between regions, may impede an integrated understanding of cognitive control decline in older adults. Here, we discuss the role of aging-related changes in functional segregation, integration, and antagonism among large-scale networks. We highlight that disrupted spontaneous network organization, impaired information co-processing, and enhanced endogenous interference promote cognitive control declines during aging. Additionally, in older adults, severe damage to structural network can weaken functional connectivity and subsequently trigger cognitive control decline, whereas a relatively intact structural network ensures the compensation of functional connectivity to mitigate cognitive control impairment. Thus, we propose that age-related changes in functional networks may be influenced by structural networks in cognitive control in aging (CCA). This review provided an integrative framework to understand the cognitive control decline in aging by viewing the brain as a multimodal networked system.

Functional connectivity of brain networks with three monochromatic wavelengths: a pilot study using resting-state functional magnetic resonance imaging

Exposure to certain monochromatic wavelengths can affect non-visual brain regions. Growing research indicates that exposure to light can have a positive impact on health-related problems such as spring asthenia, circadian rhythm disruption, and even bipolar disorders and Alzheimer’s. However, the extent and location of changes in brain areas caused by exposure to monochromatic light remain largely unknown. This pilot study (N = 7) using resting-state functional magnetic resonance shows light-dependent functional connectivity patterns on brain networks. We demonstrated that 1 min of blue, green, or red light exposure modifies the functional connectivity (FC) of a broad range of visual and non-visual brain regions. Largely, we observed: (i) a global decrease in FC in all the networks but the salience network after blue light exposure, (ii) a global increase in FC after green light exposure, particularly noticeable in the left hemisphere, and (iii) a decrease in FC on attentional networks coupled with a FC increase in the default mode network after red light exposure. Each one of the FC patterns appears to be best arranged to perform better on tasks associated with specific cognitive domains. Results can be relevant for future research on the impact of light stimulation on brain function and in a variety of health disciplines.

Impaired brain networks functional connectivity after acute mild hypoxia

This study aimed to analyze the changes in brain networks functional connectivity of pilots exposed to simulated hypoxia using resting-state functional magnetic resonance imaging (fMRI). A total of 35 healthy male pilots exposed to 14.5% oxygen concentration (corresponding to an altitude of 3000 m) underwent resting-state fMRI scans. The independent component analysis (ICA) approach was used to analyze changes in the resting-state brain networks functional connectivity of pilots after hypoxic exposure, and 9 common components in brain functional networks were identified. In the functional connections that showed significant group differences, linear regression was used to examine the association between functional connectivity and clinical characteristics. The brain networks functional connectivity after hypoxia exposure decreased significantly, including the left frontoparietal network and visual network 1-area, left frontoparietal network and visual network 2-area, right frontoparietal network and visual network 2-area, dorsal attention network and ventral attention network, dorsal attention network and auditory network, and ventral attention network and visual network 1-area. We found no correlation between the altered functional connectivity and arterial oxygen saturation level. Our findings provide insights into the mechanisms underlying hypoxia-induced cognitive impairment in pilots.

Intrinsic Network Changes in Bilateral Tinnitus Patients with Cognitive Impairment: A Resting-State Functional MRI Study

Previous studies have found a link between tinnitus and cognitive impairment, even leading to dementia. However, the mechanisms underlying this association are not clear. The purpose of this study was to explore intrinsic network changes in tinnitus and hearing loss patients with cognitive disorders. We included 17 individuals with bilateral idiopathic tinnitus, hearing loss, and cognitive impairment (PA) and 21 healthy controls. We identified resting-state networks (RSNs) and measured intra-network functional connectivity (FC) values via independent component analysis (ICA). We also evaluated correlations between RSNs and clinical characteristics. Compared with the healthy controls, the PA group showed decreased connectivity within the ventral attention network, dorsal attention network (DAN), visual network, left frontoparietal network, right frontoparietal network, sensorimotor network, and increased connectivity within the executive control network. MoCA (Montreal Cognitive Assessment) scores were negatively correlated with the FC values for left calcarine within the DAN. We identified abnormal intrinsic connectivity in several brain networks, mainly involving cognitive control, vision, sensorimotor function, and the cerebellum, in tinnitus patients with cognitive impairment. It may be possible to use the FC strength of the left calcarine within the DAN as an imaging marker to predict cognitive impairment in tinnitus patients.

Disrupted intra- and inter-network connectivity in unilateral acute tinnitus with hearing loss

Purpose

Currently, the underlying neurophysiological mechanism of acute tinnitus is still poorly understood. This study aimed to explore differences in brain functional connectivity (FC) within and between resting-state networks (RSNs) in acute tinnitus patients with hearing loss (ATHL). Furthermore, it also evaluated the correlations between FC alterations and clinical characteristics.

Methods

Two matched groups of 40 patients and 40 healthy controls (HCs) were included. Independent component analysis (ICA) was employed to obtain RSNs and FC differences were calculated within RSNs. In addition, the relationships between networks were conducted using functional network connectivity (FNC) analysis. Finally, an analysis of correlation was used to evaluate the relationship between FNC abnormalities and clinical data.

Results

Results of this study found that seven major RSNs including the auditory network (AN), cerebellum network (CN), default mode network (DMN), executive control network (ECN), sensorimotor network (SMN), ventral attention network (VAN), and visual network (VN) were extracted using the group ICA in both groups. Furthermore, it was noted that the ATHL group showed aberrant FC within the CN, ECN, and VN as compared with HCs. Moreover, different patterns of network interactions were observed between groups, including the SMN-ECN, SMN-CN, ECN-AN, DMN-VAN, and DMN-CN connections. The correlations between functional disconnection and clinical characteristics in ATHL were also found in this study.

Conclusion

In conclusion, this study indicated widespread alterations of intra- and inter-network connectivity in ATHL, suggesting that multiple large-scale network dysfunctions and interactions are involved in the early stage. Furthermore, our findings may provide new perspectives to understand the neuropathophysiological mechanism of acute tinnitus.

Impaired Interhemispheric Synchrony in Parkinson’s Disease with Fatigue

The characteristics of interhemispheric resting-state functional connectivity (FC) in Parkinson’s disease (PD) with fatigue remain unclear; therefore, we aimed to explore the changes in interhemispheric FC in PD patients with fatigue. Sixteen PD patients with fatigue (PDF), 16 PD patients without fatigue (PDNF) and 15 matched healthy controls (HCs) were enrolled in the retrospective cross-sectional study. We used voxel-mirrored homotopic connectivity (VMHC) to analyze the resting-state functional magnetic resonance imaging (fMRI) data of these subjects. Compared to PDNF, PDF patients had decreased VMHC values in the supramarginal gyri (SMG). Furthermore, the mean VMHC values of the SMG were negatively correlated with the mean fatigue severity scale (FSS/9) scores (r = −0.754, p = 0.001). Compared to HCs, PDF patients had decreased VMHC in the SMG and in the opercular parts of the inferior frontal gyri (IFG operc). The VMHC values in the IFG operc and middle frontal gyri (MFG) were notably decreased in PDNF patients compared with HCs. Our findings suggest that the reduced VMHC values within the bilateral SMG may be the unique imaging features of fatigue in PD, and may illuminate the neural mechanisms of fatigue in PD.

Comparative Study on Topological Properties of the Whole-Brain Functional Connectome in Idiopathic Rapid Eye Movement Sleep Behavior Disorder and Parkinson’s Disease Without RBD

Purpose

Idiopathic rapid eye movement Sleep Behavior Disorder (iRBD) is considered as a prodromal and most valuable warning symptom for Parkinson’s disease (PD). Although iRBD and PD without RBD (nRBD-PD) are both α-synucleinopathies, whether they share the same neurodegeneration process is not clear enough. In this study, the pattern and extent of neurodegeneration were investigated and compared between early-stage nRBD-PD and iRBD from the perspective of whole-brain functional network changes.

Methods

Twenty-one patients with iRBD, 23 patients with early-stage nRBD-PD, and 22 matched healthy controls (HCs) were enrolled. Functional networks were constructed using resting-state functional MRI (fMRI) data. Network topological properties were analyzed and compared among groups by graph theory approaches. Correlation analyses were performed between network topological properties and cognition in the iRBD and nRBD-PD groups.

Results

Both patients with iRBD and patients with early-stage nRBD-PD had attention, executive function, and some memory deficits. On global topological organization, iRBD and nRBD-PD groups still presented small-worldness, but both groups exhibited decreased global/local efficiency and increased characteristic path length. On regional topological organization, compared with HC, nRBD-PD presented decreased nodal efficiency, decreased degree centrality, and increased nodal shortest path length, while iRBD presented decreased nodal efficiency and nodal shortest path. For iRBD, brain regions with decreased nodal efficiency were included in the corresponding regions of nRBD-PD. Nodal shortest path changes were significantly different in terms of brain regions and directions between nRBD-PD and iRBD. Attention deficits were correlated with local topological properties of the occipital lobe in both iRBD and nRBD-PD groups.

Conclusion

Both global and local efficiency of functional networks declined in nRBD-PD and iRBD groups. The overlaps and differences in local topological properties between nRBD-PD and iRBD indicate that iRBD not only shares functional changes of PD but also presents distinct features.

Spatiotemporal Dynamics of Covert Attention With Different Degrees of Central Visual Field Defects: An ERP and sLORETA Study

Purpose

The present study aimed to investigate the spatiotemporal dynamics of covert attention by simulating different degrees of central visual field defects in healthy subjects.

Methods

An electroencephalogram (EEG) was recorded while 40 normal-sighted subjects performed a target discrimination task. Target stimuli simulated different defect degrees of the central visual field by artificially central scotomas (5, 10, 20, and 30 degrees of visual angle) masked on the center of black-and-white checkerboards. Event-related potentials (ERPs) and standardized low-resolution brain electromagnetic tomography (sLORETA) based on ERPs were analyzed.

Results

ERP results indicated that during early perceptual processes, compared with 5-degree and 10-degree defects, N1 amplitudes of 20-degree and 30-degree defects decreased, whereas P2 amplitudes significantly reduced in 30-degree defects. During later discrimination and decision processing, N2 amplitudes gradually increased from 5-degree to 30-degree defects, whereas P3 amplitudes gradually decreased. Source localization indicated that 5-degree and 10-degree defects had stronger activations than 20-degree and 30-degree defects from the occipital cortex to the ventral stream and dorsal streams. Especially, 30-degree defects primarily recruited additional activations in the ventrolateral prefrontal cortex and ventral stream and later caused the disconnection of dorsolateral prefrontal-posterior parietal cortices in the dorsal stream.

Conclusions

Different degrees of central visual field defects differed in distinct spatiotemporal characteristics at multiple stages of covert attention, from top-down forward feedback and attentional allocation to executive controls through ventral and dorsal processing streams, suggesting that the combination of ERP and source localization can reveal the spatiotemporal control capacity of the cortex on central visual field defects.

Distinct brain structural-functional network topological coupling explains different outcomes in tinnitus patients treated with sound therapy

Topological properties, which serve as the core of the neural network, and their couplings can reflect different therapeutic effects in tinnitus patients. We hypothesized that tinnitus patients with different outcomes after sound therapy (narrowband noise) would have distinct brain network topological alterations. Diffusion tensor imaging and resting‐state functional magnetic resonance imaging (fMRI) were prospectively performed in 60 patients with idiopathic tinnitus and 57 healthy controls (HCs). Graph‐theoretical network analyses of structural connectivity (SC), functional connectivity (FC), and SC and FC coupling were performed. Associations between clinical performance and graph‐theoretical features were also analyzed. Treatment was effective (effective group; EG) in 28 patients and ineffective (ineffective group; IG) in 32 patients. For FC, the patients in the EG showed higher local efficiency than patients in the IG. For SC, patients in both the EG and IG displayed lower normalized characteristic path length, characteristic path length, and global efficiency than the HCs. More importantly, patients in the IG had higher coupling than the HCs, whereas there was no difference in coupling between patients in the EG and HCs. Additionally, there were significant associations between the SC features and clinical performance in patients in the EG. Our findings demonstrate that tinnitus patients exhibited significant brain network topological alterations, especially in the structural brain network. More importantly, patients who demonstrated different curative effects showed distinct SC‐FC topological coupling properties. SC‐FC coupling could be an indicator that could be used to predict prognoses in patients with idiopathic tinnitus before sound therapy.

Cerebral Blood Flow and its Connectivity Deficits in Patients With Lung Cancer After Chemotherapy

Purpose: This study was performed to investigate the regional cerebral blood flow (CBF) and CBF connectivity in the chemotherapy-induced cognitive impairment of patients with lung cancer by using arterial spin labeling.

Methods: Pseudocontinuous arterial spin labeling perfusion magnetic resonance imaging and neuropsychological tests were performed for 21 patients with non-small cell lung cancer who had received chemotherapy CT (+) and 25 non-small cell lung cancer patients who need chemotherapy but did not yet received CT (-). The CT (+) group previously received platinum-based therapy for 3 months to 6 months (the time from their first chemotherapy to the MRI scan). Group comparisons were performed in the regional normalized CBF and CBF connectivity, and the relationship between the regional normalized CBF and cognitive impairment were detected.

Results: The CT (+) group exhibited higher CBF in the left insula, right caudate, right superior occipital gyrus, left superior temporal gyrus (STG), and right middle frontal gyrus (MFG). MoCA scores as well as the memory scores were negatively correlated with the increased CBF in the right MFG (r = −0.492, p = 0.023; r = −0.497, p = 0.022). Alterations in the CBF connectivity were detected only in the CT (+) group between the following: right MFG and the right precentral gyrus; the right caudate and the right lingual gyrus; right caudate and right precuneus; left STG and the bilateral MFG; and the left STG and the right middle cingulum.

Conclusion: These findings indicated that chemotherapy is associated with abnormalities in the CBF and connectivity alterations, which may contribute to the cognitive impairment in patients with lung cancer.

Aberrant Resting-State Functional Connectivity of the Dorsal Attention Network in Tinnitus

Previous functional magnetic resonance imaging (fMRI) analyses have shown that the dorsal attention network (DAN) is involved in the pathophysiological changes of tinnitus, but few relevant studies have been conducted, and the conclusions to date are not uniform. The purpose of this research was to test whether there is a change in intrinsic functional connectivity (FC) patterns between the DAN and other brain regions in tinnitus patients. Thirty-one patients with persistent tinnitus and thirty-three healthy controls were enrolled in this study. A group independent component analysis (ICA), degree centrality (DC) analysis, and seed-based FC analysis were conducted. In the group ICA, the tinnitus patients showed increased connectivity in the left superior parietal gyrus in the DAN compared to the healthy controls. Compared with the healthy controls, the tinnitus patients showed increased DC in the left inferior parietal gyrus and decreased DC in the left precuneus within the DAN. The clusters within the DAN with significant differences in the ICA or DC analysis between the tinnitus patients and the healthy controls were selected as regions of interest (ROIs) for seeds. The tinnitus patients exhibited significantly increased FC from the left superior parietal gyrus to several brain regions, including the left inferior parietal gyrus, the left superior marginal gyrus, and the right superior frontal gyrus, and decreased FC to the right anterior cingulate cortex. The tinnitus patients exhibited decreased FC from the left precuneus to the left inferior occipital gyrus, left calcarine cortex, and left superior frontal gyrus compared with the healthy controls. The findings of this study show that compared with healthy controls, tinnitus patients have altered functional connections not only within the DAN but also between the DAN and other brain regions. These results suggest that it may be possible to improve the disturbance and influence of tinnitus by regulating the DAN.

A Comparative Study of Diffusion Fiber Reconstruction Models for Pyramidal Tract Branches

Currently, comparative studies evaluating the quantification accuracy of pyramidal tracts (PT) and PT branches that were tracked based on four mainstream diffusion models are deficient. The present study aims to evaluate four mainstream models using the high-quality Human Connectome Project (HCP) dataset. Diffusion tensor imaging (DTI), diffusion spectral imaging (DSI), generalized Q-space sampling imaging (GQI), and Q-ball imaging (QBI) were used to construct the PT and PT branches in 50 healthy volunteers from the HCP. False and true PT fibers were identified based on anatomic information. One-way repeated measure analysis of variance and post hoc paired-sample t-test were performed to identify the best PT and PT branch quantification model. The number, percentage, and density of true fibers of PT obtained based on GQI and QBI were significantly larger than those based on DTI and DSI (all p < 0.0005, Bonferroni corrected), whereas false fibers yielded the opposite results (all p < 0.0005, Bonferroni corrected). More trunk branches (PT_trunk) were present in the four diffusion models compared with the upper limb (PT_Ulimb), lower limb (PT_Llimb), and cranial (PT_cranial) branches. In addition, significantly more true fibers were obtained in PT_trunk, PT_Ulimb, and PT_Llimb based on the GQI and QBI compared with DTI and DSI (all p < 0.0005, Bonferroni corrected). Finally, GQI-based group probabilistic maps showed that the four PT branches exhibited relatively unique spatial distributions. Therefore, the GQI and QBI represent better diffusion models for the PT and PT branches. The group probabilistic maps of PT branches have been shared with the public to facilitate more precise studies on the plasticity of and the damage to the motor pathway.