Small P values may not yield robust findings: an example using REST-meta-PD

Different baseline functional patterns of the frontal cortex in amyotrophic lateral sclerosis patients with Corticospinal tract hyperintensity

Nearly half of the amyotrophic lateral sclerosis (ALS) patients showed hyperintensity of the corticospinal tract (CST+), yet whether brain functional pattern differs between CST+and CST- patients remains obscure. In the current study, 19 ALS CST+, 41 ALS CST- patients and 37 healthy controls (HC) underwent resting state fMRI scans. We estimated local activity and connectivity patterns via the Amplitude of Low Frequency Fluctuations (ALFF) and the Network-Based Statistic (NBS) approaches respectively. The ALS CST+patients did not differ from the CST- patients in amyotrophic lateral sclerosis functional rating scale revised (ALSFRS-R) score and disease duration. ALFF of the superior frontal gyrus (SFG) and the inferior frontal gyrus pars opercularis (OIFG) were highest in the HC and lowest in the ALS CST- patients, resulting in significant group differences (PFWE<0.05). NBS analysis revealed a frontal network consisting of connections between SFG, OIFG, orbital frontal gyrus, middle cingulate cortex and the basal ganglia, which exhibited HC>ALS CST+ > ALS CST- group differences (PFWE=0.037) as well. The ALFF of the OIFG was significantly correlated with ALSFRS-R (R=0.34, P=0.028) and mean connectivity of the frontal network was trend-wise significantly correlated with disease duration (R=-0.31, P=0.052) in the ALS CST- patients. However, these correlations were insignificant in ALS CST+patients (P values > 0.8). In conclusion, The ALS CST+patients exhibited different patterns of baseline functional activity and connectivity in the frontal cortex which may indicate a functional compensatory effect.

The power of many brains: Catalyzing neuropsychiatric discovery through open neuroimaging data and large-scale collaboration

Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric disorders. By pooling images from various cohorts, statistical power has increased, enabling the detection of subtle abnormalities and robust associations, and fostering new research methods. Global collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted treatment. Large-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric studies. We also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric disorders. However, challenges such as data harmonization across different sites, privacy protection, and effective data sharing must be addressed. With proper governance and open science practices, we conclude with a projection of how large-scale imaging resources and collaborations could revolutionize diagnosis, treatment selection, and outcome prediction, contributing to optimal brain health.

Grey matter structural alterations in anxiety disorders: a voxel-based meta-analysis

Anxiety disorders (ADs) are a group of prevalent and destructive mental illnesses, but the current understanding of their underlying neuropathology is still unclear. Employing voxel-based morphometry (VBM), previous studies have demonstrated several common brain regions showing grey matter volume (GMV) abnormalities. However, contradictory results have been reported among these studies. Considering that different subtypes of ADs exhibit common core symptoms despite different diagnostic criteria, and previous meta-analyses have found common core GMV-altered brain regions in ADs, the present research aimed to combine the results of individual studies to identify common GMV abnormalities in ADs. Therefore, we first performed a systematic search in PubMed, Embase, and Web of Science on studies investigating GMV differences between patients with ADs and healthy controls (HCs). Then, the anisotropic effect-size signed differential mapping (AES-SDM) was applied in this meta-analysis. A total of 24 studies (including 25 data sets) were included in the current study, and 906 patients with ADs and 1003 HCs were included. Compared with the HCs, the patients with ADs showed increased GMV in the left superior parietal gyrus, right angular gyrus, left precentral gyrus, and right lingual gyrus, and decreased GMV in the bilateral insula, bilateral thalamus, left caudate, and right putamen. In conclusion, the current study has identified some abnormal GMV brain regions that are related to the pathological mechanisms of anxiety disorders. These findings could contribute to a better understanding of the underlying neuropathology of ADs.

Association between gene expression and functional-metabolic architecture in Parkinson's disease

Gene expression plays a critical role in the pathogenesis of Parkinson's disease (PD). How gene expression profiles are correlated with functional-metabolic architecture remains obscure. We enrolled 34 PD patients and 25 age-and-sex-matched healthy controls for simultaneous 18 F-FDG-PET/functional MRI scanning during resting state. We investigated the functional gradients and the ratio of standard uptake value. Principal component analysis was used to further combine the functional gradients and glucose metabolism into functional-metabolic architecture. Using partial least squares (PLS) regression, we introduced the transcriptomic data from the Allen Institute of Brain Sciences to identify gene expression patterns underlying the affected functional-metabolic architecture in PD. Between-group comparisons revealed significantly higher gradient variation in the visual, somatomotor, dorsal attention, frontoparietal, default mode, and subcortical network (pFDR  < .048) in PD. Increased FDG-uptake was found in the somatomotor and ventral attention network while decreased FDG-uptake was found in the visual network (pFDR  < .008). Spatial correlation analysis showed consistently affected patterns of functional gradients and metabolism (p = 2.47 × 10-8 ). PLS analysis and gene ontological analyses further revealed that genes were mainly enriched for metabolic, catabolic, cellular response to ions, and regulation of DNA transcription and RNA biosynthesis. In conclusion, our study provided genetic pathological mechanism to explain imaging-defined brain functional-metabolic architecture of PD.

Altered local and remote functional connectivity in mild Alzheimer's disease patients with sleep disturbances

Objectives

This study aimed to investigate local and remote functional connectivity in mild Alzheimer's disease patients with sleep disturbances (ADSD) and those without sleep disturbances (ADNSD).

Methods

Thirty eight mild AD patients with sleep disturbances and 21 mild AD patients without sleep disturbances participated in this study. All subjects underwent neuropsychological assessments and 3.0 Tesla magnetic resonance scanning. Static and dynamic regional homogeneity (ReHo) were used to represent the local functional connectivity. Seed-based whole-brain functional connectivity was used to represent the remote functional connectivity. The seed was chosen based on the results of ReHo.

Results

Compared to ADNSD, ADSD showed decreased static ReHo in the left posterior central gyrus and the right cuneus and increased dynamic ReHo in the left posterior central gyrus. As for the remote functional connectivity, comparing ADSD to ADNSD, it was found that there was a decreased functional connection between the left posterior central gyrus and the left cuneus as well as the left calcarine.

Conclusion

The current study demonstrated that, compared with ADNSD, ADSD is impaired in both local and remote functional connectivity, manifested as reduced functional connectivity involving the primary sensory network and the primary visual network. The abnormality of the above functional connectivity is one of the reasons why sleep disorders promote cognitive impairment in AD. Moreover, sleep disorders change the temporal sequence of AD pathological damage to brain functional networks, but more evidence is needed to support this conclusion.

Cerebellar and cerebral white matter changes in Parkinson's disease with resting tremor

PURPOSE

Cerebellum modulates the amplitude of resting tremor in Parkinson's disease (PD) via cerebello-thalamo-cortical (CTC) circuit. Tremor-related white matter alterations have been identified in PD patients by pathological studies, but in vivo evidence is limited; the influence of such cerebellar white matter alterations on tremor-related brain network, including CTC circuit, is also unclear. In this study, we investigated the cerebral and cerebellar white matter alterations in PD patients with resting tremor using diffusion tensor imaging (DTI).

METHODS

In this study, 30 PD patients with resting tremor (PDWR), 26 PD patients without resting tremor (PDNR), and 30 healthy controls (HCs) from the Parkinson's Progression Markers Initiative (PPMI) cohort were included. Tract-based spatial statistics (TBSS) and region of interest-based analyses were conducted to determine white matter difference. Correlation analysis between DTI measures and clinical characteristics was also performed.

RESULTS

In the whole brain, TBSS and region of interest-based analyses identified higher fractional anisotropy (FA) value, lower mean diffusivity (MD) value, and lower radial diffusivity (RD) in multiple fibers. In the cerebellum, TBSS analysis revealed significantly higher FA value, decreased RD value as well as MD value in multiple cerebellar tracts including the inferior cerebellar peduncle (ICP) and middle cerebellar peduncle (MCP) when comparing the PDWR with HC, and higher FA value in the MCP when compared with PDNR.

CONCLUSION

We identified better white matter integrity in the cerebrum and cerebellum in PDWR indicating a potential association between the cerebral and cerebellar white matter and resting tremor in PD.

Resting-state brain functional alterations and their genetic mechanisms in drug-naive first-episode psychosis

Extensive research has established the presence of resting-state brain functional damage in psychosis. However, the genetic mechanisms of such disease phenotype are yet to be unveiled. We investigated resting-state brain functional alterations in patients with drug-naive first-episode psychosis (DFP) by performing a neuroimaging meta-analysis of 8 original studies comprising 500 patients and 469 controls. Combined with the Allen Human Brain Atlas, we further conducted transcriptome-neuroimaging spatial correlations to identify genes whose expression levels were linked to brain functional alterations in DFP, followed by a range of gene functional characteristic analyses. Meta-analysis revealed a mixture of increased and decreased brain function in widespread areas including the default-mode, visual, motor, striatal, and cerebellar systems in DFP. Moreover, these brain functional alterations were spatially associated with the expression of 1662 genes, which were enriched for molecular functions, cellular components, and biological processes of the cerebral cortex, as well as psychiatric disorders including schizophrenia. Specific expression analyses demonstrated that these genes were specifically expressed in the brain tissue, in cortical neurons and immune cells, and during nearly all developmental periods. Concurrently, the genes could construct a protein-protein interaction network supported by hub genes and were linked to multiple behavioral domains including emotion, attention, perception, and motor. Our findings provide empirical evidence for the notion that brain functional damage in DFP involves a complex interaction of polygenes with various functional characteristics.

Higher reliability and validity of Wavelet-ALFF of resting-state fMRI: From multicenter database and application to rTMS modulation

Amplitude of low-frequency fluctuation (ALFF) has been widely used for localization of abnormal activity at the single-voxel level in resting-state fMRI (RS-fMRI) studies. However, previous ALFF studies were based on fast Fourier transform (FFT-ALFF). Our recent study found that ALFF based on wavelet transform (Wavelet-ALFF) showed better sensitivity and reproducibility than FFT-ALFF. The current study aimed to test the reliability and validity of Wavelet-ALFF, and apply Wavelet-ALFF to investigate the modulation effect of repetitive transcranial magnetic stimulation (rTMS). The reliability and validity were assessed on multicenter RS-fMRI datasets under eyes closed (EC) and eyes open (EO) conditions (248 healthy participants in total). We then detected the sensitivity of Wavelet-ALFF using a rTMS modulation dataset (24 healthy participants). For each dataset, Wavelet-ALFF based on five mother wavelets (i.e., db2, bior4.4, morl, meyr and sym3) and FFT-ALFF were calculated in the conventional band and five frequency sub-bands. The results showed that the reliability of both inter-scanner and intra-scanner was higher with Wavelet-ALFF than with FFT-ALFF across multiple frequency bands, especially db2-ALFF in the higher frequency band slow-2 (0.1992-0.25 Hz). In terms of validity, the multicenter ECEO datasets showed that the effect sizes of Wavelet-ALFF with all mother wavelets (especially for db2-ALFF) were larger than those of FFT-ALFF across multiple frequency bands. Furthermore, Wavelet-ALFF detected a larger modulation effect than FFT-ALFF. Collectively, Wavelet db2-ALFF showed the best reliability and validity, suggesting that db2-ALFF may offer a powerful metric for inspecting regional spontaneous brain activities in future studies.

Motor progression marker for newly diagnosed drug-naïve patients with Parkinson's disease: A resting-state functional MRI study

The effective early prediction of clinical outcomes of Parkinson's disease (PD) is of great significance in the implementation of appropriate interventions. We aimed to propose a method based on the use of baseline resting-state functional characteristics (i.e., fractional amplitude of low-frequency fluctuations, fALFF) to predict motor progression in PD patients. Resting-state functional magnetic resonance imaging was performed on 48 newly-diagnosed drug-naïve PD patients and 27 age- and sex- matched healthy controls (HCs). Two PD subgroups were defined with different annual increase of Unified PD Rating Scale Part III motor scores. Least absolute shrinkage and selection operator regression analysis was performed to explore the baseline region-functional indicators for PD discrimination as well as the predictors for future motor deficits. Two significant models composed of baseline fALFF values from cerebral subregions were proposed. The classification model that distinguished PD patients from HCs (area under the curve [AUC] = 0.897) showed the most significant imaging characteristics in the putamen and precentral gyrus. The other prediction model that evaluated the degree of future deterioration of motor symptoms in PD patients (AUC = 0.916) showed the most significant imaging characteristics in the superior occipital gyrus and caudate nucleus. Furthermore, the increased regional function in bilateral caudate nuclei was correlated with the lower annual increase in motor deficits in all PD patients. The caudate nucleus might be the core region responsible for future motor deficits in newly-diagnosed PD patients, which may aid the development of disease progression preventive strategies in clinical practice.

Altered Functional Connectivity in Pain-Related Brain Regions and Its Correlation with Pain Duration in Bone Metastasis with Cancer Pain

Bone metastatic pain is thought to be a severe type of cancer pain that has refractory characteristics and a long duration. This study is aimed at exploring the brain functional connectivity (FC) pattern in lung cancer patients with bone metastatic pain. In this study, 27 lung cancer patients with bone metastatic pain (CP+), 27 matched lung cancer patients without pain-related complaints (CP−), and 27 matched healthy controls (HC) were recruited. All participants underwent fMRI data acquisition and clinical assessments. One-way ANOVA or a Mann–Whitney U test was applied to compare clinical data according to data distribution. Seventeen hypothesis-driven pain-related brain regions were selected as regions of interest (ROIs). FC values among pain-related brain regions across the three groups were computed by using ROI–ROI functional connectivity analysis. ANCOVA with a post hoc test was applied to compare FC differences among the three groups. p < 0.05 indicated statistical significance. Correlation analysis was conducted to explore the potential relationship between the FC values and clinical characteristics. Except for years of education, no significant differences were revealed among the three groups in age, gender, or neuropsychological assessment. In the CP+ group, FC alterations were mainly concentrated in the dorsal lateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC), secondary somatosensory cortex (SII), and amygdala compared to the CP− group. Among these brain regions with statistical differences, FC between the right DLPFC and the right ACC showed a positive correlation with the duration of cancer pain in the CP+ group. In addition, in the CP− group, altered FC was found in the bilateral SII, ACC, and thalamus compared to the HC group. Altered FC in pain-related brain regions may be a brain pattern of bone metastatic pain and may be associated with the long duration of cancer pain.

Cerebral gray matter volume changes in patients with anti-N-methyl-D-aspartate receptor encephalitis: A voxel-based morphometry study

Background:

Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is an autoimmune disease with typical clinical features. Whether and how cerebral gray matter structural damage inherent to the disorder affects cognitive function in patients is still unclear. Therefore, this study aimed to explore the changes in cerebral gray matter volume and whether these alterations contribute to cognitive impairment and mood disorders.

Methods

Forty patients with anti-NMDAR encephalitis and forty healthy controls (HCs) matched for gender, age, and education were recruited. All participants underwent attention network tests (ANT), neuropsychological tests and magnetic resonance imaging (MRI). Voxel-based morphological analysis (VBM) and correlation analysis was performed on all participants. Finally, according to the course of disease, patients were divided into two groups: NMDARE_SD (short duration; course ≤ 2 years since diagnosis) and NMDARE_LD (long duration; course >2 years since diagnosis), to evaluate gray matter volume changes that differ as a function of disease course.

Results

Compared to HCs, patients with anti-NMDAR encephalitis showed decreased executive control ability and lower MoCA score, while increased anxiety and depression as reflected by HAMA and HAMD24 scores (all P < 0.05). In VBM analysis, patients showed decreased gray matter volume in bilateral thalamus, left medial prefrontal cortex (mPFC_L), left superior temporal gyrus (STG_L), and left rectus gyrus. In the analysis stratified by disease course, the NMDARE_LD group exhibited decreased gray matter volume in the left precuneus and right posterior cerebellar lobe compared to the NMDARE_SD group.

Conclusions

Patients with anti-NMDAR encephalitis have cognitive, executive, and emotional dysfunction, and the sites of gray matter atrophy are concentrated in the thalamus, frontal lobe, and temporal lobe. These abnormalities may be involved in the process of cognitive and affective dysfunction.Patients with different courses of anti-NMDAR encephalitis have different brain atrophy sites. These results may help to clarify the contradiction between clinical and imaging manifestations of anti NMDAR encephalitis, which is worthy of further longitudinal studies.

The Atypical Effective Connectivity of Right Temporoparietal Junction in Autism Spectrum Disorder: A Multi-Site Study

Social function impairment is the core deficit of autism spectrum disorder (ASD). Although many studies have investigated ASD through a variety of neuroimaging tools, its brain mechanism of social function remains unclear due to its complex and heterogeneous symptoms. The present study aimed to use resting-state functional magnetic imaging data to explore effective connectivity between the right temporoparietal junction (RTPJ), one of the key brain regions associated with social impairment of individuals with ASD, and the whole brain to further deepen our understanding of the neuropathological mechanism of ASD. This study involved 1,454 participants from 23 sites from the Autism Brain Imaging Data Exchange (ABIDE) public dataset, which included 618 individuals with ASD and 836 with typical development (TD). First, a voxel-wise Granger causality analysis (GCA) was conducted with the RTPJ selected as the region of interest (ROI) to investigate the differences in effective connectivity between the ASD and TD groups in every site. Next, to obtain further accurate and representative results, an image-based meta-analysis was implemented to further analyze the GCA results of each site. Our results demonstrated abnormal causal connectivity between the RTPJ and the widely distributed brain regions and that the connectivity has been associated with social impairment in individuals with ASD. The current study could help to further elucidate the pathological mechanisms of ASD and provides a new perspective for future research.

Reliability and Validity of Power Spectrum Slope (PSS): A Metric for Measuring Resting-State Functional Magnetic Resonance Imaging Activity of Single Voxels

Methods that capture the features of single voxels of resting-state fMRI (RS-fMRI) could precisely localize the abnormal spontaneous activity and hence guide precise brain stimulation. As one of these metrics, the amplitude of low-frequency fluctuation (ALFF) has been used in numerous studies, however, it is frequency-dependent and the division of frequency bands is still controversial. Based on the well-accepted power law of time series, this study proposed an approach, namely, power spectrum slope (PSS), to characterize the RS-fMRI time series of single voxels. Two metrics, i.e., linear coefficient b and power-law slope b’ were used and compared with ALFF. The reliability and validity of the PSS approach were evaluated on public RS-fMRI datasets (n = 145 in total) of eyes closed (EC) and eyes open (EO) conditions after image preprocessing, with 21 subjects scanned two times for test–retest reliability analyses. Specifically, we used the paired t-test between EC and EO conditions to assess the validity and intra-class correlation (ICC) to assess the reliability. The results included the following: (1) PSS detected similar spatial patterns of validity (i.e., EC–EO differences) and less test–retest reliability with those of ALFF; (2) PSS linear coefficient b showed better validity and reliability than power-law slope b’; (3) While the PPS showed less validity in most regions, PSS linear coefficient b showed exclusive EC–EO difference in the medial temporal lobe which did not show in ALFF. The power spectrum plot in the parahippocampus showed a “cross-over” of power magnitudes between EC and EO conditions in the higher frequency bands (>0.1 Hz). These results demonstrated that PSS (linear coefficient b) is complementary to ALFF for detecting the local spontaneous activity.

Modulation effect of substantia nigra iron deposition and functional connectivity on putamen glucose metabolism in Parkinson's disease

Neurodegeneration of the substantia nigra affects putamen activity in Parkinson's disease (PD), yet in vivo evidence of how the substantia nigra modulates putamen glucose metabolism in humans is missing. We aimed to investigate how substantia nigra modulates the putamen glucose metabolism using a cross‐sectional design. Resting‐state fMRI, susceptibility‐weighted imaging, and [¹⁸F]‐fluorodeoxyglucose‐PET (FDG‐PET) data were acquired. Forty‐two PD patients and 25 healthy controls (HCs) were recruited for simultaneous PET/MRI scanning. The main measurements of the current study were R2* images representing iron deposition (28 PD and 25 HCs), standardized uptake value ratio (SUVr) images representing FDG‐uptake (33 PD and 25 HCs), and resting state functional connectivity maps from resting state fMRI (34 PD and 25 HCs). An interaction term based on the general linear model was used to investigate the joint modulation effect of nigral iron deposition and nigral‐putamen functional connectivity on putamen FDG‐uptake. Compared with HCs, we found increased iron deposition in the substantia nigra (p = .007), increased FDG‐uptake in the putamen (left: P_FWE < 0.001; right: P_FWE < 0.001), and decreased functional connectivity between the substantia nigra and the anterior putamen (left P_FWE < 0.001, right: P_FWE = 0.007). We then identified significant interaction effect of nigral iron deposition and nigral‐putamen connectivity on FDG‐uptake in the putamen (p = .004). The current study demonstrated joint modulation effect of the substantia nigra iron deposition and nigral‐putamen functional connectivity on putamen glucose metabolic distribution, thereby revealing in vivo pathological mechanism of nigrostriatal neurodegeneration of PD.

Intrinsic Brain Activity Alterations in Patients With Mild Cognitive Impairment-to-Normal Reversion: A Resting-State Functional Magnetic Resonance Imaging Study From Voxel to Whole-Brain Level

Mild cognitive impairment (MCI) reversion refers to patients with MCI who revert from MCI to a normal cognitive state. Exploring the underlying neuromechanism of MCI reverters may contribute to providing new insights into the pathogenesis of Alzheimer's disease and developing therapeutic interventions. Information on patients with MCI and healthy controls (HCs) was collected from the Alzheimer's Disease Neuroimaging Initiative database. We redefined MCI reverters as patients with MCI whose logical memory scores changed from MCI to normal levels using the logical memory criteria. We explored intrinsic brain activity alterations in MCI reverters from voxel, regional, and whole-brain levels by comparing resting-state functional magnetic resonance imaging metrics of the amplitude of low-frequency of fluctuation (ALFF), the fractional amplitude of low-frequency fluctuation (fALFF), percent amplitude of fluctuation (PerAF), regional homogeneity (ReHo), and degree centrality (DC) between MCI reverters and HCs. Finally, partial correlation analyses were conducted between cognitive scale scores and resting-state functional magnetic resonance imaging metrics of brain regions, revealing significant group differences. Thirty-two patients with MCI from the Alzheimer's Disease Neuroimaging Initiative database were identified as reverters. Thirty-seven age-, sex-, and education-matched healthy individuals were also enrolled. At the voxel level, compared with the HCs, MCI reverters had increased ALFF, fALFF, and PerAF in the frontal gyrus (including the bilateral orbital inferior frontal gyrus and left middle frontal gyrus), increased PerAF in the left fusiform gyrus, and decreased ALFF and fALFF in the right inferior cerebellum. Regarding regional and whole-brain levels, MCI reverters showed increased ReHo in the left fusiform gyrus and right median cingulate and paracingulate gyri; increased DC in the left inferior temporal gyrus and left medial superior frontal; decreased DC in the right inferior cerebellum and bilateral insular gyrus relative to HCs. Furthermore, significant correlations were found between cognitive performance and neuroimaging changes. These findings suggest that MCI reverters show significant intrinsic brain activity changes compared with HCs, potentially related to the cognitive reversion of patients with MCI. These results enhance our understanding of the underlying neuromechanism of MCI reverters and may contribute to further exploration of Alzheimer's disease.

Alterations of regional spontaneous brain activities in anxiety disorders: A meta-analysis

BACKGROUND

Recent resting-state functional magnetic resonance imaging studies have provided strong evidence of abnormal regional spontaneous brain activities among anxiety-disordered patients. However, the evidence has been divergent and inconclusive. Therefore, it is necessary to perform a meta-analysis identifying a common pattern of altered regional spontaneous brain activity for anxiety disorders.

METHOD

Corresponding research of anxiety disorders, namely, whole-brain rs-fMRI studies that measured differences in regional homogeneity, amplitude of low-frequency fluctuations, or fractional amplitude of low-frequency fluctuations, were analyzed in this study. Overall, seven studies with 235 anxiety-disordered patients and 241 healthy controls were ultimately included in the meta-analysis. The meta-analysis was processed by seed-based d mapping.

RESULTS

Compared with healthy controls, patients with anxiety disorders showed significantly decreased regional spontaneous brain activities in the right putamen, the right orbital inferior frontal gyrus, and the right temporal pole. No increases in regional spontaneous brain activities were detected in patients relative to the controls.

LIMITATION

Limited number of available studies, only Asian samples, and insufficient information of sample characteristics.

CONCLUSION

The present study suggests that anxiety disorders are associated with aberrant regional brain activity in areas connected with emotion processing, which extends our understanding of anxiety disorders' pathophysiology.

Repetitive transcranial magnetic stimulation modulates cortical-subcortical connectivity in sensorimotor network

Repetitive transcranial magnetic stimulation (rTMS) holds the ability to modulate the connectivity within the stimulated network. However, whether and how the rTMS targeted over the primary motor cortex (M1) could affect the connectivity within the sensorimotor network (SMN) is not fully elucidated. Hence, in this study, we investigated the after-effects of rTMS over left M1 at different frequencies on connectivity within SMN. Forty-five healthy participants were recruited and randomly divided into three groups according to rTMS frequencies (high-frequency [HF], 3 Hz; low-frequency [LF], 1 Hz; and SHAM). Participants received 1-Hz, 3-Hz or sham stimulation and underwent two functional magnetic resonance imaging (fMRI) scanning sessions before and after rTMS intervention. Using resting-state functional connectivity (FC) approach, we found that high- and low-frequency rTMS had opposing effects on FC within the SMN, especially for connectivity with subcortical regions (i.e., putamen, thalamus and cerebellum). Specifically, the reductions in connectivity between cortical and subcortical regions within cortico-basal ganglia thalamo-cortical circuits and the cognitive loop of cerebellum, and increased connectivity between cortical and subdivisions within the sensorimotor loop of cerebellum were observed after high-frequency rTMS intervention, whereas the thalamus and cognitive cerebellum subdivisions exhibited increased connectivity, and sensorimotor cerebellum subdivisions showed decreased connectivity with stimulated target after low-frequency stimulation. Collectively, these findings demonstrated the alterations of connectivity within SMN after rTMS intervention at different frequencies and may help to understand the mechanisms of rTMS treatment for movement disorders associated with deficits in subcortical regions such as Parkinson's disease, Huntington's disease and Tourette's syndrome.

Functional Integrity of Executive Control Network Contributed to Retained Executive Abilities in Mild Cognitive Impairment

Background: Mild cognitive impairment (MCI) is considered to be a transitional state between normal aging and Alzheimer's dementia (AD). Recent studies have indicated that executive function (EF) declines during MCI. However, only a limited number of studies have investigated the neural basis of EF deficits in MCI. Herein, we investigate the changes of regional brain spontaneous activity and functional connectivity (FC) of the executive control network (ECN) between high EF and low EF groups. Methods: According to EF composite score (ADNI-EF) from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we divided MCI into two groups, including the MCI-highEF group and MCI-lowEF group. Resting-state functional MRI was utilized to investigate the fractional amplitude of low-frequency fluctuation (fALFF) and ECN functional connectivity across 23 healthy controls (HC), 11 MCI-highEF, and 14 MCI-lowEF participants. Moreover, a partial correlation analysis was carried out to examine the relationship between altered fALFF or connectivity of the ECN and the ADNI-EF. Results: Compared to HC, the MCI-highEF participants demonstrated increased fALFF in the left superior temporal gyrus (STG), as well as decreased fALFF in the right precentral gyrus, right postcentral gyrus, and left middle frontal gyrus (MFG). The MCI-lowEF participants demonstrated increased fALFF in the cerebellar vermis and decreased fALFF in the left MFG. Additionally, compared to HC, the MCI-highEF participants indicated no significant difference in connectivity of the ECN. Furthermore, the MCI-lowEF participants showed increased ECN FC in the left cuneus and left MFG, as well as decreased ECN functional connectivity in the right parahippocampal gyrus (PHG). Notably, the altered fALFF in the left MFG was positively correlated to ADNI-EF, while the altered fALFF in cerebellar vermis is negatively correlated with ADNI-EF across the two MCI groups and the HC group. Altered ECN functional connectivity in the right PHG is negatively correlated to ADNI-EF, while altered ECN functional connectivity in the left cuneus is negatively correlated to ADNI-EF across the three groups. Conclusions: Our current study demonstrates the presence of different patterns of regional brain spontaneous activity and ECN FC in the MCI-highEF group and MCI-lowEF group. Furthermore, the ECN FC of the MCI-highEF group was not disrupted, which may contribute to retained EF in MCI.