Gaussian Random Field Theory Research Articles

Altered Intrinsic Brain Spontaneous Activities in Children With Autism Spectrum Disorder Comorbid ADHD

Objective: The study involved 17 children with Autism Spectrum Disorder (ASD), 21 with ADHD, 30 with both (ASD + ADHD), and 28 typically developing children (TD). Methods: The amplitude of low-frequency fluctuations (ALFF) was measured as a regional brain function index. Intrinsic functional connectivity (iFC) was also analyzed using the region of interest (ROI) identified in ALFF analysis. Statistical analysis was done via one-way ANCOVA, Gaussian random field (GRF) theory, and post-hoc pair-wise comparisons. Results: The ASD + ADHD group showed increased ALFF in the left middle frontal gyrus (MFG.L) compared to the TD group. In terms of global brain function, the ASD group displayed underconnectivity in specific regions compared to the ASD + ADHD and TD groups. Conclusion: The findings contribute to understanding the neural mechanisms underlying ASD + ADHD.

Structural and functional changes following brain surgery in pediatric patients with intracranial space-occupying lesions.

We explored the structural and functional changes of the healthy hemisphere of the brain after surgery in children with intracranial space-occupying lesions. We enrolled 32 patients with unilateral intracranial space-occupying lesions for brain imaging and cognitive assessment. Voxel-based morphometry and surface-based morphometry analyses were used to investigate the structural images of the healthy hemisphere. Functional images were analyzed using regional homogeneity, amplitude of low-frequency fluctuations, and fractional-amplitude of low-frequency fluctuations. Voxel-based morphometry and surface-based morphometry analysis used the statistical model built into the CAT 12 toolbox. Paired t-tests were used for functional image and cognitive test scores. For structural image analysis, we used family-wise error correction of peak level (p < 0.05), and for functional image analysis, we use Gaussian random-field theory correction (voxel p < 0.001, cluster p < 0.05). We found an increase in gray matter volume in the healthy hemisphere within six months postoperatively, mainly in the frontal lobe. Regional homogeneity and fractional-amplitude of low-frequency fluctuations also showed greater functional activity in the frontal lobe. The results of cognitive tests showed that psychomotor speed and motor speed decreased significantly after surgery, and reasoning increased significantly after surgery. We concluded that in children with intracranial space-occupying lesions, the healthy hemisphere exhibits compensatory structural and functional effects within six months after surgery. This effect occurs mainly in the frontal lobe and is responsible for some higher cognitive compensation. This may provide some guidance for the rehabilitation of children after brain surgery.

Chronic Mild Sleep Restriction Does Not Lead to Marked Neuronal Alterations Compared With Maintained Adequate Sleep in Adults

BackgroundSleep restriction (SR) has been shown to upregulate neuronal reward networks in response to food stimuli, but prior studies were short-term and employed severe SR paradigms. ObjectiveOur goal was to determine whether mild SR, achieved by delaying bedtimes by 1.5 h, influences neuronal networks responsive to food stimuli compared with maintained adequate sleep (AS) >7 h/night. MethodsA randomized controlled crossover study with 2 6-wk phases, AS (≥7 h sleep/night) and SR (−1.5 h/night relative to screening), was conducted. Adults with AS duration, measured using wrist actigraphy over a 2-wk screening period, and self-reported good sleep quality were enrolled. Resting-state and food-stimulated functional neuroimaging (fMRI) was performed at the endpoint of each phase. Resting-state fMRI data analyses included a priori region-of-interest seed-based functional connectivity, whole-brain voxel-wise analyses, and network analyses. Food task-fMRI analyses compared brain activity patterns in response to food cues between conditions. Paired-sample t tests tested differences between conditions. ResultsTwenty-six participants (16 males; age 29.6 ± 5.3 y, body mass index 26.9 ± 4.0 kg/m2) contributed complete data. Total sleep time was 7 h 30 ± 28 min/night during AS compared with 6 h 12 ± 26 min/night during SR. We employed different statistical approaches to replicate prior studies in the field and to apply more robust approaches that are currently advocated in the field. Using uncorrected P value of <0.01, cluster ≥10-voxel thresholds, we replicated prior findings of increased activation in response to foods in reward networks after SR compared with AS (right insula, right inferior frontal gyrus, and right supramarginal gyrus). These findings did not survive more rigorous analytical approaches (Gaussian Random Field theory correction at 2-tailed voxel P < 0.001, cluster P < 0.05). ConclusionsThe results suggest that mild SR leads to increased reward responsivity to foods but with low confidence given the failure to meet significance from rigorous statistical analyses. Further research is necessary to inform the mechanisms underlying the role of sleep on food intake regulation.This trial was registered at clinicaltrials.gov as NCT02960776.

Static and dynamic functional connectivity combined with the triple network model in amnestic mild cognitive impairment and Alzheimer's disease.

Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) are characterized by abnormal functional connectivity (FC) of default-mode network (DMN), salience network (SN), and central executive network (CEN). Static FC (sFC) and dynamic FC (dFC) combined with triple network model can better study the dynamic and static changes of brain networks, and improve its potential diagnostic value in the diagnosis of AD spectrum disorders. Differences in sFC values and dFC variability patterns among the three brain networks of the three groups (53 AD patients, 40 aMCI patients, and 40 NCs) were computed by ANOVA using Gaussian Random Field theory (GRF) correction. The correlation between FC values (sFC values and dFC variability) in the three networks and cognitive scores (MMSE and MoCA) in AD and aMCI groups was analyzed separately. Within the DMN network, there were significant differences of sFC values in right/left medial superior frontal gyrus and dFC variability in left opercular part inferior frontal gyrus and right dorsolateral superior frontal gyrus among the three groups. Within the CEN network, there were significant differences of sFC values in left superior parietal gyrus. Within the SN network, there were significant differences of dFC variability in right Cerebelum_7b and left opercular part inferior frontal gyrus. In addition, there was a significant negative correlation between FC values (sFC values of CEN and dFC variability of SN) and MMSE and MoCA scores. It suggests that sFC, dFC combined with triple network model can be considered as potential biomarkers for AD and aMCI.

Genetic risk factors of Alzheimer’s Disease disrupt resting-state functional connectivity in cognitively intact young individuals

BackgroundPast evidence shows that changes in functional brain connectivity in multiple resting-state networks occur in cognitively healthy individuals who have non-modifiable risk factors for Alzheimer’s Disease. Here, we aimed to investigate how those changes differ in early adulthood and how they might relate to cognition.MethodsWe investigated the effects of genetic risk factors of AD, namely APOEe4 and MAPTA alleles, on resting-state functional connectivity in a cohort of 129 cognitively intact young adults (aged 17–22 years). We used Independent Component Analysis to identify networks of interest, and Gaussian Random Field Theory to compare connectivity between groups. Seed-based analysis was used to quantify inter-regional connectivity strength from the clusters that exhibited significant between-group differences. To investigate the relationship with cognition, we correlated the connectivity and the performance on the Stroop task.ResultsThe analysis revealed a decrease in functional connectivity in the Default Mode Network (DMN) in both APOEe4 carriers and MAPTA carriers in comparison with non-carriers. APOEe4 carriers showed decreased connectivity in the right angular gyrus (size = 246, p-FDR = 0.0079), which was correlated with poorer performance on the Stroop task. MAPTA carriers showed decreased connectivity in the left middle temporal gyrus (size = 546, p-FDR = 0.0001). In addition, we found that only MAPTA carriers had a decreased connectivity between the DMN and multiple other brain regions.ConclusionsOur findings indicate that APOEe4 and MAPTA alleles modulate brain functional connectivity in the brain regions within the DMN in cognitively intact young adults. APOEe4 carriers also showed a link between connectivity and cognition.

Topology of reionisation times: Concepts, measurements, and comparisons to Gaussian random field predictions

Context. In the next decade, radio telescopes, such as the Square Kilometer Array (SKA), will explore the Universe at high redshift, and particularly during the epoch of reionisation (EoR). The first structures emerged during this epoch, and their radiation reionised the previously cold and neutral gas of the Universe, creating ionised bubbles that percolate at the end of the EoR (z ∼ 6). SKA will produce 2D images of the distribution of the neutral gas at many redshifts, pushing us to develop tools and simulations to understand its properties. Aims. With this paper, we aim to measure topological statistics of the EoR in the so-called reionisation time fields from both cosmological and semi-analytical simulations. This field informs us about the time of reionisation of the gas at each position; it is used to probe the inhomogeneities of reionisation histories and can be extracted from 21 cm maps. We also compare these measurements with analytical predictions obtained within Gaussian random field (GRF) theory. Methods. The GRF theory allows us to compute many statistics of a field, namely the probability distribution functions (PDFs) of the field or its gradient, isocontour length, critical point distributions, and skeleton length. We compare these theoretical predictions to measurements made on reionisation time fields extracted from an EMMA simulation and a 21cmFAST simulation at 1 cMpc/h resolution. We also compared our results to GRFs generated from the fitted power spectra of the simulation maps. Results. Both EMMA and 21cmFAST reionisation time fields (treion(r)) are close to being Gaussian fields, in contrast with the 21 cm, density, or ionisation fraction, which have all been shown to be non-Gaussian. Only accelerating ionisation fronts at the end of the EoR seem to be the cause of small non-gaussianities in treion(r). Overall, this topological description of reionisation times provides a new quantitative and reproducible way to characterise the EoR scenario. Under the assumption of GRFs, it enables the generation of reionisation models with their propagation, percolation, or seed statistics simply from the reionisation time power spectrum. Conversely, these topological statistics provide a means to constrain the properties of the power spectrum and by extension the physics that drive the propagation of radiation.

Cosmic web & caustic skeleton: non-linear constrained realizations — 2D case studies

The cosmic web consists of a complex configuration of voids, walls, filaments, and clusters, which formed under the gravitational collapse of Gaussian fluctuations. Understanding under what conditions these different structures emerge from simple initial conditions, and how different cosmological models influence their evolution, is central to the study of the large-scale structure. Here, we present a general formalism for setting up initial random density and velocity fields satisfying non-linear constraints for specialized N-body simulations. These allow us to link the non-linear conditions on the eigenvalue and eigenvector fields of the deformation tensor, as specified by caustic skeleton theory, to the current-day cosmic web. By extending constrained Gaussian random field theory, and the corresponding Hoffman-Ribak algorithm, to non-linear constraints, we probe the statistical properties of the progenitors of the walls, filaments, and clusters of the cosmic web. Applied to cosmological N-body simulations, the proposed techniques pave the way towards a systematic investigation of the evolution of the progenitors of the present-day walls, filaments, and clusters, and the embedded galaxies, putting flesh on the bones of the caustic skeleton. The developed non-linear constrained random field theory is valid for generic cosmological conditions. For ease of visualization, the case study presented here probes the two-dimensional caustic skeleton.

Beltrami fields and knotted vortex structures in incompressible fluid flows

AbstractThis paper gives a survey on recent results about the existence of knotted vortex structures in incompressible fluids. This includes the proof of Lord Kelvin's conjecture on the existence of knotted vortex tubes in steady Euler flows and a new probabilistic approach to address Arnold's speculation that typical Beltrami fields should exhibit vortex lines of arbitrary topological complexity. We review the key tools to establish these results: the global approximation properties of Beltrami fields, the inverse localization principle in spectral theory, and the theory of Gaussian random Beltrami fields, which permits the introduction of probabilistic considerations in the picture. Finally, we include some applications of these techniques to other problems, such as the existence of vortex reconnections for smooth solutions of the 3D Navier–Stokes equation and the evolution of local hot spots under the heat equation.

A New Approach for 4-D Exospheric Tomography Based on Optimal Interpolation and Gaussian Markov Random Fields

Exospheric tomography is a computational 3-D imaging technique that provides the estimates of the neutral density distributions of the terrestrial exosphere from space-based ultraviolet (UV) measurements. Variability of neutral densities during geomagnetically active conditions has been previously reported, motivating the development of time-dependent tomographic techniques that can characterize both the spatial and temporal scales of densities during these events. However, solving the dynamic exospheric tomography problem can be challenging owing to its ill-posedness. In this letter, we introduce a novel algorithm for 4-D exospheric tomography based on optimal interpolation (OI) and Gaussian Markov random field (GMRF) theory. The OI analysis enables iterative reconstructions of the exosphere when a statistical background field is provided. Its mean is selected from previous knowledge of the exosphere, and its covariance matrix is estimated using GMRF. To validate the performance, we apply our proposed methodology to six days of UV data acquired by National Aeronautics and Space Administration (NASA) two-wide angle imaging neutral-atom spectrometer (TWINS) mission during the geomagnetic storm that occurred on June 15, 2008.

Amplitude of low-frequency fluctuations in multiple-frequency bands in patients with intracranial tuberculosis: a prospective cross-sectional study.

BackgroundResting-state functional magnetic resonance imaging (rs-fMRI) is widely used to study brain functional alteration, but there have been no reports of research regarding the application of rs-fMRI in intracranial tuberculosis. The purpose of this prospective, cross-sectional study was to investigate spontaneous neural activity at different frequency bands in patients with intracranial tuberculosis using rs-fMRI with amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF) methods.MethodsThe rs-fMRI data of 31 patients with intracranial tuberculosis and 30 gender-, age-, and education-matched healthy controls (HCs) were included. The ALFF and fALFF values in the conventional frequency band (0.01−0.08 Hz) and 2 sub-frequency bands (slow-4: 0.027–0.073 Hz; slow-5: 0.01–0.027 Hz) were calculated and compared between the groups. The resultant T-maps were corrected using the Gaussian random field (GRF) theory (voxel P<0.01, cluster P<0.05). Correlations between the ALFF and fALFF values and neurocognitive scores were assessed.ResultsCompared with the HCs, patients with intracranial tuberculosis showed decreased ALFF in the right paracentral lobule (T=−4.69) in the conventional frequency band, in the right supplementary motor area (T=−4.85) in the slow-4 band, and in the left supplementary motor area (T=−3.76) in the slow-5 band. Compared to the slow-5 band, the voxels with decreased ALFF were spatially more extensive in the slow-4 band. Compared with HCs, patients with intracranial tuberculosis showed decreased fALFF in the opercular parts of the right inferior frontal gyrus (T=−4.50) and the left inferior parietal lobe (T=−4.86) and increased fALFF in the left inferior cerebellum (T=5.84) in the conventional frequency band. In the slow-4 band, fALFF decreased in the opercular parts of the right inferior frontal gyrus (T=−5.29) and right precuneus (T=−4.34). In the slow-5 band, fALFF decreased in the left middle occipital gyrus (T=−4.65) and right middle frontal gyrus (T=−5.05).ConclusionsPatients with intracranial tuberculosis showed abnormal intrinsic brain activity at different frequency bands, and ALFF abnormalities in different brain regions could be better detected in the slow-4 band. This preliminary study might provide new insights into understanding the pathophysiological mechanism in intracranial tuberculosis.

Changes in a sensorimotor network, occipital network, and psychomotor speed within three months after focal surgical injury in pediatric patients with intracranial space-occupying lesions

BackgroundStudies on cognition and brain networks after various forms of brain injury mainly involve traumatic brain injury, neurological disease, tumours, and mental disease. There are few related studies on surgical injury and even fewer pediatric studies. This study aimed to preliminarily explore the cognitive and brain network changes in children with focal, unilateral, well-bounded intracranial space-occupying lesions (ISOLs) in the short term period after surgery.MethodsWe enrolled 15 patients (6–14 years old) with ISOLs admitted to the Department of Pediatric Neurosurgery of the Beijing Tiantan Hospital between July 2020 and August 2021. Cognitive assessment and resting-state functional magnetic resonance imaging (rs-fMRI) were performed. Regional homogeneity (Reho), seed-based analysis (SBA) and graph theory analysis (GTA) were performed. Paired T-test was used for statistical analysis of cognitive assessment and rs-fMRI. Gaussian random-field theory correction (voxel p-value < 0.001, cluster p-value < 0.05) was used for Reho and SBA. False discovery rate correction (corrected p value < 0.05) for GTA.ResultsOur results showed that psychomotor speed decreased within three months after surgery. Further, rs-fMRI data analysis suggested that sensorimotor and occipital network activation decreased with low information transmission efficiency.ConclusionWe prudently concluded that the changes in cognitive function and brain network within three months after surgery may be similar to ageing and that the brain is vulnerable during this period.

Frequency-Specific Changes of Amplitude of Low-Frequency Fluctuations in Patients with Acute Basal Ganglia Ischemic Stroke.

Objective The purpose of this study was to investigate the characteristics of different frequency bands in the spontaneous brain activity among patients with acute basal ganglia ischemic stroke (BGIS). Methods In the present study, thirty-four patients with acute BGIS and forty-four healthy controls were examined by resting-state functional magnetic resonance imaging (rs-fMRI) from May 2019 to December 2020. Two amplitude methods including amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF) calculated in three frequency bands (conventional frequency band: 0.01-0.08 Hz; slow-5 frequency band: 0.01-0.027 Hz; and slow-4 frequency band: 0.027-0.073 Hz) were conducted to evaluate the spontaneous brain activity in patients with acute BGIS and healthy controls (HCs). Gaussian Random Field Theory (GRF, voxel p < 0.01 and cluster p < 0.05) correction was applied. The correlation analyses were performed between clinical scores and altered metrics values. Results Compared to HCs, patients with acute BGIS showed decreased ALFF in the right supramarginal gyrus (SMG) in the conventional and slow-4 bands, increased fALFF in the right middle frontal gyrus (MFG) in the conventional and slow-4 bands, and increased fALFF in the bilateral caudate in the slow-5 frequency band. The fALFF value of the right caudate in the slow-5 frequency band was negatively correlated with the clinical scores. Conclusion In conclusion, this study showed the alterations in ALFF and fALFF in three frequency bands between patients with acute BGIS and HCs. The results reflected that the abnormal LFO amplitude might be related with different frequency bands and promoted our understanding of pathophysiological mechanism in acute BGIS.

Static and buckling characteristics of the porous ring reinforced by graphene nanofillers

The present work focuses on the static and buckling characteristics of the confined functionally graded porous (FGP) ring consolidated by graphene nanofillers (GNF). The ring is under a temperature rise field when a point load is applied on the crown position. The Halpin-Tsai micromechanics theory is used to evaluate the distribution of Young’s modulus, and the Gaussian random field theory is used to evaluate the distribution of the porosity and mass density, respectively. The influence of the thermal field on the buckling load is quantized by applying the energy function and nonlinear thin-walled shell theory. The analytical buckling load is examined numerically, and good agreement is obtained. Furthermore, the present analytical and numerical results are verified effectively by other closed-form predictions when the FGP-GNF ring reduces to a homogeneous ring. Finally, comprehensive parametric study is taken by analyzing the effect of parameters on the buckling load. These parameters include the temperature rise, porosity coefficient, weight fraction, geometric parameters of GNF, friction coefficient and Young’s modulus of the medium.

Uncertainty modelling and multiscale simulation of woven composite twisted structure

The woven composite twisted structure under cantilever load is studied using experimental and multiscale numerical methods. The uncertain geometry parameters inside the twisted specimen are identified using Micro-CT scanning technology, and quantified using multivariate Gaussian random field theory. A high-fidelity meso-Representative Volume Cell (RVC) database after data clustering is established using these uncertainties, in which the warp and weft yarns are no longer regular orthogonality, the yarn cross-sectional area and the yarns gap exhibit variability. The statistical uncertainty quantification and propagation are further integrated into the coupled Finite Element-Fast Fourier Transformation (FE-FFT) concurrent multiscale method to reveal the damage and failure mechanisms of the woven composite twisted structure. The numerical results are in good agreement with the experiment results. This study can be helpful of designing the woven composite blade structures.

Alternations of interhemispheric functional connectivity in children with strabismus and amblyopia: a resting-state fMRI study

Previous neuroimaging studies demonstrated that patients with strabismus or amblyopia can show significant functional and anatomical changes in the brain, but alterations of interhemispheric functional connectivity (FC) have not been well studied in this population. The current study analyzed whole-brain changes of interhemispheric FC in children with strabismus and amblyopia (CSA) using voxel-mirrored homotopic connectivity (VMHC).A total of 24 CSA (16 males and 8 females) and 24 normal controls (NCs) consisting of 16 and 8 age-, sex, and education-matched males and females, respectively, underwent functional magnetic resonance imaging (fMRI) scans in the resting state. According to Gaussian random field theory, changes in the resting state FC (rsFC) between hemispheres were evaluated using the VMHC method. The relationships between mean VMHC values in multiple brain regions and behavioral performance were evaluated by Pearson correlation analysis. In contrast to NCs, the CSA group showed significantly decreased VMHC values in the bilateral cerebellum, bilateral frontal superior orbital (frontal sup orb), bilateral temporal inferior(temporal inf),and bilateral frontal superior(frontal sup). CSA have abnormal interhemispheric FC in many brain regions, which may reflect dysfunction of eye movements and visual fusion. These findings might provide insight into the underlying pathogenetic mechanisms of CSA.

Soil Stratification and Spatial Variability Estimated Using Sparse Modeling and Gaussian Random Field Theory

We propose a method for simultaneously estimating the trend and random components of soil properties using the least absolute shrinkage and selection operator (LASSO) for sparse modeling without assuming any basis functions and Gaussian random field theory, respectively. The uncorrelated observation noise is also estimated at the same time. A two-step algorithm is introduced to avoid the shrinkage problem of LASSO. Numerical examples with random realizations show that the method avoids shrinkage. The proposed method requires four parameters, namely, the variances of the random component and observation error, autocovariance distance, and regularization parameter, for one-dimensional problems. We propose a method that uses Akaike’s information criterion or Bayesian information criterion and particle swarm optimization to determine these four parameters. It is shown that the detection ratio of the layer boundary is determined by the number of observation data and the difference between trend values. The proposed method is applied to actual cone penetration test data to estimate the trend component of the soil property.

Cerebrovascular reserve differentiates cognitively normal older adults from individuals with mild cognitive impairment

AbstractBackgroundAbnormal cerebral blood flow (CBF) is observed in early Alzheimer’s disease. Cerebrovascular reserve (CVR) represents the ability of the vasculature to maintain normal CBF. While CBF abnormalities can indicate a primary vascular dysfunction, it could also arise secondary to neurodegeneration and reduced metabolic demands. CVR, on the other hand, is a specific marker of vascular insufficiency. Our goal was to evaluate the associations between CVR, CBF, and cognition in older adults with and without MCI.Methods70 older adults (&gt;65 years 77.3 ± 8.32 years old, 42F, 46 controls i.e., NC and 24 MCI) were scanned in compliance with Institutional Review Board guidelines. Besides a T1 scan, we performed pCASL to quantify baseline CBF and a breath‐hold BOLD fMRI experiment to quantify CVR. We use a mixed‐effects model in FSL to test CVR and CBF differences between groups as well as association with cognitive tests, i.e., Montreal Cognitive Assessment (MoCA), Immediate and Delayed recall (CRAFTi/d) and Trails‐B, using Gaussian random field theory for a cluster‐wise threshold of p = 0.05. All comparisons were adjusted for age and gender.ResultsOnly CVR was significantly (p&lt;0.05) different between NC and MCI (Figure 1). While there was no group difference in CBF, the group difference between CVR was no longer significant when adjusted for baseline CBF. Investigating further, high CBF was significantly associated with lower CVR in the MCI group only. A high CBF was very weakly related to high CVR in NC (Figure 2). A high CVR was associated with a high MoCA score (Figure 3) and CRAFTi/d (Figure 4).ConclusionWe demonstrated the utility of a simple breath‐hold based CVR measurement in understanding the association between vascular mechanisms and cognition. It is likely that CBF is not different between groups because MCI participants utilize their vascular reserve to maintain baseline CBF. Consequently, an additional vascular challenge results in a lower CVR measurement. Furthermore, a higher CVR in MCI subjects such as that seen in association with cognitive tests could be a result steal phenomenon to redirect perfusion from degenerating tissue to viable tissue. However, these mechanisms need to be further investigated.

Local functional connectivity of patients with acute and remitting multiple sclerosis: A Kendall's coefficient of concordance- and coherence-regional homogeneity study.

Using Kendall's coefficient of concordance (KCC-) and Coherence (Cohe-) regional homogeneity (ReHo) to explore the alterations of brain local functional connectivity in acute and remitting relapsing-remitting multiple sclerosis (RRMS), and its clinical relevance.18 acute RRMS, 26 remitting RRMS and 20 healthy controls received resting-state functional magnetic resonance imaging scanning. After data preprocessing and ReHo (KCC-ReHo and Cohe-ReHo) calculation, analysis of variance and followed post hoc analysis was used to compare the KCC-ReHo or Cohe ReHo maps across groups.After analysis of variance analysis, regions with significant among-group differences detected by the 2 ReHo analysis were overlapped, these overlapped regions located in the left superior frontal gyrus (SFG), right SFG, left cuneus and right middle occipital gyrus (P < .01, Gaussian random field theory correction). Followed post hoc tests showed that, compared with healthy controls,(1)increased ReHo in left cuneus and right middle occipital gyrus only detected in acute RRMS not in remitting RRMS;(2)acute and remitting RRMS both demonstrated decreased ReHo in the SFG and medial frontal gyrus (MeFG).Except for the overlapped location, the regions location of altered ReHo detected by the 2 ReHo analysis also present difference. Further, correlation analysis showed disease duration was negatively correlated with the KCC-ReHo (when K = 7, 19) of left SFG (r = -0.633, P = .006; r = -0.620, P = .008), left MeFG (r = -0.608, P = .010; r = -0.555, P = .022), the KCC-ReHo (when K = 27) of left and right SFG (r = -0.551, P = .022; r = -0.603, Ρ = .010), and the Cohe-ReHo of right MeFG (r = -0.608, P = .010) in acute RRMS; meanwhile, the KCC-ReHo (when K = 7, 19) of right SFG (r = -0.590, P = .013; r = -0.599, P = .011) was negatively related to expanded disability status scale scores in the acute RRMS.Both acute and remitting RRMS patients has disease-related brain dysfunction, interestingly, relative to remitting RRMS, the acute RRMS patients mobilized more brain regions involving visual information processing in an attempt to maintain functional stability. In addition, our results also provide a methodological consideration for future ReHo analysis.

Age effect on gray matter volume changes after sleep restriction

Sleep deprivation disrupted functional and structural brain areas which are associated with cognition and emotion in healthy participants. However, the effect of age on the structural changes after sleep restriction remains unclear. In the current study, gray matter volume was calculated in 43 young adults and 37 old adults before and after sleep restriction. Two-way mixed analysis of variance (between-subject factor: deprivation; within-subject factor: age) was then employed to investigate differences in gray matter volume changes between young and old adults. Gaussian random field theory was applied for multiple comparison correction. Results revealed that sleep restriction decreases gray matter volume in the right thalamus, left precuneus, and postcentral gyrus. More importantly, we found a significant deprivation × age interaction effect mainly in the right dorsal/ventral anterior insula where the gray matter volume increased in young adults after sleep restriction but showed no difference in old adults. These findings highlight the crucial role of the anterior insula in the neural mechanisms underlying sleep lose, especially among young adults. The current work provided structural evidence for describing emotional dysfunction and suggests the potential effect of age on functional and structural changes after sleep restriction.

A comparison of random-field-theory and false-discovery-rate inference results in the analysis of registered one-dimensional biomechanical datasets.

BackgroundThe inflation of falsely rejected hypotheses associated with multiple hypothesis testing is seen as a threat to the knowledge base in the scientific literature. One of the most recently developed statistical constructs to deal with this problem is the false discovery rate (FDR), which aims to control the proportion of the falsely rejected null hypotheses among those that are rejected. FDR has been applied to a variety of problems, especially for the analysis of 3-D brain images in the field of Neuroimaging, where the predominant form of statistical inference involves the more conventional control of false positives, through Gaussian random field theory (RFT). In this study we considered FDR and RFT as alternative methods for handling multiple testing in the analysis of 1-D continuum data. The field of biomechanics has recently adopted RFT, but to our knowledge FDR has not previously been used to analyze 1-D biomechanical data, nor has there been a consideration of how FDR vs. RFT can affect biomechanical interpretations.MethodsWe reanalyzed a variety of publicly available experimental datasets to understand the characteristics which contribute to the convergence and divergence of RFT and FDR results. We also ran a variety of numerical simulations involving smooth, random Gaussian 1-D data, with and without true signal, to provide complementary explanations for the experimental results.ResultsOur results suggest that RFT and FDR thresholds (the critical test statistic value used to judge statistical significance) were qualitatively identical for many experimental datasets, but were highly dissimilar for others, involving non-trivial changes in data interpretation. Simulation results clarified that RFT and FDR thresholds converge as the true signal weakens and diverge when the signal is broad in terms of the proportion of the continuum size it occupies. Results also showed that, while sample size affected the relation between RFT and FDR results for small sample sizes (<15), this relation was stable for larger sample sizes, wherein only the nature of the true signal was important.DiscussionRFT and FDR thresholds are both computationally efficient because both are parametric, but only FDR has the ability to adapt to the signal features of particular datasets, wherein the threshold lowers with signal strength for a gain in sensitivity. Additional advantages and limitations of these two techniques as discussed further. This article is accompanied by freely available software for implementing FDR analyses involving 1-D data and scripts to replicate our results.