Cluster-level statistical inference in fMRI datasets: The unexpected behavior of random fields in high dimensions

Shared subcortical arousal systems across sensory modalities during transient modulation of attention

Subcortical arousal systems are known to play a key role in controlling sustained changes in attention and conscious awareness. Recent studies indicate that these systems have a major influence on short-term dynamic modulation of visual attention, but their role across sensory modalities is not fully understood. In this study, we investigated shared subcortical arousal systems across sensory modalities during transient changes in attention using block and event-related fMRI paradigms. We analyzed massive publicly available fMRI datasets collected while 1,561 participants performed visual, auditory, tactile, and taste perception tasks. Our analyses revealed a shared circuit of subcortical arousal systems exhibiting early transient increases in activity in midbrain reticular formation and central thalamus across perceptual modalities, as well as less consistent increases in pons, hypothalamus, basal forebrain, and basal ganglia. Identifying these networks is critical for understanding mechanisms of normal attention and consciousness and may help facilitate subcortical targeting for therapeutic neuromodulation.

Precision fMRI and cluster-failure in the individual brain

Advances in neuroimaging acquisition protocols and denoising techniques, along with increasing magnetic field strengths, have dramatically improved the temporal signal-to-noise ratio (tSNR) in functional magnetic resonance imaging (fMRI). This permits spatial resolution with submillimeter voxel sizes and ultrahigh temporal resolution and opens a route toward performing precision fMRI in the brains of individuals. Yet ultrahigh spatial and temporal resolution comes at a cost: it reduces tSNR and, therefore, the sensitivity to the blood oxygen level-dependent (BOLD) effect and other functional contrasts across the brain. Here we investigate the potential of various smoothing filters to improve BOLD sensitivity while preserving the spatial accuracy of activated clusters in single-subject analysis. We introduce adaptive-weight smoothing with optimized metrics (AWSOM), which addresses this challenge extremely well. AWSOM employs a local inference approach that is as sensitive as cluster-corrected inference of data smoothed with large Gaussian kernels, but it preserves spatial details across multiple tSNR levels. This is essential for examining whole-brain fMRI data because tSNR varies across the entire brain, depending on the distance of a brain region from the receiver coil, the type of setup, acquisition protocol, preprocessing, and resolution. We found that cluster correction in single subjects results in inflated family-wise error and false positive rates. AWSOM effectively suppresses false positives while remaining sensitive even to small clusters of activated voxels. Furthermore, it preserves signal integrity, that is, the relative activation strength of significant voxels, making it a valuable asset for a wide range of fMRI applications. Here we demonstrate these features and make AWSOM freely available to the research community for download.

Neurobiological basis of reinforcement-based decision making in adults with ADHD treated with lisdexamfetamine dimesylate: Preliminary findings and implications for mechanisms influencing clinical improvement

BACKGROUND

ADHD is often described as a disorder of altered reward sensitivity, yet few studies have examined the extent to which: (i) treatments for ADHD impact reward-related mechanisms; and (ii) changes in the reward system are associated with clinical improvement. This study addresses these issues - examining the extent to which clinical improvement following lisdexamfetamine (LDX) treatment is associated with changes in brain reward system activation.

METHODS

Twenty adults (M = 11, 55%, F = 9, 45%), ages 19-52 (M = 33.9, SD = 10.0) with ADHD participated in a randomized cross-over study with lisdexamfetamine (LDX) and placebo (PB). Changes in brain activation were assessed during functional magnetic resonance (fMRI) scans: after receiving 3-5 weeks of treatment with LDX and 3-5 weeks of no drug/PB. fMRI contrasts were derived from the passive-avoidance (PA) learning task, which assessed reward-related learning using computational variables. We analyzed the following conditions: the Choice-Phase, modulated by the expected value (EV; i.e., object-choose and object-reject), and the Feedback-Phase, modulated by the prediction error (PE; i.e., reward and punish). Clinical symptom severity was assessed via interview with the ADHD-Rating Scale (ADHD-RS-IV). To address the primary objective, we performed group-level mass-univariate regression analyses between LDX and PB of percent change of the ADHD-RS total scores and the four contrast images under the Choice- and Feedback-conditions. Significance was set at a whole-brain voxel-wise threshold of p < 0.05 with family-wise error (FWE) correction and an extent (cluster) threshold of 50 contiguous voxels.

RESULTS

Improvement in ADHD symptoms with LDX was accompanied by significantly increased activation in a series of brain regions previously implicated in reinforcement processing in the choice and feedback conditions (e.g., left caudate and putamen, right orbitofrontal cortex, left middle frontal, superior frontal, and precentral gyri).

CONCLUSIONS

These findings, while preliminary, are the first to show that ADHD symptom improvement with stimulant treatment is associated with increased responsiveness of brain systems engaged in reward processing. Results support the hypothesis that LDX treatment may restore balance to dysfunction (e.g., hypoactivation) within the brain reward circuitry in adults with ADHD. Trial RegistrationClinicaltrials.gov Identifier: NCT01924429.

Abnormal whole-brain voxelwise structure-function coupling and its association with cognitive dysfunction in patients with different cerebral small vessel disease burdens

Cerebral small vessel disease (CSVD) is a universal neurological disorder in older adults that occurs in connection with cognitive dysfunction and is a chief risk factor for dementia and stroke. While whole-brain voxelwise structural and functional abnormalities in CSVD have been heavily explored, the degree of structure-function coupling abnormality possible in patients with different CSVD burdens remains largely unknown. This study included 53 patients with severe CSVD burden (CSVD-s), 108 patients with mild CSVD burden (CSVD-m) and 76 healthy controls. A voxelwise coupling metric of low frequency fluctuations (ALFF) and voxel-based morphometry (VBM) was used to research the important differences in whole-brain structure-function coupling among groups. The correlations between ALFF/VBM decoupling and cognitive parameters in CSVD patients were then investigated. We found that compared with healthy controls, CSVD-s patients presented notably decreased ALFF/VBM coupling in the bilateral caudate nuclei and increased coupling in the right inferior temporal gyrus (ITG). In addition, compared with the CSVD-m group, the CSVD-s group demonstrated significantly decreased coupling in the bilateral caudate nuclei, right putamen and inferior frontal gyrus (IFG) and increased coupling in the left middle frontal gyrus and medial superior frontal gyrus. Notably, the ALFF/VBM decoupling values in the caudate, IFG and ITG not only showed significant correlations with attention and executive functions in CSVD patients but also prominently distinguished CSVD-s patients from CSVD-m patients and healthy controls in receiver operating characteristic curve research. Our discoveries demonstrated that decreased ALFF/VBM coupling in the basal ganglia and increased coupling in the frontotemporal lobes were connected with more severe burden and worse cognitive decline in CSVD patients. ALFF/VBM coupling might serve as a novel effective neuroimaging biomarker of CSVD burden and provide new insights into the pathophysiological mechanisms of the clinical development of CSVD.

Geometry-derived statistical significance: A probabilistic framework for detecting true positive findings in MRI data

INTRODUCTION

The false discovery rate (FDR) procedure does not incorporate the geometry of the random field and requires high statistical power at each voxel, a requirement not satisfied by the limited number of participants in imaging studies. Topological FDR, threshold free cluster enhancement (TFCE), and probabilistic TFCE improve statistical power by incorporating local geometry. However, topological FDR requires specifying a cluster defining threshold and TFCE requires specifying transformation weights.

METHODS

Geometry-derived statistical significance (GDSS) procedure overcomes these limitations by combining voxelwise p-values for the test statistic with the probabilities computed from the local geometry for the random field, thereby providing substantially greater statistical power than the procedures currently used to control for multiple comparisons. We use synthetic data and real-world data to compare its performance against the performance of these other, previously developed procedures.

RESULTS

GDSS provided substantially greater statistical power relative to the comparator procedures, which was less variable to the number of participants. GDSS was more conservative than TFCE: that is, it rejected null hypotheses at voxels with much higher effect sizes than TFCE. Our experiments also showed that the Cohen's D effect size decreases as the number of participants increases. Therefore, sample size calculations from small studies may underestimate the participants required in larger studies. Our findings also suggest effect size maps should be presented along with p-value maps for correct interpretation of findings.

CONCLUSIONS

GDSS compared with the other procedures provides considerably greater statistical power for detecting true positives while limiting false positives, especially in small sized (<40 participants) imaging cohorts.

Altered Intrinsic Brain Activity Related to Neurologic and Motor Dysfunction in Diabetic Peripheral Neuropathy Patients

CONTEXT

Brain functional alterations in type 2 diabetes with diabetic peripheral neuropathy (DPN) related to motor dysfunction remain largely unknown.

OBJECTIVE

We aimed to explore intrinsic resting brain activity in DPN.

METHODS

A total of 28 patients with DPN, 43 patients with diabetes and without DPN (NDPN), and 32 healthy controls (HCs) were recruited and underwent resting-state functional magnetic resonance imaging. We calculated the amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo). One-way analysis of covariance was applied to evaluate the above indicators among the 3 groups, and the mean ALFF/fALFF/ReHo values of altered brain regions were then correlated with clinical features of patients.

RESULTS

Compared with the NDPN group, the DPN group showed significantly decreased ALFF values in the right orbital superior frontal gyrus (ORBsup) and medial superior frontal gyrus (SFGmed), and increased ALFF values in the left inferior temporal gyrus (ITG) and decreased fALFF values in the right SFGmed. Compared with HCs, the NDPN group showed increased ALFF values in the right ORBsup, middle frontal gyrus, and left orbital middle frontal gyrus, and decreased fALFF values in the right middle temporal gyrus. Notably, the mean ALFF values of the right ORBsup were significantly negatively correlated with Toronto Clinical Scoring System scores and gait speed in diabetics. The mean ALFF/fALFF values of right SFGmed and the mean ALFF values of left ITG and right ORBsup were significantly differentiated between DPN and patients witht NDPN in receiver operating characteristic curve analysis.

CONCLUSION

Patients with DPN have abnormal brain activity in sensorimotor and cognitive brain areas, which may implicate the underlying neurophysiological mechanisms in intrinsic brain activity.

Moxibustion for primary dysmenorrhea: A resting-state functional magnetic resonance imaging study exploring the alteration of functional connectivity strength and functional connectivity

Introduction

Primary dysmenorrhea (PDM) is a common gynecological disease and chronic pain disorder. Moxibustion, a form of traditional Chinese medicine therapy, has proven to be effective for PDM. However, the central mechanisms of PDM and moxibustion for PDM are still unclear. This study aims to explore the potential central mechanism of PDM and clarify the possible mechanism of moxibustion for relieving pain.

Materials and methods

A total of 23 PDM patients and 23 matched healthy controls (HCs) were enrolled. For PDM patients, resting-state functional magnetic resonance imaging (rs-fMRI) data were collected pre- and post-moxibustion treatment of 3 consecutive menstrual cycles, respectively. For HCs, rs-fMRI data were collected in the baseline. The resting-state functional connectivity strength (rs-FCS) analysis and the resting-state functional connectivity (rs-FC) analysis based on the region of interest (ROI) were combined to be conducted.

Results

Compared to HCs, PDM patients showed weaker rs-FCS in the left inferior frontal gyrus (IFG). After the moxibustion treatment, rs-FCS in the left IFG was increased with clinical improvement. Then, the left IFG was chosen as ROI, and the rs-FC analysis was conducted. It showed that the left IFG rs-FC in the bilateral anterior cingulate cortex (ACC)/middle cingulate cortex (MCC), the left posterior cingulate cortex (PCC)/precuneus (PCU), and the left parahippocampal gyrus (PHG) decreased after moxibustion treatment, most of which belong to the default mode network (DMN).

Conclusion

Our results highlight the role of the left IFG and the DMN in PDM. Specifically, the central mechanism of moxibustion for analgesia may be related to modulating the disorders of the reappraisal and processing of pain stimuli through influencing the cognition of pain.

Morphological brain changes between active and inactive phases of thyroid associated ophthalmopathy: a voxel-based morphometry study

AIM

To explore the morphological brain changes among active thyroid-associated ophthalmopathy (TAO) patients, inactive TAO patients and healthy controls and to investigate the neuropathological relationship of TAO using magnetic resonance imaging (MRI) data.

METHODS

In this observational case-control study, we included 35 inactive TAO patients, 37 active TAO patients and 23 healthy controls. Voxel-based morphometry (VBM) analysis was conducted to evaluate the gray matter volume (GMV) changes among groups, and the correlations between GMV alterations and clinical parameters in active and inactive TAO groups were investigated.

RESULTS

Active TAO patients showed significantly increased GMV in the right inferior frontal gyrus, left superior frontal gyrus (SFG), orbital superior frontal gyrus, orbital middle frontal gyrus, precuneus and postcentral gyrus compared with controls and significantly increased GMV in the right middle temporal gyrus, left SFG and precuneus compared with the inactive TAO group. No significant differences were observed between the inactive TAO group and healthy controls. Notably, the receiver operating characteristic (ROC) curve analysis demonstrated altered GMV among groups and significantly (p<0.001) differentiated active TAO from inactive TAO and healthy controls. In addition, the mean GMV in precuneus and postcentral gyrus were significantly associated with clinical parameters in active TAO.

CONCLUSION

Our findings suggested the localized GMV alterations among groups were associated with the pathophysiology of TAO and served as a potential discriminative pattern to detect clinical phases of TAO at the individual level. The altered brain morphometry may suggest a corresponding process of self-repair and remodeling of the brain structure as the disease progresses in TAO.

Impact of APOE ε4 Carrier Status on Associations Between Subthreshold, Positive Amyloid-β Deposition, Brain Function, and Cognitive Performance in Cognitively Normal Older Adults: A Prospective Study

Background

A growing body of evidence suggests a deteriorating effect of subthreshold amyloid-beta (Aβ) accumulation on cognition before the onset of clinical symptoms of Alzheimer's disease (AD). Despite the association between the Aβ-dependent pathway and the APOE ε4 allele, the impact of this allele on the progression from the subthreshold Aβ deposits to cognitive function impairment is unclear. Furthermore, the comparative analysis of positive Aβ accumulation in the preclinical phase is lacking.

Objective

This study aimed to explore the differential effect of the APOE ε4 carrier status on the association between Aβ deposition, resting-state brain function, and cognitive performance in cognitively normal (CN) older adults, depending on the Aβ burden status.

Methods

One hundred and eighty-two older CN adults underwent resting-state functional magnetic resonance imaging, [18F] flutemetamol (FMM) positron emission tomography, a neuropsychological battery, and APOE genotyping. We evaluated the resting-state brain function by measuring the local and remote functional connectivity (FC) and measured the remote FC in the default-mode network (DMN), central-executive network (CEN), and salience network (SN). In addition, the subjects were dichotomized into those with subthreshold and positive Aβ deposits using a neocortical standardized uptake value ratio with the cut-off value of 0.62, which was calculated with respect to the pons.

Results

The present result showed that APOE ε4 carrier status moderated the relationship between Aβ deposition, local and remote resting-state brain function, and cognitive performance in each CN subthreshold and positive Aβ group. We observed the following: (i) the APOE ε4 carrier status-Aβ deposition and APOE ε4 carrier status-local FC interaction for the executive and memory function; (ii) the APOE ε4 carrier status-regional Aβ accumulation interaction for the local FC; and (iv) the APOE ε4 carrier status-local FC interaction for the remote inter-network FC between the DMN and CEN, contributing higher cognitive performance in the APOE ε4 carrier with higher inter-network FC. Finally, these results were modulated according to Aβ positivity.

Conclusion

This study is the first attempt to thoroughly examine the influence of the APOE ε4 carrier status from the subthreshold to positive Aβ accumulation during the preclinical phase.

Altered Brain Morphometry in Cerebral Small Vessel Disease With Cerebral Microbleeds: An Investigation Combining Univariate and Multivariate Pattern Analyses

Purpose

The objective of this study was to evaluate whether altered gray matter volume (GMV) and white matter volume (WMV) are associated with the presence of cerebral microbleeds (CMBs) in cerebral small vessel disease (CSVD).

Materials and Methods

In this study, we included 26 CSVD patients with CMBs (CSVD-c), 43 CSVD patients without CMBs (CSVD-n) and 39 healthy controls. All participants underwent cognitive assessment testing. Both univariate analysis and multivariate pattern analysis (MVPA) approaches were applied to investigate differences in brain morphometry among groups.

Results

In univariate analysis, GMV and WMV differences were compared among groups using voxel-based morphometry (VBM) with diffeomorphic anatomical registration through exponentiated lie algebra (DARTEL). Compared to healthy controls, the CSVD-c group and CSVD-n group showed significantly lower GMV than the control group in similar brain clusters, mainly including the right superior frontal gyrus (medial orbital), left anterior cingulate gyrus, right inferior frontal gyrus (triangular part) and left superior frontal gyrus (medial), while the CSVD-n group also showed significantly lower WMV in the cluster of the left superior frontal gyrus (medial). No significant GMV or WMV differences were found between the CSVD-c group and the CSVD-n group. Specifically, we applied the multiple kernel learning (MKL) technique in MVPA to combine GMV and WMV features, yielding an average of >80% accuracy for three binary classification problems, which was a considerable improvement over the individual modality approach. Consistent with the univariate analysis, the MKL weight maps revealed default mode network and subcortical region damage associated with CSVD compared to controls. On the other hand, when classifying the CSVD-c group and CSVD-n group in the MVPA analysis, we found that some WMVs were highly weighted regions (left olfactory cortex and right middle frontal gyrus), which hinted at the presence of different white matter alterations in the CSVD-c group.

Conclusion

Our findings not only suggested that the localized alterations in GMV and WMV appeared to be associated with the pathophysiology of CSVD but also indicated that altered brain morphometry could be a potential discriminative pattern to detect CSVD at the individual level.

Altered Spontaneous Brain Activity Related to Neurologic Dysfunction in Patients With Cerebral Small Vessel Disease

Cerebral small vessel disease (CSVD) encompasses several diseases affecting the small arteries, arterioles, venules, and capillaries of the brain and refers to several pathological processes and etiologies. Neuroimaging is considered the gold standard for detecting CSVD, which can present diverse features on MRI. Cerebral microbleeds (CMBs) in CSVD have been demonstrated to play a synergistic role in both cerebrovascular and neurodegenerative pathology. Considering previous studies on brain structural abnormalities in CSVD, in the present study, we aimed to explore altered spontaneous brain activity among CSVD patients using amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF) and regional homogeneity (ReHo) methods based on resting-state functional MRI. In this study, we recruited 24 CSVD patients with CMBs (CSVD-c), 42 CSVD patients without CMBs (CSVD-n) and 36 healthy controls from outpatient clinics in Shandong Provincial Hospital affiliated to Shandong First Medical University between September 2018 and June 2019. All subjects underwent 3-T MRI, including blood oxygen level-dependent (BOLD) and susceptibility-weighted imaging (SWI). Anatomic structures were segmented, ALFF/fALFF values were calculated, and ReHo maps were generated. Further statistical analysis was applied to study the difference in ALFF/fALFF/ReHo among the three groups and the association between ALFF/fALFF/ReHo changes in different brain regions and clinical characteristics. Twenty-four CSVD-c patients (age: 67.54 ± 6.00 years, 10 females), 42 CSVD-n patients (age: 66.33 ± 5.25 years, 22 females) and 36 healthy subjects (age: 64.14 ± 8.57 years, 19 females) were evaluated. Compared with controls, the CSVD-c group showed significantly increased ALFF values in the right insula, putamen and left precuneus; decreased fALFF values in the right precentral gyrus and postcentral gyrus; and increased ReHo values in the left precuneus, fusiform gyrus, right supplementary motor area (SMA), and superior frontal gyrus. Notably, the mean ALFF values of the right insula and putamen were not only significantly related to all clinical parameters but also demonstrated the best performance in Receiver Operating Characteristic (ROC) curve analysis. These findings reveal CSVD-c patients have dysfunctions in the default mode network, sensorimotor network and frontoparietal network, which may implicate the underlying neurophysiological mechanisms of intrinsic brain activity. The correlation between altered spontaneous neuronal activity and clinical parameters provides early useful diagnostic biomarkers for CSVD.

Altered Spontaneous Brain Activity Related to Neurologic and Sleep Dysfunction in Children With Obstructive Sleep Apnea Syndrome

Childhood obstructive sleep apnea (OSA) is a common chronic sleep-related breathing disorder in children, which leads to growth retardation, neurocognitive impairments, and serious complications. Considering the previous studies about brain structural abnormalities in OSA, in the present study, we aimed to explore the altered spontaneous brain activity among OSA patients, using amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) methods based on resting-state functional magnetic resonance imaging (MRI). Thirty-one untreated OSA children and 33 age-and gender-matched healthy children (HC) were included in this study. Compared with controls, the OSA group showed significant lower ALFF in the right lingual gyrus, decreased fALFF in the left middle frontal gyrus (MFG), but increased fALFF in the left precuneus. Decreased ReHo was found in the left inferior frontal gyrus (orbital part) and left middle frontal gyrus. Notably, the mean fALFF value of left MFG was not only significantly related to multiple sleep parameters but also demonstrated the best performance in ROC curve analysis. These findings revealed OSA children were associated with dysfunctions in the default mode network, the frontal lobe, and the lingual gyrus, which may implicate the underlying neurophysiological mechanisms of intrinsic brain activity. The correlation between the altered spontaneous neuronal activity and the clinical index provides early useful diagnostic biomarkers for OSA children as well.

Small vessel disease disrupts EEG postural brain networks in 'unexplained dizziness in the elderly'

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Unexplained dizziness in the elderly may result from cerebral small vessel disease.

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Dizzy elderly patients differed from controls in EEG power when standing.

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EEG power when standing correlated with subjective (perceived) instability.

Objective

To examine the hypothesis that small vessel disease disrupts postural networks in older adults with unexplained dizziness in the elderly (UDE).

Methods

Simultaneous electroencephalography and postural sway measurements were undertaken in upright, eyes closed standing, and sitting postures (as baseline) in 19 younger adults, 33 older controls and 36 older patients with UDE. Older adults underwent magnetic resonance imaging to determine whole brain white matter hyperintensity volumes, a measure of small vessel disease. Linear regression was used to estimate the effect of instability on electroencephalographic power and connectivity.

Results

Ageing increased theta and alpha desynchronisation on standing. In older controls, delta and gamma power increased, and theta and alpha power reduced with instability. Dizzy older patients had higher white matter hyperintensity volumes and more theta desynchronisation during periods of instability. White matter hyperintensity volume and delta power during periods of instability were correlated, positively in controls but negatively in dizzy older patients. Delta power correlated with subjective dizziness and instability.

Conclusions

Neural resource demands of postural control increase with age, particularly in patients with UDE, driven by small vessel disease.

Significance

EEG correlates of postural control saturate in older adults with UDE, offering a neuro-physiological basis to this common syndrome.

Impact of Transcranial Direct Current Stimulation on Cognitive Function, Brain Functional Segregation, and Integration in Patients with Mild Cognitive Impairment According to Amyloid-Beta Deposition and APOE ε4-Allele: A Pilot Study

Anodal transcranial direct current stimulation (anodal-tDCS) is known to improve cognition and normalize abnormal network configuration during resting-state functional magnetic resonance imaging (fMRI) in patients with mild cognitive impairment (MCI). We aimed to evaluate the impact of sequential anodal-tDCS on cognitive functions, functional segregation, and integration parameters in patients with MCI, according to high-risk factors for Alzheimer’s disease (AD): amyloid-beta (Aβ) deposition and APOE ε4-allele status. In 32 patients with MCI ([¹⁸ F] flutemetamol-: n = 10, [¹⁸ F] flutemetamol+: n = 22; APOE ε4-: n = 13, APOE ε4+: n = 19), we delivered anodal-tDCS (2 mA/day, five times/week, for 2 weeks) over the left dorsolateral prefrontal cortex and assessed the neuropsychological test battery and resting-state fMRI measurements before and after 2 weeks stimulation. We observed a non-significant impact of an anodal-tDCS on changes in neuropsychological battery scores between MCI patients with and without high-risk factors of AD, Aβ retention and APOE ε4-allele. However, there was a significant difference in brain functional segregation and integration parameters between MCI patients with and without AD high-risk factors. We also found a significant effect of tDCS-by-APOE ε4-allele interaction on changes in the functional segregation parameter of the temporal pole. In addition, baseline Aβ deposition significantly associated negatively with change in global functional integrity of hippocampal formation. Anodal-tDCS might help to enhance restorative and compensatory intrinsic functional changes in MCI patients, modulated by the presence of Aβ retention and the APOE ε4-allele.

Frequency-dependent changes in fractional amplitude of low-frequency oscillations in Alzheimer's disease: a resting-state fMRI study

Alzheimer's disease (AD) is the most common neurodegenerative disease in elderly individuals. We conducted this study to examine whether alterations in the fractional amplitudes of low-frequency fluctuations (fALFF) in the AD spectrum were frequency-dependent and symptom-relevant. A total of 43 patients with subjective cognitive decline (SCD), 52 with amnestic mild cognitive impairment (aMCI), 44 with Alzheimer's dementia (d-AD) and 55 well-matched controls participated in resting-state functional magnetic resonance imaging (rs-fMRI) scans. The amplitudes were measured using fALFF within the slow-4 (0.027-0.073 Hz) and slow-5 (0.01-0.027 Hz) bands. Repeated-measures analysis of variance was performed on fALFF within two bands and correlated with neuropsychological test scores. The significant main effects of frequency and group on fALFF differed widely across brain regions. There were more varied areas in the slow-5 band than the slow-4 band. The fALFF associated with primary disease effects was mainly distributed in the parietal lobe. Obvious frequency band and group interaction effects were observed in the left angular gyrus, left calcarine fissure and surrounding cortex, left superior cerebellum, left cuneus and right lingual gyrus. Neuropsychological tests scores were significantly correlated with the fALFF magnitude of the left cuneus and right lingual in the slow-5 band. Our results suggested that the AD continuum had abnormal amplitudes in intrinsic brain activity, and these abnormalities were frequency-dependent and mainly associated with the slow-5 band rather than the slow-4 band. This may guide the frequency choice of future rs-fMRI studies and provide new insights into the neuropathophysiology of AD.

Improving the sensitivity of cluster-based statistics for functional magnetic resonance imaging data

Because of the high dimensionality of neuroimaging data, identifying a statistical test that is both valid and maximally sensitive is an important challenge. Here, we present a combination of two approaches for functional magnetic resonance imaging (fMRI) data analysis that together result in substantial improvements of the sensitivity of cluster‐based statistics. The first approach is to create novel cluster definitions that optimize sensitivity to plausible effect patterns. The second is to adopt a new approach to combine test statistics with different sensitivity profiles, which we call the min(p) method. These innovations are made possible by using the randomization inference framework. In this article, we report on a set of simulations and analyses of real task fMRI data that demonstrate (a) that the proposed methods control the false‐alarm rate, (b) that the sensitivity profiles of cluster‐based test statistics vary depending on the cluster defining thresholds and cluster definitions, and (c) that the min(p) method for combining these test statistics results in a drastic increase of sensitivity (up to fivefold), compared to existing fMRI analysis methods. This increase in sensitivity is not at the expense of the spatial specificity of the inference.

Limbic hypoconnectivity in idiopathic REM sleep behaviour disorder with impulse control disorders

INTRODUCTION

Current neuroimaging research has revealed several brain alterations in idiopathic REM sleep behaviour disorder (iRBD) that mirror and precede those reported in PD. However, none have specifically addressed the presence of changes across the reward system, and their role in the emergence of impulse control disorders (ICDs). We aimed to compare the volumetric and functional connectivity characteristics of the reward system in relation to the psychobehavioral profile of patients with iRBD versus healthy controls and PD patients.

METHODS

Twenty patients with polysomnography confirmed iRBD along with 17 PD patients and 14 healthy controls (HC) underwent structural and functional resting-state brain MRI analysis. Participants completed the questionnaire for impulsive-compulsive disorders in PD (QUIP), the short UPPS-P impulsive behaviour scale, as well as neuropsychological testing of cognitive function.

RESULTS

A higher percentage of iRBD patients reported hypersexuality, compared to HC and PD (p = 0.008). Whole-brain and striatal voxel-based morphometry analyses showed no significant clusters of reduced grey matter volume between groups. However, iRBD compared to HC demonstrated functional hypoconnectivity between the limbic striatum and temporo-occipital regions. Furthermore, the presence of ICDs correlated with hypoconnectivity between the limbic striatum and clusters located in cuneus, lingual and fusiform gyrus.

CONCLUSION

Altered functional connectivity between the limbic striatum and posterior cortical regions was associated with increased hypersexuality in iRBD. It is possible that this change may ultimately predispose individuals to the emergence of ICDs when they receive dopaminergic medications, after transitioning to PD.

Use of random matrix theory in the discovery of resting state brain networks

Connectomics identifies brain networks in vivo in resting state functional MRI. However, the presence of noise produces spurious identification of brain networks, which have low test-retest reliability. A Network Based Statistics approach to network identification has been previously proposed that affords much better statistical power relative to Bonferroni method but nevertheless provides a sufficiently conservative, family-wise control for false positives. We propose the use of Random Matrix Theory (RMT) to discover brain networks and to associate those networks with demographic and clinical variables. We parcellated the brain into cortical and subcortical regions using either an anatomical or a functional brain atlas. We applied RMT to study functional connectivity across brain regions by first computing the correlation matrix for time courses in those brain regions and then identifying eigenvalues that deviate from the theoretical random distribution that RMT predicts, on the assumption that real brain networks would produce eigenvalues that differ significantly from the random distribution. We assessed the specificity and test-retest reliability of identified networks through application of this RMT-based approach to (1) synthetic data generated under the null-hypothesis, (2) resting state functional MRI data from 4 real-world cohorts of patients and healthy controls, and (3) synthetic data generated by the addition of increasing amounts of noise to real-world datasets. Our findings showed that RMT method was robust to the atlas used for parcellating the brain and did not discover a brain network in synthetic data when in fact a network was not present (i.e., specificity was high); RMT-identified networks in the real-world dataset had high test-retest reliability; and RMT-based method consistently discovered the same network in the presence of increasing noise in the real-world dataset.

Cluster failure or power failure? Evaluating sensitivity in cluster-level inference

Pioneering work in human neuroscience has relied on the ability to map brain function using task-based fMRI, but the empirical validity of these inferential methods is still being characterized. A recent landmark study by Eklund and colleagues showed that popular multiple comparison corrections based on cluster extent suffer from unexpectedly low specificity (i.e., high false positive rate). Yet that study's focus on specificity, while important, is incomplete. The validity of a method depends also on its sensitivity (i.e., true positive rate or power), yet the sensitivity of cluster correction remains poorly understood. Here, we assessed the sensitivity of gold-standard nonparametric cluster correction by resampling real data from five tasks in the Human Connectome Project and comparing results with those from the full "ground truth" datasets (n ​= ​480-493). Critically, we found that sensitivity after correction is lower than may be practical for many fMRI applications. In particular, sensitivity to medium-sized effects (|Cohen's d| ​= ​0.5) was less than 20% across tasks on average, about three times smaller than without any correction. Furthermore, cluster extent correction exhibited a spatial bias in sensitivity that was independent of effect size. In comparison, correction based on the Threshold-Free Cluster Enhancement (TFCE) statistic approximately doubled sensitivity across tasks but increased spatial bias. These results suggest that we have, until now, only measured the tip of the iceberg in the activation-mapping literature due to our goal of limiting the familywise error rate through cluster extent-based inference. There is a need to revise our practices to improve sensitivity; we therefore conclude with a list of modern strategies to boost sensitivity while maintaining respectable specificity in future investigations.

Surface-based analysis increases the specificity of cortical activation patterns and connectivity results

Spatial smoothing of functional magnetic resonance imaging (fMRI) data can be performed on volumetric images and on the extracted surface of the brain. Smoothing on the unfolded cortex should theoretically improve the ability to separate signals between brain areas that are near together in the folded cortex but are more distant in the unfolded cortex. However, surface-based method approaches (SBA) are currently not utilized as standard procedure in the preprocessing of neuroimaging data. Recent improvements in the quality of cortical surface modeling and improvements in its usability nevertheless advocate this method. In the current study, we evaluated the benefits of an up-to-date surface-based smoothing in comparison to volume-based smoothing. We focused on the effect of signal contamination between different functional systems using the primary motor and primary somatosensory cortex as an example. We were particularly interested in how this signal contamination influences the results of activity and connectivity analyses for these brain regions. We addressed this question by performing fMRI on 19 subjects during a tactile stimulation paradigm and by using simulated BOLD responses. We demonstrated that volume-based smoothing causes contamination of the primary motor cortex by somatosensory cortical responses, leading to false positive motor activation. These false positive motor activations were not found by using surface-based smoothing for reasonable kernel sizes. Accordingly, volume-based smoothing caused an exaggeration of connectivity estimates between these regions. In conclusion, this study showed that surface-based smoothing decreases signal contamination considerably between neighboring functional brain regions and improves the validity of activity and connectivity results.

Motor Imagery Training With Neurofeedback From the Frontal Pole Facilitated Sensorimotor Cortical Activity and Improved Hand Dexterity

To develop a real-time neurofeedback system from the anterior prefrontal cortex (aPFC) using functional near-infrared spectroscopy (fNIRS) for motor rehabilitation, we investigated the effects of motor imagery training with neurofeedback from the aPFC on hand dexterity and cerebral hemodynamic activity during a motor rehabilitation task. Thirty-one right-handed healthy subjects participated in this study. They received motor imagery training six times for 2 weeks under fNIRS neurofeedback from the aPFC, in which they were instructed to increase aPFC activity. The real group subjects (n = 16) were shown real fNIRS neurofeedback signals from the aPFC, whereas the sham group subjects (n = 15) were shown irrelevant randomized signals during neurofeedback training. Before and after the training, hand dexterity was assessed by a motor rehabilitation task, during which cerebral hemodynamic activity was also measured. The results indicated that aPFC activity was increased during the training, and performance improvement rates in the rehabilitation task after the training was increased in the real group when compared with the sham group. Improvement rates of mean aPFC activity across the training were positively correlated with performance improvement rates in the motor rehabilitation task. During the motor rehabilitation task after the training, the hemodynamic activity in the left somatosensory motor-related areas [premotor area (PM), primary motor area (M1), and primary somatosensory area (S1)] was increased in the real group, whereas the hemodynamic activity was increased in the supplementary motor area in the sham group. This hemodynamic activity increases in the somatosensory motor-related areas after the training correlated with aPFC activity during the last 2 days of motor imagery training. Furthermore, improvement rates of M1 hemodynamic activity after the training was positively correlated with performance improvement rates in the motor rehabilitation task. The results suggest that the aPFC might shape activity in the somatosensory motor-related areas to improve hand dexterity. These findings further suggest that the motor imagery training using neurofeedback signals from the aPFC might be useful to patients with motor disability.

Distinct Spontaneous Brain Activity Patterns in Different Biologically-Defined Alzheimer's Disease Cognitive Stage: A Preliminary Study

Background: The National Institute on Aging-Alzheimer's Association (NIA-AA) has proposed a biological definition of Alzheimer's disease (AD): individuals with both abnormal amyloid and tau biomarkers (A+T+) would be defined as AD. It remains unclear why different cognitive status is present in subjects with biological AD. Resting-state functional magnetic resonance imaging (rsfMRI) has provided an opportunity to reveal the brain activity patterns in a biologically-defined AD cohort. Accordingly, we aimed to investigate distinct brain activity patterns in subjects with existed AD pathology but in the different cognitive stages. Method: We selected individuals with AD pathology (A+T+) and healthy controls (HC, A-T-) based on the cerebrospinal fluid (CSF) biomarkers. According to the cognitive stage, we divided the A+T+ cohort into three groups: (1) preclinical AD; (2) prodromal AD; and (3) AD with dementia (d-AD). We compared spontaneous brain activity measured by a fractional amplitude of low-frequency fluctuation (fALFF) approach among four groups. Results: The analysis of covariance (ANCOVA) results showed significant differences in fALFF in the posterior cingulate cortex/precuneus (PCC/PCu). Further, compared to HC, we found increased fALFF values in the right inferior frontal gyrus (IFG) in the preclinical AD stage, whereas prodromal AD patients showed reduced fALFF in the bilateral precuneus, right middle frontal gyrus (MFG), right precentral gyrus, and postcentral gyrus. Within the d-AD group, both hyperactivity (right fusiform gyrus, right parahippocampal gyrus (PHG)/hippocampus, and inferior temporal gyrus) and hypoactivity (bilateral precuneus, left posterior cingulate cortex, left cuneus and superior occipital gyrus) were detected. Conclusion: We found the distinct brain activity patterns in different cognitive stages among the subjects defined as AD biologically. Our findings may be helpful in understanding mechanisms leading to cognitive changes in the AD pathophysiological process.

Identifying Cortical Substrates Underlying the Phenomenology of Stereopsis and Realness: A Pilot fMRI Study

Viewing a real scene or a stereoscopic image (e.g., 3D movies) with both eyes yields a vivid subjective impression of object solidity, tangibility, immersive negative space and sense of realness; something that is not experienced when viewing single pictures of 3D scenes normally with both eyes. This phenomenology, sometimes referred to as stereopsis, is conventionally ascribed to the derivation of depth from the differences in the two eye's images (binocular disparity). Here we report on a pilot study designed to explore if dissociable neural activity associated with the phenomenology of realness can be localized in the cortex. In order to dissociate subjective impression from disparity processing, we capitalized on the finding that the impression of realness associated with stereoscopic viewing can also be generated when viewing a single picture of a 3D scene with one eye through an aperture. Under a blocked fMRI design, subjects viewed intact and scrambled images of natural 3-D objects, and scenes under three viewing conditions: (1) single pictures viewed normally with both eyes (binocular); (2) single pictures viewed with one eye through an aperture (monocular-aperture); and (3) stereoscopic anaglyph images of the same scenes viewed with both eyes (binocular stereopsis). Fixed-effects GLM contrasts aimed at isolating the phenomenology of stereopsis demonstrated a selective recruitment of similar posterior parietal regions for both monocular and binocular stereopsis conditions. Our findings provide preliminary evidence that the cortical processing underlying the subjective impression of realness may be dissociable and distinct from the derivation of depth from disparity.

Internally Guided Lower Limb Movement Recruits Compensatory Cerebellar Activity in People With Parkinson's Disease

Background: Externally guided (EG) and internally guided (IG) movements are postulated to recruit two parallel neural circuits, in which motor cortical neurons interact with either the cerebellum or striatum via distinct thalamic nuclei. Research suggests EG movements rely more heavily on the cerebello-thalamo-cortical circuit, whereas IG movements rely more on the striato-pallido-thalamo-cortical circuit (1). Because Parkinson's (PD) involves striatal dysfunction, individuals with PD have difficulty generating IG movements (2).

Objectives: Determine whether individuals with PD would employ a compensatory mechanism favoring the cerebellum over the striatum during IG lower limb movements.

Methods: 22 older adults with mild-moderate PD, who had abstained at least 12 h from anti-PD medications, and 19 age-matched controls performed EG and IG rhythmic foot-tapping during functional magnetic resonance imaging. Participants with PD tapped with their right (more affected) foot. External guidance was paced by a researcher tapping participants' ipsilateral 3rd metacarpal in a pattern with 0.5 to 1 s intervals, while internal guidance was based on pre-scan training in the same pattern. BOLD activation was compared between tasks (EG vs. IG) and groups (PD vs. control).

Results: Both groups recruited the putamen and cerebellar regions. The PD group demonstrated less activation in the striatum and motor cortex than controls. A task (EG vs. IG) by group (PD vs. control) interaction was observed in the cerebellum with increased activation for the IG condition in the PD group.

Conclusions: These findings support the hypothesized compensatory shift in which the dysfunctional striatum is assisted by the less affected cerebellum to accomplish IG lower limb movement in individuals with mild-moderate PD. These findings are of relevance for temporal gait dysfunction and freezing of gait problems frequently noted in many people with PD and may have implications for future therapeutic application.

Acute psychosocial stress alters thalamic network centrality

Acute stress triggers a broad psychophysiological response that is adaptive if rapidly activated and terminated. While the brain controls the stress response, it is strongly affected by it. Previous research of stress effects on brain activation and connectivity has mainly focused on pre-defined brain regions or networks, potentially missing changes in the rest of the brain. We here investigated how both stress reactivity and stress recovery are reflected in whole-brain network topology and how changes in functional connectivity relate to other stress measures. Healthy young males (n = 67) completed the Trier Social Stress Test or a control task. From 60 min before until 105 min after stress onset, blocks of resting-state fMRI were acquired. Subjective, autonomic, and endocrine measures of the stress response were assessed throughout the experiment. Whole-brain network topology was quantified using Eigenvector centrality (EC) mapping, which detects central hubs of a network. Stress influenced subjective affect, autonomic activity, and endocrine measures. EC differences between groups as well as before and after stress exposure were found in the thalamus, due to widespread connectivity changes in the brain. Stress-driven EC increases in the thalamus were significantly correlated with subjective stress ratings and showed non-significant trends for a correlation with heart rate variability and saliva cortisol. Furthermore, increases in thalamic EC and in saliva cortisol persisted until 105 min after stress onset. We conclude that thalamic areas are central for information processing after stress exposure and may provide an interface for the stress response in the rest of the body and in the mind.