A four-dimensional probabilistic atlas of the human brain

Trying to forget alcohol: Brain mechanisms underlying memory suppression in young binge drinkers

People are able to voluntarily suppress unwanted thoughts or memories, a phenomenon known as suppression-induced forgetting or memory suppression. Despite harmful alcohol use, such as binge drinking, has been linked to impaired inhibitory control (IC) and augmented alcohol-cue reactivity, no study to date has assessed memory inhibition abilities towards alcohol-related cues in binge drinkers (BDs). Thus, the present preregistered study aimed to evaluate the behavioral and neurofunctional mechanisms associated with memory inhibition, specifically those related to the suppression of alcohol-related memories, in young BDs. For this purpose, electroencephalographic activity was recorded in eighty-two college students aged between 18 and 24 years old from the University of Minho (50% females; 40 non/low-drinkers [N/LDS] and 42 BDs) while they performed the Think/No-Think Alcohol task. Brain functional connectivity (FC) was calculated using the phase locking value and, subsequently, a dynamic seed-based analysis was conducted to explore the FC patterns between IC and memory networks. Comparatively to N/LDs, BDs exhibited decreased alpha-band FC between the anterior cingulate cortex and the left fusiform gyrus during attempts to suppress non-alcohol memories, accompanied by unsuccessful forgetting of those memories. Conversely, BDs displayed augmented gamma-band FC between the IC network and memory regions -i.e., hippocampus, parahippocampus and fusiform gyrus- during suppression of alcohol-related memories. Inhibitory abnormalities in BDs may lead to hypoconnectivity between IC and memory networks and deficient suppression of non-alcohol-related memories. However, while suppressing highly salient and reward-predicting stimuli, such as alcohol-related memories, BDs display a hyperconnectivity pattern between IC and memory networks, likely due to their augmented attention towards intrusive alcoholic memories and the attempts to compensate for potential underlying IC deficits. These findings hold important implications for alcohol research and treatment, as they open up new avenues for reducing alcohol use by shifting the focus to empowering suppression/control over alcohol-related memories. CLINICAL TRIAL REGISTRATION: [http://www.ClinicalTrials.gov], identifier [NCT05237414].

Perspectives on Optimized Transcranial Electrical Stimulation Based on Spatial Electric Field Modeling in Humans

Background: Transcranial electrical stimulation (tES) generates an electric field (or current density) in the brain through surface electrodes attached to the scalp. Clinical significance has been demonstrated, although with moderate and heterogeneous results partly due to a lack of control of the delivered electric currents. In the last decade, computational electric field analysis has allowed the estimation and optimization of the electric field using accurate anatomical head models. This review examines recent tES computational studies, providing a comprehensive background on the technical aspects of adopting computational electric field analysis as a standardized procedure in medical applications. Methods: Specific search strategies were designed to retrieve papers from the Web of Science database. The papers were initially screened based on the soundness of the title and abstract and then on their full contents, resulting in a total of 57 studies. Results: Recent trends were identified in individual- and population-level analysis of the electric field, including head models from non-neurotypical individuals. Advanced optimization techniques that allow a high degree of control with the required focality and direction of the electric field were also summarized. There is also growing evidence of a correlation between the computationally estimated electric field and the observed responses in real experiments. Conclusions: Computational pipelines and optimization algorithms have reached a degree of maturity that provides a rationale to improve tES experimental design and a posteriori analysis of the responses for supporting clinical studies.

Are human connectomes heritable?

A complete understanding of human behavior and disease depends upon our ability to parse genetic and environmental influences in the human brain. The heritability of a trait quantifies the degree of its variability due to genetic influences. Classical approach for quantifying heritability operate on simple traits, and sometimes do not properly model and control for other potential sources of variation, such as age or sex. We therefore develop Causal Heritability of Networks (CHaiN) to rigorously quantify heritability of human brain networks (i.e., connectomes). We applied CHaiN to 1024 anatomical connectomes derived from the Human Connectome Project. Connectomes appeared to be heritable, but heritability was insignificant once we addressed variability within networks. These results suggest that previous conclusions on connectome heritability may be driven by the shared network structures, and highlights the importance of modeling networks and other sources of variability when studying heritability of connectomes.

Decoding Autism: Uncovering patterns in brain connectivity through sparsity analysis with rs-fMRI data

BACKGROUND

In the realm of neuro-disorders, precise diagnosis and treatment rely heavily on objective imaging-based biomarker identification. This study employs a sparsity approach on resting-state fMRI to discern relevant brain region connectivity for predicting Autism.

NEW METHOD

The proposed methodology involves four key steps: (1) Utilizing three probabilistic brain atlases to extract functionally homogeneous brain regions from fMRI data. (2) Employing a hybrid approach of Graphical Lasso and Akaike Information Criteria to optimize sparse inverse covariance matrices for representing the brain functional connectivity. (3) Employing statistical techniques to scrutinize functional brain structures in Autism and Control subjects. (4) Implementing both autoencoder-based feature extraction and entire feature-based approach coupled with AI-based learning classifiers to predict Autism.

RESULTS

The ensemble classifier with the extracted feature set achieves a classification accuracy of 84.7% ± 0.3% using the MSDL atlas. Meanwhile, the 1D-CNN model, employing all features, exhibits superior classification accuracy of 88.6% ± 1.7% with the Smith 2009 (rsn70) atlas.

COMPARISON WITH EXISTING METHOD (S)

The proposed methodology outperforms the conventional correlation-based functional connectivity approach with a notably high prediction accuracy of more than 88%, whereas considering all direct and noisy indirect region-based functional connectivity, the traditional methods bound the prediction accuracy within 70% to 79%.

CONCLUSIONS

This study underscores the potential of sparsity-based FC analysis using rs-fMRI data as a prognostic biomarker for detecting Autism.

Reward anticipation-related neural activation following cued reinforcement in adults with psychotic psychopathology and biological relatives

BACKGROUND

Schizophrenia is associated with hypoactivation of reward sensitive brain areas during reward anticipation. However, it is unclear whether these neural functions are similarly impaired in other disorders with psychotic symptomatology or individuals with genetic liability for psychosis. If abnormalities in reward sensitive brain areas are shared across individuals with psychotic psychopathology and people with heightened genetic liability for psychosis, there may be a common neural basis for symptoms of diminished pleasure and motivation.

METHODS

We compared performance and neural activity in 123 people with a history of psychosis (PwP), 81 of their first-degree biological relatives, and 49 controls during a modified Monetary Incentive Delay task during fMRI.

RESULTS

PwP exhibited hypoactivation of the striatum and anterior insula (AI) during cueing of potential future rewards with each diagnostic group showing hypoactivations during reward anticipation compared to controls. Despite normative task performance, relatives demonstrated caudate activation intermediate between controls and PwP, nucleus accumbens activation more similar to PwP than controls, but putamen activation on par with controls. Across diagnostic groups of PwP there was less functional connectivity between bilateral caudate and several regions of the salience network (medial frontal gyrus, anterior cingulate, AI) during reward anticipation.

CONCLUSIONS

Findings implicate less activation and connectivity in reward processing brain regions across a spectrum of disorders involving psychotic psychopathology. Specifically, aberrations in striatal and insular activity during reward anticipation seen in schizophrenia are partially shared with other forms of psychotic psychopathology and associated with genetic liability for psychosis.

A precision functional atlas of personalized network topography and probabilities

Although the general location of functional neural networks is similar across individuals, there is vast person-to-person topographic variability. To capture this, we implemented precision brain mapping functional magnetic resonance imaging methods to establish an open-source, method-flexible set of precision functional network atlases-the Masonic Institute for the Developing Brain (MIDB) Precision Brain Atlas. This atlas is an evolving resource comprising 53,273 individual-specific network maps, from more than 9,900 individuals, across ages and cohorts, including the Adolescent Brain Cognitive Development study, the Developmental Human Connectome Project and others. We also generated probabilistic network maps across multiple ages and integration zones (using a new overlapping mapping technique, Overlapping MultiNetwork Imaging). Using regions of high network invariance improved the reproducibility of executive function statistical maps in brain-wide associations compared to group average-based parcellations. Finally, we provide a potential use case for probabilistic maps for targeted neuromodulation. The atlas is expandable to alternative datasets with an online interface encouraging the scientific community to explore and contribute to understanding the human brain function more precisely.

Spatial correspondence of cortical activity measured with whole head fNIRS and fMRI: Toward clinical use within subject

Functional near infrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI) both measure the hemodynamic response, and so both imaging modalities are expected to have a strong correspondence in regions of cortex adjacent to the scalp. To assess whether fNIRS can be used clinically in a manner similar to fMRI, 22 healthy adult participants underwent same-day fMRI and whole-head fNIRS testing while they performed separate motor (finger tapping) and visual (flashing checkerboard) tasks. Analyses were conducted within and across subjects for each imaging approach, and regions of significant task-related activity were compared on the cortical surface. The spatial correspondence between fNIRS and fMRI detection of task-related activity was good in terms of true positive rate, with fNIRS overlap of up to 68 % of the fMRI for analyses across subjects (group analysis) and an average overlap of up to 47.25 % for individual analyses within subject. At the group level, the positive predictive value of fNIRS was 51 % relative to fMRI. The positive predictive value for within subject analyses was lower (41.5 %), reflecting the presence of significant fNIRS activity in regions without significant fMRI activity. This could reflect task-correlated sources of physiologic noise and/or differences in the sensitivity of fNIRS and fMRI measures to changes in separate (vs. combined) measures of oxy and de-oxyhemoglobin. The results suggest whole-head fNIRS as a noninvasive imaging modality with promising clinical utility for the functional assessment of brain activity in superficial regions of cortex physically adjacent to the skull.

Functional connectivity of sensorimotor network is enhanced in spastic diplegic cerebral palsy: A multimodal study using fMRI and MEG

OBJECTIVE

To assess the effects to functional connectivity (FC) caused by lesions related to spastic diplegic cerebral palsy (CP) in children and adolescents using multiple imaging modalities.

METHODS

We used resting state magnetoencephalography (MEG) envelope signals in alpha, beta and gamma ranges and resting state functional magnetic resonance imaging (fMRI) signals to quantify FC between selected sensorimotor regions of interest (ROIs) in 11 adolescents with spastic diplegic cerebral palsy and 24 typically developing controls. Motor performance of the hands was quantified with gross motor, fine motor and kinesthesia tests.

RESULTS

In fMRI, participants with CP showed enhanced FC within posterior parietal regions; in MEG, they showed enhanced interhemispheric FC between sensorimotor regions and posterior parietal regions both in alpha and lower beta bands. There was a correlation between the kinesthesia score and fronto-parietal connectivity in the control population.

CONCLUSIONS

CP is associated with enhanced FC in sensorimotor network. This difference is not correlated with hand coordination performance. The effect of the lesion is likely not fully captured by temporal correlation of ROI signals.

SIGNIFICANCE

Brain lesions can show as increased temporal correlation of activity between remote brain areas. We suggest this effect is likely separate from typical physiological correlates of functional connectivity.

Visualizing interferential stimulation of human brains

Introduction

Transcranial electrical stimulation (TES) is limited in focally stimulating deep-brain regions, even with optimized stimulation montages. Recently, interferential stimulation (IFS), also known as transcranial temporal interference stimulation (TI, TIS, or tTIS), has drawn much attention in the TES community as both computational and experimental studies show that IFS can reach deep-brain areas. However, the underlying electrodynamics of IFS is complicated and difficult to visualize. Existing literature only shows static visualization of the interfered electric field induced by IFS. These could result in a simplified understanding that there is always one static focal spot between the two pairs of stimulation electrodes. This static visualization can be frequently found in the IFS literature. Here, we aimed to systematically visualize the entire dynamics of IFS.

Methods and results

Following the previous study, the lead field was solved for the MNI-152 head, and optimal montages using either two pairs of electrodes or two arrays of electrodes were found to stimulate a deep-brain region close to the left striatum with the highest possible focality. We then visualized the two stimulating electrical currents injected with similar frequencies. We animated the instant electric field vector at the target and one exemplary off-target location both in 3D space and as a 2D Lissajous curve. We finally visualized the distribution of the interfered electric field and the amplitude modulation envelope at an axial slice going through the target location. These two quantities were visualized in two directions: radial-in and posterior-anterior.

Discussion

We hope that with intuitive visualization, this study can contribute as an educational resource to the community's understanding of IFS as a powerful modality for non-invasive focal deep-brain stimulation.

[Usefulness of Voxel-Based Quantification (VBQ) Smoothing in Relaxation Time Mapping]

PURPOSE

Voxel-based quantification (VBQ) smoothing is a technique used to smooth quantitative parametric maps in the Montreal Neurological Institute standard space. Although VBQ smoothing could suppress changes in quantitative values at tissue boundaries, its effectiveness on relaxation time (T1 and T2 values and proton density PD) maps has not been investigated. The purpose of this study was to clarify the usefulness of VBQ smoothing in relaxation time mapping.

METHOD

T1 and T2 values and PD maps of the brains of 20 healthy participants were obtained using a two-dimensional multi-dynamic multi-echo sequence. VBQ and Gaussian smoothing were applied to the relaxation time maps by varying the kernel size by 1 mm from 1 to 6 mm. Changes in relaxation time before and after VBQ and Gaussian smoothing for the putamen, caudate nucleus, substantia nigra, and corpus callosum on the relaxation time maps were evaluated.

RESULT

The changes in relaxation time after VBQ smoothing application were smaller than those in that after Gaussian smoothing application. Although the differences in the relaxation time for all tissues before and after VBQ and Gaussian smoothing applications increased with increasing kernel size for all relaxation times for both methods, the changes in the relaxation time for VBQ smoothing were smaller than those in that for Gaussian smoothing.

CONCLUSION

VBQ smoothing can suppress the change in the relaxation time on the boundary of the tissue and is thus a useful smoothing technique in relaxation time mapping.

Different associations between amyloid-βeta 42, amyloid-βeta 40, and amyloid-βeta 42/40 with soluble phosphorylated-tau and disease burden in Alzheimer's disease: a cerebrospinal fluid and fluorodeoxyglucose-positron emission tomography study

BACKGROUND

Despite the high sensitivity of cerebrospinal fluid (CSF) amyloid beta (Aβ)42 to detect amyloid pathology, the Aβ42/Aβ40 ratio (amyR) better estimates amyloid load, with higher specificity for Alzheimer's disease (AD). However, whether Aβ42 and amyR have different meanings and whether Aβ40 represents more than an Aβ42-corrective factor remain to be clarified. Our study aimed to compare the ability of Aβ42 and amyR to detect AD pathology in terms of p-tau/Aβ42 ratio and brain glucose metabolic patterns using fluorodeoxyglucose-positron emission tomography (FDG-PET).

METHODS

CSF biomarkers were analyzed with EUROIMMUN ELISA. We included 163 patients showing pathological CSF Aβ42 and normal p-tau (A + T -  = 98) or pathological p-tau levels (A + T +  = 65) and 36 control subjects (A - T -). A + T - patients were further stratified into those with normal (CSFAβ42 + /amyR -  = 46) and pathological amyR (CSFAβ42 + /amyR +  = 52). We used two distinct cut-offs to determine pathological values of p-tau/Aβ42: (1) ≥ 0.086 and (2) ≥ 0.122. FDG-PET patterns were evaluated in a subsample of patients (n = 46) and compared to 24 controls.

RESULTS

CSF Aβ40 levels were the lowest in A - T - and in CSFAβ42 + /amyR - , higher in CSFAβ42 + /amyR + and highest in A + T + (F = 50.75; p < 0.001), resembling CSF levels of p-tau (F = 192; p < 0.001). We found a positive association between Aβ40 and p-tau in A - T - (β = 0.58; p < 0.001), CSFAβ42 + /amyR - (β = 0.47; p < 0.001), and CSFAβ42 + /amyR + patients (β = 0.48; p < 0.001) but not in A + T + . Investigating biomarker changes as a function of amyR, we observed a weak variation in CSF p-tau (+ 2 z-scores) and Aβ40 (+ 0.8 z-scores) in the normal amyR range, becoming steeper over the pathological threshold of amyR (p-tau: + 5 z-scores, Aβ40: + 4.5 z-score). CSFAβ42 + /amyR + patients showed a significantly higher probability of having pathological p-tau/Aβ42 than CSFAβ42 + /amyR - (cut-off ≥ 0.086: OR 23.3; cut-off ≥ 0.122: OR 8.8), which however still showed pathological values of p-tau/Aβ42 in some cases (cut-off ≥ 0.086: 35.7%; cut-off ≥ 0.122: 17.3%) unlike A - T - . Accordingly, we found reduced FDG metabolism in the temporoparietal regions of CSFAβ42 + /amyR - compared to controls, and further reduction in frontal areas in CSFAβ42 + /amyR + , like in A + T + .

CONCLUSIONS

Pathological p-tau/Aβ42 and FDG hypometabolism typical of AD can be found in patients with decreased CSF Aβ42 levels alone. AmyR positivity, associated with higher Aβ40 levels, is accompanied by higher CSF p-tau and widespread FDG hypometabolism.

Sleep Dysregulation Is Associated with 18F-FDG PET and Cerebrospinal Fluid Biomarkers in Alzheimer's Disease

Background

Sleep impairment has been commonly reported in Alzheimer's disease (AD) patients. The association between sleep dysregulation and AD biomarkers has been separately explored in mild cognitive impairment (MCI) and AD patients.

Objective

The present study investigated cerebrospinal-fluid (CSF) and 18F-fluoro-deoxy-glucose positron emission tomography (18F-FDG-PET) biomarkers in MCI and AD patients in order to explore their association with sleep parameters measured with polysomnography (PSG).

Methods

MCI and AD patients underwent PSG, 18F-FDG-PET, and CSF analysis for detecting and correlating these biomarkers with sleep architecture.

Results

Thirty-five patients were included in the study (9 MCI and 26 AD patients). 18F-FDG uptake in left Brodmann area 31 (owing to the posterior cingulate cortex) correlated negatively with REM sleep latency (p = 0.013) and positively with REM sleep (p = 0.033). 18F-FDG uptake in the hippocampus was negatively associated with sleep onset latency (p = 0.041). Higher CSF orexin levels were associated with higher sleep onset latency (p = 0.042), Non-REM stage 1 of sleep (p = 0.031), wake after sleep onset (p = 0.028), and lower sleep efficiency (p = 0.045). CSF levels of Aβ42 correlated negatively with the wake bouts index (p = 0.002). CSF total-tau and phosphorylated tau levels correlated positively with total sleep time (p = 0.045) and time in bed (p = 0.031), respectively.

Conclusion

Sleep impairment, namely sleep fragmentation, REM sleep dysregulation, and difficulty in initiating sleep correlates with AD biomarkers, suggesting an effect of sleep on the pathological processes in different AD stages. Targeting sleep for counteracting the AD pathological processes represents a timely need for clinicians and researchers.

Assessment of sodium (23Na) brain MRI at 3T - preliminary results

Purpose

The purpose of this work was to establish a database of tissue sodium concentration (TSC) in the normal brain of healthy volunteers. Tissue sodium concentration can be used as a sensitive marker of tissue viability in stroke or radiation therapy monitoring.

Material and methods

Thirty-seven volunteers were scanned with a 23Na protocol in the span of one year; within this group, 29 studies were of acceptable quality. The study was approved by the Local Bioethics Committee. Data were acquired during a single magnetic resonance (MR) scanner session. The single scanner session consisted of 23Na 3D radial gradient echo (GRE) acquisition, MPRage, SPACE-FLAIR, and Resolve-DTI. MPRage images were segmented to obtain masks of the grey matter (GM), white matter (WM), and cerebrospinal fluid (CSF), which were registered to the sodium image space for image analysis. Images were transformed into TSC maps - a signal calibration curve obtained from the reference phantom of known sodium concentration and known relaxation time.

Results

The collected data were analysed in 2 different ways: volunteers were divided by sex and by age. No significant differences in TSC were found between sexes. In all comparisons there was a significant difference in TSC between younger and older volunteers. In healthy volunteers mean TSC were as follows: GM 33.21 ± 4.76 mmol/l, WM 28.41 ± 4.03 mmol/l and for CSF 41.3 ± 6.69 mmol/l.

Conclusions

This preliminary work is a base for further work with sodium imaging in brain lesions. The entirety of the col-lected data will be useful in the future as a baseline brain TSC for comparison to values obtained from pathologies.

Automated acute ischemic stroke lesion delineation based on apparent diffusion coefficient thresholds

Purpose

Automated lesion segmentation is increasingly used in acute ischemic stroke magnetic resonance imaging (MRI). We explored in detail the performance of apparent diffusion coefficient (ADC) thresholding for delineating baseline diffusion-weighted imaging (DWI) lesions.

Methods

Retrospective, exploratory analysis of the prospective observational single-center 1000Plus study from September 2008 to June 2013 (clinicaltrials.org; NCT00715533). We built a fully automated lesion segmentation algorithm using a fixed ADC threshold (≤620 × 10-6 mm2/s) to delineate the baseline DWI lesion and analyzed its performance compared to manual assessments. Diagnostic capabilities of best possible ADC thresholds were investigated using receiver operating characteristic curves. Influential patient factors on ADC thresholding techniques' performance were studied by conducting multiple linear regression.

Results

108 acute ischemic stroke patients were selected for analysis. The median Dice coefficient for the algorithm was 0.43 (IQR 0.20-0.64). Mean ADC values in the DWI lesion (β = -0.68, p < 0.001) and DWI lesion volumes (β = 0.29, p < 0.001) predicted performance. Optimal individual ADC thresholds differed between subjects with a median of ≤691 × 10-6 mm2/s (IQR ≤660-750 × 10-6 mm2/s). Mean ADC values in the DWI lesion (β = -0.96, p < 0.001) and mean ADC values in the brain parenchyma (β = 0.24, p < 0.001) were associated with the performance of individual thresholds.

Conclusion

The performance of ADC thresholds for delineating acute stroke lesions varies substantially between patients. It is influenced by factors such as lesion size as well as lesion and parenchymal ADC values. Considering the inherent noisiness of ADC maps, ADC threshold-based automated delineation of very small lesions is not reliable.

Periventricular and juxtacortical characterization of UManitoba-JHU functionally defined human white matter atlas networks

Background

The open-access UManitoba-JHU functionally defined human white matter (WM) atlas contains specific WM pathways and general WM regions underlying 12 functional brain networks in ICBM152 template space. However, it is not known whether any of these WM networks are disproportionately co-localized with periventricular and/or juxtacortical WM (PVWM and JCWM), which could potentially impact their ability to infer network-specific effects in future studies-particularly in patient populations expected to have disproportionate PVWM and/or JCWM damage.

Methods

The current study therefore identified intersecting regions of PVWM and JCWM (defined as WM within 5 mm of the ventricular and cortical boundaries) and: (1) the ICBM152 global WM mask, and (2) all 12 UManitoba-JHU WM networks. Dice Similarity Coefficient (DSC), Jaccard Similarity Coefficient (JSC), and proportion of volume (POV) values between PVWM (and JCWM) and each functionally defined WM network were then compared to corresponding values between PVWM (and JCWM) and global WM.

Results

Between the 12 WM networks and PVWM, 8 had lower DSC, JSC, and POV; 1 had lower DSC and JSC, but higher POV; and 3 had higher DSC, JSC, and POV compared to global WM. For JCWM, all 12 WM networks had lower DSC, JSC, and POV compared to global WM.

Conclusion

The majority of UManitoba-JHU functionally defined WM networks exhibited lower than average spatial similarity with PVWM, and all exhibited lower than average spatial similarity with JCWM. This suggests that they can be used to explore network-specific WM changes, even in patient populations with known predispositions toward PVWM and/or JCWM damage.

[Evaluation of the Accuracy of Relaxation Time Measurements Using 3D-QALAS at 3.0 T MRI and Comparison with 2D-MDME]

PURPOSE

Three-dimensional (3D) quantification using an interleaved Look-Locker acquisition sequence with a T₂ preparation pulse (QALAS) is a quantitative sequence used to measure relaxation times. The accuracy of the relaxation time measurement of 3D-QALAS at 3.0 T and the bias of 3D-QALAS have not yet been assessed. The purpose of this study was to clarify the accuracy of the relaxation time measurements using 3D-QALAS at 3.0 T MRI.

METHODS

The accuracy of the T₁ and T₂ values for 3D-QALAS was evaluated using a phantom. Subsequently, the T₁ and T₂ values and proton density of the brain parenchyma in healthy subjects were measured using 3D-QALAS and compared with those of 2D multi-dynamic multi-echo (MDME).

RESULTS

In the phantom study, the average T₁ value of 3D-QALAS was 8.3% prolonged than that for conventional inversion recovery spin-echo; the average T₂ value for 3D-QALAS was 18.4% shorter than that for multi-echo spin-echo. The in vivo assessment showed that the mean T₁ and T₂ values and PD for 3D-QALAS were prolonged by 5.3%, shortened by 9.6%, and increased by 7.0%, respectively, compared with those for 2D-MDME.

CONCLUSION

Although 3D-QALAS at 3.0 T has high accuracy T₁ value, which is less than 1000 ms, the T₁ value could be overestimated for tissues with it longer than that T₁ value. The T₂ value for 3D-QALAS could be underestimated for tissues with T₂ values, and this tendency increases with longer T₂ values.

Predicting Motor Outcomes Using Atlas-Based Voxel Features of Post-Stroke Neuroimaging: A Scoping Review

BACKGROUND

Atlas-based voxel features have the potential to aid motor outcome prognostication after stroke, but are seldom used in clinically feasible prediction models. This could be because neuroimaging feature development is a non-standardized, complex, multistep process. This is a barrier to entry for researchers and poses issues for reproducibility and validation in a field of research where sample sizes are typically small.

OBJECTIVES

The primary aim of this review is to describe the methodologies currently used in motor outcome prediction studies using atlas-based voxel neuroimaging features. Another aim is to identify neuroanatomical regions commonly used for motor outcome prediction.

METHODS

A Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol was constructed and OVID Medline and Scopus databases were searched for relevant studies. The studies were then screened and details about imaging modality, image acquisition, image normalization, lesion segmentation, region of interest determination, and imaging measures were extracted.

RESULTS

Seventeen studies were included and examined. Common limitations were a lack of detailed reporting on image acquisition and the specific brain templates used for normalization and a lack of clear reasoning behind the atlas or imaging measure selection. A wide variety of sensorimotor regions relate to motor outcomes and there is no consensus use of one single sensorimotor atlas for motor outcome prediction.

CONCLUSION

There is an ongoing need to validate imaging predictors and further improve methodological techniques and reporting standards in neuroimaging feature development for motor outcome prediction post-stroke.

Reduced connectivity of primary auditory and motor cortices during exposure to auditory white noise

Auditory white noise (WN) is widely used in daily life for inducing sleep, and in neuroscience to mask unwanted environmental noise and cues. However, WN was recently reported to influence corticospinal excitability and behavioral performance. Here, we expand previous preliminary findings on the influence of WN exposure on cortical functioning, and we hypothesize that it may modulate cortical connectivity. We tested our hypothesis by performing magnetoencephalography in 20 healthy subjects. WN reduces cortical connectivity of the primary auditory and motor regions with very distant cortical areas, showing a right lateralized connectivity reduction for primary motor cortex. The present results, together with previous finding concerning WN impact on corticospinal excitability and behavioral performance, further support the role of WN as a modulator of cortical function. This suggest avoiding its unrestricted use as a masking tool, while purposely designed and controlled WN application could be exploited to harness brain function and to treat neuropsychiatric conditions.

Computation of group-level electric field in lower limb motor area for different tDCS montages

OBJECTIVE

Transcranial direct current stimulation (tDCS) injects a weak electric current into the brain via electrodes attached to the scalp to modulate cortical excitability. tDCS is used to rebalance brain activity between affected and unaffected hemispheres in rehabilitation. However, a systematic quantitative evaluation of tDCS montage is not reported for the lower limbs. In this study, we computationally investigated the generated electric field intensity, polarity, and co-stimulation of cortical areas for lower limb targeting using high-resolution head models.

METHODS

Volume conductor models have thus been employed to estimate the electric field in the brain. A total of 18 head models of healthy subjects were used to calculate the group-level electric fields generated from four montages of tDCS for modulation of lower limbs.

RESULTS

C1-C2 montage delivered higher electric field intensities while reaching deeper regions of the lower-limb motor area. It produced a uniform polarization on the same hemisphere target with comparable intensities between hemispheres but with higher variability.

CONCLUSIONS

Proper montage selection allows reaching deeper regions of the lower-limb motor area with uniform polarization.

SIGNIFICANCE

First systematic computational study providing support to tDCS experimental studies using montages for the lower limb while considering polarity factor for balancing brain activity.

Functional magnetic resonance imaging of headache: Issues, best-practices, and new directions, a narrative review

OBJECTIVE

To ensure readers are informed consumers of functional magnetic resonance imaging (fMRI) research in headache, to outline ongoing challenges in this area of research, and to describe potential considerations when asked to collaborate on fMRI research in headache, as well as to suggest future directions for improvement in the field.

BACKGROUND

Functional MRI has played a key role in understanding headache pathophysiology, and mapping networks involved with headache-related brain activity have the potential to identify intervention targets. Some investigators have also begun to explore its use for diagnosis.

METHODS/RESULTS

The manuscript is a narrative review of the current best practices in fMRI in headache research, including guidelines on transparency and reproducibility. It also contains an outline of the fundamentals of MRI theory, task-related study design, resting-state functional connectivity, relevant statistics and power analysis, image preprocessing, and other considerations essential to the field.

CONCLUSION

Best practices to increase reproducibility include methods transparency, eliminating error, using a priori hypotheses and power calculations, using standardized instruments and diagnostic criteria, and developing large-scale, publicly available datasets.

Reproducibility of cerebellar involvement as quantified by consensus structural MRI biomarkers in advanced essential tremor

Essential tremor (ET) is the most prevalent movement disorder with poorly understood etiology. Some neuroimaging studies report cerebellar involvement whereas others do not. This discrepancy may stem from underpowered studies, differences in statistical modeling or variation in magnetic resonance imaging (MRI) acquisition and processing. To resolve this, we investigated the cerebellar structural differences using a local advanced ET dataset augmented by matched controls from PPMI and ADNI. We tested the hypothesis of cerebellar involvement using three neuroimaging biomarkers: VBM, gray/white matter volumetry and lobular volumetry. Furthermore, we assessed the impacts of statistical models and segmentation pipelines on results. Results indicate that the detected cerebellar structural changes vary with methodology. Significant reduction of right cerebellar gray matter and increase of the left cerebellar white matter were the only two biomarkers consistently identified by multiple methods. Results also show substantial volumetric overestimation from SUIT-based segmentation-partially explaining previous literature discrepancies. This study suggests that current estimation of cerebellar involvement in ET may be overemphasized in MRI studies and highlights the importance of methods sensitivity analysis on results interpretation. ET datasets with large sample size and replication studies are required to improve our understanding of regional specificity of cerebellum involvement in ET. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on 21 March 2022. The protocol, as accepted by the journal, can be found at: https://doi.org/10.6084/m9.figshare.19697776 .

Using carpet plots to analyze blood transit times in the brain during hypercapnic challenge magnetic resonance imaging

Blood arrival time and blood transit time are useful metrics in characterizing hemodynamic behaviors in the brain. Functional magnetic resonance imaging in combination with a hypercapnic challenge has been proposed as a non-invasive imaging tool to determine blood arrival time and replace dynamic susceptibility contrast (DSC) magnetic resonance imaging, a current gold-standard imaging tool with the downsides of invasiveness and limited repeatability. Using a hypercapnic challenge, blood arrival times can be computed by cross-correlating the administered CO₂ signal with the fMRI signal, which increases during elevated CO₂ due to vasodilation. However, whole-brain transit times derived from this method can be significantly longer than the known cerebral transit time for healthy subjects (nearing 20 s vs. the expected 5-6 s). To address this unrealistic measurement, we here propose a novel carpet plot-based method to compute improved blood transit times derived from hypercapnic blood oxygen level dependent fMRI, demonstrating that the method reduces estimated blood transit times to an average of 5.32 s. We also investigate the use of hypercapnic fMRI with cross-correlation to compute the venous blood arrival times in healthy subjects and compare the computed delay maps with DSC-MRI time to peak maps using the structural similarity index measure (SSIM). The strongest delay differences between the two methods, indicated by low structural similarity index measure, were found in areas of deep white matter and the periventricular region. SSIM measures throughout the remainder of the brain reflected a similar arrival sequence derived from the two methods despite the exaggerated spread of voxel delays computed using CO₂ fMRI.

EEG Resting-State Functional Networks in Amnestic Mild Cognitive Impairment

Background. Alzheimer's cognitive-behavioral syndrome is the result of impaired connectivity between nerve cells, due to misfolded proteins, which accumulate and disrupt specific brain networks. Electroencephalography, because of its excellent temporal resolution, is an optimal approach for assessing the communication between functionally related brain regions. Objective. To detect and compare EEG resting-state networks (RSNs) in patients with amnesic mild cognitive impairment (aMCI), and healthy elderly (HE). Methods. We recruited 125 aMCI patients and 70 healthy elderly subjects. One hundred and twenty seconds of artifact-free EEG data were selected and compared between patients with aMCI and HE. We applied standard low-resolution brain electromagnetic tomography (sLORETA)-independent component analysis (ICA) to assess resting-state networks. Each network consisted of a set of images, one for each frequency (delta, theta, alpha1/2, beta1/2). Results. The functional ICA analysis revealed 17 networks common to groups. The statistical procedure demonstrated that aMCI used some networks differently than HE. The most relevant findings were as follows. Amnesic-MCI had: i) increased delta/beta activity in the superior frontal gyrus and decreased alpha1 activity in the paracentral lobule (ie, default mode network); ii) greater delta/theta/alpha/beta in the superior frontal gyrus (i.e, attention network); iii) lower alpha in the left superior parietal lobe, as well as a lower delta/theta and beta, respectively in post-central, and in superior frontal gyrus(ie, attention network). Conclusions. Our study confirms sLORETA-ICA method is effective in detecting functional resting-state networks, as well as between-groups connectivity differences. The findings provide support to the Alzheimer's network disconnection hypothesis.

Functional Correlates of Striatal Dopamine Transporter Cerebrospinal Fluid Levels in Alzheimer's Disease: A Preliminary 18F-FDG PET/CT Study

The aim of our study was to investigate regional glucose metabolism with 18F-FDG positron emission tomography/computed tomography in a population of patients with Alzheimer's disease (AD) in relation to cerebrospinal (CSF) levels of striatal dopamine transporter (DAT). All patients underwent lumbar puncture and received a biomarker-based diagnosis of AD. Differences in regional brain glucose metabolism were assessed by Statistical Parametric Mapping version 12 with the use of age, gender, and MMSE as covariates in the analysis. A positive correlation between CSF DAT levels and glucose metabolism at the level of two brain areas involved in the pathophysiological process of Alzheimer's disease, the substantia nigra and the posterior cingulate gyrus, has been highlighted. Results indicate that patients with higher CSF DAT levels have a better metabolic pattern in two key zones, suggesting less advanced disease status in patients with more conserved dopaminergic systems.

Radial diffusivity reflects general decline rather than specific cognitive deterioration in multiple sclerosis

Advanced structural brain imaging techniques, such as diffusion tensor imaging (DTI), have been used to study the relationship between DTI-parameters and cognitive scores in multiple sclerosis (MS). In this study, we assessed cognitive function in 61 individuals with MS and a control group of 35 healthy individuals with the Symbol Digit Modalities Test, the California Verbal Learning Test-II, the Brief Visuospatial Memory Test-Revised, the Controlled Oral Word Association Test, and Stroop-test. We also acquired diffusion-weighted images (b = 1000; 32 directions), which were processed to obtain the following DTI scalars: fractional anisotropy, mean, axial, and radial diffusivity. The relation between DTI scalars and cognitive parameters was assessed through permutations. Although fractional anisotropy and axial diffusivity did not correlate with any of the cognitive tests, mean and radial diffusivity were negatively correlated with all of these tests. However, this effect was not specific to any specific white matter tract or cognitive test and demonstrated a general effect with only low to moderate individual voxel-based correlations of <0.6. Similarly, lesion and white matter volume show a general effect with medium to high voxel-based correlations of 0.5-0.8. In conclusion, radial diffusivity is strongly related to cognitive impairment in MS. However, the strong associations of radial diffusivity with both cognition and whole brain lesion volume suggest that it is a surrogate marker for general decline in MS, rather than a marker for specific cognitive functions.

Cerebral tomoelastography based on multifrequency MR elastography in two and three dimensions

Purpose: Magnetic resonance elastography (MRE) generates quantitative maps of the mechanical properties of biological soft tissues. However, published values obtained by brain MRE vary largely and lack detail resolution, due to either true biological effects or technical challenges. We here introduce cerebral tomoelastography in two and three dimensions for improved data consistency and detail resolution while considering aging, brain parenchymal fraction (BPF), systolic blood pressure, and body mass index (BMI). Methods: Multifrequency MRE with 2D- and 3D-tomoelastography postprocessing was applied to the brains of 31 volunteers (age range: 22-61 years) for analyzing the coefficient of variation (CV) and effects of biological factors. Eleven volunteers were rescanned after 1 day and 1 year to determine intraclass correlation coefficient (ICC) and identify possible long-term changes. Results: White matter shear wave speed (SWS) was slightly higher in 2D-MRE (1.28 ± 0.02 m/s) than 3D-MRE (1.22 ± 0.05 m/s, p < 0.0001), with less variation after 1 day in 2D (0.33 ± 0.32%) than in 3D (0.96 ± 0.66%, p = 0.004), which was also reflected in a slightly lower CV and higher ICC in 2D (1.84%, 0.97 [0.88-0.99]) than in 3D (3.89%, 0.95 [0.76-0.99]). Remarkably, 3D-MRE was sensitive to a decrease in white matter SWS within only 1 year, whereas no change in white matter volume was observed during this follow-up period. Across volunteers, stiffness correlated with age and BPF, but not with blood pressure and BMI. Conclusion: Cerebral tomoelastography provides high-resolution viscoelasticity maps with excellent consistency. Brain MRE in 2D shows less variation across volunteers in shorter scan times than 3D-MRE, while 3D-MRE appears to be more sensitive to subtle biological effects such as aging.

Cognitive functioning, cerebrospinal fluid Alzheimer's disease biomarkers and cerebral glucose metabolism in late-onset epilepsy of unknown aetiology: A prospective study

Epilepsy is increasing, being more common in older adults, with more than 20% of late-onset cases with unknown aetiology (LOEU). Although epilepsy was associated with cognitive impairment, few studies evaluated the trajectories of cognitive decline in patients with LOEU. The present study aimed at assessing biomarkers of Alzheimer's disease (AD) in patients with LOEU and evaluating their cognitive performance for 12 months. For this study, 55 patients diagnosed with LOEU and 21 controls were included. Participants underwent cognitive evaluation and cerebrospinal fluid (CSF) biomarker analysis (ß-amyloid₄₂ , tau proteins) before starting anti-seizure medication and then repeated the cognitive evaluation at the 12-month follow-up. A subgroup of LOEU patients and controls also performed ¹⁸ F-fluoro-2-deoxy-D-glucose positron emission tomography (¹⁸ F-FDG PET) before starting anti-seizure medication. At baseline, LOEU patients showed lower Mini-Mental State Examination (MMSE) score, worse cognitive performance in several domains, lower β-amyloid₄₂ and higher tau proteins CSF levels than controls. Significantly reduced glucose consumption was observed in the right posterior cingulate cortex and left praecuneus areas in LOEU patients than controls, and this finding correlated with memory impairment. In the longitudinal analysis, a significant decrease in MMSE and an increase in verbal fluency scores were found in LOEU patients. These findings evidence that LOEU patients have a significant cognitive impairment, and alteration of cerebral glucose consumption and CSF AD biomarkers than controls. Moreover, they showed a progressive global cognitive decline at follow-up, although verbal fluency was preserved. Further studies are needed to better understand the pathophysiological aspects of LOEU and its association with AD.

Dynamic changes of brain networks during standing balance control under visual conflict

Stance balance control requires a very accurate tuning and combination of visual, vestibular, and proprioceptive inputs, and conflict among these sensory systems may induce posture instability and even falls. Although there are many human mechanics and psychophysical studies for this phenomenon, the effects of sensory conflict on brain networks and its underlying neural mechanisms are still unclear. Here, we combined a rotating platform and a virtual reality (VR) headset to control the participants’ physical and visual motion states, presenting them with incongruous (sensory conflict) or congruous (normal control) physical-visual stimuli. Further, to investigate the effects of sensory conflict on stance stability and brain networks, we recorded and calculated the effective connectivity of source-level electroencephalogram (EEG) and the average velocity of the plantar center of pressure (COP) in healthy subjects (18 subjects: 10 males, 8 females). First, our results showed that sensory conflict did have a detrimental effect on stance posture control [sensor F(1, 17) = 13.34, P = 0.0019], but this effect decreases over time [window*sensor F(2, 34) = 6.72, P = 0.0035]. Humans show a marked adaptation to sensory conflict. In addition, we found that human adaptation to the sensory conflict was associated with changes in the cortical network. At the stimulus onset, congruent and incongruent stimuli had similar effects on brain networks. In both cases, there was a significant increase in information interaction centered on the frontal cortices (p < 0.05). Then, after a time window, synchronized with the restoration of stance stability under conflict, the connectivity of large brain regions, including posterior parietal, visual, somatosensory, and motor cortices, was generally lower in sensory conflict than in controls (p < 0.05). But the influence of the superior temporal lobe on other cortices was significantly increased. Overall, we speculate that a posterior parietal-centered cortical network may play a key role in integrating congruous sensory information. Furthermore, the dissociation of this network may reflect a flexible multisensory interaction strategy that is critical for human posture balance control in complex and changing environments. In addition, the superior temporal lobe may play a key role in processing conflicting sensory information.

Clinically compatible subject-specific dynamic parallel transmit pulse design for homogeneous fat saturation and water-excitation at 141657T: Proof-of-concept for 14165CEST MRI of the brain

PURPOSE

To evaluate the benefits and challenges of dynamic parallel transmit (pTx) pulses for fat saturation (FS) and water-excitation (WE), in the context of CEST MRI.

METHODS

"Universal" k_T -points (for FS) and spiral non-selective (for WE) trajectories were optimized offline for flip angle (FA) homogeneity. Routines to optimize the pulse shape online, based on the subject's fields maps, were implemented (target FA of 110°/0° for FS, 0°/5° for WE at fat/water frequencies). The pulses were inserted in a CEST sequence with a pTx readout. The different fat suppression schemes and their effects on CEST contrasts were compared in 12 volunteers at 7T.

RESULTS

With a 25%-shorter pulse duration, pTx FS largely improved the FA homogeneity (root-mean-square-error (RMSE) = 12.3° vs. 53.4° with circularly-polarized mode, at the fat frequency). However, the spectral selectivity was degraded mainly in the cerebellum and close to the sinuses (RMSE = 5.8° vs. 0.2° at the water frequency). Similarly, pTx WE showed a trade-off between FA homogeneity and spectral selectivity compared to pTx non-selective pulses (RMSE = 0.9° and 1.1° at the fat and water frequencies, vs. 4.6° and 0.5°). In the brain, CEST metrics were reduced by up to 31.9% at -3.3 ppm with pTx FS, suggesting a mitigated lipid-induced bias.

CONCLUSION

This clinically compatible implementation of dynamic pTx pulses improved the fat suppression homogeneity at 7T taking into account the subject-specific B₀ heterogeneities online. This study highlights the lipid-induced biases on the CEST z-spectrum. The results are promising for body applications where B₀ heterogeneities and fat are more substantial.

Demographic reporting across a decade of neuroimaging: a systematic review

Diversity of participants in biomedical research with respect to race, ethnicity, and biological sex is crucial, particularly given differences in disease prevalence, recovery, and survival rates between demographic groups. The objective of this systematic review was to report on the demographics of neuroimaging studies using magnetic resonance imaging (MRI). The Web of Science database was used and data collection was performed between June 2021 to November 2021; all articles were reviewed independently by at least two researchers. Articles utilizing MR data acquired in the United States, with n ≥ 10 human subjects, and published between 2010–2020 were included. Non-primary research articles and those published in journals that did not meet a quality control check were excluded. Of the 408 studies meeting inclusion criteria, approximately 77% report sex, 10% report race, and 4% report ethnicity. Demographic reporting also varied as function of disease studied, participant age range, funding, and publisher. We anticipate quantitative data on the extent, or lack, of reporting will be necessary to ensure inclusion of diverse populations in biomedical research.

Research on Top Archer’s EEG Microstates and Source Analysis in Different States

The electroencephalograph (EEG) microstate is a method used to describe the characteristics of the EEG signal through the brain scalp electrode potential’s spatial distribution; as such, it reflects the changes in the brain’s functional state. The EEGs of 13 elite archers from China’s national archery team and 13 expert archers from China’s provincial archery team were recorded under the alpha rhythm during the resting state (with closed eyes) and during archery aiming. By analyzing the differences between the EEG microstate parameters and the correlation between these parameters with archery performance, as well as by combining our findings through standardized low-resolution brain electromagnetic tomography source analysis (sLORETA), we explored the changes in the neural activity of professional archers of different levels, under different states. The results of the resting state study demonstrated that the duration, occurrence, and coverage in microstate D of elite archers were significantly higher than those of expert archers and that their other microstates had the greatest probability of transferring to microstate D. During the archery aiming state, the average transition probability of the other microstates transferring to microstate in the left temporal region was the highest observed in the two groups of archers. Moreover, there was a significant negative correlation between the duration and coverage of microstates in the frontal region of elite archers and their archery performance. Our findings indicate that elite archers are more active in the dorsal attention system and demonstrate a higher neural efficiency during the resting state. When aiming, professional archers experience an activation of brain regions associated with archery by suppressing brain regions unrelated to archery tasks. These findings provide a novel theoretical basis for the study of EEG microstate dynamics in archery and related cognitive motor tasks, particularly from the perspective of the subject’s mental state.

Hypothalamic microstructure and function are related to body mass, but not mental or cognitive abilities across the adult lifespan

Physical, mental, and cognitive resources are essential for healthy aging. Aging impacts on the structural integrity of various brain regions, including the hippocampus. Even though recent rodent studies hint towards a critical role of the hypothalamus, there is limited evidence on functional consequences of age-related changes of this region in humans. Given its central role in metabolic regulation and affective processing and its connections to the hippocampus, it is plausible that hypothalamic integrity and connectivity are associated with functional age-related decline. We used data of n = 369 participants (18-88 years) from the Cambridge Centre for Ageing and Neuroscience repository to determine functional impacts of potential changes in hypothalamic microstructure across the lifespan. First, we identified age-related changes in microstructure as a function of physical, mental, and cognitive health and compared those findings to changes in hippocampal microstructure. Second, we investigated the relationship of hypothalamic microstructure and resting-state functional connectivity and related those changes to age as well as physical health. Our results showed that hypothalamic microstructure is not affected by depressive symptoms (mental health), cognitive performance (cognitive health), and comparatively stable across the lifespan, but affected by body mass (physical health). Furthermore, body mass changes connectivity to limbic regions including the hippocampus, amygdala, and nucleus accumbens, suggesting functional alterations in the metabolic and reward systems. Our results demonstrate that hypothalamic structure and function are affected by body mass, focused on neural density and dispersion, but not inflammation. Still, observed effect sizes were small, encouraging detailed investigations of individual hypothalamic subunits.

The quest for multiscale brain modeling

Addressing the multiscale organization of the brain, which is fundamental to the dynamic repertoire of the organ, remains challenging. In principle, it should be possible to model neurons and synapses in detail and then connect them into large neuronal assemblies to explain the relationship between microscopic phenomena, large-scale brain functions, and behavior. It is more difficult to infer neuronal functions from ensemble measurements such as those currently obtained with brain activity recordings. In this article we consider theories and strategies for combining bottom-up models, generated from principles of neuronal biophysics, with top-down models based on ensemble representations of network activity and on functional principles. These integrative approaches are hoped to provide effective multiscale simulations in virtual brains and neurorobots, and pave the way to future applications in medicine and information technologies.

Auditory driven gamma synchrony is associated with cortical thickness in widespread cortical areas

OBJECTIVE

Gamma synchrony is a fundamental functional property of the cerebral cortex, impaired in multiple neuropsychiatric conditions (i.e. schizophrenia, Alzheimer's disease, stroke etc.). Auditory stimulation in the gamma range allows to drive gamma synchrony of the entire cortical mantle and to estimate the efficiency of the mechanisms sustaining it. As gamma synchrony depends strongly on the interplay between parvalbumin-positive interneurons and pyramidal neurons, we hypothesize an association between cortical thickness and gamma synchrony. To test this hypothesis, we employed a combined magnetoencephalography (MEG) - Magnetic Resonance Imaging (MRI) study.

METHODS

Cortical thickness was estimated from anatomical MRI scans. MEG measurements related to exposure of 40 Hz amplitude modulated tones were projected onto the cortical surface. Two measures of cortical synchrony were considered: (a) inter-trial phase consistency at 40 Hz, providing a vertex-wise estimation of gamma synchronization, and (b) phase-locking values between primary auditory cortices and whole cortical mantle, providing a measure of long-range cortical synchrony. A correlation between cortical thickness and synchronization measures was then calculated for 72 MRI-MEG scans.

RESULTS

Both inter-trial phase consistency and phase locking values showed a significant positive correlation with cortical thickness. For inter-trial phase consistency, clusters of strong associations were found in the temporal and frontal lobes, especially in the bilateral auditory and pre-motor cortices. Higher phase-locking values corresponded to higher cortical thickness in the frontal, temporal, occipital and parietal lobes.

DISCUSSION AND CONCLUSIONS

In healthy subjects, a thicker cortex corresponds to higher gamma synchrony and connectivity in the primary auditory cortex and beyond, likely reflecting underlying cell density involved in gamma circuitries. This result hints towards an involvement of gamma synchrony together with underlying brain structure in brain areas for higher order cognitive functions. This study contributes to the understanding of inherent cortical functional and structural brain properties, which might in turn constitute the basis for the definition of useful biomarkers in patients showing aberrant gamma synchronization.

18F-FDG PET, cognitive functioning, and CSF biomarkers in patients with obstructive sleep apnoea before and after continuous positive airway pressure treatment

Introduction

Dysregulation of cerebral glucose consumption, alterations in cerebrospinal fluid (CSF) biomarkers, and cognitive impairment have been reported in patients with obstructive sleep apnoea (OSA). On these bases, OSA has been considered a risk factor for Alzheimer’s disease (AD). This study aimed to measure cognitive performance, CSF biomarkers, and cerebral glucose consumption in OSA patients and to evaluate the effects of continuous positive airway pressure (CPAP) treatment on these biomarkers over a 12-month period.

Methods

Thirty-four OSA patients and 34 controls underwent ¹⁸F-fluoro-2-deoxy-d-glucose positron emission tomography (¹⁸F-FDG PET), cognitive evaluation, and CSF analysis. A subgroup of 12 OSA patients treated with beneficial CPAP and performing the 12-month follow-up was included in the longitudinal analysis, and cognitive evaluation and ¹⁸F-FDG PET were repeated.

Results

Significantly reduced glucose consumption was observed in the bilateral praecuneus, posterior cingulate cortex, and frontal areas in OSA patients than controls. At baseline, OSA patients also showed lower β-amyloid₄₂ and higher phosphorylated-tau CSF levels than controls. Increased total tau and phosphorylated tau levels correlated with a reduction in brain glucose consumption in a cluster of different brain areas. In the longitudinal analysis, OSA patients showed an improvement in cognition and a global increase in cerebral ¹⁸F-FDG uptake.

Conclusions

Cognitive impairment, reduced cerebral glucose consumption, and alterations in CSF biomarkers were observed in OSA patients, which may reinforce the hypothesis of AD neurodegenerative processes triggered by OSA. Notably, cognition and brain glucose consumption improved after beneficial CPAP treatment. Further studies are needed to evaluate the long-term effects of CPAP treatment on these AD biomarkers.

Nocturnal Hypoxia and Sleep Fragmentation May Drive Neurodegenerative Processes: The Compared Effects of Obstructive Sleep Apnea Syndrome and Periodic Limb Movement Disorder on Alzheimer’s Disease Biomarkers

Background: Sleep disorders may cause dysregulation of cerebral glucose metabolism and synaptic functions, as well as alterations in cerebrospinal fluid (CSF) biomarker levels. Objective: This study aimed at measuring sleep, CSF Alzheimer’s disease (AD) biomarkers, and cerebral glucose consumption in patients with obstructive sleep apnea syndrome (OSAS) and patients with periodic limb movement disorder (PLMD), compared to controls. Methods: OSAS and PLMD patients underwent 18F-fluoro-2-deoxy-D-glucose positron emission tomography (18F-FDG PET), polysomnographic monitoring, and lumbar puncture to quantify CSF levels of amyloid-β42 (Aβ42), total tau, and phosphorylated tau. All patients were compared to controls, who were not affected by sleep or neurodegenerative disorders. Results: Twenty OSAS patients, 12 PLMD patients, and 15 controls were included. Sleep quality and sleep structure were altered in both OSAS and PLMD patients when compared to controls. OSAS and PLMD patients showed lower CSF Aβ42 levels than controls. OSAS patients showed a significant increase in glucose uptake in a wide cluster of temporal-frontal areas and cerebellum, as well as a reduced glucose consumption in temporal-parietal regions compared to controls. PLMD patients showed increased brain glucose consumption in the left parahippocampal gyrus and left caudate than controls. Conclusion: Sleep dysregulation and nocturnal hypoxia present in OSAS patients, more than sleep fragmentation in PLMD patients, were associated with the alteration in CSF and 18F-FDG PET AD biomarkers, namely reduction of CSF Aβ42 levels and cerebral glucose metabolism dysregulation mainly in temporal areas, thus highlighting the possible role of sleep disorders in driving neurodegenerative processes typical of AD pathology.

Test-retest reliability of multi-parametric maps (MPM) of brain microstructure

Multiparameter mapping (MPM) is a quantitative MRI protocol that is promising for studying microstructural brain changes in vivo with high specificity. Reliability values are an important prior knowledge for efficient study design and facilitating replicable findings in development, aging and neuroplasticity research. To explore longitudinal reliability of MPM we acquired the protocol in 31 healthy young subjects twice over a rescan interval of 4 weeks. We assessed the within-subject coefficient of variation (WCV), the between-subject coefficient of variation (BCV), and the intraclass correlation coefficient (ICC). Using these metrics, we investigated the reliability of (semi-) quantitative magnetization transfer saturation (MT_sat), proton density (PD), transversal relaxation (R2*) and longitudinal relaxation (R1). To increase relevance for explorative studies in development and training-induced plasticity, we assess reliability both on local voxel- as well as ROI-level. Finally, we disentangle contributions and interplay of within- and between-subject variability to ICC and assess the optimal degree of spatial smoothing applied to the data. We reveal evidence that voxelwise ICC reliability of MPMs is moderate to good with median values in cortex (subcortical GM): MT: 0.789 (0.447) PD: 0.553 (0.264) R1: 0.555 (0.369) R2*: 0.624 (0.477). The Gaussian smoothing kernel of 2 to 4 mm FWHM resulted in optimal reproducibility. We discuss these findings in the context of longitudinal intervention studies and the application to research designs in neuroimaging field.

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

Purpose

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

Methods

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

Results

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

Conclusions

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

"It's a beer!": Brain functional hyperconnectivity during processing of alcohol-related images in young binge drinkers

Alcohol attentional bias has been pointed as a major marker of alcohol misuse. Recent evidence has revealed that brain functional connectivity (FC) may be a valuable index of the brain networks' integrity in young binge drinkers (BDs). However, there is no study to date examining the FC networks linked to the processing of alcohol-related images in this population. The present study aimed to explore the FC signatures underlying alcohol attention bias in young BDs. Thus, electroencephalographic (EEG) activity was recorded in 54 college students (55.5% females; 27 non/low-drinkers and 27 BDs) while performing a visual alcohol cue-reactivity task. We evaluated whole-brain FC profiles during the processing of alcoholic and non-alcoholic cues, as well as their potential relationship with craving and severity of alcohol use. Results showed that, at the behavioural level, BDs rated alcohol-related images as more pleasant/attractive than non/low-drinkers. Furthermore, at the electrophysiological level, BDs exhibited increased beta-band FC-particularly in the fronto-parieto-occipital network-when processing alcoholic cues. Conversely, they displayed reduced theta-band FC relatively to non/low-drinkers for non-alcoholic images. These hyper-/hypo-connectivity patterns were associated with higher alcohol craving levels. Findings are congruent with previous neurofunctional studies reporting an attentional bias towards alcohol-related information in BDs. These results may have important clinical implications as this neural reactivity to alcoholic cues may contribute to the maintenance and/or escalation of the drinking pattern. Finally, the present study constitutes the first evidence showing that FC networks may be a sensitive indicator to alcohol attentional bias in BDs.

Post-concussive mTBI in Student Athletes: MRI Features and Machine Learning

Purpose: To determine and characterize the radiomics features from structural MRI (MPRAGE) and Diffusion Tensor Imaging (DTI) associated with the presence of mild traumatic brain injuries on student athletes with post-concussive syndrome (PCS).

Material and Methods: 122 student athletes (65 M, 57 F), median (IQR) age 18.8 (15–20) years, with a mixed level of play and sports activities, with a known history of concussion and clinical PCS, and 27 (15 M, 12 F), median (IQR) age 20 (19, 21) years, concussion free athlete subjects were MRI imaged in a clinical MR machine. MPRAGE and DTI-FA and DTI-ADC images were used to extract radiomic features from white and gray matter regions within the entire brain (2 ROI) and the eight main lobes of the brain (16 ROI) for a total of 18 analyzed regions. Radiomic features were divided into five different data sets used to train and cross-validate five different filter-based Support Vector Machines. The top selected features of the top model were described. Furthermore, the test predictions of the top four models were ensembled into a single average prediction. The average prediction was evaluated for the association to the number of concussions and time from injury.

Results: Ninety-one PCS subjects passed inclusion criteria (91 Cases, 27 controls). The average prediction of the top four models had a sensitivity of 0.80, 95% CI: [0.71, 0.88] and specificity of 0.74 95%CI [0.54, 0.89] for distinguishing subjects from controls. The white matter features were strongly associated with mTBI, while the whole-brain analysis of gray matter showed the worst association. The predictive index was significantly associated with the number of concussions (p < 0.0001) and associated with the time from injury (p < 0.01).

Conclusion: MRI Radiomic features are associated with a history of mTBI and they were successfully used to build a predictive machine learning model for mTBI for subjects with PCS associated with a history of one or more concussions.

mGluR 5 and GABA A receptor‐specific parametric PET atlas construction— PET / MR data processing pipeline, validation, and application

The glutamate and γ‐aminobutyric acid neuroreceptor subtypes mGluR₅ and GABA_A are hypothesized to be involved in the development of a variety of psychiatric diseases. However, detailed information relating to their in vivo distribution is generally unavailable. Maps of such distributions could potentially aid clinical studies by providing a reference for the normal distribution of neuroreceptors and may also be useful as covariates in advanced functional magnetic resonance imaging (MR) studies. In this study, we propose a comprehensive processing pipeline for the construction of standard space, in vivo distributions of non‐displaceable binding potential (BP_ND), and total distribution volume (V_T) based on simultaneously acquired bolus‐infusion positron emission tomography (PET) and MR data. The pipeline was applied to [¹¹C]ABP688‐PET/MR (13 healthy male non‐smokers, 26.6 ± 7.0 years) and [¹¹C]Flumazenil‐PET/MR (10 healthy males, 25.8 ± 3.0 years) data. Activity concentration templates, as well as V_T and BP_ND atlases of mGluR₅ and GABA_A, were generated from these data. The maps were validated by assessing the percent error δ from warped space to native space in a selection of brain regions. We verified that the average δ_ABP = 3.0 ± 1.0% and δ_FMZ = 3.8 ± 1.4% were lower than the expected variabilities σ of the tracers (σ_ABP = 4.0%–16.0%, σ_FMZ = 3.9%–9.5%). An evaluation of PET‐to‐PET registrations based on the new maps showed higher registration accuracy compared to registrations based on the commonly used [¹⁵O]H₂O‐template distributed with SPM12. Thus, we conclude that the resulting maps can be used for further research and the proposed pipeline is a viable tool for the construction of standardized PET data distributions.

Resting state network connectivity is attenuated by fMRI acoustic noise

INTRODUCTION

During the past decades there has been an increasing interest in tracking brain network fluctuations in health and disease by means of resting state functional magnetic resonance imaging (rs-fMRI). Rs-fMRI however does not provide the ideal environmental setting, as participants are continuously exposed to noise generated by MRI coils during acquisition of Echo Planar Imaging (EPI). We investigated the effect of EPI noise on resting state activity and connectivity using magnetoencephalography (MEG), by reproducing the acoustic characteristics of rs-fMRI environment during the recordings. As compared to fMRI, MEG has little sensitivity to brain activity generated in deep brain structures, but has the advantage to capture both the dynamic of cortical magnetic oscillations with high temporal resolution and the slow magnetic fluctuations highly correlated with BOLD signal.

METHODS

Thirty healthy subjects were enrolled in a counterbalanced design study including three conditions: a) silent resting state (Silence), b) resting state upon EPI noise (fMRI), and c) resting state upon white noise (White). White noise was employed to test the specificity of fMRI noise effect. The amplitude envelope correlation (AEC) in alpha band measured the connectivity of seven Resting State Networks (RSN) of interest (default mode network, dorsal attention network, language, left and right auditory and left and right sensory-motor). Vigilance dynamic was estimated from power spectral activity.

RESULTS

fMRI and White acoustic noise consistently reduced connectivity of cortical networks. The effects were widespread, but noise and network specificities were also present. For fMRI noise, decreased connectivity was found in the right auditory and sensory-motor networks. Progressive increase of slow theta-delta activity related to drowsiness was found in all conditions, but was significantly higher for fMRI . Theta-delta significantly and positively correlated with variations of cortical connectivity.

DISCUSSION

rs-fMRI connectivity is biased by unavoidable environmental factors during scanning, which warrant more careful control and improved experimental designs. MEG is free from acoustic noise and allows a sensitive estimation of resting state connectivity in cortical areas. Although underutilized, MEG could overcome issues related to noise during fMRI, in particular when investigation of motor and auditory networks is needed.

Population-specific brain [18F]-FDG PET templates of Chinese subjects for statistical parametric mapping

Statistical Parametric Mapping (SPM) is a computational approach for analysing functional brain images like Positron Emission Tomography (PET). When performing SPM analysis for different patient populations, brain PET template images representing population-specific brain morphometry and metabolism features are helpful. However, most currently available brain PET templates were constructed using the Caucasian data. To enrich the family of publicly available brain PET templates, we created Chinese-specific template images based on 116 [¹⁸F]-fluorodeoxyglucose ([¹⁸F]-FDG) PET images of normal participants. These images were warped into a common averaged space, in which the mean and standard deviation templates were both computed. We also developed the SPM analysis programmes to facilitate easy use of the templates. Our templates were validated through the SPM analysis of Alzheimer’s and Parkinson’s patient images. The resultant SPM t-maps accurately depicted the disease-related brain regions with abnormal [¹⁸F]-FDG uptake, proving the templates’ effectiveness in brain function impairment analysis.

Measurement(s)	brain metabolism measurement
Technology Type(s)	FDG-Positron Emission Tomography
Factor Type(s)	age • sex
Sample Characteristic - Organism	Homo sapiens
Sample Characteristic - Location	China

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.16382418

Novel microscope-based visual display and nasopharyngeal registration for auditory brainstem implantation: a feasibility study in an ex vivo model

Purpose

An auditory brainstem implant (ABI) represents an alternative for patients with profound hearing loss who are constrained from receiving a cochlear implant. The positioning of the ABI electrode influences the patient’s auditory capacity and, therefore, quality of life and is challenging even with available intraoperative electrophysiological monitoring. This work aims to provide and assess the feasibility of visual-spatial assistance for ABI positioning.

Methods

The pose of the forceps instrument that grasps the electrode was electromagnetically navigated and interactively projected in the eyepieces of a surgical microscope with respect to a target point. Intraoperative navigation was established with an experimental technique for automated nasopharyngeal patient registration. Two ABI procedures were completed in a human specimen head.

Results

An intraoperative usability study demonstrated lower localization error when using the proposed visual display versus standard cross-sectional views. The postoperative evaluations of the preclinical study showed that the center of the electrode was misplaced to the planned position by 1.58 mm and 3.16 mm for the left and the right ear procedure, respectively.

Conclusion

The results indicate the potential to enhance intraoperative feedback during ABI positioning with the presented system. Further improvements consider estimating the pose of the electrode itself to allow for better orientation during placement.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11548-021-02514-x.

One Year Follow-Up of Taste-Related Reward Associations with Weight Loss Suggests a Critical Time to Mitigate Weight Regain Following Bariatric Surgery

Background: Weight regain is a concerning issue in bariatric patients. We previously demonstrated that taste-related reward processing was associated with six-month weight loss outcomes following Roux-en-Y gastric bypass (RYGB) but not vertical sleeve gastrectomy (VSG). Here, we assessed whether these taste factors persisted in predicting weight loss, and weight regain, at one year post-surgery. Methods: Adult women enrolled in a longitudinal study of taste preferences following bariatric surgery completed behavioral and neuroimaging assessments at one year post-surgery. Results: RYGB produced better weight loss relative to VSG, with weight regain and greater weight loss variability observed from six months to one year post-VSG. Changes in liking for high fat at 2 weeks post-surgery from baseline remained a predictor of weight loss in RYGB, but other predictors did not persist. Average liking ratings rebounded to baseline and higher self-reported food cravings and dietary disinhibition correlated with poorer weight loss at one year post-surgery. Conclusion: Initial anatomical and metabolic changes resulting from RYGB that reset neural processing of reward stimuli in the mesolimbic pathway appear to be temporary and may be contingent upon post-operative eating behaviors returning to preoperative obesogenic tendencies. Six months post-surgery may be a critical window for implementing interventions to mitigate weight gain.

Reduced Effective Connectivity in the Motor Cortex in Parkinson's Disease

Fast rhythms excess is a hallmark of Parkinson’s Disease (PD). To implement innovative, non-pharmacological, neurostimulation interventions to restore cortical-cortical interactions, we need to understand the neurophysiological mechanisms underlying these phenomena. Here, we investigated effective connectivity on source-level resting-state electroencephalography (EEG) signals in 15 PD participants and 10 healthy controls. First, we fitted multivariate auto-regressive models to the EEG source waveforms. Second, we estimated causal connections using Granger Causality, which provide information on connections’ strength and directionality. Lastly, we sought significant differences connectivity patterns between the two populations characterizing the network graph features—i.e., global efficiency and node strength. Causal brain networks in PD show overall poorer and weaker connections compared to controls quantified as a reduction of global efficiency. Motor areas appear almost isolated, with a strongly impoverished information flow particularly from parietal and occipital cortices. This striking isolation of motor areas may reflect an impaired sensory-motor integration in PD. The identification of defective nodes/edges in PD network may be a biomarker of disease and a potential target for future interventional trials.

Associations of observed preschool performance monitoring with brain functional connectivity in adolescence

Monitoring one's performance helps detect errors and adapt to prevent future mistakes. However, elevated performance monitoring is associated with increased checking behaviors and perfectionism and is characteristic of multiple psychiatric disorders. Understanding how heightened performance monitoring in early childhood relates to subsequent brain connectivity may elucidate mechanistic risk factors that influence brain and psychiatric outcomes. The aim of this study was to examine the association between performance monitoring in preschool-aged children and functional connectivity during adolescence. In the current prospective longitudinal study, we performed seed-based functional connectivity analysis using a dorsal anterior cingulate cortex (dACC) seed to assess brain-behavior relationships between observationally coded performance monitoring in preschool-aged children and adolescent functional connectivity (n = 79). We also utilized enrichment analysis to investigate network-level connectome-wide associations. Seed-based analysis revealed negative correlations between preschool performance monitoring and adolescent fc between dACC and orbitofrontal and dorsolateral prefrontal cortex while a positive correlation was observed between dACC-occipital cortex connectivity. Enrichment analysis revealed a negative correlation between preschool performance monitoring and connectivity between motor (MOT) - cingulo-opercular (CO) and salience (SN) - Reward (REW) and a positive correlation with MOT-DMN, and cerebellum (CB) - motor connectivity. Elevated performance monitoring in early childhood is associated with functional connectivity during adolescence in regions and networks associated with cognitive control, sensorimotor processing and cortico-striatal-thalamic-cortico (CTSC) aberrations. These regions and networks are implicated in psychiatric disorders characterized by elevated performance monitoring. Findings shed light on a mechanistic risk factor in early childhood with long-term associations with neural functioning.

The BigBrainWarp toolbox for integration of BigBrain 3D histology with multimodal neuroimaging

Neuroimaging stands to benefit from emerging ultrahigh-resolution 3D histological atlases of the human brain; the first of which is 'BigBrain'. Here, we review recent methodological advances for the integration of BigBrain with multi-modal neuroimaging and introduce a toolbox, 'BigBrainWarp', that combines these developments. The aim of BigBrainWarp is to simplify workflows and support the adoption of best practices. This is accomplished with a simple wrapper function that allows users to easily map data between BigBrain and standard MRI spaces. The function automatically pulls specialised transformation procedures, based on ongoing research from a wide collaborative network of researchers. Additionally, the toolbox improves accessibility of histological information through dissemination of ready-to-use cytoarchitectural features. Finally, we demonstrate the utility of BigBrainWarp with three tutorials and discuss the potential of the toolbox to support multi-scale investigations of brain organisation.

Pandora: 4-D White Matter Bundle Population-Based Atlases Derived from Diffusion MRI Fiber Tractography

Brain atlases have proven to be valuable neuroscience tools for localizing regions of interest and performing statistical inferences on populations. Although many human brain atlases exist, most do not contain information about white matter structures, often neglecting them completely or labelling all white matter as a single homogenous substrate. While few white matter atlases do exist based on diffusion MRI fiber tractography, they are often limited to descriptions of white matter as spatially separate "regions" rather than as white matter "bundles" or fascicles, which are well-known to overlap throughout the brain. Additional limitations include small sample sizes, few white matter pathways, and the use of outdated diffusion models and techniques. Here, we present a new population-based collection of white matter atlases represented in both volumetric and surface coordinates in a standard space. These atlases are based on 2443 subjects, and include 216 white matter bundles derived from 6 different automated state-of-the-art tractography techniques. This atlas is freely available and will be a useful resource for parcellation and segmentation.