Reliability of functional magnetic resonance imaging activation during working memory in a multi-site study: analysis from the North American Prodrome Longitudinal Study

Identifying subgroups of urge suppression in Obsessive-Compulsive Disorder using machine learning

Obsessive-compulsive disorder (OCD) is phenomenologically heterogeneous. While predominant models suggest fear and harm prevention drive compulsions, many patients also experience uncomfortable sensory-based urges ("sensory phenomena") that may be associated with heightened interoceptive sensitivity. Using an urge-to-blink eyeblink suppression paradigm to model sensory-based urges, we previously found that OCD patients as a group had more eyeblink suppression failures and greater activation of sensorimotor-interoceptive regions than controls. However, conventional approaches assuming OCD homogeneity may obscure important within-group variability, impeding precision treatment development. This study investigated the heterogeneity of urge suppression failure in OCD and examined relationships with clinical characteristics and neural activation. Eighty-two patients with OCD and 38 controls underwent an fMRI task presenting 60-s blocks of eyeblink suppression alternating with free-blinking blocks. Latent profile analysis identified OCD subgroups based on number of erroneous blinks during suppression. Subgroups were compared on behavior, clinical characteristics, and brain activation during task. Three patient subgroups were identified. Despite similar overall OCD severity, the subgroup with the most erroneous eyeblinks had the highest sensory phenomena severity, interoceptive sensitivity, and subjective urge intensity. Compared to other subgroups, this subgroup exhibited more neural activity in somatosensory and interoceptive regions during the early phase (first 30 s) of blink suppression and reduced activity in the middle frontal gyrus during the late phase (second 30 s) as the suppression period elapsed. Heterogeneity of urge suppression in OCD was associated with clinical characteristics and brain function. Our results reveal potential treatment targets that could inform personalized medicine.

Neuropsychological outcome after frontal surgery for pediatric-onset epilepsy with focal cortical dysplasia in adolescent and young adult

OBJECTIVE

We investigated neuropsychological outcome in patients with pharmacoresistant pediatric-onset epilepsy caused by focal cortical dysplasia (FCD), who underwent frontal lobe resection during adolescence and young adulthood.

METHODS

Twenty-seven patients were studied, comprising 15 patients who underwent language-dominant side resection (LDR) and 12 patients who had languagenondominant side resection (n-LDR). We evaluated intelligence (language function, arithmetic ability, working memory, processing speed, visuo-spatial reasoning), executive function, and memory in these patients before and two years after resection surgery. We analyzed the relationship between neuropsychological outcome and resected regions (side of language dominance and location).

RESULTS

Although 75% of the patients showed improvement or no change in individual neuropsychological tests after surgical intervention, 25% showed decline. The cognitive tests that showed improvement or decline varied between LDR and n-LDR. In patients who had LDR, decline was observed in Vocabulary and Phonemic Fluency (both 5/15 patients), especially after resection of ventrolateral frontal cortex, and improvement was observed in WCST-Category (7/14 patients), Block Design (6/15 patients), Digit Symbol (4/15 patients), and Delayed Recall (3/9 patients). In patients who underwent n-LDR, improvement was observed in Vocabulary (3/12 patients), but decline was observed in Block Design (2/9 patients), and WCST-Category (2/9 patients) after resection of dorsolateral frontal cortex; and Arithmetic (3/10 patients) declined after resection of dorsolateral frontal cortex or ventrolateral frontal cortex. General Memory (3/8 patients), Visual Memory (3/8 patients), Delayed Recall (3/8 patients), Verbal Memory (2/9 patients), and Digit Symbol (3/12 patients) also declined after n-LDR.

CONCLUSION

Postoperative changes in cognitive function varied depending on the location and side of the resection. For precise presurgical prediction of neuropsychological outcome after surgery, further prospective studies are needed to accumulate data of cognitive changes in relation to the resection site.

Somatotopic disruption of the functional connectivity of the primary sensorimotor cortex in complex regional pain syndrome type 1

In complex regional pain syndrome (CRPS), the representation area of the affected limb in the primary sensorimotor cortex (SM1) reacts abnormally during sensory stimulation and motor actions. We recorded 3T functional magnetic resonance imaging resting-state data from 17 upper-limb CRPS type 1 patients and 19 healthy control subjects to identify alterations of patients' SM1 function during spontaneous pain and to find out how the spatial distribution of these alterations were related to peripheral symptoms. Seed-based correlations and independent component analyses indicated that patients' upper-limb SM1 representation areas display (i) reduced interhemispheric connectivity, associated with the combined effect of intensity and spatial extent of limb pain, (ii) increased connectivity with the right anterior insula that positively correlated with the duration of CRPS, (iii) increased connectivity with periaqueductal gray matter, and (iv) disengagement from the other parts of the SM1 network. These findings, now reported for the first time in CRPS, parallel the alterations found in patients suffering from other chronic pain conditions or from limb denervation; they also agree with findings in healthy persons who are exposed to experimental pain or have used their limbs asymmetrically. Our results suggest that CRPS is associated with a sustained and somatotopically specific alteration of SM1 function, that has correspondence to the spatial distribution of the peripheral manifestations and to the duration of the syndrome.

Confounding Effects on the Performance of Machine Learning Analysis of Static Functional Connectivity Computed from rs-fMRI Multi-site Data

Resting-state functional magnetic resonance imaging (rs-fMRI) is a non-invasive imaging technique widely used in neuroscience to understand the functional connectivity of the human brain. While rs-fMRI multi-site data can help to understand the inner working of the brain, the data acquisition and processing of this data has many challenges. One of the challenges is the variability of the data associated with different acquisitions sites, and different MRI machines vendors. Other factors such as population heterogeneity among different sites, with variables such as age and gender of the subjects, must also be considered. Given that most of the machine-learning models are developed using these rs-fMRI multi-site data sets, the intrinsic confounding effects can adversely affect the generalizability and reliability of these computational methods, as well as the imposition of upper limits on the classification scores. This work aims to identify the phenotypic and imaging variables producing the confounding effects, as well as to control these effects. Our goal is to maximize the classification scores obtained from the machine learning analysis of the Autism Brain Imaging Data Exchange (ABIDE) rs-fMRI multi-site data. To achieve this goal, we propose novel methods of stratification to produce homogeneous sub-samples of the 17 ABIDE sites, as well as the generation of new features from the static functional connectivity values, using multiple linear regression models, ComBat harmonization models, and normalization methods. The main results obtained with our statistical models and methods are an accuracy of 76.4%, sensitivity of 82.9%, and specificity of 77.0%, which are 8.8%, 20.5%, and 7.5% above the baseline classification scores obtained from the machine learning analysis of the static functional connectivity computed from the ABIDE rs-fMRI multi-site data.

Relationships between interoceptive sensibility and resting-state functional connectivity of the insula in obsessive-compulsive disorder

Patients with obsessive-compulsive disorder (OCD) exhibit abnormality in their subjective perception of internal sensation, a process known as interoceptive sensibility (IS), as well as altered functioning of the insula, a key neural structure for interoception. We investigated the multivariate structure of IS in 77 OCD patients and 53 controls and examined associations of IS with resting-state functional connectivity (FC) of the insula within the OCD group. For each group, principal component analysis was performed on 8 subscales of the Multidimensional Assessment of Interoceptive Awareness assessing putatively "adaptive" and "maladaptive" aspects of IS. Associations between IS components and insula FC in the OCD group were evaluated using seed regions placed in each of 3 subdivisions of the insula (posterior, anterior dorsal, and anterior ventral). Behaviorally, controls showed a 2-component solution broadly categorized into "adaptive" and "maladaptive" IS, while OCD patients exhibited a 3-component solution. The general tendency to notice or be aware of sensation loaded onto an "adaptive" IS component in controls but loaded onto both "adaptive" and "maladaptive" IS components in OCD. Within OCD, insula FC was differentially associated with distinct aspects of IS, identifying network connections that could serve as future targets for the modulation of IS in OCD.

A longitudinal multi-scanner multimodal human neuroimaging dataset

Human neuroimaging has led to an overwhelming amount of research into brain function in healthy and clinical populations. However, a better appreciation of the limitations of small sample studies has led to an increased number of multi-site, multi-scanner protocols to understand human brain function. As part of a multi-site project examining social cognition in schizophrenia, a group of "travelling human phantoms" had structural T1, diffusion, and resting-state functional MRIs obtained annually at each of three sites. Scan protocols were carefully harmonized across sites prior to the study. Due to scanner upgrades at each site (all sites acquired PRISMA MRIs during the study) and one participant being replaced, the end result was 30 MRI scans across 4 people, 6 MRIs, and 4 years. This dataset includes multiple neuroimaging modalities and repeated scans across six MRIs. It can be used to evaluate differences across scanners, consistency of pipeline outputs, or test multi-scanner harmonization approaches.

The instability of functional connectomes across the first year of life

The uniqueness and stability of the adolescent and adult functional connectome has been demonstrated to be high (80-95 % identification) using connectome-based identification (ID) or "fingerprinting". However, it is unclear to what extent individuals exhibit similar distinctiveness and stability in infancy, a developmental period of rapid and unparalleled brain development. In this study, we examined connectome-based ID rates within and across the first year of life using a longitudinal infant dataset at 1.5 month and 9 months of age. We also calculated the test-retest reliability of individual connections across the first year of life using the intraclass correlation coefficient (ICC). Overall, we found substantially lower infant ID rates than have been reported in adult and adolescent populations. Within-session ID rates were moderate and significant (ID = 48.94-70.83 %). Between-session ID rates were very low and not significant, with task-to-task connectomes resulting in the highest between-session ID rate (ID = 26.6 %). Similarly, average edge-level test-retest reliability was higher within-session than between-session (mean within-session ICC = 0.17, mean between-session ICC = 0.10). These findings suggest a lack of uniqueness and stability in functional connectomes across the first year of life consistent with the unparalleled changes in brain functional organization during this critical period.

The neural and molecular basis of working memory function in psychosis: a multimodal PET-fMRI study

Working memory (WM) deficits predict clinical and functional outcomes in schizophrenia but are poorly understood and unaddressed by existing treatments. WM encoding and WM retrieval have not been investigated in schizophrenia without the confounds of illness chronicity or the use of antipsychotics and illicit substances. Moreover, it is unclear if WM deficits may be linked to cannabinoid 1 receptor dysfunction in schizophrenia. Sixty-six volunteers (35 controls, 31 drug-free patients with diagnoses of schizophrenia or schizoaffective disorder) completed the Sternberg Item-Recognition paradigm during an fMRI scan. Neural activation during WM encoding and WM retrieval was indexed using the blood-oxygen-level-dependent hemodynamic response. A subset of volunteers (20 controls, 20 drug-free patients) underwent a dynamic PET scan to measure [11C] MePPEP distribution volume (ml/cm3) to index CB1R availability. In a whole-brain analysis, there was a significant main effect of group on task-related BOLD responses in the superior parietal lobule during WM encoding, and the bilateral hippocampus during WM retrieval. Region of interest analyses in volunteers who had PET/fMRI indicated that there was a significant main effect of group on task-related BOLD responses in the right hippocampus, left DLPFC, left ACC during encoding; and in the bilateral hippocampus, striatum, ACC and right DLPFC during retrieval. Striatal CB1R availability was positively associated with mean striatal activation during WM retrieval in male patients (R = 0.5, p = 0.02) but not male controls (R = -0.20, p = 0.53), and this was significantly different between groups, Z = -2.20, p = 0.02. Striatal CB1R may contribute to the pathophysiology of WM deficits in male patients and have implications for drug development in schizophrenia.

Cross-paradigm connectivity: reliability, stability, and utility

While functional neuroimaging studies typically focus on a particular paradigm to investigate network connectivity, the human brain appears to possess an intrinsic "trait" architecture that is independent of any given paradigm. We have previously proposed the use of "cross-paradigm connectivity (CPC)" to quantify shared connectivity patterns across multiple paradigms and have demonstrated the utility of such measures in clinical studies. Here, using generalizability theory and connectome fingerprinting, we examined the reliability, stability, and individual identifiability of CPC in a group of highly-sampled healthy traveling subjects who received fMRI scans with a battery of five paradigms across multiple sites and days. Compared with single-paradigm connectivity matrices, the CPC matrices showed higher reliability in connectivity diversity, lower reliability in connectivity strength, higher stability, and higher individual identification accuracy. All of these assessments increased as a function of number of paradigms included in the CPC analysis. In comparisons involving different paradigm combinations and different brain atlases, we observed significantly higher reliability, stability, and identifiability for CPC matrices constructed from task-only data (versus those from both task and rest data), and higher identifiability but lower stability for CPC matrices constructed from the Power atlas (versus those from the AAL atlas). Moreover, we showed that multi-paradigm CPC matrices likely reflect the brain's "trait" structure that cannot be fully achieved from single-paradigm data, even with multiple runs. The present results provide evidence for the feasibility and utility of CPC in the study of functional "trait" networks and offer some methodological implications for future CPC studies.

Comparison of Four fMRI Paradigms Probing Emotion Processing

Previous fMRI research has applied a variety of tasks to examine brain activity underlying emotion processing. While task characteristics are known to have a substantial influence on the elicited activations, direct comparisons of tasks that could guide study planning are scarce. We aimed to provide a comparison of four common emotion processing tasks based on the same analysis pipeline to suggest tasks best suited for the study of certain target brain regions. We studied an n-back task using emotional words (EMOBACK) as well as passive viewing tasks of emotional faces (FACES) and emotional scenes (OASIS and IAPS). We compared the activation patterns elicited by these tasks in four regions of interest (the amygdala, anterior insula, dorsolateral prefrontal cortex (dlPFC) and pregenual anterior cingulate cortex (pgACC)) in three samples of healthy adults (N = 45). The EMOBACK task elicited activation in the right dlPFC and bilateral anterior insula and deactivation in the pgACC while the FACES task recruited the bilateral amygdala. The IAPS and OASIS tasks showed similar activation patterns recruiting the bilateral amygdala and anterior insula. We conclude that these tasks can be used to study different regions involved in emotion processing and that the information provided is valuable for future research and the development of fMRI biomarkers.

Parametric study of transcranial alternating current stimulation for brain alpha power modulation

Transcranial alternating current stimulation, a non-invasive brain stimulation technique, has been used to increase alpha (8-12 Hz) power, the latter being associated with various brain functions and states. Heterogeneity among stimulation parameters across studies makes it difficult to implement reliable transcranial alternating current stimulation protocols, explaining the absence of consensus on optimal stimulation parameters to modulate the alpha rhythm. This project documents the differential impact of controlling for key transcranial alternating current stimulation parameters, namely the intensity, the frequency and the stimulation site (anterior versus posterior). Phase 1:20 healthy participants underwent 4 different stimulation conditions. In each experimental condition, stimulation via 2 electrodes was delivered for 20 min. Stimulation conditions were administered at PO7-PO8 or F3-F4 at individual's alpha frequency, or at individual's theta frequency or sham. Stimulation intensity was set according to each participant's comfort following a standardized unpleasantness scale (≤ 40 out of 100) and could not exceed 6 mA. All conditions were counterbalanced. Phase 2: participants who tolerated higher intensity of stimulation (4-6 mA) underwent alpha-frequency stimulation applied over PO7-PO8 at 1 mA to investigate within-subject modulation of stimulation response according to stimulation intensity. Whether set over posterior or anterior cortical sites, alpha-frequency stimulation showed greater increase in alpha power relative to stimulation at theta frequency and sham stimulation. Posterior alpha-frequency stimulation showed a greater increase in alpha power relative to the adjacent frequency bands over frontal and occipito-parietal brain areas. Low intensity (1 mA) posterior alpha stimulation showed a similar increase in alpha power than at high (4-6 mA) intensity when measured immediately after stimulation. However, when tested at 60 min or 120 min, low intensity stimulation was associated with significantly superior alpha power increase relative to high intensity stimulation. This study shows that posterior individual's alpha frequency stimulation at higher intensities is well tolerated but fails to increase stimulation aftereffects recorded within 2 h of stimulation on brain oscillations of the corresponding frequency band. In sharp contrast, stimulating at 1 mA (regardless of phosphene generation or sensory perception) effectively and selectively modulates alpha power within that 2-h time window, thus validating that it as a reliable stimulus intensity for future studies. This study also shows that posterior alpha-frequency stimulation preferentially modulates endogenous brain oscillations of the corresponding frequency band. Moreover, our data suggest that posterior alpha-frequency transcranial alternating current stimulation is a reliable and precise non-invasive brain stimulation technique for persistent modulation of both frontal and occipito-parietal alpha power.

Working memory training effects across the lifespan: Evidence from human and experimental animal studies

Working memory refers to a cognitive function that provides temporary storage and manipulation of the information necessary for complex cognitive tasks. Due to its central role in general cognition, several studies have investigated the possibility that training on working memory tasks could improve not only working memory function but also increase other cognitive abilities or modulate other behaviors. This possibility is still highly controversial, with prior studies providing contradictory findings. The lack of systematic approaches and methodological shortcomings complicates this debate even more. This review highlights the impact of working memory training at different ages on humans. Finally, it demonstrates several findings about the neural substrate of training in both humans and experimental animals, including non-human primates and rodents.

Effects of highly purified cannabidiol (CBD) on fMRI of working memory in treatment-resistant epilepsy

OBJECTIVE

We aimed to determine changes in working memory and functional connectivity via functional magnetic resonance imaging (fMRI)-modified Sternberg task after treatment with highly purified cannabidiol (CBD, Epidiolex®; 100 mg/mL) in patients with treatment-resistant epilepsy (TRE).

METHODS

Twenty patients with TRE (mean age: 35.8 years; 7 male) performed fMRI Sternberg task before receiving CBD ("PRE") and after reaching stable dosage of CBD (15-25 mg/kg/day; "ON"). Each patient performed 2 runs of the modified Sternberg task during PRE and ON fMRI. Twenty-three healthy controls (HCs; mean age: 25 years; 11 M) also completed the task. All were presented with a sequence of 2 or 6 letters and instructed to remember them (encoding). After a delay, a single letter was shown, and participants recalled if letter was shown in sequence (retrieval). Paired t-tests were used to analyze accuracy/response times. For each subject, event-related modeling of encoding (2 and 6 letters) and retrieval was performed. Paired t-tests controlling for seizure frequency change and scanner type were performed to assess changes in neural recruitment during encoding and retrieval in key regions of interest.

RESULTS

There was nonsignificant increase in mean modified Sternberg task accuracy from PRE to ON-CBD (28.6 vs. 32.1%). PRE and ON accuracy was worse than HCs (75.5%, p < 0.001). ON-PRE comparison revealed increased activation in the right inferior frontal gyrus (IFG) during 6-letter encoding. ON-HC comparison revealed increased activation in bilateral IFG and insula during 2-letter encoding. PRE-HC comparison revealed decreased activation in the left middle frontal gyrus during 6-letter encoding. None of these activations were associated with working memory performance.

SIGNIFICANCE

Treatment-resistant epilepsy results in poorer working memory performance and lower neural recruitment compared with HCs. Treatment with CBD results in no significant changes in working memory performance and in significant increases in neural activity in regions important for verbal memory and attention compared with HCs during memory encoding.

Reliability of mismatch negativity event-related potentials in a multisite, traveling subjects study

OBJECTIVE

To determine the optimal methods for measuring mismatch negativity (MMN), an auditory event-related potential (ERP), and quantify sources of MMN variance in a multisite setting.

METHODS

Reliability of frequency, duration, and double (frequency + duration) MMN was determined from eight traveling subjects, tested on two occasions at eight laboratory sites. Deviant-specific variance components were estimated for MMN peak amplitude and latency measures using different ERP processing methods. Generalizability (G) coefficients were calculated using two-facet (site and occasion), fully-crossed models and single-facet (occasion) models within each laboratory to assess MMN reliability.

RESULTS

G-coefficients calculated from two-facet models indicated fair (0.4 < G<=0.6) duration MMN reliability at electrode Fz, but poor (G < 0.4) double and frequency MMN reliability. Single-facet G-coefficients averaged across laboratory resulted in improved reliability (G > 0.5). MMN amplitude reliability was greater than latency reliability, and reliability with mastoid referencing significantly outperformed nose-referencing.

CONCLUSIONS

EEG preprocessing methods have an impact on the reliability of MMN amplitude. Within site MMN reliability can be excellent, consistent with prior single site studies.

SIGNIFICANCE

With standardized data collection and ERP processing, MMN can be reliably obtained in multisite studies, providing larger samples sizeswithin rare patient groups.

Toward Leveraging Human Connectomic Data in Large Consortia: Generalizability of fMRI-Based Brain Graphs Across Sites, Sessions, and Paradigms

While graph theoretical modeling has dramatically advanced our understanding of complex brain systems, the feasibility of aggregating connectomic data in large imaging consortia remains unclear. Here, using a battery of cognitive, emotional and resting fMRI paradigms, we investigated the generalizability of functional connectomic measures across sites and sessions. Our results revealed overall fair to excellent reliability for a majority of measures during both rest and tasks, in particular for those quantifying connectivity strength, network segregation and network integration. Processing schemes such as node definition and global signal regression (GSR) significantly affected resulting reliability, with higher reliability detected for the Power atlas (vs. AAL atlas) and data without GSR. While network diagnostics for default-mode and sensori-motor systems were consistently reliable independently of paradigm, those for higher-order cognitive systems were reliable predominantly when challenged by task. In addition, based on our present sample and after accounting for observed reliability, satisfactory statistical power can be achieved in multisite research with sample size of approximately 250 when the effect size is moderate or larger. Our findings provide empirical evidence for the generalizability of brain functional graphs in large consortia, and encourage the aggregation of connectomic measures using multisite and multisession data.

Harmonization of Brain Diffusion MRI: Concepts and Methods

MRI diffusion data suffers from significant inter- and intra-site variability, which hinders multi-site and/or longitudinal diffusion studies. This variability may arise from a range of factors, such as hardware, reconstruction algorithms and acquisition settings. To allow a reliable comparison and joint analysis of diffusion data across sites and over time, there is a clear need for robust data harmonization methods. This review article provides a comprehensive overview of diffusion data harmonization concepts and methods, and their limitations. Overall, the methods for the harmonization of multi-site diffusion images can be categorized in two main groups: diffusion parametric map harmonization (DPMH) and diffusion weighted image harmonization (DWIH). Whereas DPMH harmonizes the diffusion parametric maps (e.g., FA, MD, and MK), DWIH harmonizes the diffusion-weighted images. Defining a gold standard harmonization technique for dMRI data is still an ongoing challenge. Nevertheless, in this paper we provide two classification tools, namely a feature table and a flowchart, which aim to guide the readers in selecting an appropriate harmonization method for their study.

Reliability of a functional magnetic resonance imaging task of emotional conflict in healthy participants

Task-based functional neuroimaging methods are increasingly being used to identify biomarkers of treatment response in psychiatric disorders. To facilitate meaningful interpretation of neural correlates of tasks and their potential changes with treatment over time, understanding the reliability of the blood-oxygen-level dependent (BOLD) signal of such tasks is essential. We assessed test-retest reliability of an emotional conflict task in healthy participants collected as part of the Canadian Biomarker Integration Network in Depression. Data for 36 participants, scanned at three time points (weeks 0, 2, and 8) were analyzed, and intra-class correlation coefficients (ICC) were used to quantify reliability. We observed moderate reliability (median ICC values between 0.5 and 0.6), within occipital, parietal, and temporal regions, specifically for conditions of lower cognitive complexity, that is, face, congruent or incongruent trials. For these conditions, activation was also observed within frontal and sub-cortical regions, however, their reliability was poor (median ICC < 0.2). Clinically relevant prognostic markers based on task-based fMRI require high predictive accuracy at an individual level. For this to be achieved, reliability of BOLD responses needs to be high. We have shown that reliability of the BOLD response to an emotional conflict task in healthy individuals is moderate. Implications of these findings to further inform studies of treatment effects and biomarker discovery are discussed.

Optimization of energy state transition trajectory supports the development of executive function during youth

Executive function develops during adolescence, yet it remains unknown how structural brain networks mature to facilitate activation of the fronto-parietal system, which is critical for executive function. In a sample of 946 human youths (ages 8-23y) who completed diffusion imaging, we capitalized upon recent advances in linear dynamical network control theory to calculate the energetic cost necessary to activate the fronto-parietal system through the control of multiple brain regions given existing structural network topology. We found that the energy required to activate the fronto-parietal system declined with development, and the pattern of regional energetic cost predicts unseen individuals' brain maturity. Finally, energetic requirements of the cingulate cortex were negatively correlated with executive performance, and partially mediated the development of executive performance with age. Our results reveal a mechanism by which structural networks develop during adolescence to reduce the theoretical energetic costs of transitions to activation states necessary for executive function.

A decade of test-retest reliability of functional connectivity: A systematic review and meta-analysis

BACKGROUND

Once considered mere noise, fMRI-based functional connectivity has become a major neuroscience tool in part due to early studies demonstrating its reliability. These fundamental studies revealed only the tip of the iceberg; over the past decade, many test-retest reliability studies have continued to add nuance to our understanding of this complex topic. A summary of these diverse and at times contradictory perspectives is needed.

OBJECTIVES

We aimed to summarize the existing knowledge regarding test-retest reliability of functional connectivity at the most basic unit of analysis: the individual edge level. This entailed (1) a meta-analytic estimate of reliability and (2) a review of factors influencing reliability.

METHODS

A search of Scopus was conducted to identify studies that estimated edge-level test-retest reliability. To facilitate comparisons across studies, eligibility was restricted to studies measuring reliability via the intraclass correlation coefficient (ICC). The meta-analysis included a random effects pooled estimate of mean edge-level ICC, with studies nested within datasets. The review included a narrative summary of factors influencing edge-level ICC.

RESULTS

From an initial pool of 212 studies, 44 studies were identified for the qualitative review and 25 studies for quantitative meta-analysis. On average, individual edges exhibited a "poor" ICC of 0.29 (95% CI = 0.23 to 0.36). The most reliable measurements tended to involve: (1) stronger, within-network, cortical edges, (2) eyes open, awake, and active recordings, (3) more within-subject data, (4) shorter test-retest intervals, (5) no artifact correction (likely due in part to reliable artifact), and (6) full correlation-based connectivity with shrinkage.

CONCLUSION

This study represents the first meta-analysis and systematic review investigating test-retest reliability of edge-level functional connectivity. Key findings suggest there is room for improvement, but care should be taken to avoid promoting reliability at the expense of validity. By pooling existing knowledge regarding this key facet of accuracy, this study supports broader efforts to improve inferences in the field.

Multivariate approaches improve the reliability and validity of functional connectivity and prediction of individual behaviors

Brain functional connectivity features can predict cognition and behavior at the level of the individual. Most studies measure univariate signals, correlating timecourses from the average of constituent voxels in each node. While straightforward, this approach overlooks the spatial patterns of voxel-wise signals within individual nodes. Given that multivariate spatial activity patterns across voxels can improve fMRI measures of mental representations, here we asked whether using voxel-wise timecourses can better characterize region-by-region interactions relative to univariate approaches. Using two fMRI datasets, the Human Connectome Project sample and a local test-retest sample, we measured multivariate functional connectivity with multivariate distance correlation and univariate connectivity with Pearson's correlation. We compared multivariate and univariate connectivity estimates, demonstrating that relative to univariate estimates, multivariate estimates exhibited higher reliability at both the edge-level and connectome-level, stronger prediction of individual differences, and greater sensitivity to brain states within individuals. Our findings suggest that multivariate estimates reliably provide more powerful information about an individual's functional brain organization and its relation to cognitive skills.

Harmonizing 1.5T/3T Diffusion Weighted MRI through Development of Deep Learning Stabilized Microarchitecture Estimators

Diffusion weighted magnetic resonance imaging (DW-MRI) is interpreted as a quantitative method that is sensitive to tissue microarchitecture at a millimeter scale. However, the sensitization is dependent on acquisition sequences (e.g., diffusion time, gradient strength, etc.) and susceptible to imaging artifacts. Hence, comparison of quantitative DW-MRI biomarkers across field strengths (including different scanners, hardware performance, and sequence design considerations) is a challenging area of research. We propose a novel method to estimate microstructure using DW-MRI that is robust to scanner difference between 1.5T and 3T imaging. We propose to use a null space deep network (NSDN) architecture to model DW-MRI signal as fiber orientation distributions (FOD) to represent tissue microstructure. The NSDN approach is consistent with histologically observed microstructure (on previously acquired ex vivo squirrel monkey dataset) and scan-rescan data. The contribution of this work is that we incorporate identical dual networks (IDN) to minimize the influence of scanner effects via scan-rescan data. Briefly, our estimator is trained on two datasets. First, a histology dataset was acquired on three squirrel monkeys with corresponding DW-MRI and confocal histology (512 independent voxels). Second, 37 control subjects from the Baltimore Longitudinal Study of Aging (67-95 y/o) were identified who had been scanned at 1.5T and 3T scanners (b-value of 700 s/mm2, voxel resolution at 2.2mm, 30-32 gradient volumes) with an average interval of 4 years (standard deviation 1.3 years). After image registration, we used paired white matter (WM) voxels for 17 subjects and 440 histology voxels for training and 20 subjects and 72 histology voxels for testing. We compare the proposed estimator with super-resolved constrained spherical deconvolution (CSD) and a previously presented regression deep neural network (DNN). NSDN outperformed CSD and DNN in angular correlation coefficient (ACC) 0.81 versus 0.28 and 0.46, mean squared error (MSE) 0.001 versus 0.003 and 0.03, and general fractional anisotropy (GFA) 0.05 versus 0.05 and 0.09. Further validation and evaluation with contemporaneous imaging are necessary, but the NSDN is promising avenue for building understanding of microarchitecture in a consistent and device-independent manner.

Retrospective harmonization of multi-site diffusion MRI data acquired with different acquisition parameters

A joint and integrated analysis of multi-site diffusion MRI (dMRI) datasets can dramatically increase the statistical power of neuroimaging studies and enable comparative studies pertaining to several brain disorders. However, dMRI data sets acquired on multiple scanners cannot be naively pooled for joint analysis due to scanner specific nonlinear effects as well as differences in acquisition parameters. Consequently, for joint analysis, the dMRI data has to be harmonized, which involves removing scanner-specific differences from the raw dMRI signal. In this work, we propose a dMRI harmonization method that is capable of removing scanner-specific effects, while accounting for minor differences in acquisition parameters such as b-value, spatial resolution and number of gradient directions. We validate our algorithm on dMRI data acquired from two sites: Philadelphia Neurodevelopmental Cohort (PNC) with 800 healthy adolescents (ages 8-22 years) and Brigham and Women's Hospital (BWH) with 70 healthy subjects (ages 14-54 years). In particular, we show that gender and age-related maturation differences in different age groups are preserved after harmonization, as measured using effect sizes (small, medium and large), irrespective of the test sample size. Since we use matched control subjects from different scanners to estimate scanner-specific effects, our goal in this work is also to determine the minimum number of well-matched subjects needed from each site to achieve best harmonization results. Our results indicate that at-least 16 to 18 well-matched healthy controls from each site are needed to reliably capture scanner related differences. The proposed method can thus be used for retrospective harmonization of raw dMRI data across sites despite differences in acquisition parameters, while preserving inter-subject anatomical variability.

A longitudinal human phantom reliability study of multi-center T1-weighted, DTI, and resting state fMRI data

Multi-center MRI studies can enhance power, generalizability, and discovery for clinical neuroimaging research in brain disorders. Here, we sought to establish the utility of a clustering algorithm as an alternative to more traditional intra-class correlation coefficient approaches in a longitudinal multi-center human phantom study. We completed annual reliability scans on 'travelling human phantoms'. Acquisitions across sites were harmonized prospectively. Twenty-seven MRI sessions were available across four participants, scanned on five scanners, across three years. For each scan, three metrics were extracted: cortical thickness (CT), white matter fractional anisotropy (FA), and resting state functional connectivity (FC). For each metric, hierarchical clustering (Ward's method) was performed. The cluster solutions were compared to participant and scanner using the adjusted Rand index (ARI). For all metrics, data clustered by participant rather than by scanner (ARI > 0.8 comparing clusters to participants, ARI < 0.2 comparing clusters to scanners). These results demonstrate that hierarchical clustering can reliably identify structural and functional scans from different participants imaged on different scanners across time. With increasing interest in data-driven approaches in psychiatric and neurologic brain imaging studies, our findings provide a framework for multi-center analytic approaches aiming to identify subgroups of participants based on brain structure or function.

Aberrant Cortical Integration in First-Episode Psychosis During Natural Audiovisual Processing

BACKGROUND

Functional magnetic resonance imaging studies of psychotic disorders have reported both hypoactivity and hyperactivity in numerous brain regions. In line with the dysconnection hypothesis, these regions include cortical integrative hub regions. However, most earlier studies focused on a single cognitive function at a time, assessed by delivering artificial stimuli to patients with chronic psychosis. Thus, it remains unresolved whether these findings are present already in early psychosis and whether they translate to real-life-like conditions that require multisensory processing and integration.

METHODS

Scenes from the movie Alice in Wonderland (2010) were shown to 51 patients with first-episode psychosis (16 women) and 32 community-based control subjects (17 women) during 3T functional magnetic resonance imaging. We compared intersubject correlation, a measure of similarity of brain signal time courses in each voxel, between the groups. We also quantified the hubness as the number of connections each region has.

RESULTS

Intersubject correlation was significantly lower in patients with first-episode psychosis than in control subjects in the medial and lateral prefrontal, cingulate, precuneal, and parietotemporal regions, including the default mode network. Regional magnitude of between-group difference in intersubject correlation was associated with the hubness.

CONCLUSIONS

Our findings provide novel evidence for the dysconnection hypothesis by showing that during complex real-life-like stimulation, the most prominent functional alterations in psychotic disorders relate to integrative brain functions. Presence of such abnormalities in first-episode psychosis rules out long-term effects of illness or medication. These methods can be used in further studies to map widespread hub alterations in a single functional magnetic resonance imaging session and link them to potential downstream and upstream pathways.

Functional connectivity of intrinsic cognitive networks during resting state and task performance in preadolescent children

Earlier studies on adults have shown that functional connectivity (FC) of brain networks can vary depending on the brain state and cognitive challenge. Network connectivity has been investigated quite extensively in children in resting state, much less during tasks and is largely unexplored between these brain states. Here we used functional magnetic resonance imaging and independent component analysis to investigate the functional architecture of large-scale brain networks in 16 children (aged 7–11 years, 11 males) and 16 young adults (aged 22–29 years, 10 males) during resting state and visual working memory tasks. We identified the major neurocognitive intrinsic connectivity networks (ICNs) in both groups. Children had stronger FC than adults within the cingulo-opercular network in resting state, during task performance, and after controlling for performance differences. During tasks, children had stronger FC than adults also within the default mode (DMN) and right frontoparietal (rFPN) networks, and between the anterior DMN and the frontopolar network, whereas adults had stronger coupling between the anterior DMN and rFPN. Furthermore, children compared to adults modulated the FC strength regarding the rFPN differently between the brain states. The FC within the anterior DMN correlated with age and performance in children so that the younger they were, the stronger was the FC, and the stronger the FC within this network, the slower they performed the tasks. The group differences in the network connectivity reported here, and the observed correlations with task performance, provide insight into the normative development of the preadolescent brain and link maturation of functional connectivity with improving cognitive performance.

Multi-site harmonization of diffusion MRI data in a registration framework

Diffusion MRI (dMRI) data acquired on different scanners varies significantly in its content throughout the brain even if the acquisition parameters are nearly identical. Thus, proper harmonization of such data sets is necessary to increase the sample size and thereby the statistical power of neuroimaging studies. In this paper, we present a novel approach to harmonize dMRI data (the raw signal, instead of dMRI derived measures such as fractional anisotropy) using rotation invariant spherical harmonic (RISH) features embedded within a multi-modal image registration framework. All dMRI data sets from all sites are registered to a common template and voxel-wise differences in RISH features between sites at a group level are used to harmonize the signal in a subject-specific manner. We validate our method on diffusion data acquired from seven different sites (two GE, three Philips, and two Siemens scanners) on a group of age-matched healthy subjects. We demonstrate the efficacy of our method by statistically comparing diffusion measures such as fractional anisotropy, mean diffusivity and generalized fractional anisotropy across these sites before and after data harmonization. Validation was also done on a group oftest subjects, which were not used to "learn" the harmonization parameters. We also show results using TBSS before and after harmonization for independent validation of the proposed methodology. Using synthetic data, we show that any abnormality in diffusion measures due to disease is preserved during the harmonization process. Our experimental results demonstrate that, for nearly identical acquisition protocol across sites, scanner-specific differences in the signal can be removed using the proposed method in a model independent manner.

Statistical harmonization corrects site effects in functional connectivity measurements from multi-site fMRI data

Acquiring resting-state functional magnetic resonance imaging (fMRI) datasets at multiple MRI scanners and clinical sites can improve statistical power and generalizability of results. However, multi-site neuroimaging studies have reported considerable nonbiological variability in fMRI measurements due to different scanner manufacturers and acquisition protocols. These undesirable sources of variability may limit power to detect effects of interest and may even result in erroneous findings. Until now, there has not been an approach that removes unwanted site effects. In this study, using a relatively large multi-site (4 sites) fMRI dataset, we investigated the impact of site effects on functional connectivity and network measures estimated by widely used connectivity metrics and brain parcellations. The protocols and image acquisition of the dataset used in this study had been homogenized using identical MRI phantom acquisitions from each of the neuroimaging sites; however, intersite acquisition effects were not completely eliminated. Indeed, in this study, we found that the magnitude of site effects depended on the choice of connectivity metric and brain atlas. Therefore, to further remove site effects, we applied ComBat, a harmonization technique previously shown to eliminate site effects in multi-site diffusion tensor imaging (DTI) and cortical thickness studies. In the current work, ComBat successfully removed site effects identified in connectivity and network measures and increased the power to detect age associations when using optimal combinations of connectivity metrics and brain atlases. Our proposed ComBat harmonization approach for fMRI-derived connectivity measures facilitates reliable and efficient analysis of retrospective and prospective multi-site fMRI neuroimaging studies.

Influences on the Test-Retest Reliability of Functional Connectivity MRI and its Relationship with Behavioral Utility

Best practices are currently being developed for the acquisition and processing of resting-state magnetic resonance imaging data used to estimate brain functional organization—or “functional connectivity.” Standards have been proposed based on test–retest reliability, but open questions remain. These include how amount of data per subject influences whole-brain reliability, the influence of increasing runs versus sessions, the spatial distribution of reliability, the reliability of multivariate methods, and, crucially, how reliability maps onto prediction of behavior. We collected a dataset of 12 extensively sampled individuals (144 min data each across 2 identically configured scanners) to assess test–retest reliability of whole-brain connectivity within the generalizability theory framework. We used Human Connectome Project data to replicate these analyses and relate reliability to behavioral prediction. Overall, the historical 5-min scan produced poor reliability averaged across connections. Increasing the number of sessions was more beneficial than increasing runs. Reliability was lowest for subcortical connections and highest for within-network cortical connections. Multivariate reliability was greater than univariate. Finally, reliability could not be used to improve prediction; these findings are among the first to underscore this distinction for functional connectivity. A comprehensive understanding of test–retest reliability, including its limitations, supports the development of best practices in the field.

The effect of high-dose atorvastatin on neural activity and cognitive function

BACKGROUND

Functional magnetic resonance imaging (fMRI) has not been used to assess the effects of statins on the brain. We assessed the effect of statins on cognition using standard neuropsychological assessments and brain neural activation with fMRI on two tasks.

METHODS

Healthy statin-naïve men and women (48±15 years) were randomized to 80 mg/day atorvastatin (n=66; 27 men) or placebo (n=84; 48 men) for 6 months. Participants completed cognitive testing while on study drug and 2 months after treatment cessation using alternative test and task versions.

RESULTS

There were few changes in standard neuropsychological tests with drug treatment (all P>.56). Total and delayed recall from the Hopkins Verbal Learning Test-Revised increased in both groups (P<.05). The Stroop Color-Word score increased (P<.01) and the 18-Point Clock Test decreased in the placebo group (P=.02) after drug cessation. There were, however, small but significant group-time interactions for each fMRI task: participants on placebo had greater activation in the right putamen/dorsal striatum during the maintenance phase of the Sternberg task while on placebo but the effect was reversed after drug washout (P<.001). Participants on atorvastatin had greater activation in the bilateral precuneus during the encoding phase of the Figural Memory task while on-drug but the effect was reversed after drug washout (P<.001).

CONCLUSION

Six months of high dose atorvastatin therapy is not associated with measurable changes in neuropsychological test scores, but did evoke transient differences in brain activation patterns. Larger, longer-term clinical trials are necessary to confirm these findings and evaluate their clinical implications.

Reliability of functional magnetic resonance imaging activation during working memory in a multisite study: Clarification and implications for statistical power

In this technical note, we clarify the meaning of the generalizability-theory based coefficients reported in our multisite reliability study of fMRI measures of regional brain activation during working memory processing (Forsyth et al., Neuroimage 2014;97:51-52). While the original paper reported generalizability and dependability coefficients based on the design of our traveling subjects study (in which each subject was scanned twice at each of eight sites), those coefficients are of limited applicability outside of the reliability study context. Here we report generalizability and dependability coefficients that represent the reliability one can expect for a multisite study in which a given subject is scanned once on a scanner drawn randomly from the pool of available scanners (i.e., analogous to the more typical multisite study design). We also characterize the implications of a multisite versus single site study design for statistical power, including a figure that shows sample size requirements to detect activation in two key nodes of the working memory circuitry given observed differences in reliability of measurement between single and multisite designs.

Volumetric Differences in Cerebellar Lobes in Individuals from Multiplex Alcohol Dependence Families and Controls: Their Relationship to Externalizing and Internalizing Disorders and Working Memory

Offspring from families with multiple cases of alcohol dependence have a greater likelihood of developing alcohol dependence and related substance use disorders. Greater susceptibility for these disorders may be related to cerebellar morphology. Because posterior regions of the cerebellum are associated with cognitive abilities, we investigated whether high-risk offspring would display regionally specific differences in cerebellar morphology and whether these would be related to working memory performance. The relationship to externalizing and internalizing psychopathology was of interest because cerebellar morphology has previously been associated with a cognitive affective syndrome. A total of 131 participants underwent magnetic resonance imaging (MRI) with volumes of the cerebellar lobes obtained with manual tracing. These individuals were from high-risk (HR) for alcohol dependence families (N = 72) or from low-risk (LR) control families (N = 59). All were enrolled in a longitudinal follow-up that included repeated clinical assessments during childhood and young-adulthood prior to the scan that provided information on Axis I psychopathology. The Working Memory Index of the Wechsler Memory Scale was given at the time of the scan. Larger volumes of the corpus medullare and inferior posterior lobes and poorer working memory performance were found for the HR offspring relative to LR controls. Across all subjects, a significant positive association between working memory and total volume of corpus of the cerebellum was seen, controlling for familial risk. Presence of an internalizing or externalizing disorder interacting with familial risk was also associated with volume of the corpus medullare.

Combined mnemonic strategy training and high-definition transcranial direct current stimulation for memory deficits in mild cognitive impairment

INTRODUCTION

Memory deficits characterize Alzheimer's dementia and the clinical precursor stage known as mild cognitive impairment. Nonpharmacologic interventions hold promise for enhancing functioning in these patients, potentially delaying functional impairment that denotes transition to dementia. Previous findings revealed that mnemonic strategy training (MST) enhances long-term retention of trained stimuli and is accompanied by increased blood oxygen level-dependent signal in the lateral frontal and parietal cortices as well as in the hippocampus. The present study was designed to enhance MST generalization, and the range of patients who benefit, via concurrent delivery of transcranial direct current stimulation (tDCS).

METHODS

This protocol describes a prospective, randomized controlled, four-arm, double-blind study targeting memory deficits in those with mild cognitive impairment. Once randomized, participants complete five consecutive daily sessions in which they receive either active or sham high definition tDCS over the left lateral prefrontal cortex, a region known to be important for successful memory encoding and that has been engaged by MST. High definition tDCS (active or sham) will be combined with either MST or autobiographical memory recall (comparable to reminiscence therapy). Participants undergo memory testing using ecologically relevant measures and functional magnetic resonance imaging before and after these treatment sessions as well as at a 3-month follow-up. Primary outcome measures include face-name and object-location association tasks. Secondary outcome measures include self-report of memory abilities as well as a spatial navigation task (near transfer) and prose memory (medication instructions; far transfer). Changes in functional magnetic resonance imaging will be evaluated during both task performance and the resting-state using activation and connectivity analyses.

DISCUSSION

The results will provide important information about the efficacy of cognitive and neuromodulatory techniques as well as the synergistic interaction between these promising approaches. Exploratory results will examine patient characteristics that affect treatment efficacy, thereby identifying those most appropriate for intervention.

Enhancing the Informativeness and Replicability of Imaging Genomics Studies

Imaging genomics is a new field of investigation that seeks to gain insights into the impact of human genetic variation on the structure, chemistry, and function of neural systems in health and disease. Because publications in this field have increased over the past decade, increasing concerns have been raised about false-positive results entering the literature. Here, we provide an overview of the field of imaging genomic and genetic approaches and discuss factors related to research design and analysis that can enhance the informativeness and replicability of these studies. We conclude that imaging genetic studies can provide important insights into the role of human genetic variation on neural systems and circuits, both in the context of normal quantitative variation and in relation to neuropsychiatric disease. We also argue that demonstrating genetic association to imaging-derived traits is subject to the same constraints as any other genetic study, including stringent type I error control. Adequately powered studies are necessary; however, there are currently limited data available to allow precise estimates of effect sizes for candidate gene studies. Independent replication is necessary before a result can be considered definitive, and for studies with small sample sizes it is necessary before publication. Increased transparency of methods and enhanced data sharing will further enhance replicability.

Test-retest reliability of longitudinal task-based fMRI: Implications for developmental studies

Great advances have been made in functional Magnetic Resonance Imaging (fMRI) studies, including the use of longitudinal design to more accurately identify changes in brain development across childhood and adolescence. While longitudinal fMRI studies are necessary for our understanding of typical and atypical patterns of brain development, the variability observed in fMRI blood-oxygen-level dependent (BOLD) signal and its test-retest reliability in developing populations remain a concern. Here we review the current state of test-retest reliability for child and adolescent fMRI studies (ages 5–18 years) as indexed by intraclass correlation coefficients (ICC). In addition to highlighting ways to improve fMRI test-retest reliability in developmental cognitive neuroscience research, we hope to open a platform for dialogue regarding longitudinal fMRI study designs, analyses, and reporting of results.

Hypoconnectivity of Resting-State Networks in Persons with Aphasia Compared with Healthy Age-Matched Adults

Aphasia is a language disorder affecting more than one million people in the US. While language function has traditionally been the focus of neuroimaging research, other cognitive functions are affected in this population, which has implications not only for those specific processes but also for the interaction of language and other cognitive functions. Resting state fMRI (rs-fMRI) is a practical and informative way to explore and characterize general cognitive engagement and/or health in this population, but it is currently underutilized. The aim of this study was to explore the functional connectivity in resting state networks (RSNs) and in the semantic network in seven persons with aphasia (PWA) who were at least 6 months post onset compared with 11 neurologically healthy adults (NHA) in order to gain a more comprehensive understanding of general cognitive engagement in aphasia. These preliminary results show that PWA exhibit hypoconnectivity in the semantic network and all RSNs except the visual network. Compared with NHA, PWA appear to have fewer cross- and left-hemispheric connections. However, PWA exhibit some stronger connections than NHA within the semantic network, which could indicate compensatory mechanisms. Importantly, connectivity for RSNs appear to increase with decreasing aphasia severity and decrease with increasing lesion size. This knowledge has the potential to improve aphasia therapy by furthering the understanding of lesion effects on the cognitive system as a whole, which can guide treatment target selection and promotion of favorable neural reorganization for optimal recovery of function.

Multisite reliability of MR-based functional connectivity

Recent years have witnessed an increasing number of multisite MRI functional connectivity (fcMRI) studies. While multisite studies provide an efficient way to accelerate data collection and increase sample sizes, especially for rare clinical populations, any effects of site or MRI scanner could ultimately limit power and weaken results. Little data exists on the stability of functional connectivity measurements across sites and sessions. In this study, we assess the influence of site and session on resting state functional connectivity measurements in a healthy cohort of traveling subjects (8 subjects scanned twice at each of 8 sites) scanned as part of the North American Prodrome Longitudinal Study (NAPLS). Reliability was investigated in three types of connectivity analyses: (1) seed-based connectivity with posterior cingulate cortex (PCC), right motor cortex (RMC), and left thalamus (LT) as seeds; (2) the intrinsic connectivity distribution (ICD), a voxel-wise connectivity measure; and (3) matrix connectivity, a whole-brain, atlas-based approach to assessing connectivity between nodes. Contributions to variability in connectivity due to subject, site, and day-of-scan were quantified and used to assess between-session (test-retest) reliability in accordance with Generalizability Theory. Overall, no major site, scanner manufacturer, or day-of-scan effects were found for the univariate connectivity analyses; instead, subject effects dominated relative to the other measured factors. However, summaries of voxel-wise connectivity were found to be sensitive to site and scanner manufacturer effects. For all connectivity measures, although subject variance was three times the site variance, the residual represented 60-80% of the variance, indicating that connectivity differed greatly from scan to scan independent of any of the measured factors (i.e., subject, site, and day-of-scan). Thus, for a single 5min scan, reliability across connectivity measures was poor (ICC=0.07-0.17), but increased with increasing scan duration (ICC=0.21-0.36 at 25min). The limited effects of site and scanner manufacturer support the use of multisite studies, such as NAPLS, as a viable means of collecting data on rare populations and increasing power in univariate functional connectivity studies. However, the results indicate that aggregation of fcMRI data across longer scan durations is necessary to increase the reliability of connectivity estimates at the single-subject level.

Cortical salience network activation precedes the development of delusion severity

BACKGROUND

Delusion is the most characteristic symptom of psychosis. While researchers suggested an association between changes of the cortical salience network (CSN) and delusion, whether these CSN findings are a cause or a consequence of delusion remains unknown.

METHOD

To assess the effect of CSN functioning to forthcoming changes in delusion scores, we measured brain activation with 3-T functional magnetic resonance imaging in two independent samples of first-episode psychosis patients (total of 27 patients and 23 healthy controls). During scanning, the patients evaluated statements about whether an individual's psychosis-related experiences should be described as a mental illness, and control statements that were also evaluated by healthy controls. Symptoms were assessed at the baseline and at 2 months follow-up with Brief Psychiatric Rating Scale.

RESULTS

Both tasks activated the CSN in comparison with rest. Activation of CSN ('illness evaluation v. control task' contrast) in patients positively correlated with worsening of or less improvement in delusions at the 2-month follow-up assessment. This finding was independent of delusion and clinical insight scores at the baseline evaluation.

CONCLUSIONS

Our findings link symptom-evaluation-related CSN functioning to severity of delusion and, importantly, add a new layer of evidence for the contribution of CSN functioning to the longitudinal course of delusions.

Evidence for Thalamocortical Circuit Abnormalities and Associated Cognitive Dysfunctions in Underweight Individuals with Anorexia Nervosa

Anorexia nervosa (AN) is characterized by extremely low body weight resulting from pathological food restriction, and carries a mortality rate among the highest of any psychiatric illness. AN, particularly during the acute, underweight state of the illness, has been associated with abnormalities across a range of brain regions, including the frontal cortex and basal ganglia. Few studies of AN have investigated the thalamus, a key mediator of information flow through frontal-basal ganglia circuit loops. We examined both thalamic surface morphology using anatomical MRI and thalamo-frontal functional connectivity using resting-state functional MRI. Individuals with AN (n=28) showed localized inward deformations of the thalamus relative to healthy controls (HC, n=22), and abnormal functional connectivity between the thalamus and the dorsolateral and anterior prefrontal cortices. Alterations in thalamo-frontal connectivity were associated with deficits in performance on tasks probing cognitive control (Stroop task) and working memory (Letter-Number Sequencing (LNS) task). Our findings suggest that abnormalities in thalamo-frontal circuits may have a role in mediating aspects of cognitive dysfunction in underweight individuals with AN.

Inter-site and inter-scanner diffusion MRI data harmonization

We propose a novel method to harmonize diffusion MRI data acquired from multiple sites and scanners, which is imperative for joint analysis of the data to significantly increase sample size and statistical power of neuroimaging studies. Our method incorporates the following main novelties: i) we take into account the scanner-dependent spatial variability of the diffusion signal in different parts of the brain; ii) our method is independent of compartmental modeling of diffusion (e.g., tensor, and intra/extra cellular compartments) and the acquired signal itself is corrected for scanner related differences; and iii) inter-subject variability as measured by the coefficient of variation is maintained at each site. We represent the signal in a basis of spherical harmonics and compute several rotation invariant spherical harmonic features to estimate a region and tissue specific linear mapping between the signal from different sites (and scanners). We validate our method on diffusion data acquired from seven different sites (including two GE, three Philips, and two Siemens scanners) on a group of age-matched healthy subjects. Since the extracted rotation invariant spherical harmonic features depend on the accuracy of the brain parcellation provided by Freesurfer, we propose a feature based refinement of the original parcellation such that it better characterizes the anatomy and provides robust linear mappings to harmonize the dMRI data. We demonstrate the efficacy of our method by statistically comparing diffusion measures such as fractional anisotropy, mean diffusivity and generalized fractional anisotropy across multiple sites before and after data harmonization. We also show results using tract-based spatial statistics before and after harmonization for independent validation of the proposed methodology. Our experimental results demonstrate that, for nearly identical acquisition protocol across sites, scanner-specific differences can be accurately removed using the proposed method.

Muscle, functional and cognitive adaptations after flywheel resistance training in stroke patients: a pilot randomized controlled trial

BACKGROUND

Resistance exercise (RE) improves neuromuscular function and physical performance after stroke. Yet, the effects of RE emphasizing eccentric (ECC; lengthening) actions on muscle hypertrophy and cognitive function in stroke patients are currently unknown. Thus, this study explored the effects of ECC-overload RE training on skeletal muscle size and function, and cognitive performance in individuals with stroke.

METHODS

Thirty-two individuals with chronic stroke (≥6 months post-stroke) were randomly assigned into a training group (TG; n = 16) performing ECC-overload flywheel RE of the more-affected lower limb (12 weeks, 2 times/week; 4 sets of 7 maximal closed-chain knee extensions; <2 min of contractile activity per session) or a control group (CG; n = 16), maintaining daily routines. Before and after the intervention, quadriceps femoris volume, maximal force and power for each leg were assessed, and functional and dual task performance, and cognitive functions were measured.

RESULTS

Quadriceps femoris volume of the more-affected leg increased by 9.4 % in TG. Muscle power of the more-affected, trained (48.2 %), and the less-affected, untrained limb (28.1 %) increased after training. TG showed enhanced balance (8.9 %), gait performance (10.6 %), dual-task performance, executive functions (working memory, verbal fluency tasks), attention, and speed of information processing. CG showed no changes.

CONCLUSION

ECC-overload flywheel resistance exercise comprising 4 min of contractile activity per week offers a powerful aid to regain muscle mass and function, and functional performance in individuals with stroke. While the current intervention improved cognitive functions, the cause-effect relationship, if any, with the concomitant neuromuscular adaptations remains to be explored.

TRIAL REGISTRATION

Clinical Trials NCT02120846.

Reproducibility of Resting State Connectivity in Patients with Stable Multiple Sclerosis

Given increasing efforts to use resting-state fMRI (rfMRI) as a biomarker of disease progression in multiple sclerosis (MS) we here explored the reproducibility of longitudinal rfMRI over three months in patients with clinically and radiologically stable MS. To pursue this aim, two approaches were applied in nine rfMRI networks: First, the intraclass correlation coefficient (ICC 3,1) was assessed for the mean functional connectivity maps across the entire network and a region of interest (ROI). Second, the ratio of overlap between Z-thresholded connectivity maps for each network was assessed. We quantified between-session functional reproducibility of rfMRI for 20 patients with stable MS and 14 healthy controls (HC). Nine rfMRI networks (RSNs) were examined at baseline and after 3 months of follow-up: three visual RSNs, the default-mode network, sensorimotor-, auditory-, executive control, and the left and right fronto-parietal RSN. ROI analyses were constrained to thresholded overlap masks for each individual (Z>0) at baseline and follow-up.In both stable MS and HC mean functional connectivity across the entire network did not reach acceptable ICCs for several networks (ICC<0.40) but we found a high reproducibility of ROI ICCs and of the ratio of overlap. ROI ICCs of all nine networks were between 0.98 and 0.99 for HC and ranged from 0.88 to 0.99 in patients with MS, respectively. The ratio of overlap for all networks was similar for both groups, ranging from 0.60 to 0.75.Our findings attest to a high reproducibility of rfMRI networks not only in HC but also in patients with stable MS when applying ROI analysis. This supports the utility of rfMRI to monitor functional changes related to disease progression or therapeutic interventions in MS.

Between- and within-site variability of fMRI localizations

This study provides first data about the spatial variability of fMRI sensorimotor localizations when investigating the same subjects at different fMRI sites. Results are comparable to a previous patient study. We found a median between-site variability of about 6 mm independent of task (motor or sensory) and experimental standardization (high or low). An intraclass correlation coefficient analysis using data quality measures indicated a major influence of the fMRI site on variability. In accordance with this, within-site localization variability was considerably lower (about 3 mm). We conclude that the fMRI site is a considerable confound for localization of brain activity. However, when performed by experienced clinical fMRI experts, brain pathology does not seem to have a relevant impact on the reliability of fMRI localizations. Hum Brain Mapp 37:2151-2160, 2016. © 2016 Wiley Periodicals, Inc.

Longitudinal fMRI studies: Exploring brain plasticity and repair in MS

Functional magnetic resonance imaging (fMRI) has greatly advanced our understanding of cerebral functional changes occurring in patients with multiple sclerosis (MS). However, most of our knowledge regarding brain plasticity and repair in MS as evidenced by fMRI has been extrapolated from cross-sectional studies across different phenotypes of the disease. This topical review provides an overview of this research, but also highlights limitations of existing fMRI studies with cross-sectional design. We then review the few existing longitudinal fMRI studies and discuss the feasibility and constraints of serial fMRI in individuals with MS. We further emphasize the potential to track fMRI changes in evolving disease and the insights this may give in terms of mechanisms of adaptation and repair, focusing on serial fMRI to monitor response to disease-modifying therapies or rehabilitation interventions. Finally, we offer recommendations for designing future research studies to overcome previous methodological shortcomings.

Harmonizing Diffusion MRI Data Across Multiple Sites and Scanners

Harmonizing diffusion MRI (dMRI) images across multiple sites is imperative for joint analysis of the data to significantly increase the sample size and statistical power of neuroimaging studies. In this work, we develop a method to harmonize diffusion MRI data across multiple sites and scanners that incorporates two main novelties: i) we take into account the spatial variability of the signal (for different sites) in different parts of the brain as opposed to existing methods, which consider one linear statistical covariate for the entire brain; ii) our method is model-free, in that no a-priori model of diffusion (e.g., tensor, compartmental models, etc.) is assumed and the signal itself is corrected for scanner related differences. We use spherical harmonic basis functions to represent the signal and compute several rotation invariant features, which are used to estimate a regionally specific linear mapping between signal from different sites (and scanners). We validate our method on diffusion data acquired from four different sites (including two GE and two Siemens scanners) on a group of healthy subjects. Diffusion measures such fractional anisotropy, mean diffusivity and generalized fractional anisotropy are compared across multiple sites before and after the mapping. Our experimental results demonstrate that, for identical acquisition protocol across sites, scanner-specific differences can be accurately removed using the proposed method.

Reliability of an fMRI paradigm for emotional processing in a multisite longitudinal study

Multisite neuroimaging studies can facilitate the investigation of brain-related changes in many contexts, including patient groups that are relatively rare in the general population. Though multisite studies have characterized the reliability of brain activation during working memory and motor functional magnetic resonance imaging tasks, emotion processing tasks, pertinent to many clinical populations, remain less explored. A traveling participants study was conducted with eight healthy volunteers scanned twice on consecutive days at each of the eight North American Longitudinal Prodrome Study sites. Tests derived from generalizability theory showed excellent reliability in the amygdala ( Eρ2 = 0.82), inferior frontal gyrus (IFG; Eρ2 = 0.83), anterior cingulate cortex (ACC; Eρ2 = 0.76), insula ( Eρ2 = 0.85), and fusiform gyrus ( Eρ2 = 0.91) for maximum activation and fair to excellent reliability in the amygdala ( Eρ2 = 0.44), IFG ( Eρ2 = 0.48), ACC ( Eρ2 = 0.55), insula ( Eρ2 = 0.42), and fusiform gyrus ( Eρ2 = 0.83) for mean activation across sites and test days. For the amygdala, habituation ( Eρ2 = 0.71) was more stable than mean activation. In a second investigation, data from 111 healthy individuals across sites were aggregated in a voxelwise, quantitative meta-analysis. When compared with a mixed effects model controlling for site, both approaches identified robust activation in regions consistent with expected results based on prior single-site research. Overall, regions central to emotion processing showed strong reliability in the traveling participants study and robust activation in the aggregation study. These results support the reliability of blood oxygen level-dependent signal in emotion processing areas across different sites and scanners and may inform future efforts to increase efficiency and enhance knowledge of rare conditions in the population through multisite neuroimaging paradigms.