Interaction of Alzheimer Disease and Traumatic Brain Injury on Cortical Thickness.

INTRODUCTION: Traumatic brain injury (TBI) is associated with an accelerated course of dementia, although biological relationships are incompletely understood. METHODS: The study examined 1124 participants, including 343 with Alzheimer disease (AD), 127 with AD with TBI, 266 cognitively normal adults with TBI, and 388 cognitively normal adults without TBI. Cortical thickness was quantified from T1-weighted magnetic resonance imaging data. Multiple linear regression was used to determine the interaction between AD and TBI on cortical thickness. RESULTS: Among those with AD, TBI was associated with an earlier age of AD onset but, counterintuitively, less cortical thinning in frontotemporal regions relative to non-AD controls. DISCUSSION: AD with TBI represents a distinct group from AD, likely with distinct pathologic contributions beyond gray matter loss. This finding has important implications for the diagnosis and treatment of AD in the presence of TBI and indicates that models of AD, aging, and neural loss should account for TBI history.

Neuropsychiatric symptoms and brain morphology in patients with mild cognitive impairment, cerebrovascular disease and Parkinson disease: A cross sectional and longitudinal study.

OBJECTIVES: Neuropsychiatric symptoms (NPS) increase risk of developing dementia and are linked to various neurodegenerative conditions, including mild cognitive impairment (MCI due to Alzheimer's disease [AD]), cerebrovascular disease (CVD), and Parkinson's disease (PD). We explored the structural neural correlates of NPS cross-sectionally and longitudinally across various neurodegenerative diagnoses. METHODS: The study included individuals with MCI due to AD, (n = 74), CVD (n = 143), and PD (n = 137) at baseline, and at 2-years follow-up (MCI due to AD, n = 37, CVD n = 103, and PD n = 84). We assessed the severity of NPS using the Neuropsychiatric Inventory Questionnaire. For brain structure we included cortical thickness and subcortical volume of predefined regions of interest associated with corticolimbic and frontal-executive circuits. RESULTS: Cross-sectional analysis revealed significant negative correlations between appetite with both circuits in the MCI and CVD groups, while apathy was associated with these circuits in both the MCI and PD groups. Longitudinally, changes in apathy scores in the MCI group were negatively linked to the changes of the frontal-executive circuit. In the CVD group, changes in agitation and nighttime behavior were negatively associated with the corticolimbic and frontal-executive circuits, respectively. In the PD group, changes in disinhibition and apathy were positively associated with the corticolimbic and frontal-executive circuits, respectively. CONCLUSIONS: The observed correlations suggest that underlying pathological changes in the brain may contribute to alterations in neural activity associated with MBI. Notably, the difference between cross-sectional and longitudinal results indicates the necessity of conducting longitudinal studies for reproducible findings and drawing robust inferences.

Feasibility of diffusion-tensor and correlated diffusion imaging for studying white-matter microstructural abnormalities: Application in COVID-19.

There has been growing attention on the effect of COVID-19 on white-matter microstructure, especially among those that self-isolated after being infected. There is also immense scientific interest and potential clinical utility to evaluate the sensitivity of single-shell diffusion magnetic resonance imaging (MRI) methods for detecting such effects. In this work, the performances of three single-shell-compatible diffusion MRI modeling methods are compared for detecting the effect of COVID-19, including diffusion-tensor imaging, diffusion-tensor decomposition of orthogonal moments and correlated diffusion imaging. Imaging was performed on self-isolated patients at the study initiation and 3-month follow-up, along with age- and sex-matched controls. We demonstrate through simulations and experimental data that correlated diffusion imaging is associated with far greater sensitivity, being the only one of the three single-shell methods to demonstrate COVID-19-related brain effects. Results suggest less restricted diffusion in the frontal lobe in COVID-19 patients, but also more restricted diffusion in the cerebellar white matter, in agreement with several existing studies highlighting the vulnerability of the cerebellum to COVID-19 infection. These results, taken together with the simulation results, suggest that a significant proportion of COVID-19 related white-matter microstructural pathology manifests as a change in tissue diffusivity. Interestingly, different b-values also confer different sensitivities to the effects. No significant difference was observed in patients at the 3-month follow-up, likely due to the limited size of the follow-up cohort. To summarize, correlated diffusion imaging is shown to be a viable single-shell diffusion analysis approach that allows us to uncover opposing patterns of diffusion changes in the frontal and cerebellar regions of COVID-19 patients, suggesting the two regions react differently to viral infection.

Cerebello-cerebral Functional Connectivity Networks in Major Depressive Disorder: a CAN-BIND-1 Study Report.

Neuroimaging studies have demonstrated aberrant structure and function of the "cognitive-affective cerebellum" in major depressive disorder (MDD), although the specific role of the cerebello-cerebral circuitry in this population remains largely uninvestigated. The objective of this study was to delineate the role of cerebellar functional networks in depression. A total of 308 unmedicated participants completed resting-state functional magnetic resonance imaging scans, of which 247 (148 MDD; 99 healthy controls, HC) were suitable for this study. Seed-based resting-state functional connectivity (RsFc) analysis was performed using three cerebellar regions of interest (ROIs): ROI1 corresponded to default mode network (DMN)/inattentive processing; ROI2 corresponded to attentional networks, including frontoparietal, dorsal attention, and ventral attention; ROI3 corresponded to motor processing. These ROIs were delineated based on prior functional gradient analyses of the cerebellum. A general linear model was used to perform within-group and between-group comparisons. In comparison to HC, participants with MDD displayed increased RsFc within the cerebello-cerebral DMN (ROI1) and significantly elevated RsFc between the cerebellar ROI1 and bilateral angular gyrus at a voxel threshold (p < 0.001, two-tailed) and at a cluster level (p < 0.05, FDR-corrected). Group differences were non-significant for ROI2 and ROI3. These results contribute to the development of a systems neuroscience approach to the diagnosis and treatment of MDD. Specifically, our findings confirm previously reported associations between MDD, DMN, and cerebellum, and highlight the promising role of these functional and anatomical locations for the development of novel imaging-based biomarkers and targets for neuromodulation therapies. ClinicalTrials.gov TRN: NCT01655706; Date of Registration: August 2nd, 2012.

Altered connectivity of default mode and executive control networks among female patients with persistent post-concussion symptoms.

OBJECTIVE: To examine the roles of the default mode network (DMN) and executive control network (ECN) in prolonged recovery after mild traumatic brain injury (mTBI), and relationships with indices of white matter microstructural injury. METHODS: Seventeen mTBI patients with persistent symptoms were imaged an average of 21.5 months post-injury, along with 23 healthy controls. Resting-state functional magnetic resonance imaging (rs-fMRI) was used to evaluate functional connectivity (FC) of the DMN and ECN. Diffusion tensor imaging (DTI) quantified fractional anisotropy, along with mean, axial and radial diffusivity of white matter tracts. RESULTS: Compared to controls, patients with mTBI had increased functional connectivity of the DMN and ECN to brain regions implicated in salience and frontoparietal networks, and increased white matter diffusivity within the cerebrum and brainstem. Among the patients, FC was correlated with better neurocognitive test scores, while diffusivity was correlated with more severe self-reported symptoms. The FC and diffusivity values within abnormal brain regions were not significantly correlated. CONCLUSION: For female mTBI patients with prolonged symptoms, hyper-connectivity may represent a compensatory response that helps to mitigate the effects of mTBI on cognition. These effects are unrelated to indices of microstructural injury, which are correlated with symptom severity, suggesting that rs-fMRI and DTI may capture distinct aspects of pathophysiology.

Resting state fMRI scanner instabilities revealed by longitudinal phantom scans in a multi-center study.

Quality assurance (QA) is crucial in longitudinal and/or multi-site studies, which involve the collection of data from a group of subjects over time and/or at different locations. It is important to regularly monitor the performance of the scanners over time and at different locations to detect and control for intrinsic differences (e.g., due to manufacturers) and changes in scanner performance (e.g., due to gradual component aging, software and/or hardware upgrades, etc.). As part of the Ontario Neurodegenerative Disease Research Initiative (ONDRI) and the Canadian Biomarker Integration Network in Depression (CAN-BIND), QA phantom scans were conducted approximately monthly for three to four years at 13 sites across Canada with 3T research MRI scanners. QA parameters were calculated for each scan using the functional Biomarker Imaging Research Network's (fBIRN) QA phantom and pipeline to capture between- and within-scanner variability. We also describe a QA protocol to measure the full-width-at-half-maximum (FWHM) of slice-wise point spread functions (PSF), used in conjunction with the fBIRN QA parameters. Variations in image resolution measured by the FWHM are a primary source of variance over time for many sites, as well as between sites and between manufacturers. We also identify an unexpected range of instabilities affecting individual slices in a number of scanners, which may amount to a substantial contribution of unexplained signal variance to their data. Finally, we identify a preliminary preprocessing approach to reduce this variance and/or alleviate the slice anomalies, and in a small human data set show that this change in preprocessing can have a significant impact on seed-based connectivity measurements for some individual subjects. We expect that other fMRI centres will find this approach to identifying and controlling scanner instabilities useful in similar studies.

Sex differences in acute and long-term brain recovery after concussion.

Concussion is associated with acute disturbances in brain function and behavior, with potential long-term effects on brain health. However, it is presently unclear whether there are sex differences in acute and long-term brain recovery. In this study, magnetic resonance imaging (MRI) was used to scan 61 participants with sport-related concussion (30 male, 31 female) longitudinally at acute injury, medical clearance to return to play (RTP), and 1-year post-RTP. A large cohort of 167 controls (80 male, 87 female) was also imaged. Each MRI session assessed cerebral blood flow (CBF), along with white matter fractional anisotropy (FA) and mean diffusivity (MD). For concussed athletes, the parameters were converted to difference scores relative to matched control subgroups, and partial least squares modeled the main and sex-specific effects of concussion. Although male and female athletes did not differ in acute symptoms or time to RTP , all MRI measures showed significant sex differences during recovery. Males had greater reductions in occipital-parietal CBF (mean difference and 95%CI: 9.97 ml/100 g/min, [4.84, 15.12] ml/100 g/min, z = 3.73) and increases in callosal MD (9.07 × 10-5 , [-14.14, -3.60] × 10-5 , z = -3.46), with greatest effects at 1-year post-RTP. In contrast, females had greater reductions in FA of the corona radiata (16.50 × 10-3 , [-22.38, -11.08] × 10-3 , z = -5.60), with greatest effects at RTP. These findings provide new insights into how the brain recovers after a concussion, showing sex differences in both the acute and chronic phases of injury.

Tablet Technology for Writing and Drawing during Functional Magnetic Resonance Imaging: A Review.

Functional magnetic resonance imaging (fMRI) is a powerful modality to study brain activity. To approximate naturalistic writing and drawing behaviours inside the scanner, many fMRI-compatible tablet technologies have been developed. The digitizing feature of the tablets also allows examination of behavioural kinematics with greater detail than using paper. With enhanced ecological validity, tablet devices have advanced the fields of neuropsychological tests, neurosurgery, and neurolinguistics. Specifically, tablet devices have been used to adopt many traditional paper-based writing and drawing neuropsychological tests for fMRI. In functional neurosurgery, tablet technologies have enabled intra-operative brain mapping during awake craniotomy in brain tumour patients, as well as quantitative tremor assessment for treatment outcome monitoring. Tablet devices also play an important role in identifying the neural correlates of writing in the healthy and diseased brain. The fMRI-compatible tablets provide an excellent platform to support naturalistic motor responses and examine detailed behavioural kinematics.

Distinguishing cognitive effort and working memory load using scale-invariance and alpha suppression in EEG.

Despite being intuitive, cognitive effort has proven difficult to define quantitatively. Here, we proposed to study cognitive effort by investigating the degree to which the brain deviates from its default state, where brain activity is scale-invariant. Specifically, we measured such deviations by examining changes in scale-invariance of brain activity as a function of task difficulty and posited suppression of scale-invariance as a proxy for exertion of cognitive effort. While there is some fMRI evidence supporting this proposition, EEG investigations on the matter are scant, despite the EEG signal being more suitable for analysis of scale invariance (i.e., having a much broader frequency range). In the current study we validated the correspondence between scale-invariance (H) of cortical activity recorded by EEG and task load during two working memory (WM) experiments with varying set sizes. Then, we used this neural signature to disentangle cognitive effort from the number of items stored in WM within participants. Our results showed monotonic decreases in H with increased set size, even after set size exceeded WM capacity. This behavior of H contrasted with behavioral performance and an oscillatory indicator of WM load (i.e., alpha-band desynchronization), both of which showed a plateau at difficulty levels surpassing WM capacity. This is the first reported evidence for the suppression of scale-invariance in EEG due to task difficulty, and our work suggests that H suppression may be used to quantify changes in cognitive effort even when working memory load is at maximum capacity.

The relationship between symptom burden and systemic inflammation differs between male and female athletes following concussion.

BACKGROUND: Inflammation appears to be an important component of concussion pathophysiology. However, its relationship to symptom burden is unclear. Therefore, the purpose of this study was to evaluate the relationship between symptoms and inflammatory biomarkers measured in the blood of male and female athletes following a sport-related concussion (SRC). RESULTS: Forty athletes (n = 20 male, n = 20 female) from nine interuniversity sport teams at a single institution provided blood samples within one week of an SRC. Twenty inflammatory biomarkers were quantitated by immunoassay. The Sport Concussion Assessment Tool version 5 (SCAT-5) was used to evaluate symptoms. Partial least squares (PLS) analyses were used to evaluate the relationship(s) between biomarkers and symptoms. In males, a positive correlation between interferon (IFN)-γ and symptom severity was observed following SRC. The relationship between IFN-γ and symptoms was significant among all symptom clusters, with cognitive symptoms displaying the largest effect. In females, a significant negative relationship was observed between symptom severity and cytokines IFN-γ, tumor necrosis factor (TNF)-α, and myeloperoxidase (MPO); a positive relationship was observed between symptom severity and MCP-4. Inflammatory mediators were significantly associated with all symptom clusters in females; the somatic symptom cluster displayed the largest effect. CONCLUSION: These results provide supportive evidence of a divergent relationship between inflammation and symptom burden in male and female athletes following SRC. Future investigations should be cognizant of the potentially sex-specific pathophysiology underlying symptom presentation.

Scale-free functional brain dynamics during recovery from sport-related concussion.

Studies using blood-oxygenation-level-dependent functional magnetic resonance imaging (BOLD fMRI) have characterized how the resting brain is affected by concussion. The literature to date, however, has largely focused on measuring changes in the spatial organization of functional brain networks. In the present study, changes in the temporal dynamics of BOLD signals are examined throughout concussion recovery using scaling (or fractal) analysis. Imaging data were collected for 228 university-level athletes, 61 with concussion and 167 athletic controls. Concussed athletes were scanned at the acute phase of injury (1-7 days postinjury), the subacute phase (8-14 days postinjury), medical clearance to return to sport (RTS), 1 month post-RTS and 1 year post-RTS. The wavelet leader multifractal approach was used to assess scaling ( c1 ) and multifractal ( c2 ) behavior. Significant longitudinal changes were identified for c1 , which was lowest at acute injury, became significantly elevated at RTS, and returned near control levels by 1 year post-RTS. No longitudinal changes were identified for c2 . Secondary analyses showed that clinical measures of acute symptom severity and time to RTP were related to longitudinal changes in c1 . Athletes with both higher symptoms and prolonged recovery had elevated c1 values at RTS, while athletes with higher symptoms but rapid recovery had reduced c1 at acute injury. This study provides the first evidence for long-term recovery of BOLD scale-free brain dynamics after a concussion.

Neural Basis of Long-term Musical Memory in Cognitively Impaired Older Persons.

OBJECTIVE: The objective of this study was to determine whether exposure to long-known music would evoke more extensive activation of brain regions minimally affected by Alzheimer disease (AD) pathology and outside traditional memory networks using a functional magnetic resonance imaging paradigm involving listening to long-known and recently-learned music in older adults with cognitive impairment to provide insight into mechanisms of long-term musical memory preservation in cognitively impaired older persons. METHODS: Seventeen subjects with a diagnosis of mild AD or mild cognitive impairment were recruited for this study. Subjects were scanned using functional magnetic resonance imaging while they performed a music listening task, which included short clips of personally selected music from the patient's past and newly-composed music heard for the first time 60 minutes before scanning. From this task, we obtained group-level maps comparing brain areas associated with long-known and recently-heard music in all subjects. RESULTS: Exposure to long-known music preferentially activated brain regions including the medial prefrontal cortex, precuneus, anterior insula, basal ganglia, hippocampus, amygdala, and cerebellum relative to recently-heard music. These areas are involved in autobiographical memory and associated emotional responses. In addition, they are minimally affected by early stage AD pathology, thus providing a neural basis for long-known musical memory survival. CONCLUSIONS: Long-known music activates a bilateral network of prefrontal, emotional, motor, auditory, and subcortical regions (cerebellum, putamen, limbic structures). This extensive activation, relative to recently-heard music, may offer structural and functional clues as to why long-term musical memory appears to be relatively preserved among cognitively impaired older persons.

White matter during concussion recovery: Comparing diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI).

Concussion pathophysiology in humans remains incompletely understood. Diffusion tensor imaging (DTI) has identified microstructural abnormalities in otherwise normal appearing brain tissue, using measures of fractional anisotropy (FA), axial diffusivity (AD), and radial diffusivity (RD). The results of prior DTI studies suggest that acute alterations in microstructure persist beyond medical clearance to return to play (RTP), but these measures lack specificity. To better understand the observed effects, this study combined DTI with neurite orientation dispersion and density imaging (NODDI), which employs a more sophisticated description of water diffusion in the brain. A total of 66 athletes were recruited, including 33 concussed athletes, scanned within 7 days after concussion and at RTP, along with 33 matched controls. Both univariate and multivariate methods identified DTI and NODDI parameters showing effects of concussion on white matter. Spatially extensive decreases in FA and increases in AD and RD were associated with reduced intra-neurite water volume, at both the symptomatic phase of injury and RTP, indicating that effects persist beyond medical clearance. Subsequent analyses also demonstrated that concussed athletes with higher symptom burden and a longer recovery time had greater reductions in FA and increased AD, RD, along with increased neurite dispersion. This study provides the first longitudinal evaluation of concussion from acute injury to RTP using combined DTI and NODDI, significantly enhancing our understanding of the effects of concussion on white matter microstructure.

Evidence of a distinct peripheral inflammatory profile in sport-related concussion.

BACKGROUND: Inflammation is considered a hallmark of concussion pathophysiology in experimental models, yet is understudied in human injury. Despite the growing use of blood biomarkers in concussion, inflammatory biomarkers have not been well characterized. Furthermore, it is unclear if the systemic inflammatory response to concussion differs from that of musculoskeletal injury. The purpose of this paper was to characterize systemic inflammation after injury in athletes with sport-related concussion or musculoskeletal injury. METHODS: A prospective, observational cohort study was conducted employing 175 interuniversity athletes (sport-related concussion, n = 43; musculoskeletal injury, n = 30; healthy, n = 102) from 12 sports at a sports medicine clinic at an academic institution. High-sensitivity immunoassay was used to evaluate 20 inflammatory biomarkers in the peripheral blood of athletes within 7 days of injury (subacute) and at medical clearance. Healthy athletes were sampled prior to the start of their competitive season. Partial least squares regression analyses were used to identify salient biomarker contributions to class separation between injured and healthy athletes, as well as to evaluate the relationship between biomarkers and days to recovery in injured athletes. RESULTS: In the subacute period after injury, compared to healthy athletes, athletes with sport-related concussion had higher levels of the chemokines' monocyte chemoattractant protein-4 (p < 0.001) and macrophage inflammatory protein-1ß (p = 0.001); athletes with musculoskeletal injury had higher levels of thymus and activation-regulated chemokine (p = 0.001). No significant differences in biomarker profiles were observed at medical clearance. Furthermore, concentrations of monocyte chemoattractant protein-1 (p = 0.007) and monocyte chemoattractant protein-4 (p < 0.001) at the subacute time point were positively correlated with days to recovery in athletes with sport-related concussion, while thymus and activation-regulated chemokine was (p = 0.001) positively correlated with days to recovery in athletes with musculoskeletal injury. CONCLUSION: Sport-related concussion is associated with perturbations to systemic inflammatory chemokines that differ from those observed in athletes with a musculoskeletal injury. These results support inflammation as an important facet of secondary injury after sport-related concussion that can be measured systemically in a human model of injury.

Delusions in Alzheimer Disease are Associated With Decreased Default Mode Network Functional Connectivity.

OBJECTIVE: Approximately one-third of patients with Alzheimer disease (AD) develop delusions. Delusions have been linked to numerous adverse outcomes, including worsened cognitive and functional decline, increased caregiver burden, and higher mortality rates. Previous studies have indicated that both AD and neuropsychiatric symptoms within AD are associated with abnormal functional connectivity of the resting brain, but no studies have focused on how delusions alter resting-state functional connectivity. The authors' objective was to test for differences in resting brain function between delusional and non-delusional patients with AD. The authors hypothesized that patients with AD with delusions would exhibit reduced connectivity of the default mode network (DMN) compared with patients with AD without delusions. METHODS: Resting-state functional magnetic resonance imaging was used to investigate differences in functional connectivity between 15 patients with AD with delusions and 15 comparable patients with AD without delusions. A group-level principal component analysis was used to identify functional networks accounting for greatest variability over all subjects, and the DMN was selected for between-group analysis. Dual regression was used to reconstruct individual subject component maps, and a two-sample t test was used to compare groups with and without delusion, adjusted at a false discovery rate of 0.05. RESULTS: The two cohorts were comparable demographically and cognitively. The patients with delusions showed significantly reduced connectivity of the left inferior parietal lobule (IPL) with the rest of the DMN. CONCLUSION: Delusions in AD are associated with reduced connectivity within the DMN, specifically the left IPL. The authors' findings provide insight into the underlying neuropathophysiology of delusions in AD.

Gray Matter Changes Associated With the Development of Delusions in Alzheimer Disease.

OBJECTIVE: Delusions affect approximately a third of Alzheimer disease (AD) patients and are associated with poor outcomes. Previous studies investigating the neuroanatomic correlates of delusions have yet to reach a consensus, with findings of reduced volume across all lobes, particularly in frontal regions. The current study examined the gray matter (GM) differences associated with delusions in AD. METHODS: Using voxel-based morphometry, we assessed GM in 23 AD patients who developed delusions (AD+D) and 36 comparable AD patients who did not (AD-D) at baseline and follow-up. Analysis of variance was used to identify consistent differences between AD+D and AD-D patients across time points (main effect of group), consistent changes from baseline to follow-up (main effect of time), and differential changes between AD+D and AD-D over time (interaction of group and time). All data were obtained from the National Alzheimer's Coordinating Center database. RESULTS: The AD+D group had consistently lower frontal GM volume, although both groups showed decreased GM in frontotemporal brain regions over time. An interaction was observed between delusions and longitudinal change, with AD+D patients having significantly elevated GM in predominantly temporal areas at baseline assessment, becoming significantly lower than the AD-D group at follow-up. CONCLUSION: These findings suggest that, there are specific volumetric markers that distinguish patients with delusions from those without, before, and after the onset of delusions. Specifically, the decline of GM in temporal areas that had elevated levels prior to the onset of delusions may be involved in the manifestation of delusions.

BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods.

The rate of progress in human neurosciences is limited by the inability to easily apply a wide range of analysis methods to the plethora of different datasets acquired in labs around the world. In this work, we introduce a framework for creating, testing, versioning and archiving portable applications for analyzing neuroimaging data organized and described in compliance with the Brain Imaging Data Structure (BIDS). The portability of these applications (BIDS Apps) is achieved by using container technologies that encapsulate all binary and other dependencies in one convenient package. BIDS Apps run on all three major operating systems with no need for complex setup and configuration and thanks to the comprehensiveness of the BIDS standard they require little manual user input. Previous containerized data processing solutions were limited to single user environments and not compatible with most multi-tenant High Performance Computing systems. BIDS Apps overcome this limitation by taking advantage of the Singularity container technology. As a proof of concept, this work is accompanied by 22 ready to use BIDS Apps, packaging a diverse set of commonly used neuroimaging algorithms.

Optimizing fMRI preprocessing pipelines for block-design tasks as a function of age.

Functional Magnetic Resonance Imaging (fMRI) is a powerful neuroimaging tool, which is often hampered by significant noise confounds. There is evidence that our ability to detect activations in task fMRI is highly dependent on the preprocessing steps used to control noise and artifact. However, the vast majority of studies examining preprocessing pipelines in fMRI have focused on young adults. Given the widespread use of fMRI for characterizing the neurobiology of aging, it is critical to examine how the impact of preprocessing choices varies as a function of age. In this study, we employ the NPAIRS cross-validation framework, which optimizes pipelines based on metrics of prediction accuracy (P) and spatial reproducibility (R), to compare the effects of pipeline optimization between young (21-33 years) and older (61-82 years) cohorts, for three different block-design contrasts. Motion is shown to be a greater issue in the older cohort, and we introduce new statistical approaches to control for potential biases due to head motion during pipeline optimization. In comparison, data-driven methods of physiological noise correction show comparable benefits for both young and old cohorts. Using our optimization framework, we demonstrate that the optimal pipelines tend to be highly similar across age cohorts. In addition, there is a comparable, significant benefit of pipeline optimization across age cohorts, for (P, R) metrics and independent validation measures of activation overlap (both between-subject, within-session and within-subject, between-session). The choice of task contrast consistently shows a greater impact than the age cohort, for (P, R) metrics and activation overlap. Finally, adaptive pipeline optimization per task run shows improved sensitivity to age-related changes in brain activity, particularly for weaker, more complex cognitive contrasts. The current study provides the first detailed examination of preprocessing pipelines across age cohorts, demonstrating a significant benefit of adaptive pipeline optimization across age groups.

Quantifying functional connectivity in multi-subject fMRI data using component models.

Functional magnetic resonance imaging (fMRI) is increasingly used to characterize functional connectivity between brain regions. Given the vast number of between-voxel interactions in high-dimensional fMRI data, it is an ongoing challenge to detect stable and generalizable functional connectivity in the brain among groups of subjects. Component models can be used to define subspace representations of functional connectivity that are more interpretable. It is, however, unclear which component model provides the optimal representation of functional networks for multi-subject fMRI datasets. A flexible cross-validation approach that assesses the ability of the models to predict voxel-wise covariance in new data, using three different measures of generalization was proposed. This framework is used to compare a range of component models with varying degrees of flexibility in their representation of functional connectivity, evaluated on both simulated and experimental resting-state fMRI data. It was demonstrated that highly flexible subject-specific component subspaces, as well as very constrained average models, are poor predictors of whole-brain functional connectivity, whereas the best-generalizing models account for subject variability within a common spatial subspace. Within this set of models, spatial Independent Component Analysis (sICA) on concatenated data provides more interpretable brain patterns, whereas a consistent-covariance model that accounts for subject-specific network scaling (PARAFAC2) provides greater stability in functional connectivity relationships between components and their spatial representations. The proposed evaluation framework is a promising quantitative approach to evaluating component models, and reveals important differences between subspace models in terms of predictability, robustness, characterization of subject variability, and interpretability of the model parameters. Hum Brain Mapp 38:882-899, 2017. © 2016 Wiley Periodicals, Inc.

White matter microstructure in athletes with a history of concussion: Comparing diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI).

Sport concussion is associated with disturbances in brain function in the absence of gross anatomical lesions, and may have long-term health consequences. Diffusion-weighted magnetic resonance imaging (MRI) methods provide a powerful tool for investigating alterations in white matter microstructure reflecting the long-term effects of concussion. In a previous study, diffusion tensor imaging (DTI) showed that athletes with a history of concussion had elevated fractional anisotropy (FA) and reduced mean diffusivity (MD) parameters. To better understand these effects, this study compared DTI results to neurite orientation dispersion and density imaging (NODDI), which was used to estimate the intracellular volume fraction (VIC ) and orientation dispersion index (ODI). Sixty-eight (68) varsity athletes were recruited, including 37 without a history of concussion and 31 with concussion >6 months prior to imaging. Univariate analyses showed elevated FA and decreased MD for concussed athletes, along with increased VIC and reduced ODI, indicating greater neurite density and coherence of neurite orientation within white matter. Multivariate analyses also showed that for athletes with a history of concussion, white matter regions with increased FA had increased VIC and decreased ODI, with greater effects among athletes who were imaged a longer time since their last concussion. These findings enhance our understanding of the relationship between the biophysics of water diffusion and concussion neurobiology for young, healthy adults. Hum Brain Mapp 38:4201-4211, 2017. © 2017 Wiley Periodicals, Inc.