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Objective: We propose and develop a novel biclustering (N-BiC) approach for performing N-way biclustering of neuroimaging data. Our approach is applicable to an arbitrary number of features from both imaging and behavioral data (e.g., symptoms). We applied it to structural MRI data from patients with schizophrenia., Methods: It uses a source-based morphometry approach [i.e., independent component analysis of gray matter segmentation maps] to decompose the data into a set of spatial maps, each of which includes regions that covary among individuals. Then, the loading parameters for components of interest are entered to an exhaustive search, which incorporates a modified depth-first search technique to carry out the biclustering, with the goal of obtaining submatrices where the selected rows (individuals) show homogeneity in their expressions of selected columns (components) and vice versa., Results: Findings demonstrate that multiple biclusters have an evident association with distinct brain networks for the different types of symptoms in schizophrenia. The study identifies two components: inferior temporal gyrus (16) and brainstem (7), which are related to positive (distortion/excess of normal function) and negative (diminution/loss of normal function) symptoms in schizophrenia, respectively., Conclusion: N-BiC is a data-driven method of biclustering MRI data that can exhaustively explore relationships/substructures from a dataset without any prior information with a higher degree of robustness than earlier biclustering applications., Significance: The use of such approaches is important to investigate the underlying biological substrates of mental illness by grouping patients into homogeneous subjects, as the schizophrenia diagnosis is known to be relatively nonspecific and heterogeneous.

Objectives: The chronic effects of neurotrauma consortium (CENC) observational study is a multisite investigation designed to examine the long-term longitudinal effects of mild traumatic brain injury (mTBI). All participants in this initial CENC cohort had a history of deployment in Operation Enduring Freedom (Afghanistan), Operation Iraqi Freedom (Iraq), and/or their follow-on conflicts (Operation Freedom's Sentinel). All participants undergo extensive medical, neuropsychological, and neuroimaging assessments and either meet criteria for any lifetime mTBI or not. These assessments are integrated into six CENC core studies-Biorepository, Biostatistics, Data and Study Management, Neuroimaging, and Neuropathology., Methods: The current study outlines the quantitative neuroimaging methods managed by the Neuroimaging Core using FreeSurfer automated software for image quantification., Results: At this writing, 319 participants from the CENC observational study have completed all baseline assessments including the imaging protocol and tertiary data quality assurance procedures., Conclusions/discussion: The preliminary findings of this initial cohort are reported to describe how the Neuroimaging Core manages neuroimaging quantification for CENC studies., (© 2019 John Wiley & Sons, Ltd.)

It has been known for decades that head motion/other artifacts affect the blood oxygen level-dependent signal. Recent recommendations predominantly focus on denoising resting state data, which may not apply to task data due to the different statistical relationships that exist between signal and noise sources. Several blind-source denoising strategies (FIX and AROMA) and more standard motion parameter (MP) regression (0, 12, or 24 parameters) analyses were therefore compared across four sets of event-related functional magnetic resonance imaging (erfMRI) and block-design (bdfMRI) datasets collected with multiband 32- (repetition time [TR] = 460 ms) or older 12-channel (TR = 2,000 ms) head coils. The amount of motion varied across coil designs and task types. Quality control plots indicated small to moderate relationships between head motion estimates and percent signal change in both signal and noise regions. Blind-source denoising strategies eliminated signal as well as noise relative to MP24 regression; however, the undesired effects on signal depended both on algorithm (FIX > AROMA) and design (bdfMRI > erfMRI). Moreover, in contrast to previous results, there were minimal differences between MP12/24 and MP0 pipelines in both erfMRI and bdfMRI designs. MP12/24 pipelines were detrimental for a task with both longer block length (30 ± 5 s) and higher correlations between head MPs and design matrix. In summary, current results suggest that there does not appear to be a single denoising approach that is appropriate for all fMRI designs. However, even nonaggressive blind-source denoising approaches appear to remove signal as well as noise from task-related data at individual subject and group levels., (© 2019 Wiley Periodicals, Inc.)

Previous studies have shown that mild traumatic brain injury (mTBI) can cause abnormalities in clinically relevant magnetic resonance imaging (MRI) sequences. No large-scale study, however, has prospectively assessed this in athletes with sport-related concussion (SRC). The aim of the current study was to characterize and compare the prevalence of acute, trauma-related MRI findings and clinically significant, non-specific MRI findings in athletes with and without SRC. College and high-school athletes were prospectively enrolled and participated in scanning sessions between January 2015 through August 2017. Concussed contact sport athletes ( n  = 138; 14 female [F]; 19.5 ± 1.6 years) completed up to four scanning sessions after SRC. Non-concussed contact ( n  = 135; 15 F; 19.7 ± 1.6) and non-contact athletes ( n  = 96; 15 F; 20.0 ± 1.7) completed similar scanning sessions and served as controls. Board-certified neuroradiologists, blinded to SRC status, reviewed T 1 -weighted and T 2 -weighted fluid-attenuated inversion recovery and T 2 *-weighted and T 2 -weighted images for acute (i.e., injury-related) or non-acute findings that prompted recommendation for clinical follow-up. Concussed athletes were more likely to have MRI findings relative to contact (30.4% vs. 15.6%; odds ratio [OR] = 2.32; p  = 0.01) and non-contact control athletes (19.8%; OR = 2.11; p  = 0.04). Female athletes were more likely to have MRI findings than males (43.2% vs. 19.4%; OR = 2.62; p  = 0.01). One athlete with SRC had an acute, injury-related finding; group differences were largely driven by increased rate of non-specific white matter hyperintensities in concussed athletes. This prospective, large-scale study demonstrates that <1% of SRCs are associated with acute injury findings on qualitative structural MRI, providing empirical support for clinical guidelines that do not recommend use of MRI after SRC.

Inhibitory failure represents a core dysfunction in patients with schizophrenia (SP), which has predominantly been tested in the literature using reactive (ie, altering behavior after a stimulus) rather than proactive (ie, purposefully changing behavior before a stimulus) response inhibition tasks. The current study replicates/extends our previous findings of SP exhibiting sensorimotor cortex (SMC) hyperactivity and connectivity abnormalities in independent samples of patients and controls. Specifically, 49 clinically well-characterized SP and 54 matched healthy controls (HC) performed a proactive response inhibition task while undergoing functional magnetic resonance imaging and resting-state data collection. Results indicated that the majority of SP (84%) and HC (88%) successfully inhibited all overt motor responses following a cue, eliminating behavioral confounds frequently present in this population. Observations of left SMC hyperactivity during proactive response inhibition, reduced cortical connectivity with left SMC, and increased connectivity between left SMC and ventrolateral thalamus were replicated for SP relative to HC in the current study. Similarly, negative symptoms (eg, motor retardation) were again associated with SMC functional and connectivity abnormalities. In contrast, findings of a negative blood oxygenation level-dependent response in the SMC of HC did not replicate. Collectively, current and previous findings suggest that SMC connectivity abnormalities may be more robust relative to evoked hemodynamic signals during proactive response inhibition. In addition, there is strong support that these SMC abnormalities are a key component of SP pathology, along with dysfunction within other sensory cortices, and may be associated with certain clinical deficits such as negative symptoms., (© The Author(s) 2018. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Brain functional networks identified from fMRI data can provide potential biomarkers for brain disorders. Group independent component analysis (GICA) is popular for extracting brain functional networks from multiple subjects. In GICA, different strategies exist for reconstructing subject-specific networks from the group-level networks. However, it is unknown whether these strategies have different sensitivities to group differences and abilities in distinguishing patients. Among GICA, spatio-temporal regression (STR) and spatially constrained ICA approaches such as group information guided ICA (GIG-ICA) can be used to propagate components (indicating networks) to a new subject that is not included in the original subjects. In this study, based on the same a priori network maps, we reconstructed subject-specific networks using these two methods separately from resting-state fMRI data of 151 schizophrenia patients (SZs) and 163 healthy controls (HCs). We investigated group differences in the estimated functional networks and the functional network connectivity (FNC) obtained by each method. The networks were also used as features in a cross-validated support vector machine (SVM) for classifying SZs and HCs. We selected features using different strategies to provide a comprehensive comparison between the two methods. GIG-ICA generally showed greater sensitivity in statistical analysis and better classification performance (accuracy 76.45 ± 8.9%, sensitivity 0.74 ± 0.11, specificity 0.79 ± 0.11) than STR (accuracy 67.45 ± 8.13%, sensitivity 0.65 ± 0.11, specificity 0.71 ± 0.11). Importantly, results were also consistent when applied to an independent dataset including 82 HCs and 82 SZs. Our work suggests that the functional networks estimated by GIG-ICA are more sensitive to group differences, and GIG-ICA is promising for identifying image-derived biomarkers of brain disease., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group., Methods: The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide., Results: Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset., Conclusions: The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia., (Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Mild traumatic brain injury (mTBI) can result in symptoms that affect a person's cognitive and social abilities. Improvements in diagnostic methodologies are necessary given that current clinical techniques have limited accuracy and are solely based on self-reports. Recently, resting state functional network connectivity (FNC) has shown potential as an important imaging modality for the development of mTBI biomarkers. The present work explores the use of dynamic functional network connectivity (dFNC) for mTBI detection. Forty eight mTBI patients (24 males) and age-gender matched healthy controls were recruited. We identified a set of dFNC states and looked at the possibility of using each state to classify subjects in mTBI patients and healthy controls. A linear support vector machine was used for classification and validated using leave-one-out cross validation. One of the dFNC states achieved a high classification performance of 92% using the area under the curve method. A series of t -test analysis revealed significant dFNC increases between cerebellum and sensorimotor networks. This significant increase was detected in the same dFNC state useful for classification. Results suggest that dFNC can be used to identify optimal dFNC states for classification excluding those that does not contain useful features.

Background: Chronic alcohol use disorders (AUDs) and traumatic brain injury (TBI) are highly comorbid and share commonly affected neuronal substrates (i.e., prefrontal cortex, limbic system, and cerebellum). However, no studies have examined how combined physical trauma and heavy drinking affect neurocircuitry relative to heavy drinking alone., Methods: The current study investigated whether comorbid AUDs and mild or moderate TBI (AUDs+TBI) would negatively affect maladaptive drinking behaviors (n = 90 AUDs+TBI; n = 62 AUDs) as well as brain structure (i.e., increased atrophy; n = 62 AUDs+TBI; n = 44 AUDs) and function (i.e., activation during gustatory cue reactivity; n = 55 AUDs+TBI; n = 37 AUDs) relative to AUDs alone., Results: Participants reported a much higher incidence of trauma (59.2%) compared with the general population. There were no differences in demographic and clinical measures between groups, suggesting that they were well matched. Although maladaptive drinking behaviors tended to be worse for the AUDs+TBI group, effect sizes were small and not statistically significant. Increased alcohol-cue reactivity was observed in bilateral anterior insula and orbitofrontal cortex, anterior cingulate cortex, medial prefrontal cortex, posterior cingulate cortex, dorsal striatum, thalamus, brainstem, and cerebellum across both groups relative to a carefully matched appetitive control. However, there were no significant differences in structural integrity or functional activation between AUDs+TBI and AUDs participants, even when controlling for AUD severity., Conclusions: Current results indicate that a combined history of mild or moderate TBI was not sufficient to alter drinking behaviors and/or underlying neurocircuitry at detectable levels relative to heavy drinking alone. Future studies should examine the potential long-term effects of combined alcohol and trauma on brain functioning., (Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

The past few years have seen an emergence of approaches that leverage temporal changes in whole-brain patterns of functional connectivity (the chronnectome). In this chronnectome study, we investigate the replicability of the human brain's inter-regional coupling dynamics during rest by evaluating two different dynamic functional network connectivity (dFNC) analysis frameworks using 7 500 functional magnetic resonance imaging (fMRI) datasets. To quantify the extent to which the emergent functional connectivity (FC) patterns are reproducible, we characterize the temporal dynamics by deriving several summary measures across multiple large, independent age-matched samples. Reproducibility was demonstrated through the existence of basic connectivity patterns (FC states) amidst an ensemble of inter-regional connections. Furthermore, application of the methods to conservatively configured (statistically stationary, linear and Gaussian) surrogate datasets revealed that some of the studied state summary measures were indeed statistically significant and also suggested that this class of null model did not explain the fMRI data fully. This extensive testing of reproducibility of similarity statistics also suggests that the estimated FC states are robust against variation in data quality, analysis, grouping, and decomposition methods. We conclude that future investigations probing the functional and neurophysiological relevance of time-varying connectivity assume critical importance., (Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.)

Introduction: Dynamic functional network connectivity (dFNC), derived from magnetic resonance imaging (fMRI), is an important technique in the search for biomarkers of brain diseases such as mild traumatic brain injury (mTBI). At the individual level, mTBI can affect cognitive functions and change personality traits. Previous research aimed at detecting significant changes in the dFNC of mTBI subjects. However, one of the main concerns in dFNC analysis is the appropriateness of methods used to correct for subject movement. In this work, we focus on the effect that rearranging movement correction at different points of the processing pipeline has in dFNC analysis utilizing mTBI data., Methods: The sample cohort consists of 50 mTBI patients and matched healthy controls. A 5-min resting-state run was completed by each participant. Data were preprocessed using different pipeline alternatives varying with the place where motion-related variance was removed. In all pipelines, group-independent component analysis (gICA) followed by dFNC analysis was performed. Additional tests were performed varying the detection of temporal spikes, the number of gICA components, and the sliding-window size. A linear support vector machine was used to test how each pipeline affects classification accuracy., Results: Results suggest that correction for motion variance before spatial smoothing, but leaving correction for spiky time courses after gICA produced the best mean classification performance. The number of gICA components and the sliding-window size were also important in determining classification performance. Variance in spikes correction affected some pipelines more than others with fewer significant differences than the other parameters., Conclusion: The sequence of preprocessing steps motion regression, smoothing, gICA, and despiking produced data most suitable for differentiating mTBI from healthy subjects. However, the selection of optimal preprocessing parameters strongly affected the final results.

Although diffusion magnetic resonance imaging (dMRI) has been widely used to characterize the effects of repetitive mild traumatic brain injury (rmTBI), to date no studies have investigated how novel geometric models of microstructure relate to more typical diffusion tensor imaging (DTI) sequences. Moreover, few studies have evaluated the sensitivity of different registration pipelines (non-linear, linear and tract-based spatial statistics) for detecting dMRI abnormalities in clinical populations. Results from single-subject analyses in healthy controls (HC) indicated a strong negative relationship between fractional anisotropy (FA) and orientation dispersion index (ODI) in both white and gray matter. Equally important, only moderate relationships existed between all other estimates of free/intracellular water volume fractions and more traditional DTI metrics (FA, mean, axial and radial diffusivity). These findings suggest that geometric measures provide differential information about the cellular microstructure relative to traditional DTI measures. Results also suggest greater sensitivity for non-linear registration pipelines that maximize the anatomical information available in T 1 -weighted images. Clinically, rmTBI resulted in a pattern of decreased FA and increased ODI, largely overlapping in space, in conjunction with increased intracellular and free water fractions, highlighting the potential role of edema following repeated head trauma. In summary, current results suggest that geometric models of diffusion can provide relatively unique information regarding potential mechanisms of pathology that contribute to long-term neurological damage.

Growing evidence suggests that sports-related concussions (SRC) may lead to acute changes in intrinsic functional connectivity, although most studies to date have been cross-sectional in nature with relatively modest sample sizes. We longitudinally assessed changes in local and global resting state functional connectivity using metrics that do not require a priori seed or network selection (regional homogeneity; ReHo and global brain connectivity; GBC, respectively). A large sample of collegiate athletes (N = 43) was assessed approximately one day (1.74 days post-injury, N = 34), one week (8.44 days, N = 34), and one month post-concussion (32.47 days, N = 30). Healthy contact sport-athletes served as controls (N = 51). Concussed athletes showed improvement in mood symptoms at each time point (p's < 0.05), but had significantly higher mood scores than healthy athletes at every time point (p's < 0.05). In contrast, self-reported symptoms and cognitive deficits improved over time following concussion (p's < 0.001), returning to healthy levels by one week post-concussion. ReHo in sensorimotor, visual, and temporal cortices increased over time post-concussion, and was greatest at one month post-injury. Conversely, ReHo in the frontal cortex decreased over time following SRC, with the greatest decrease evident at one month post-concussion. Differences in ReHo relative to healthy athletes were primarily observed at one month post-concussion rather than the more acute time points. Contrary to our hypothesis, no significant cross-sectional or longitudinal differences in GBC were observed. These results are suggestive of a delayed onset of local connectivity changes following SRC.

Resting state functional network connectivity (rsFNC) derived from functional magnetic resonance (fMRI) imaging is emerging as a possible biomarker to identify several brain disorders. Recently it has been pointed out that methods used to preprocess head motion variance might not fully remove all unwanted effects in the data. Proposed processing pipelines locate the treatment of head motion effects either close to the beginning or as one of the final steps. In this work, we assess several preprocessing pipelines applied in group independent component analysis (gICA) methods to study the rsFNC of the brain. The evaluation method utilizes patient/control classification performance based on linear support vector machines and leave-one-out cross validation. In addition, we explored group tests and correlation with severity measures in the patient population. We also tested the effect of removing high frequencies via filtering. Two real data cohorts were used: one consisting of 48 mTBI and one composed of 21 smokers, both with their corresponding matched controls. A simulation procedure was designed to test the classification power of each pipeline. Results show that data preprocessing can change the classification performance. In real data, regressing motion variance before gICA produced clearer group differences and stronger correlation with nicotine dependence., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Examination of intrinsic functional connectivity using functional MRI (fMRI) has provided important findings regarding dysconnectivity in schizophrenia. Extending these results using a complementary neuroimaging modality, magnetoencephalography (MEG), we present the first direct comparison of functional connectivity between schizophrenia patients and controls, using these two modalities combined. We developed a novel MEG approach for estimation of networks using MEG that incorporates spatial independent component analysis (ICA) and pairwise correlations between independent component timecourses, to estimate intra- and intern-network connectivity. This analysis enables group-level inference and testing of between-group differences. Resting state MEG and fMRI data were acquired from a large sample of healthy controls (n=45) and schizophrenia patients (n=46). Group spatial ICA was performed on fMRI and MEG data to extract intrinsic fMRI and MEG networks and to compensate for signal leakage in MEG. Similar, but not identical spatial independent components were detected for MEG and fMRI. Analysis of functional network connectivity (FNC; i.e., pairwise correlations in network (ICA component) timecourses) revealed a differential between-modalities pattern, with greater connectivity among occipital networks in fMRI and among frontal networks in MEG. Most importantly, significant differences between controls and patients were observed in both modalities. MEG FNC results in particular indicated dysfunctional hyperconnectivity within frontal and temporal networks in patients, while in fMRI FNC was always greater for controls than for patients. This is the first study to apply group spatial ICA as an approach to leakage correction, and as such our results may be biased by spatial leakage effects. Results suggest that combining these two neuroimaging modalities reveals additional disease-relevant patterns of connectivity that were not detectable with fMRI or MEG alone., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Objectives: Blast explosions are the most frequent mechanism of traumatic brain injury (TBI) in recent wars, but little is known about their long-term effects., Methods: Functional connectivity (FC) was measured in 17 veterans an average of 5.46 years after their most serious blast related TBI, and in 15 demographically similar veterans without TBI or blast exposure. Subcortical FC was measured in bilateral caudate, putamen, and globus pallidus. The default mode and fronto-parietal networks were also investigated., Results: In subcortical regions, between-groups t tests revealed altered FC from the right putamen and right globus pallidus. However, following analysis of covariance (ANCOVA) with age, depression (Center for Epidemiologic Studies Depression Scale), and posttraumatic stress disorder symptom (PTSD Checklist - Civilian version) measures, significant findings remained only for the right globus pallidus with anticorrelation in bilateral temporal occipital fusiform cortex, occipital fusiform gyrus, lingual gyrus, and cerebellum, as well as the right occipital pole. No group differences were found for the default mode network. Although reduced FC was found in the fronto-parietal network in the TBI group, between-group differences were nonsignificant after the ANCOVA., Conclusions: FC of the globus pallidus is altered years after exposure to blast related TBI. Future studies are necessary to explore the trajectory of changes in FC in subcortical regions after blast TBI, the effects of isolated versus repetitive blast-related TBI, and the relation to long-term outcomes in veterans. (JINS, 2016, 22, 631-642).

Objectives: One of the most prominent features of schizophrenia is relatively lower general cognitive ability (GCA). An emerging approach to understanding the roots of variation in GCA relies on network properties of the brain. In this multi-center study, we determined global characteristics of brain networks using graph theory and related these to GCA in healthy controls and individuals with schizophrenia., Methods: Participants (N=116 controls, 80 patients with schizophrenia) were recruited from four sites. GCA was represented by the first principal component of a large battery of neurocognitive tests. Graph metrics were derived from diffusion-weighted imaging., Results: The global metrics of longer characteristic path length and reduced overall connectivity predicted lower GCA across groups, and group differences were noted for both variables. Measures of clustering, efficiency, and modularity did not differ across groups or predict GCA. Follow-up analyses investigated three topological types of connectivity--connections among high degree "rich club" nodes, "feeder" connections to these rich club nodes, and "local" connections not involving the rich club. Rich club and local connectivity predicted performance across groups. In a subsample (N=101 controls, 56 patients), a genetic measure reflecting mutation load, based on rare copy number deletions, was associated with longer characteristic path length., Conclusions: Results highlight the importance of characteristic path lengths and rich club connectivity for GCA and provide no evidence for group differences in the relationships between graph metrics and GCA.

Functional magnetic resonance imaging (fMRI) of the blood oxygen level dependent (BOLD) response has commonly been used to investigate the neuropathology underlying cognitive and sensory deficits in patients with schizophrenia (SP) by examining the positive phase of the BOLD response, assuming a fixed shape for the hemodynamic response function (HRF). However, the individual phases (positive and post-stimulus undershoot (PSU)) of the HRF may be differentially affected by a variety of underlying pathologies. The current experiment used a multisensory detection task with a rapid event-related fMRI paradigm to investigate both the positive and PSU phases of the HRF in SP and healthy controls (HC). Behavioral results indicated no significant group differences during task performance. Analyses that examined the shape of the HRF indicated two distinct group differences. First, SP exhibited a reduced and/or prolonged PSU following normal task-related positive BOLD activation in secondary auditory and visual sensory areas relative to HC. Second, SP did not show task-induced deactivation in the anterior node of the default-mode network (aDMN) relative to HC. In contrast, when performing traditional analyses that focus on the positive phase, there were no group differences. Interestingly, the magnitude of the PSU in secondary auditory and visual areas was positively associated with the magnitude of task-induced deactivation within the aDMN, suggesting a possible common neural mechanism underlying both of these abnormalities (failure in neural inhibition). Results are consistent with recent views that separate neural processes underlie the two phases of the HRF and that they are differentially affected in SP. Hum Brain Mapp 37:745-755, 2016. © 2015 Wiley Periodicals, Inc., (© 2015 Wiley Periodicals, Inc.)

There is great interest in developing physiological-based biomarkers such as diffusion tensor imaging to aid in the management of concussion, which is currently entirely dependent on clinical judgment. However, the time course for recovery of white matter abnormalities following sports-related concussion (SRC) is unknown. We collected diffusion tensor imaging and behavioral data in forty concussed collegiate athletes on average 1.64 days (T1; n = 33), 8.33 days (T2; n = 30), and 32.15 days post-concussion (T3; n = 26), with healthy collegiate contact-sport athletes (HA) serving as controls (n = 46). We hypothesized that fractional anisotropy (FA) would be increased acutely and partially recovered by one month post-concussion. Mood symptoms were assessed using structured interviews. FA differences were assessed using both traditional and subject-specific analyses. An exploratory analysis of tau plasma levels was conducted in a subset of participants. Results indicated that mood symptoms improved over time post-concussion, but remained elevated at T3 relative to HA. Across both group and subject-specific analyses, concussed athletes exhibited increased FA in several white matter tracts at each visit post-concussion with no longitudinal evidence of recovery. Increased FA at T1 and T3 was significantly associated with an independent, real-world outcome measure for return-to-play. Finally, we observed a nonsignificant trend for reduced tau in plasma of concussed athletes at T1 relative to HA, with tau significantly increasing by T2. These results suggest white matter abnormalities following SRC may persist beyond one month and have potential as an objective biomarker for concussion outcome. Hum Brain Mapp 37:833-845, 2016. © 2015 Wiley Periodicals, Inc., (© 2015 Wiley Periodicals, Inc.)

Mild traumatic brain injury (mTBI) is the most common neurological disorder and is typically characterized by temporally limited cognitive impairment and emotional symptoms. Previous examinations of intrinsic resting state networks in mTBI have primarily focused on abnormalities in static functional connectivity, and deficits in dynamic functional connectivity have yet to be explored in this population. Resting-state data was collected on 48 semi-acute (mean = 14 days post-injury) mTBI patients and 48 matched healthy controls. A high-dimensional independent component analysis (N = 100) was utilized to parcellate intrinsic connectivity networks (ICN), with a priori hypotheses focusing on the default-mode network (DMN) and sub-cortical structures. Dynamic connectivity was characterized using a sliding window approach over 126 temporal epochs, with standard deviation serving as the primary outcome measure. Finally, distribution-corrected z-scores (DisCo-Z) were calculated to investigate changes in connectivity in a spatially invariant manner on a per-subject basis. Following appropriate correction for multiple comparisons, no significant group differences were evident on measures of static or dynamic connectivity within a priori ICN. Reduced (HC > mTBI patients) static connectivity was observed in the DMN at uncorrected (p < 0.005) thresholds. Finally, a trend (p = 0.07) for decreased dynamic connectivity in patients across all ICN was observed during spatially invariant analyses (DisCo-Z). In the semi-acute phase of recovery, mTBI was not reliably associated with abnormalities in static or dynamic functional connectivity within the DMN or sub-cortical structures.

Functional magnetic resonance imaging (fMRI) offers great promise for elucidating the neuropathology associated with a single or repetitive mild traumatic brain injury (mTBI). The current review discusses the physiological underpinnings of the blood-oxygen level dependent response and how trauma affects the signal. Methodological challenges associated with fMRI data analyses are considered next, followed by a review of current mTBI findings. The majority of evoked studies have examined working memory and attentional functioning, with results suggesting a complex relationship between cognitive load/attentional demand and neuronal activation. Researchers have more recently investigated how brain trauma affects functional connectivity, and the benefits/drawbacks of evoked and functional connectivity studies are also discussed. The review concludes by discussing the major clinical challenges associated with fMRI studies of brain-injured patients, including patient heterogeneity and variations in scan-time post-injury. We conclude that the fMRI signal represents a complex filter through which researchers can measure the physiological correlates of concussive symptoms, an important goal for the burgeoning field of mTBI research., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Efforts to identify meaningful functional imaging-based biomarkers are limited by the ability to reliably characterize inter-individual differences in human brain function. Although a growing number of connectomics-based measures are reported to have moderate to high test-retest reliability, the variability in data acquisition, experimental designs, and analytic methods precludes the ability to generalize results. The Consortium for Reliability and Reproducibility (CoRR) is working to address this challenge and establish test-retest reliability as a minimum standard for methods development in functional connectomics. Specifically, CoRR has aggregated 1,629 typical individuals' resting state fMRI (rfMRI) data (5,093 rfMRI scans) from 18 international sites, and is openly sharing them via the International Data-sharing Neuroimaging Initiative (INDI). To allow researchers to generate various estimates of reliability and reproducibility, a variety of data acquisition procedures and experimental designs are included. Similarly, to enable users to assess the impact of commonly encountered artifacts (for example, motion) on characterizations of inter-individual variation, datasets of varying quality are included.

Algorithms that are capable of capturing subject-specific abnormalities (SSA) in neuroimaging data have long been an area of focus for diverse neuropsychiatric conditions such as multiple sclerosis, schizophrenia, and traumatic brain injury. Several algorithms have been proposed that define SSA in patients (i.e., comparison group) relative to image intensity levels derived from healthy controls (HC) (i.e., reference group) based on extreme values. However, the assumptions underlying these approaches have not always been fully validated, and may be dependent on the statistical distributions of the transformed data. The current study evaluated variations of two commonly used techniques ("pothole" method and standardization with an independent reference group) for identifying SSA using simulated data (derived from normal, t and chi-square distributions) and fractional anisotropy maps derived from 50 HC. Results indicated substantial group-wise bias in the estimation of extreme data points using the pothole method, with the degree of bias being inversely related to sample size. Statistical theory was utilized to develop a distribution-corrected z-score (DisCo-Z) threshold, with additional simulations demonstrating elimination of the bias and a more consistent estimation of extremes based on expected distributional properties. Data from previously published studies examining SSA in mild traumatic brain injury were then re-analyzed using the DisCo-Z method, with results confirming the evidence of group-wise bias. We conclude that the benefits of identifying SSA in neuropsychiatric research are substantial, but that proposed SSA approaches require careful implementation under the different distributional properties that characterize neuroimaging data., (Copyright © 2014 Wiley Periodicals, Inc.)

Background: Altered functional connectivity in critical networks has been associated with chronic alcohol abuse. In turn, changes in connectivity in executive control networks (ECNs) may undermine the ability to control alcohol consumption. It was hypothesized that network connectivity would be reduced in individuals with problematic alcohol use (ALC) compared with controls and that diminished network connectivity would be associated with greater failure to control drinking., Methods: Resting-state functional magnetic resonance imaging was analyzed to identify 14 previously identified intrinsic connectivity networks (ICNs) using a priori regions of interest in cases ranging from binge drinkers to those with severe alcohol use disorder, as well as control subjects. Analyses tested for differences in network connectivity strength between 255 ALC cases and 87 age- and gender-matched controls. Further, structural equation analysis, using 383 ALC cases, tested whether functional connectivity strength mediated the relationship between years of regular drinking and alcohol problems., Results: The age- and gender-matched analysis showed that ALC had significantly lower network connectivity strength than controls in the left executive control (LECN), basal ganglia, and primary visual networks. For all ALC, LECN connectivity strength is negatively correlated with failed control and alcohol disorder severity. Edges connecting parietal regions with dorsolateral prefrontal, middle frontal, and temporal regions within the LECN drove these relationships. A positive association between years of drinking and severity of alcohol problems was mediated by reduced ECN connectivity., Conclusions: This study reports relationships between network strength and problematic alcohol use, suggesting that chronic drinking negatively impacts brain connectivity, specifically in the LECN. Altered functional connectivity, related to chronic alcohol abuse, may contribute to the etiology of alcohol dependence and relapse., (Copyright © 2014 by the Research Society on Alcoholism.)

The orienting of attention to the spatial location of sensory stimuli in one modality based on sensory stimuli presented in another modality (i.e., cross-modal orienting) is a common mechanism for controlling attentional shifts. The neuronal mechanisms of top-down cross-modal orienting have been studied extensively. However, the neuronal substrates of bottom-up audio-visual cross-modal spatial orienting remain to be elucidated. Therefore, behavioral and event-related functional magnetic resonance imaging (FMRI) data were collected while healthy volunteers (N = 26) performed a spatial cross-modal localization task modeled after the Posner cuing paradigm. Behavioral results indicated that although both visual and auditory cues were effective in producing bottom-up shifts of cross-modal spatial attention, reorienting effects were greater for the visual cues condition. Statistically significant evidence of inhibition of return was not observed for either condition. Functional results also indicated that visual cues with auditory targets resulted in greater activation within ventral and dorsal frontoparietal attention networks, visual and auditory "where" streams, primary auditory cortex, and thalamus during reorienting across both short and long stimulus onset asynchronys. In contrast, no areas of unique activation were associated with reorienting following auditory cues with visual targets. In summary, current results question whether audio-visual cross-modal orienting is supramodal in nature, suggesting rather that the initial modality of cue presentation heavily influences both behavioral and functional results. In the context of localization tasks, reorienting effects accompanied by the activation of the frontoparietal reorienting network are more robust for visual cues with auditory targets than for auditory cues with visual targets., (Copyright © 2013 Wiley Periodicals, Inc.)

Abstract Although several functional magnetic resonance imaging (fMRI) studies have been conducted in human models of mild traumatic brain injury (mTBI), to date no studies have explicitly examined how injury may differentially affect both the positive phase of the hemodynamic response function (HRF) as well as the post-stimulus undershoot (PSU). Animal models suggest that the acute and semi-acute stages of mTBI are associated with significant disruptions in metabolism and to the microvasculature, both of which could impact on the HRF. Therefore, fMRI data were collected on a cohort of 30 semi-acute patients with mTBI (16 males; 27.83±9.97 years old; 13.00±2.18 years of education) and 30 carefully matched healthy controls (HC; 16 males; 27.17±10.08 years old; 13.37±2.31 years of education) during a simple sensory-motor task. Patients reported increased cognitive, somatic, and emotional symptoms relative to controls, although no group differences were detected on traditional neuropsychological examination. There were also no differences between patients with mTBI and controls on fMRI data using standard analytic techniques, although mTBI exhibited a greater volume of activation during the task qualitatively. A significant Group×Time interaction was observed in the right supramarginal gyrus, bilateral primary and secondary visual cortex, and the right parahippocampal gyrus. The interaction was the result of an earlier time-to-peak and positive magnitude shift throughout the estimated HRF in patients with mTBI relative to HC. This difference in HRF shape combined with the greater volume of activated tissue may be indicative of a potential compensatory mechanism to injury. The current study demonstrates that direct examination and modeling of HRF characteristics beyond magnitude may provide additional information about underlying neuropathology that is not available with more standard fMRI analyses.

Enhanced motivational salience towards smoking cues is a consequence of chronic nicotine use, but the degree to which this value increases beyond that of other appetitive cues is unknown. In addition, it is unclear how connectivity between brain regions influences cue reactivity and how cue reactivity and functional connectivity are related to nicotine dependence severity. This study examined neural responses during the presentation of smoking cues and appetitive control cues, as well as functional connectivity in 116 smokers with a range of nicotine dependence severity. Smoking cues elicited greater response above baseline than food cues in orbitofrontal cortex (OFC) and supplementary motor area (SMA) and less deactivation below baseline in middle frontal gyrus, inferior parietal lobe, and middle temporal gyrus. Psychophysiological interaction (PPI) analysis using right OFC as a seed revealed increased connectivity with somatosensory cortex and lateral inferior parietal lobe during smoking cues compared with food cues. Similarly, a PPI analysis using left insula as a seed showed stronger connectivity with somatosensory cortex, right insula, OFC, and striatum. Finally, relationships with nicotine dependence scores showed enhanced response in insula and dorsal anterior cingulate cortex in the smoking vs food comparison, and increased connectivity between insula and circuits involved in motivated behavior. Combined, these results suggest that smokers engage attentional networks and default mode networks involved in self-referential processing to a greater degree during smoking cues. In addition, individuals with greater nicotine dependence severity show increased engagement of sensorimotor and motor preparation circuits, suggesting increased reliance on habitual behavior.

The cortical (auditory and prefrontal) and/or subcortical (thalamic and hippocampal) generators of abnormal electrophysiological responses during sensory gating remain actively debated in the schizophrenia literature. Functional magnetic resonance imaging has the spatial resolution for disambiguating deep or simultaneous sources but has been relatively under-utilized to investigate generators of the gating response. Thirty patients with chronic schizophrenia (SP) and 30 matched controls participated in the current experiment. Hemodynamic response functions (HRFs) for single (S1) and pairs (S1 + S2) of identical ("gating-out" redundant information) or nonidentical ("gating-in" novel information) tones were generated through deconvolution. Increased or prolonged activation for patients in conjunction with deactivation for controls was observed within auditory cortex, prefrontal cortex, and thalamus in response to single tones during the late hemodynamic response, and these group differences were not associated with clinical or cognitive symptomatology. Although patient hyperactivation to paired-tones conditions was present in several regions of interest, the effects were not statistically significant for either the gating-out or gating-in conditions. Finally, abnormalities in the postundershoot of the auditory HRF were also observed for both single and paired-tones conditions in patients. In conclusion, the amalgamation of the entire electrophysiological response to both S1 and S2 stimuli may limit hemodynamic sensitivity to paired tones during sensory gating, which may be more readily overcome by paradigms that use multiple stimuli rather than pairs. Patient hyperactivation following single tones is suggestive of deficits in basic inhibition, neurovascular abnormalities, or a combination of both factors., (Copyright © 2012 Wiley Periodicals, Inc., a Wiley company.)

Though previous examinations of intrinsic resting-state networks (RSNs) in healthy populations have consistently identified several RSNs that represent connectivity patterns evoked by cognitive and sensory tasks, the effects of different analytic approaches on the reliability and reproducibility of these RSNs have yet to be fully explored. Thus, the primary aim of the current study was to investigate the effect of method (independent component analyses [ICA] vs. seed-based analyses) on RSN reproducibility (independent datasets) for ICA and reliability (independent time points) in both methods using functional magnetic resonance imaging. Good to excellent reproducibility was observed in 9 out of 10 commonly identified RSNs, indicating the robustness of these intrinsic fluctuations at the group level. Reliability analyses showed that results were dependent on three main methodological factors: (1) group versus subject-level analyses (group>subject); (2) whether data from different visits were analyzed separately or jointly with ICA (combined>separate ICA); and (3) whether ICA output was used to directly assess reliability or to inform seed-based analyses (seed-based>ICA). These results suggest that variations in the analytic technique have a significant impact on individual reliability measurements, but do not significantly affect the reproducibility or reliability of RSNs at the group level. Further investigation into the effect of the analytic technique on RSN quantification is warranted to increase the utility of RSN analyses in clinical studies.

Pediatric mild traumatic brain injury (pmTBI) is the most prevalent neurological insult in children and is associated with both acute and chronic neurobehavioral sequelae. However, little is known about underlying pathophysiology and how injuries change as a function of recovery. Fractional anisotropy, axial diffusivity, and radial diffusivity were examined in 15 semi-acute pmTBI patients and 15 well-matched controls, with a subset of participants returning for a second visit. A novel analytic strategy was applied to capture spatially heterogeneous white matter injuries (lesions) in addition to standard analyses. Evidence of cognitive dysfunction after pmTBI was observed in the domains of attention (p = 0.02, d = -0.92) and processing speed (p = 0.05, d = -0.73) semi-acutely. Region of interest (ROI) and voxelwise analyses indicated increased anisotropic diffusion for pmTBI patients, with an elevated number of clusters with high anisotropy. Metrics of increased anisotropy were able to objectively classify pmTBI from healthy controls at 90% accuracy but were not associated with neuropsychological deficits. Little evidence of recovery in white matter abnormalities was observed over a 4-month interval in returning patients, indicating that physiological recovery may lag behind subjective reports of normality. Increased anisotropic diffusion has been previously linked with cytotoxic edema after TBI, and the magnitude and duration of these abnormalities appear to be greater in pediatric patients. Current findings suggest that developing white matter may be more susceptible to initial mechanical injury forces and that anisotropic diffusion provides an objective biomarker of pmTBI.

Previous work suggests that the ability to selectively attend to and resolve conflicting information may be the most enduring cognitive deficit following mild traumatic brain injury (mTBI). The current study used fMRI to evaluate potential differences in hemodynamic activation in 22 mTBI patients and 22 carefully matched healthy controls (HC) during a multimodal selective attention task (numeric Stroop). Behavioral data indicated faster reaction times for congruent versus incongruent trials and for stimuli presented at 0.66 compared to 0.33 Hz across both groups, with minimal differences in behavioral performance across the groups. Similarly, there were no group-wise differences in functional activation within lateral and medial prefrontal cortex during the execution of cognitive control (incongruent versus congruent trials). In contrast, within-group comparisons indicated robust patterns of attention-related modulations (ARM) within the bilateral dorsolateral prefrontal cortex and bilateral visual streams for HC but not mTBI patients. In addition, mTBI patients failed to exhibit task-induced deactivation within the default-mode network (DMN) under conditions of higher attentional load. In summary, in spite of near normal behavioral performance, current results suggest within-group abnormalities during both the top-down allocation of visual attention and in regulating the DMN during the semi-acute stage of mTBI.

Mild traumatic brain injury is the most prevalent neurological insult and frequently results in neurobehavioural sequelae. However, little is known about the pathophysiology underlying the injury and how these injuries change as a function of time. Although diffusion tensor imaging holds promise for in vivo characterization of white matter pathology, both the direction and magnitude of anisotropic water diffusion abnormalities in axonal tracts are actively debated. The current study therefore represents both an independent replication effort (n = 28) of our previous findings (n = 22) of increased fractional anisotropy during semi-acute injury, as well as a prospective study (n = 26) on the putative recovery of diffusion abnormalities. Moreover, new analytical strategies were applied to capture spatially heterogeneous white matter injuries, which minimize implicit assumptions of uniform injury across diverse clinical presentations. Results indicate that whereas a general pattern of high anisotropic diffusion/low radial diffusivity was present in various white matter tracts in both the replication and original cohorts, this pattern was only consistently observed in the genu of the corpus callosum across both samples. Evidence for a greater number of localized clusters with increased anisotropic diffusion was identified across both cohorts at trend levels, confirming heterogeneity in white matter injury. Pooled analyses (50 patients; 50 controls) suggested that measures of diffusion within the genu were predictive of patient classification, albeit at very modest levels (71% accuracy). Finally, we observed evidence of recovery in lesion load in returning patients across a 4-month interval, which was correlated with a reduction in self-reported post-concussive symptomatology. In summary, the corpus callosum may serve as a common point of injury in mild traumatic brain injury secondary to anatomical (high frequency of long unmyelinated fibres) and biomechanics factors. A spatially heterogeneous pattern of increased anisotropic diffusion exists in various other white matter tracts, and these white matter anomalies appear to diminish with recovery. This macroscopic pattern of diffusion abnormalities may be associated with cytotoxic oedema following mechanical forces, resulting in changes in ionic homeostasis, and alterations in the ratio of intracellular and extracellular water. Animal models more specific to the types of mild traumatic brain injury typically incurred by humans are needed to confirm the histological correlates of these macroscopic markers of white matter pathology.

The resting state amplitude of low frequency fluctuations (ALFF) in functional magnetic resonance imaging has been shown to be reliable in healthy subjects, and to correlate with antipsychotic treatment response in antipsychotic-naïve schizophrenia patients. We found moderate to high test-retest stability of ALFF in chronically treated schizophrenia patients assessed twice over a median interval of 2.5 months., (Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.)

A 1H magnetic resonance spectroscopic imaging study at 3T and short echo time was conducted to evaluate both the reproducibility, as measured by the interscan coefficient of variation (CV), and test-retest reliability, as measured by the intraclass correlation coefficient (ICC), of measurements of glutamate (Glu), combined glutamate and glutamine (Glx), myo-inositol (mI), N-acetylaspartate, creatine, and choline in 21 healthy subjects. The effect of partial volume correction on these measures and the relationship of reproducibility and reliability to data quality were also examined. A 1H magnetic resonance spectroscopic imaging slice was prescribed above the lateral ventricles and single repeat scans were performed within 30 min to minimize physiologic variability. Interscan CVs based on all the voxels varied from 0.05 to 0.07 for N-acetylaspartate, creatine, and choline to 0.10-0.13 for mI, Glu, and Glx. Findings on the reproducibility of gray and white matter estimates of N-acetylaspartate, creatine, and choline are consistent with previous studies using longer echo times, with CVs in the range of 0.02-0.04 and ICC in the range of 0.65-0.90. CVs for Glu, Glx, and mI are much lower than reported in previous studies at 1.5 T, while white matter mI (CV=0.04, ICC=0.93) and gray matter Glx (CV=0.04, ICC=0.68) demonstrated both high reproducibility and test-retest reliability., (Copyright © 2011 Wiley-Liss, Inc.)

Changes in the default mode network (DMN) have been linked to multiple neurological disorders including schizophrenia. The anticorrelated relationship the DMN shares with task-related networks permits the quantification of this network both during task (task-induced deactivations: TID) and during periods of passive mental activity (extended rest). However, the effects of different methodologies (TID vs. extended rest) for quantifying the DMN in the same clinical population are currently not well understood. Moreover, several different analytic techniques, including independent component analyses (ICA) and seed-based correlation analyses, exist for examining functional connectivity during extended resting states. The current study compared both methodologies and analytic techniques in a group of patients with schizophrenia (SP) and matched healthy controls. Results indicated that TID analyses, ICA, and seed-based correlation all consistently identified the midline (anterior and posterior cingulate gyrus) and lateral parietal cortex as core regions of the DMN, as well as more variable involvement of temporal lobe structures. In addition, SP exhibited increased deactivation during task, as well as decreased functional connectivity with frontal regions and increased connectivity with posterior and subcortical areas during periods of extended rest. The increased posterior and reduced anterior connectivity may partially explain some of the cognitive dysfunction and clinical symptoms that are frequently associated with schizophrenia., (2009 Wiley-Liss, Inc.)

The semiacute phase of mild traumatic brain injury (mTBI) is associated with deficits in the cognitive domains of attention, memory, and executive function, which previous work suggests may be related to a specific deficit in disengaging attentional focus. However, to date, there have only been a few studies that have employed dynamic imaging techniques to investigate the potential neurological basis of these cognitive deficits during the semiacute stage of injury. Therefore, event-related functional magnetic resonance imaging was used to investigate the neurological correlates of attentional dysfunction in a clinically homogeneous sample of 16 patients with mTBI during the semiacute phase of injury (<3 weeks). Behaviorally, patients with mTBI exhibited deficits in disengaging and reorienting auditory attention following invalid cues as well as a failure to inhibit attentional allocation to a cued spatial location compared to a group of matched controls. Accordingly, patients with mTBI also exhibited hypoactivation within thalamus, striatum, midbrain nuclei, and cerebellum across all trials as well as hypoactivation in the right posterior parietal cortex, presupplementary motor area, bilateral frontal eye fields, and right ventrolateral prefrontal cortex during attentional disengagement. Finally, the hemodynamic response within several regions of the attentional network predicted response times better for controls than for patients with mTBI. These objective neurological findings represent a potential biomarker for the behavioral deficits in spatial attention that characterize the initial recovery phase of mTBI., (2009 Wiley-Liss, Inc.)

Single-voxel proton magnetic resonance imaging ((1)H-MRS) and proton MR spectroscopic imaging ((1)H-MRSI) were used to compare brain metabolite levels in semi-acute mild traumatic brain injury (mTBI) patients (n = 10) and matched healthy controls (n = 9). The (1)H-MRS voxel was positioned in the splenium, a region known to be susceptible to axonal injury in TBI, and a single (1)H-MRSI slice was positioned above the lateral ventricles. To increase sensitivity to the glutamate (Glu) and the combined glutamate-glutamine (Glx) signal, an inter-pulse echo time shown to emphasize the major Glu signals was used along with an analysis method that reduces partial volume errors by using water as a concentration standard. Our preliminary findings indicate significantly lower levels of gray matter Glx and higher levels of white matter creatine-phosphocreatine (Cr) in mTBI subjects relative to healthy controls. Furthermore, Cr levels were predictive of executive function and emotional distress in the combined groups. These results suggest that perturbations in Cr, a critical component of the brain's energy metabolism, and Glu, the brain's major neurotransmitter, may occur following mTBI. Moreover, the different pattern of results for gray and white matter suggests tissue-specific metabolic responses to mTBI.

There has been a growing interest in the neuroimaging community regarding resting state data (i.e., passive mental activity) and the subsequent activation of the so-called default mode network (DMN). Although this network was originally characterized by a pattern of deactivation during active cognitive states, more recent applications of data-driven techniques such as independent component analysis (ICA) have permitted the analysis of brain activation during extended periods of truly passive mental activity. However, ICA requires the resultant components to be evaluated for "goodness of fit" via either human raters or more automated techniques. To our knowledge, an investigation on the reliability of either technique in determining the component that best corresponds to default-mode activity has not been performed. Moreover, it is not clear how automated techniques, which are necessarily dependent upon a template mask, are affected by the structures used to compose the mask. The current study investigated both interrater (human-human) reliability and intermethod (human-machine) reliability for determining DMN activation in 42 healthy controls. Results indicated that near perfect interrater reliability was achieved, whereas intermethod reliability was only within the moderate range. The latter was significantly improved via a weighted combination of the anterior and posterior cingulate nodes of the DMN. Implications for fully automating the component selection process are discussed., (Copyright 2009 Wiley-Liss, Inc)

Background: Functional magnetic resonance imaging (FMRI) studies comparing schizophrenia patients and controls may have been confounded by the vascular effects of heavier long-term cigarette use in patients., Methods: The blood oxygen level dependent (BOLD) response to a simple sensorimotor task was compared between schizophrenia patient with a smoking history (mean 17 pack years) and carefully matched patient non-smokers and control non-smokers., Results: Group differences in activation magnitude and spatial extent were non-significant., Conclusions: Typical smoking histories in schizophrenia patients do not significantly confound FMRI results in simple sensorimotor tasks when patient demographics are carefully controlled.

Although functional magnetic resonance imaging (FMRI) has arguably become the most ubiquitously used imaging modality, questions remain about the reproducibility of the observed patterns of activation and the acquisition time required to achieve statistically significant and reproducible maps. In the current study, we investigated the reliability of activation in Broca's area, on both a voxel-wise and region of interest level, in response to the covert generation of a single word at 4 T. We also assessed the effects of different parametric (P < 0.01; P < 0.005; P < 0.001) and spatial thresholds (25%, 50% and 75%) on the reproducibility of activation within our region of interest and other randomly selected areas of the brain. We report that the inter-trial consistency of activation within Broca's area for a single trial design using multi-echo EPI is roughly equivalent to previous studies that averaged across a much larger number of trials. However, reliability estimates varied dramatically (approximately 55%) depending on the different parametric and spatial criteria thresholds that were applied to the data. These results show that increased sensitivity at high field strength can be used to reduce the time needed to localize functional activation patterns, which is beneficial for clinical studies such as pre-surgical mapping. Additional benefits of single trial designs, such as the ability to immediately assess for extraneous cognitive processes, are also discussed.

Auditory information communicated through vocalizations, music, or sounds in the environment is commonly used to orient and direct attention to different locations in extrapersonal space. The neural networks subserving attention to auditory space remain poorly understood in comparison to our knowledge about attention in the visual system. The present study investigated whether a parietal-prefrontal right-hemisphere network controls endogenous orienting and reorienting of attention to the location of sounds just as it does for visual-spatial information. Seventeen healthy adults underwent event-related functional magnetic resonance imaging (FMRI) while performing an endogenous auditory orienting task, in which peripheral cues correctly (valid) or incorrectly (invalid) specified the location of a forthcoming sound. The results showed that a right precuneus and bilateral temporal-frontal network mediated the reorienting of auditory attention at both short and long stimulus onset asynchronies (SOAs). In contrast, the more automatic stage of auditory reorienting at the shorter SOA was associated with activation in a bilateral inferior parietal-frontal oculomotor network. These findings suggest that the reorienting of auditory attention is generally supported by a similar inferior parietal-frontal network as visual attention, but in both hemispheres. However, peripheral auditory cues also appear to elicit an automatic orienting response to the spatial location of a sound followed by a period of reduced processing of information that occurs in the same location later in time.

Our perception of time depends on multiple psychological processes that allow us to anticipate events. In this study, we used event-related functional magnetic resonance imaging (fMRI) to differentiate neural systems involved in formulating representations of time from processes associated with making decisions about their duration. A time perception task consisting of two randomly presented standard intervals was used to ensure that intervals were encoded on each trial and to enhance memory requirements. During the encoding phase of a trial, activation was observed in the right caudate nucleus, right inferior parietal cortex and left cerebellum. Activation in these regions correlated with timing sensitivity (coefficient of variation). In contrast, encoding-related activity in the right parahippocampus and hippocampus correlated with the bisection point and right precuneus activation was associated with a measure of memory distortion. Decision processes were studied by examining brain activation during the decision phase of a trial that was associated with the difficulty of interval discriminations. Activation in the right parahippocampus was greater for easier than harder discriminations. In contrast, activation was greater for harder than easier discriminations in systems involved in working memory (left middle-frontal and parietal cortex) and auditory rehearsal (left inferior-frontal and superior-temporal cortex). Activity in the auditory rehearsal network correlated with memory distortion. Our results support the independence of systems that mediate interval encoding and decision processes. The results also suggest that distortions in memory for time may be due to strategic processing in cortical systems involved in either encoding or rehearsal.

Studies in brain damaged patients conclude that the left hemisphere is dominant for controlling heterogeneous sequences performed by either hand, presumably due to the cognitive resources involved in planning complex sequential movements. To determine if this lateralized effect is due to asymmetries in primary sensorimotor or association cortex, whole-brain functional magnetic resonance imaging was used to measure differences in volume of activation while healthy right-handed subjects performed repetitive (simple) or heterogeneous (complex) finger sequences using the right or left hand. Advanced planning, as evidenced by reaction time to the first key press, was greater for the complex than simple sequences and for the left than right hand. In addition to the expected greater contralateral activation in the sensorimotor cortex (SMC), greater left hemisphere activation was observed for left, relative to right, hand movements in the ipsilateral left superior parietal area and for complex, relative to simple, sequences in the left premotor and parietal cortex, left thalamus, and bilateral cerebellum. No such volumetric asymmetries were observed in the SMC. Whereas the overall MR signal intensity was greater in the left than right SMC, the extent of this asymmetry did not vary with hand or complexity level. In contrast, signal intensity in the parietal and premotor cortex was greater in the left than right hemisphere and for the complex than simple sequences. Signal intensity in the caudal anterior cerebellum was greater bilaterally for the complex than simple sequences. These findings suggest that activity in the SMC is associated with execution requirements shared by the simple and complex sequences independent of their differential cognitive requirements. In contrast, consistent with data in brain damaged patients, the left dorsal premotor and parietal areas are engaged when advanced planning is required to perform complex motor sequences that require selection of different effectors and abstract organization of the sequence, regardless of the performing hand.

Background and Purpose: Verbal working memory (VWM) deficits have been a well-replicated finding among patients with multiple sclerosis (MS). Functional magnetic resonance imaging (FMRI) studies have described a VWM system in healthy samples; however, functional neuroimaging of this system among MS patients is just beginning to appear., Methods: Fifteen MS patients and 15 sex-, age-, education-, and IQ-matched healthy control (HC) participants completed a 2-Back VWM task as whole-brain FMRI was conducted., Results: Each group exhibited increased brain activity compared to the O-Back control task in regions associated with the 2-Back in previous neuroimaging studies. These included Broca's area, supplementary motor area (SMA), premotor cortices (PMC), and dorsolateral prefrontal cortices (DLPFC). MS patients exhibited greater cortical activity than did HC participants in left primary motor and somatosensory cortices, PMC, DLPFC, anterior cingulate, and bilateral SMA. MS patients exhibited relatively less activation in Broca's area, bilateral cerebellum, and other regions not typically associated with the 2-Back (e.g., right fusiform gyrus, left lingual gyrus, right hippocampus). Performance accuracy and reaction time did not differ between groups., Conclusions: Normal performance of a challenging VWM task among high-functioning MS patients is associated with a shift toward greater activity in regions related to sensorimotor functions and anterior attentional/executive components of the VWM system. Posterior memory storage systems appeared unaffected, while portions of the visual processing and subvocal rehearsal systems were less active. Although a shift in neural activity was noted relative to HC participants, deviation from regions normally involved in VWM function was not observed in this patient sample.

Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.

Brain functional networks identified from fMRI data can provide potential biomarkers for brain disorders. Group independent component analysis (GICA) is popular for extracting brain functional networks from multiple subjects. In GICA, different strategies exist for reconstructing subject-specific networks from the group-level networks. However, it is unknown whether these strategies have different sensitivities to group differences and abilities in distinguishing patients. Among GICA, spatio-temporal regression (STR) and spatially constrained ICA approaches such as group information guided ICA (GIG-ICA) can be used to propagate components (indicating networks) to a new subject that is not included in the original subjects. In this study, based on the same a priori network maps, we reconstructed subject-specific networks using these two methods separately from resting-state fMRI data of 151 schizophrenia patients (SZs) and 163 healthy controls (HCs). We investigated group differences in the estimated functional networks and the functional network connectivity (FNC) obtained by each method. The networks were also used as features in a cross-validated support vector machine (SVM) for classifying SZs and HCs. We selected features using different strategies to provide a comprehensive comparison between the two methods. GIG-ICA generally showed greater sensitivity in statistical analysis and better classification performance (accuracy 76.45 ± 8.9%, sensitivity 0.74 ± 0.11, specificity 0.79 ± 0.11) than STR (accuracy 67.45 ± 8.13%, sensitivity 0.65 ± 0.11, specificity 0.71 ± 0.11). Importantly, results were also consistent when applied to an independent dataset including 82 HCs and 82 SZs. Our work suggests that the functional networks estimated by GIG-ICA are more sensitive to group differences, and GIG-ICA is promising for identifying image-derived biomarkers of brain disease.

Timing is crucial to many aspects of human performance. To better understand its neural underpinnings, we used event-related fMRI to examine the time course of activation associated with different components of a time perception task. We distinguished systems associated with encoding time intervals from those related to comparing intervals and implementing a response. Activation in the basal ganglia occurred early, and was uniquely associated with encoding time intervals, whereas cerebellar activation unfolded late, suggesting an involvement in processes other than explicit timing. Early cortical activation associated with encoding of time intervals was observed in the right inferior parietal cortex and bilateral premotor cortex, implicating these systems in attention and temporary maintenance of intervals. Late activation in the right dorsolateral prefrontal cortex emerged during comparison of time intervals. Our results illustrate a dynamic network of cortical-subcortical activation associated with different components of temporal information processing.

Background: Functional underpinnings of cognitive control deficits in unbiased samples (i.e., all comers) of patients with psychotic spectrum disorders (PSD) remain actively debated. While many studies suggest hypofrontality in the lateral prefrontal cortex (PFC) and greater deficits during proactive relative to reactive control, few have examined the full hemodynamic response. Methods: Patients with PSD (n = 154) and healthy controls (n = 65) performed the AX continuous performance task (AX-CPT) during rapid (460 ms) functional neuroimaging and underwent full clinical characterization. Results: Behavioural results indicated generalized cognitive deficits (slower and less accurate) across proactive and reactive control conditions in patients with PSD relative to healthy controls. We observed a delayed/prolonged neural response in the left dorsolateral PFC, the sensorimotor cortex and the superior parietal lobe during proactive control for patients with PSD. These proactive hemodynamic abnormalities were better explained by negative rather than by positive symptoms or by traditional diagnoses according to the Diagnostic and Statistical Manual of Mental Disorders Fourth Edition, Text Revision (DSM-IV-TR), with subsequent simulations unequivocally demonstrating how these abnormalities could be erroneously interpreted as hypoactivation. Conversely, true hypoactivity, unassociated with clinical symptoms or DSM-IV-TR diagnoses, was observed within the ventrolateral PFC during reactive control. Limitations: In spite of guidance for AX-CPT use in neuroimaging studies, one-third of patients with PSD could not perform the task above chance and were more clinically impaired. Conclusion: Current findings question the utility of the AX-CPT for neuroimaging-based appraisal of cognitive control across the full spectrum of patients with PSD. Previously reported lateral PFC "hypoactivity" during proactive control may be more indicative of a delayed/prolonged neural response, important for rehabilitative purposes. Negative symptoms may better explain certain behavioural and hemodynamic abnormalities in patients with PSD relative to DSM-IV-TR diagnoses. [ABSTRACT FROM AUTHOR]