Joshua S. Siegel

Statistical Improvements in Functional Magnetic Resonance Imaging Analyses Produced by Censoring High-Motion Data Points

Subject motion degrades the quality of task functional magnetic resonance imaging (fMRI) data. Here, we test two classes of methods to counteract the effects of motion in task fMRI data: (1) a variety of motion regressions and (2) motion censoring (“motion scrubbing”). In motion regression, various regressors based on realignment estimates were included as nuisance regressors in general linear model (GLM) estimation. In motion censoring, volumes in which head motion exceeded a threshold were withheld from GLM estimation. The effects of each method were explored in several task fMRI data sets and compared using indicators of data quality and signal‐to‐noise ratio. Motion censoring decreased variance in parameter estimates within‐ and across‐subjects, reduced residual error in GLM estimation, and increased the magnitude of statistical effects. Motion censoring performed better than all forms of motion regression and also performed well across a variety of parameter spaces, in GLMs with assumed or unassumed response shapes. We conclude that motion censoring improves the quality of task fMRI data and can be a valuable processing step in studies involving populations with even mild amounts of head movement. Hum Brain Mapp 35:1981–1996, 2014.

Disruptions of network connectivity predict impairment in multiple behavioral domains after stroke

Significance Since the early days of neuroscience, the relative merit of structural vs. functional network accounts in explaining neurological deficits has been intensely debated. Using a large stroke cohort and a machine-learning approach, we show that visual memory and verbal memory deficits are better predicted by functional connectivity than by lesion location, and visual and motor deficits are better predicted by lesion location than functional connectivity. In addition, we show that disruption to a subset of cortical areas predicts general cognitive deficit (spanning multiple behavior domains). These results shed light on the complementary value of structural vs. functional accounts of stroke, and provide a physiological mechanism for general multidomain deficits seen after stroke. Deficits following stroke are classically attributed to focal damage, but recent evidence suggests a key role of distributed brain network disruption. We measured resting functional connectivity (FC), lesion topography, and behavior in multiple domains (attention, visual memory, verbal memory, language, motor, and visual) in a cohort of 132 stroke patients, and used machine-learning models to predict neurological impairment in individual subjects. We found that visual memory and verbal memory were better predicted by FC, whereas visual and motor impairments were better predicted by lesion topography. Attention and language deficits were well predicted by both. Next, we identified a general pattern of physiological network dysfunction consisting of decrease of interhemispheric integration and intrahemispheric segregation, which strongly related to behavioral impairment in multiple domains. Network-specific patterns of dysfunction predicted specific behavioral deficits, and loss of interhemispheric communication across a set of regions was associated with impairment across multiple behavioral domains. These results link key organizational features of brain networks to brain–behavior relationships in stroke.

The effects of hemodynamic lag on functional connectivity and behavior after stroke

Stroke disrupts the brain’s vascular supply, not only within but also outside areas of infarction. We investigated temporal delays (lag) in resting state functional magnetic resonance imaging signals in 130 stroke patients scanned two weeks, three months and 12 months post stroke onset. Thirty controls were scanned twice at an interval of three months. Hemodynamic lag was determined using cross-correlation with the global gray matter signal. Behavioral performance in multiple domains was assessed in all patients. Regional cerebral blood flow and carotid patency were assessed in subsets of the cohort using arterial spin labeling and carotid Doppler ultrasonography. Significant hemodynamic lag was observed in 30% of stroke patients sub-acutely. Approximately 10% of patients showed lag at one-year post-stroke. Hemodynamic lag corresponded to gross aberrancy in functional connectivity measures, performance deficits in multiple domains and local and global perfusion deficits. Correcting for lag partially normalized abnormalities in measured functional connectivity. Yet post-stroke FC–behavior relationships in the motor and attention systems persisted even after hemodynamic delays were corrected. Resting state fMRI can reliably identify areas of hemodynamic delay following stroke. Our data reveal that hemodynamic delay is common sub-acutely, alters functional connectivity, and may be of clinical importance.

Dissociated functional connectivity profiles for motor and attention deficits in acute right-hemisphere stroke

Strokes often cause multiple behavioural deficits that are correlated at the population level. Here, we show that motor and attention deficits are selectively associated with abnormal patterns of resting state functional connectivity in the dorsal attention and motor networks. We measured attention and motor deficits in 44 right hemisphere-damaged patients with a first-time stroke at 1-2 weeks post-onset. The motor battery included tests that evaluated deficits in both upper and lower extremities. The attention battery assessed both spatial and non-spatial attention deficits. Summary measures for motor and attention deficits were identified through principal component analyses on the raw behavioural scores. Functional connectivity in structurally normal cortex was estimated based on the temporal correlation of blood oxygenation level-dependent signals measured at rest with functional magnetic resonance imaging. Any correlation between motor and attention deficits and between functional connectivity in the dorsal attention network and motor networks that might spuriously affect the relationship between each deficit and functional connectivity was statistically removed. We report a double dissociation between abnormal functional connectivity patterns and attention and motor deficits, respectively. Attention deficits were significantly more correlated with abnormal interhemispheric functional connectivity within the dorsal attention network than motor networks, while motor deficits were significantly more correlated with abnormal interhemispheric functional connectivity patterns within the motor networks than dorsal attention network. These findings indicate that functional connectivity patterns in structurally normal cortex following a stroke link abnormal physiology in brain networks to the corresponding behavioural deficits.

Normalization of network connectivity in hemispatial neglect recovery

We recently reported that spatial and nonspatial attention deficits in stroke patients with hemispatial neglect are correlated at 2 weeks postonset with widespread alterations of interhemispheric and intrahemispheric functional connectivity (FC) measured with resting‐state functional magnetic resonance imaging across multiple brain networks. The mechanisms underlying neglect recovery are largely unknown. In this study, we test the hypothesis that recovery of hemispatial neglect correlates with a return of network connectivity toward a normal pattern, herein defined as “network normalization.”

Tasks Driven by Perceptual Information Do Not Recruit Sustained BOLD Activity in Cingulo-Opercular Regions

Sustained blood oxygen level dependent (BOLD) signal in the dorsal anterior cingulate cortex/medial superior frontal cortex (dACC/msFC) and bilateral anterior insula/frontal operculum (aI/fO) is found in a broad majority of tasks examined and is believed to function as a putative task set maintenance signal. For example, a meta-analysis investigating task-control signals identified the dorsal anterior cingulate cortex and anterior insula as exhibiting sustained activity across a variety of task types. Re-analysis of tasks included in that meta-analysis showed exceptions, suggesting that tasks where the information necessary to determine a response was present in the stimulus (i.e., perceptually driven) does not show strong sustained cingulo-opercular activity. In a new experiment, we tested the generality of this observation while addressing alternative explanations about sustained cingulo-opercular activity (including task difficulty and verbal vs. non-verbal task demands). A new, difficult, perceptually driven task was compared with 2 new tasks that depended on information beyond that provided by the stimulus. The perceptually driven task showed a lack of cingulo-opercular activity in contrast to the 2 newly constructed tasks. This finding supports the idea that sustained cingulo-opercular activity contributes to maintenance of task set in only a subset of tasks.

The circuitry of abulia: insights from functional connectivity MRI.

Background Functional imaging and lesion studies have associated willed behavior with the anterior cingulate cortex (ACC). Abulia is a syndrome characterized by apathy and deficiency of motivated behavior. Abulia is most frequently associated with ACC damage, but also occurs following damage to subcortical nuclei (striatum, globus pallidus, thalamic nuclei). We present resting state functional connectivity MRI (fcMRI) data from an individual who suffered a stroke leading to abulia. We hypothesized that, although structural imaging revealed no damage to the patients ACC, fcMRI would uncover aberrant function in this region and in the relevant cortical networks. Methods Resting state correlations in the patients gray matter were compared to those of age-matched controls. Using a novel method to identify abnormal patterns of functional connectivity in single subjects, we identified areas and networks with aberrant connectivity. Results Networks associated with memory (default mode network) and executive function (cingulo-opercular network) were abnormal. The patients anterior cingulate was among the areas showing aberrant functional connectivity. In a rescan 3 years later, deficits remained stable and fcMRI findings were replicated. Conclusions These findings suggest that the aberrant functional connectivity mapping approach described may be useful for linking stroke symptoms to disrupted network connectivity.

Brain connectivity and neurological disorders after stroke

PURPOSE OF REVIEW An important challenge in neurology is identifying the neural mechanisms underlying behavioral deficits after brain injury. Here, we review recent advances in understanding the effects of focal brain lesions on brain networks and behavior. RECENT FINDINGS Neuroimaging studies indicate that the human brain is organized in large-scale resting state networks (RSNs) defined via functional connectivity, that is the temporal correlation of spontaneous activity between different areas. Prior studies showed that focal brain lesion induced behaviorally relevant changes of functional connectivity beyond the site of damage. Recent work indicates that across domains, functional connectivity changes largely conform to two patterns: a reduction in interhemispheric functional connectivity and an increase in intrahemispheric functional connectivity between networks that are normally anticorrelated, for example dorsal attention and default networks. Abnormal functional connectivity can exhibit a high degree of behavioral specificity such that deficits in a given behavioral domain are selectively related to functional connectivity of the corresponding RSN, but some functional connectivity changes allow prediction across domains. Finally, as behavioral recovery proceeds, the prestroke pattern of functional connectivity is restored. SUMMARY Investigating changes in RSNs may shed light on the neural mechanisms underlying brain dysfunction after stroke. Therefore, resting state functional connectivity may represent an important tool for clinical diagnosis, tracking recovery and rehabilitation.

Measuring functional connectivity in stroke: Approaches and considerations

Recent research has demonstrated the importance of global changes to the functional organization of brain network following stroke. Resting functional magnetic resonance imaging (R-fMRI) is a non-invasive tool that enables the measurement of functional connectivity (FC) across the entire brain while placing minimal demands on the subject. For these reasons, it is a uniquely appealing tool for studying the distant effects of stroke. However, R-fMRI studies rely on a number of premises that cannot be assumed without careful validation in the context of stroke. Here, we describe strategies to identify and mitigate confounds specific to R-fMRI research in cerebrovascular disease. Five main topics are discussed: (a) achieving adequate co-registration of lesioned brains, (b) identifying and removing hemodynamic lags in resting BOLD, (c) identifying other vascular disruptions that affect the resting BOLD signal, (d) selecting an appropriate control cohort, and (e) acquiring sufficient fMRI data to reliably identify FC changes. For each topic, we provide guidelines for steps to improve the interpretability and reproducibility of FC-stroke research. We include a table of confounds and approaches to identify and mitigate each. Our recommendations extend to any research using R-fMRI to study diseases that might alter cerebrovascular flow and dynamics or brain anatomy.

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