Erik B. Beall

Resting state sensorimotor functional connectivity in multiple sclerosis inversely correlates with transcallosal motor pathway transverse diffusivity.

Recent studies indicate that functional connectivity using low‐frequency BOLD fluctuations (LFBFs) is reduced between the bilateral primary sensorimotor regions in multiple sclerosis. In addition, it has been shown that pathway‐dependent measures of the transverse diffusivity of water in white matter correlate with related clinical measures of functional deficit in multiple sclerosis. Taken together, these methods suggest that MRI methods can be used to probe both functional connectivity and anatomic connectivity in subjects with known white matter impairment. We report the results of a study comparing anatomic connectivity of the transcallosal motor pathway, as measured with diffusion tensor imaging (DTI) and functional connectivity of the bilateral primary sensorimotor cortices (SMC), as measured with LFBFs in the resting state. High angular resolution diffusion imaging was combined with functional MRI to define the transcallosal white matter pathway connecting the bilateral primary SMC. Maps were generated from the probabilistic tracking employed and these maps were used to calculate the mean pathway diffusion measures fractional anisotropy 〈FA〉, mean diffusivity 〈MD〉, longitudinal diffusivity 〈λ1〉, and transverse diffusivity 〈λ2〉. These were compared with LFBF‐based functional connectivity measures (Fc) obtained at rest in a cohort of 11 multiple sclerosis patients and ∼10 age‐ and gender‐matched control subjects. The correlation between 〈FA〉 and Fc for MS patients was r = −0.63, P < 0.04. The correlation between all subjects 〈λ2〉 and Fc was r = 0.42, P < 0.05. The correlation between all subjects 〈λ2〉 and Fc was r = −0.50, P < 0.02. None of the control subject correlations were significant, nor were 〈FA〉, 〈λ1〉, or 〈MD〉 significantly correlated with Fc for MS patients. This constitutes the first in vivo observation of a correlation between measures of anatomic connectivity and functional connectivity using spontaneous LFBFs. Hum Brain Mapp, 2008.

Isolating physiologic noise sources with independently determined spatial measures

To properly account for the presence of physiologic noise in fMRI data, parallel measurement of pulse and respiratory data is necessary. In some cases, this parallel measurement is difficult or impossible due to the experimental paradigm or lack of available monitoring equipment. We present a robust method for determining the direct-sampled pulse and respiratory data for a subject from the fMRI data itself, utilizing an independently determined spatial weighting matrix. It is shown that temporal independent component analysis can reliably separate the spatial and temporal patterns of physiologic noise through correlation if the parallel measurement is made. The spatial patterns thus determined can be applied to a separate scan of the same subject to produce the temporal pattern specific to this independent scan. The robustness of this method leads to the more general method of creating spatial weight matrices in standard brain space averaged over multiple subjects in order to acquire the physiologic signals without the necessity of any (further) parallel measurements. The resulting cardiac and respiratory estimators can effectively be used in a manner similar to that of a direct-sampled physiologic signal, e.g., direct input to retrospective correction methods, evaluation of cardiac and respiratory effects of tasks, etc. Spatial mixing matrices for estimating cardiac and respiratory sources for the acquisition protocols described here (and others as they are developed) are offered to investigators and can be obtained through e-mail from the corresponding author.

Neural activation during response inhibition differentiates blast from mechanical causes of mild to moderate traumatic brain injury.

Military personnel involved in Operations Enduring Freedom and Iraqi Freedom (OEF/OIF) commonly experience blast-induced mild to moderate traumatic brain injury (TBI). In this study, we used task-activated functional MRI (fMRI) to determine if blast-related TBI has a differential impact on brain activation in comparison with TBI caused primarily by mechanical forces in civilian settings. Four groups participated: (1) blast-related military TBI (milTBI; n=21); (2) military controls (milCON; n=22); (3) non-blast civilian TBI (civTBI; n=21); and (4) civilian controls (civCON; n=23) with orthopedic injuries. Mild to moderate TBI (MTBI) occurred 1 to 6 years before enrollment. Participants completed the Stop Signal Task (SST), a measure of inhibitory control, while undergoing fMRI. Brain activation was evaluated with 2 (mil, civ)×2 (TBI, CON) analyses of variance, corrected for multiple comparisons. During correct inhibitions, fMRI activation was lower in the TBI than CON subjects in regions commonly associated with inhibitory control and the default mode network. In contrast, inhibitory failures showed significant interaction effects in the bilateral inferior temporal, left superior temporal, caudate, and cerebellar regions. Specifically, the milTBI group demonstrated more activation than the milCON group when failing to inhibit; in contrast, the civTBI group exhibited less activation than the civCON group. Covariance analyses controlling for the effects of education and self-reported psychological symptoms did not alter the brain activation findings. These results indicate that the chronic effects of TBI are associated with abnormal brain activation during successful response inhibition. During failed inhibition, the pattern of activation distinguished military from civilian TBI, suggesting that blast-related TBI has a unique effect on brain function that can be distinguished from TBI resulting from mechanical forces associated with sports or motor vehicle accidents. The implications of these findings for diagnosis and treatment of TBI are discussed.

Adaptive cyclic physiologic noise modeling and correction in functional MRI.

Physiologic noise in BOLD-weighted MRI data is known to be a significant source of the variance, reducing the statistical power and specificity in fMRI and functional connectivity analyses. We show a dramatic improvement on current noise correction methods in both fMRI and fcMRI data that avoids overfitting. The traditional noise model is a Fourier series expansion superimposed on the periodicity of parallel measured breathing and cardiac cycles. Correction using this model results in removal of variance matching the periodicity of the physiologic cycles. Using this framework allows easy modeling of noise. However, using a large number of regressors comes at the cost of removing variance unrelated to physiologic noise, such as variance due to the signal of functional interest (overfitting the data). It is our hypothesis that there are a small variety of fits that describe all of the significantly coupled physiologic noise. If this is true, we can replace a large number of regressors used in the model with a smaller number of the fitted regressors and thereby account for the noise sources with a smaller reduction in variance of interest. We describe these extensions and demonstrate that we can preserve variance in the data unrelated to physiologic noise while removing physiologic noise equivalently, resulting in data with a higher effective SNR than with current corrections techniques. Our results demonstrate a significant improvement in the sensitivity of fMRI (up to a 17% increase in activation volume for fMRI compared with higher order traditional noise correction) and functional connectivity analyses.

SimPACE: generating simulated motion corrupted BOLD data with synthetic-navigated acquisition for the development and evaluation of SLOMOCO: a new, highly effective slicewise motion correction.

Head motion in functional MRI and resting-state MRI is a major problem. Existing methods do not robustly reflect the true level of motion artifact for in vivo fMRI data. The primary issue is that current methods assume that motion is synchronized to the volume acquisition and thus ignore intra-volume motion. This manuscript covers three sections in the use of gold-standard motion-corrupted data to pursue an intra-volume motion correction. First, we present a way to get motion corrupted data with accurately known motion at the slice acquisition level. This technique simulates important data acquisition-related motion artifacts while acquiring real BOLD MRI data. It is based on a novel motion-injection pulse sequence that introduces known motion independently for every slice: Simulated Prospective Acquisition CorrEction (SimPACE). Secondly, with data acquired using SimPACE, we evaluate several motion correction and characterization techniques, including several commonly used BOLD signal- and motion parameter-based metrics. Finally, we introduce and evaluate a novel, slice-based motion correction technique. Our novel method, SLice-Oriented MOtion COrrection (SLOMOCO) performs better than the volumetric methods and, moreover, accurately detects the motion of independent slices, in this case equivalent to the known injected motion. We demonstrate that SLOMOCO can model and correct for nearly all effects of motion in BOLD data. Also, none of the commonly used motion metrics was observed to robustly identify motion corrupted events, especially in the most realistic scenario of sudden head movement. For some popular metrics, performance was poor even when using the ideal known slice motion instead of volumetric parameters. This has negative implications for methods relying on these metrics, such as recently proposed motion correction methods such as data censoring and global signal regression.

Hippocampal volume is related to cognitive decline and fornicial diffusion measures in multiple sclerosis.

PURPOSE To assess for associations between hippocampal atrophy and measures of cognitive function, hippocampal magnetization transfer ratio (MTR), and diffusion measures of the fornix, the largest efferent white matter tract from the hippocampus, in patients with multiple sclerosis (MS) and controls. MATERIALS AND METHODS A total of 53 patients with MS and 20 age- and sex-matched healthy controls participated in cognitive testing and scanning including high spatial-resolution diffusion imaging and a T1-MPRAGE scan. Hippocampal volume and fornicial thickness measures were calculated and compared to mean values of fornicial transverse diffusivity, mean diffusivity, longitudinal diffusivity, fractional anisotropy, mean hippocampal MTR, and scores on measures of episodic memory, processing speed, and working memory tasks. RESULTS In patients with MS, hippocampal volume was significantly related to fornicial diffusion measures (P<7×10(-4)) and to measures of verbal (P=0.030) and visual spatial (P=0.004) episodic memory and a measure of information processing speed (P<0.037). DISCUSSION These results highlight the role of the hippocampus in cognitive dysfunction in patients with MS and suggest that measures of hippocampal atrophy could be used to capture aspects of disease progression.

Effects of electroconvulsive therapy on brain functional activation and connectivity in depression.

Objective Past neuroimaging work has suggested that increased activation to cognitive and emotional tasks and decreased connectivity in frontal regions are related to cognitive inefficiency in depression; normalization of these relationships has been associated with successful treatment. The present study investigated brain function before and after electroconvulsive therapy (ECT) in patients with major depressive disorder (MDD) and demonstrated the effect of treatment on cortical activation patterns. Methods Six ECT-naive patients with depression (mean ± SD age, 39.0 ± 5.4 years) were treated with ECT. Within 1 week before and 1 to 3 weeks after ECT, the patients underwent a magnetic resonance imaging session with functional magnetic resonance image scanning during working memory and affective tasks and during rest. Changes in voxelwise statistical maps of brain response to each task in regions identified to be relevant from past studies of depression were compared with changes in depression severity as measured by the Hamilton Depression Rating Score. Changes in functional connectivity between brain regions were also compared with changes in depression severity. Results Activation during both tasks was generally found to be decreased after ECT. Remission of depression was significantly associated with reduced affective deactivation after ECT in the orbitofrontal cortex (P = 0.03). Whole-brain functional connectivity of the anterior cingulate cortex showed a consistent increase in connectivity to the right dorsolateral prefrontal cortex and posterior cingulate cortex after ECT. Conclusions These results suggest that successful ECT for MDD is associated with decreased activation to cognitive and emotional tasks and an increase in resting connectivity.

Assessment of Inter-Hemispheric Imbalance Using Imaging and Noninvasive Brain Stimulation in Patients With Chronic Stroke

OBJECTIVE To determine how interhemispheric balance in stroke, measured using transcranial magnetic stimulation (TMS), relates to balance defined using neuroimaging (functional magnetic resonance [fMRI], diffusion-tensor imaging [DTI]) and how these metrics of balance are associated with clinical measures of upper-limb function and disability. DESIGN Cross sectional. SETTING Laboratory. PARTICIPANTS Patients with chronic stroke (N = 10; age, 63 ± 9 y) in a population-based sample with unilateral upper-limb paresis. INTERVENTIONS Not applicable. MAIN OUTCOME MEASURES Interhemispheric balance was measured with TMS, fMRI, and DTI. TMS defined interhemispheric differences in the recruitment of corticospinal output, size of the corticomotor output maps, and degree of mutual transcallosal inhibition that they exerted on one another. fMRI studied whether cortical activation during the movement of the paretic hand was lateralized to the ipsilesional or to the contralesional primary motor cortex (M1), premotor cortex (PMC), and supplementary motor cortex (SMA). DTI was used to define interhemispheric differences in the integrity of the corticospinal tracts projecting from the M1. Clinical outcomes tested function (upper extremity Fugl-Meyer [UEFM]) and perceived disability in the use of the paretic hand (Motor Activity Log [MAL] amount score). RESULTS Interhemispheric balance assessed with TMS relates differently to fMRI and DTI. Patients with high fMRI lateralization to the ipsilesional hemisphere possessed stronger ipsilesional corticomotor output maps (M1: r = .831, P = .006; PMC: r = .797, P = .01) and better balance of mutual transcallosal inhibition (r = .810, P = .015). Conversely, we found that patients with less integrity of the corticospinal tracts in the ipsilesional hemisphere show greater corticospinal output of homologous tracts in the contralesional hemisphere (r = .850, P = .004). However, an imbalance in integrity and output do not relate to transcallosal inhibition. Clinically, although patients with less integrity of corticospinal tracts from the ipsilesional hemisphere showed worse impairments (UEFM) (r = -.768, P = .016), those with low fMRI lateralization to the ipsilesional hemisphere had greater perception of disability (MAL amount score) (M1: r = .883, P = .006; PMC: r = .817, P = .007; SMA: r = .633, P = .062). CONCLUSIONS In patients with chronic motor deficits of the upper limb, fMRI may serve to mark perceived disability and transcallosal influence between hemispheres. DTI-based integrity of the corticospinal tracts, however, may be useful in categorizing the range of functional impairments of the upper limb. Further, in patients with extensive corticospinal damage, DTI may help infer the role of the contralesional hemisphere in recovery.

The non-separability of physiologic noise in functional connectivity MRI with spatial ICA at 3 T

The impact of physiologic noise on spatial ICA analyses of resting state BOLD-weighted MRI data is investigated. Using FastICA and Infomax ICA, two common ICA algorithms, we apply a group spatial ICA method across multiple subjects. We compare the spatial maps from five commonly identified functional networks and show that physiologic noise correction techniques introduce significant changes in the spatial ICA decomposition of all five networks, greater than the changes introduced by either algorithmic indeterminacy (re-running ICA) or the changes introduced by decreasing the decomposition dimensionality due to physiologic noise removal. In addition, we demonstrate that the sources associated with these components have significant temporal correlation to parallel measures of cardiac and respiratory rates, and these are reduced after correction. We conclude that ICA decomposition is significantly affected by physiologic noise and the ICA process alone is not sufficient to separate physiologic noise effects in the brain. It is recommended that physiologic noise correction be applied to timeseries data prior to ICA decomposition.

The Effect of Forced-Exercise Therapy for Parkinson's Disease on Motor Cortex Functional Connectivity

Parkinsons disease (PD) is a progressive neurologic disorder primarily characterized by an altered motor function. Lower extremity forced exercise (FE) has been shown to reduce motor symptoms in patients with PD. Recent functional magnetic resonance imaging (fMRI) studies have shown that FE and medication produce similar changes in brain activation patterns. Functional connectivity MRI (fcMRI) affords the ability to look at how strongly nodes of the motor circuit communicate with each other and can provide insight into the complementary effects of various therapies. Past work has demonstrated an abnormal motor connectivity in patients with PD compared to controls and subsequent normalization after treatment. Here we compare the effects of FE and medication using both resting and continuous visuomotor task fcMRI. Ten patients with mild to moderate PD completed three fMRI and fcMRI scanning sessions randomized under the following conditions: on PD medication, off PD medication, and FE+off medication. Blinded clinical ratings of motor function (a Unified Parkinsons Disease Rating Motor Scale-III exam) indicated that FE and medication resulted in 51% and 33% improvement in clinical ratings, respectively. In most nodes of the motor circuit, the observed changes in the functional connectivity produced by FE and medication were strongly positively correlated. These findings suggest that medication and FE likely use the same pathways to produce symptomatic relief in patients with PD. However, the connectivity changes, while consistent across therapy, were inconsistent in polarity for each patient. This finding may explain some past inconsistencies in connectivity changes after medication therapy.