Publications (35) View all
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Article: Elucidating the Neurobiology of Self-Reported Fatigue in Multiple Sclerosis (MS): The Interplay of Networks.
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ABSTRACT: Objective: To examine the correlation between fractional anisotropy (FA), a measure of white matter integrity (WMI), and selfreported fatigue in patients with multiple sclerosis (MS). Background: Fatigue – the most common and disabling symptom seen in patients with MS – is a multifaceted and poorly understood phenomenon; and likely to represent dysfunction of disparate neurocognitive networks. How different aspects of self-reported fatigue – psychological, cognitive or physical – correlates with WMI of the whole brain is unknown. Diffusion tensor imaging (DTI) allows evaluation of WMI in the whole brain. Participants and Methods: DTI data from 21 patients (19 female) with relapsing remitting MS were processed using FSL. Fatigue was assessed using the Modified Fatigue Impact Scale (MFIS), and each of its subscales – physical, cognitive and psychosocial – as well as the total score – were correlated with the FA maps in a voxel-wise analysis. Results: The MFIS-physical subscore (21.2 � 8.1) correlated positively with FA scores in bilateral cingulate; and correlated negatively with bilateral precuneus. The MFIS-cognitive subscore (22.1 � 7.4) correlated positively with FA scores in WM tracts of bilateral basal ganglia; and correlated negatively with right insula. The MFIS-psychosocial subscore (4.3 � 1.9) correlated positively with FA scores in WM tracts of right caudate; and correlated negatively with right insula. Conclusions: These findings suggest that 1) cognitive and psychosocial fatigue seem to rely on the same network, and 2) this is different from the network underlying physical fatigue. This fractionation represents a significant breakthrough in understanding the neurobiology of self-reported fatigue.Archives of Physical Medicine and Rehabilitation 10/2012; 93(10):e3. · 2.28 Impact Factor -
Article: Functional magnetic resonance imaging movers and shakers: Does subject-movement cause sampling bias?
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ABSTRACT: Head movement during functional magnetic resonance imaging (fMRI) degrades data quality. The effects of small movements can be ameliorated during data postprocessing, but data associated with severe movement is frequently discarded. In discarding these data, it is often assumed that head-movement is a source of random error, and that data can be discarded from subjects with severe movement without biasing the sample. We tested this assumption by examining whether head movement was related to task difficulty and cognitive status among persons with multiple sclerosis (MS). Thirty-four persons with MS were scanned while performing a working memory task with three levels of difficulty (the N-back task). Maximum movement (angle, shift) was estimated for each difficulty level. Cognitive status was assessed by combining performance on a working memory and processing speed task. An interaction was found between task difficulty and cognitive status (high vs. low cognitive ability): there was a linear increase in movement as task difficulty increased that was larger among subjects with lower cognitive ability. Analyses of the signal-to-noise ratio (SNR) confirmed that increases in movement degraded data quality. Similar, though far smaller, effects were found in a cohort of healthy control (HC) subjects. Therefore, discarding data with severe movement artifact may bias MS samples such that only those with less-severe cognitive impairment are included in the analyses. However, even if such data are not discarded outright, subjects who move more (MS and HC) will contribute less to the group-level results because of degraded SNR. Hum Brain Mapp, 2012. © 2012 Wiley Periodicals, Inc.Human Brain Mapping 07/2012; · 5.88 Impact Factor -
Article: Cognitive Reserve Modifies the Brain Network Underlying Cognitive Fatigue in Multiple Sclerosis (MS)
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ABSTRACT: Objective: To examine the brain network underlying cognitive fatigue in persons with higher vs. lower levels of cognitive reserve. Background Central or Cognitive Fatigue is a common but poorly understood symptom in MS. Dysfunction in frontal cortex– basal ganglia circuit (the fatigue network) may underlie MS-related fatigue. Cognitive reserve(CR), associated with educational attainment, is protective against cognitive impairment in patients with MS. Moreover, patients with lower education have been reported to have higher self-reported fatigue. However it is unclear how CR may protect against fatigue. Understanding this relationship may help to explain some of the heterogeneity in the literature on MS-related fatigue. Design/Methods: We examined brain activity in 18 MS patients, using 3T functional magnetic resonance imaging(fMRI) during the performance of a cognitively fatiguing task: the Symbol Digit Modality Task(SDMT). We performed a multiple regression analysis investigating how self reported fatigue (Fatigue Severity Scale- FSS) predicted brain activity across the two groups – high and low cognitive reserve, measured by Wechsler Test of Adult Reading(WTAR) – while controlling for age and brain atrophy. Results: The subjects with low CR showed a negative correlation between FSS and brain activity in caudate, medial frontal and superior frontal gyri and a positive correlation in the cerebellum. The subjects with high CR showed a negative correlation between FSS and brain activity in the precuneus and cingulate. Conclusions: The results, suggesting that CR modifies the brain network underlying cognitive fatigue, provide a new dimension to understand cognitive fatigue in MS. The areas associated with fatigue in the low-CR group overlap with the areas known to be the part of fatigue network. The areas associated with fatigue in the high-CR group overlap in only one area: the precuneus. This differential pattern of association may help to better understand the role of CR in MS-related fatigue and help develop novel therapeutic strategies.Neurology 04/2012; 78:P03.076. · 8.31 Impact Factor -
Conference Proceeding: Evidence for Persistent Recruitment of the Executive Control Network to Maintain Cognitive Performance in Multiple Sclerosis (MS).
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ABSTRACT: Objective: When individuals with MS and healthy controls (HCs) are asked to perform the same task, individuals with MS usually recruit additional brain regions. However, the mechanisms involved are unknown and little is known how such changes may help to maintain cognition despite ongoing tissue damage. Because functional connectivity (FC) analysis assesses entire networks rather than individual brain regions, we used FC to investigate this issue. Participants and Methods: We examined brain activity in 15 clinically definite relapsing-remitting MS patients, (mean disease duration113.5 ± 90.5 months) with minimal cognitive impairment and 12 age and education matched HCs, using 3T functional magnetic resonance imaging (fMRI) during the performance of a demanding task: the Task Switching Paradigm (TSP). We performed a seed based functional brain network analysis with seeds in the areas known to be important in taskswitching (dorso-lateral prefrontal, parietal, pre-SMA. Results: The MS subjects performed similarly to the HCs on the neuropsychological measures administered and showed similar executive function performance in the TSP. Although task-related activations were similar for MS and HC participants, the functional connectivity patterns were different. HC showed significantly greater correlations between left pre-SMA and bilateral temporal, cingulate and cerebellar regions (P < 0.01). The MS group showed correlations between pre-SMA and the bilateral dorsolateral prefrontal cortex with bilateral inferior parietal lobule (P < 0.01). Conclusions: The differences in FC pattern between high functioning MS subjects and HCs, despite similar task performance and BOLD activation patterns, suggest that HCs are able to use the “automatic attentional” network during TSPwhileMSsubjectsmust rely more on the “executive control” network to perform at a similar level. This finding has considerable significance to explain the nature of cognitive impairment in MS and has potential applications for cognitive neurorehabilitation.Fortieth Annual Meeting of International Neuropsychological Society, Montreal, Canada; 02/2012 -
Article: Increased cerebral activation after behavioral treatment for memory deficits in MS.
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ABSTRACT: Deficits in new learning and memory are common in persons with multiple sclerosis (MS), though few studies have examined the efficacy of memory retraining in MS. Previous research from our laboratory has demonstrated that the modified Story Memory Technique (mSMT) significantly improves new learning and memory in MS. The present double-blind, placebo-controlled, randomized clinical trial was designed to examine changes in cerebral activation following mSMT treatment. Sixteen individuals with clinically definite MS were randomly assigned to treatment (n = 8) or placebo-control (n = 8) groups, matched for age, education, and disease characteristics. Baseline and follow-up fMRI was collected during performance of learning and memory tasks. No baseline activation differences on fMRI were seen between groups. After treatment, greater activation was evident in the treatment group during performance of a memory task within a widespread cortical network involving frontal, parietal, precuneus, and parahippocampal regions. All participants in the treatment group showed increased activation in frontal and temporal regions in particular. In contrast, the control group showed no significant changes in cerebral activation at follow-up. A significant association was found between increased activation in the right middle frontal gyrus and improved memory performance post-treatment. The increased activation seen likely reflects increased use of strategies taught during treatment when learning new information. This study is the first to demonstrate a significant change in cerebral activation resulting from a behavioral memory intervention in an MS sample. Behavioral interventions can show significant changes in the brain, validating clinical utility.Journal of Neurology 01/2012; 259(7):1337-46. · 3.47 Impact Factor
