Methylphenidate may improve mental fatigue in individuals with multiple sclerosis: A pilot clinical trial.

BACKGROUND: Fatigue is the most common symptom in multiple sclerosis (MS), previously attributed to dopamine imbalance. Evidence suggests that methylphenidate, a psychostimulant that increases striatal and prefrontal dopamine levels, is effective in reducing fatigue in various disorders. However, its effect on state vs. trait mental fatigue in MS is yet to be examined. METHODS: This pilot study investigates the efficacy of methylphenidate on decreasing self-reported mental fatigue in 12 individuals with MS in a double-blind, placebo-controlled, cross-over randomized clinical trial. RESULTS: Our results show that "state", but not "trait" MS-related fatigue, was reduced after 4 weeks of methylphenidate administration as compared to placebo.

Fatigue in Gulf War Illness is associated with tonically high activation in the executive control network.

Gulf War Illness (GWI) is a chronic, multi-symptom illness that affects approximately 25% of Gulf veterans, with cognitive fatigue as one of its primary symptoms. Here, we investigated the neural networks associated with cognitive fatigue in GWI by asking 35 veterans with GWI and 25 healthy control subjects to perform a series of fatiguing tasks while in the MRI scanner. Two types of cognitive fatigue were assessed: state fatigue, which is the fatigue that developed as the tasks were completed, and trait fatigue, or one's propensity to experience fatigue when assessed over several weeks. Our results showed that the neural networks associated with state and trait fatigue differed. Irrespective of group, the network underlying trait fatigue included areas associated with memory whereas the neural network associated with state fatigue included key areas of a fronto-striatal-thalamic circuit that has been implicated in fatigue in other populations. As in other investigations of fatigue, the caudate of the basal ganglia was implicated in fatigue. Furthermore, individuals with GWI showed greater activation than the HC group in frontal and parietal areas for the less difficult task. This suggests that an inability to modulate brain activation as task demands change may underlie fatigue in GWI.

Cognitive fatigue in individuals with traumatic brain injury is associated with caudate activation.

We investigated differences in brain activation associated with cognitive fatigue between persons with traumatic brain injury (TBI) and healthy controls (HCs). Twenty-two participants with moderate-severe TBI and 20 HCs performed four blocks of a difficult working memory task and four blocks of a control task during fMRI imaging. Cognitive fatigue, assessed before and after each block, was used as a covariate to assess fatigue-related brain activation. The TBI group reported more fatigue than the HCs, though their performance was comparable. Regarding brain activation, the TBI group showed a Task X Fatigue interaction in the caudate tail resulting from a positive correlation between fatigue and brain activation for the difficult task and a negative relationship for the control task. The HC group showed the same Task X Fatigue interaction in the caudate head. Because we had prior hypotheses about the caudate, we performed a confirmatory analysis of a separate dataset in which the same subjects performed a processing speed task. A relationship between Fatigue and brain activation was evident in the caudate for this task as well. These results underscore the importance of the caudate nucleus in relation to cognitive fatigue.

The relationship between outcome prediction and cognitive fatigue: A convergence of paradigms.

Cognitive fatigue is common after strenuous cognitive effort. A large body of literature has implicated a network of brain areas in fatigue, including the basal ganglia and cortical areas including ventro-medal prefrontal cortex and anterior cingulate cortex (ACC). Furthermore, the ACC has been shown to be involved in processes such as error and conflict monitoring, outcome prediction, and effort processing. Thus, the ACC appears to be one common denominator between clinical work on fatigue and research on outcome prediction and effort. In the present study, we examined whether the same region of the ACC is activated during the processing of errors and fatigue. Cognitive fatigue was induced by having subjects perform a difficult working memory task, during which they rated on-task fatigue. Activation associated with error processing was determined by using error trials on the working memory task. After localizing the region engaged in error processing, we evaluated whether there was a relationship between BOLD activation of that region and on-task fatigue scores. The results showed that as subjects became more fatigued, they responded with longer latencies and increased accuracy for the more difficult task. Moreover, the ACC areas that were activated by error processing were also associated with fatigue. These results suggest that cognitive fatigue may be related to changes in effort and reward. We speculate that as the brain detects these changes, cognitive fatigue is generated as a way for the brain to signal itself that the effort required for the task no longer merits the rewards received for performing it.

A pilot study of changes in functional brain activity during a working memory task after mSMT treatment: The MEMREHAB trial.

BACKGROUND: Working memory deficits are common in multiple sclerosis (MS). The modified Story Memory Technique (mSMT) has been shown to improve new learning and memory in MS, but its effects on working memory (WM) are currently unknown. OBJECTIVE: The present study presents a secondary analysis of data from a larger double-blind, placebo-controlled, randomized clinical trial and examines changes in cerebral activation on a WM task following mSMT treatment. METHODS: Sixteen participants with clinically definite MS were randomly assigned to treatment (n=7) or placebo-control groups (n=9) matched for gender, age and education. Baseline and immediate follow-up functional Magnetic Resonance Imaging (fMRI) was obtained for all subjects. During fMRI participants completed an N-back task, consisting of 0-, 1-and 2-back conditions. RESULTS: Significant increases in cerebral activation were noted in the dorsolateral prefrontal cortex, supplementary motor area and inferior parietal lobule at follow-up in the treatment group. No significant changes were noted in the placebo control group. CONCLUSION: Due to the small sample size, results of the current study should be interpreted as preliminary. However, the observed pattern of activation of the frontoparietal network involved in WM found in the treatment group, suggests that mSMT training increases recruitment of attention- and WM-related neural networks. We conclude that mSMT treatment leads to changes in WM-related cerebral activation.

Altered Effective Connectivity during a Processing Speed Task in Individuals with Multiple Sclerosis.

OBJECTIVES: Processing speed impairment is the most prevalent cognitive deficit in individuals with multiple sclerosis (MS). However, the neural mechanisms associated with processing speed remain under debate. The current investigation provides a dynamic representation of the functioning of the brain network involved in processing speed by examining effective connectivity pattern during a processing speed task in healthy adults and in MS individuals with and without processing speed impairment. METHODS: Group assignment (processing speed impaired vs. intact) was based on participants' performance on the Symbol Digit Modalities test (Parmenter, Testa, Schretlen, Weinstock-Guttman, & Benedict, 2010). First, brain regions involved in the processing speed task were determined in healthy participants. Time series from these functional regions of interest of each group of participants were then subjected to the effective connectivity analysis (Independent Multiple-Sample Greedy Equivalence Search and Linear, Non-Gaussian Orientation, Fixed Structure algorithms) that showed causal influences of one region on another during task performance. RESULTS: The connectivity pattern of the processing speed impaired group was significantly different from the connectivity pattern of the processing speed intact group and of the healthy control group. Differences in the strength of common connections were also observed. CONCLUSIONS: Effective connectivity results reveal that MS individuals with processing speed impairment not only have connections that differ from healthy participants and MS individuals without processing speed impairment, but also have increased strengths of connections.