Symmetrical drug-related intertriginous and flexural exanthema like eruption associated with COVID-19 vaccination.

This is a case of symmetrical drug-related intertriginous and flexural exanthema-like eruption following ChAdOx1 nCoV-19 (AstraZeneca-Oxford) vaccination. Investigations, including repeated skin swabs, ruled out an infectious cause. He was subsequently treated with oral prednisolone, which led to a resolution of his symptoms.

Cognitive fatigue in traumatic brain injury: a pilot study comparing state and trait fatigue.

OBJECTIVE: Cognitive fatigue is a common and disabling symptom following a traumatic brain injury (TBI). Literature on cognitive fatigue has distinguished between two types of fatigue: "state" fatigue refers to the acute experience of fatigue, whereas "trait" fatigue refers to the susceptibility to fatigue over an extended period. However, it is not clear whether state and trait fatigue are distinguishable constructs. Here, we examine the relationship between state and trait fatigue in individuals with TBI, hypothesizing that trait and state measures assess different constructs. PARTICIPANTS: Twenty-one participants with moderate-severe TBI were recruited. DESIGN: Participants underwent a cognitively fatiguing task while in an MRI scanner and completed self-report measures examining trait and state fatigue. RESULTS: No correlation was found between state and trait fatigue. However, the two measures of trait fatigue, Fatigue Severity Scale (FSS) and the Modified Fatigue Impact Scale (MFIS), correlated with one another; additionally only trait fatigue correlated with depression scores, consistent with the literature. CONCLUSION: These findings suggest that trait and state fatigue may not be interdependent and that it is important to carefully define the type of fatigue under consideration when assessing fatigue in individuals with TBI.

Using functional connectivity changes associated with cognitive fatigue to delineate a fatigue network.

Cognitive fatigue, or fatigue related to mental work, is a common experience. A growing body of work using functional neuroimaging has identified several regions that appear to be related to cognitive fatigue and that potentially comprise a "fatigue network". These include the striatum of the basal ganglia, the dorsolateral prefrontal cortex (DLPFC), the dorsal anterior cingulate cortex (dACC), the ventro-medial prefrontal cortex (vmPFC) and the anterior insula. However, no work has been conducted to assess whether the connectivity between these regions changes as a function of cognitive fatigue. We used a task-based functional neuroimaging paradigm to induce fatigue in 39 healthy individuals, regressed the signal associated with the task out of the data, and investigated how the functional connectivity between these regions changed as cognitive fatigue increased. We observed functional connectivity between these regions and other frontal regions largely decreased as cognitive fatigue increased while connectivity between these seeds and more posterior regions increased. Furthermore the striatum, the DLPFC, the insula and the vmPFC appeared to be central 'nodes' or hubs of the fatigue network. These findings represent the first demonstration that the functional connectivity between these areas changes as a function of cognitive fatigue.

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.

Information processing speed in multiple sclerosis: Relevance of default mode network dynamics.

Objective: To explore the added value of dynamic functional connectivity (dFC) of the default mode network (DMN) during resting-state (RS), during an information processing speed (IPS) task, and the within-subject difference between these conditions, on top of conventional brain measures in explaining IPS in people with multiple sclerosis (pwMS). Methods: In 29 pwMS and 18 healthy controls, IPS was assessed with the Letter Digit Substitution Test and Stroop Card I and combined into an IPS-composite score. White matter (WM), grey matter (GM) and lesion volume were measured using 3 T MRI. WM integrity was assessed with diffusion tensor imaging. During RS and task-state fMRI (i.e. symbol digit modalities task, IPS), stationary functional connectivity (sFC; average connectivity over the entire time series) and dFC (variation in connectivity using a sliding window approach) of the DMN was calculated, as well as the difference between both conditions (i.e. task-state minus RS; ΔsFC-DMN and ΔdFC-DMN). Regression analysis was performed to determine the most important predictors for IPS. Results: Compared to controls, pwMS performed worse on IPS-composite (p = 0.022), had lower GM volume (p < 0.05) and WM integrity (p < 0.001), but no alterations in sFC and dFC at the group level. In pwMS, 52% of variance in IPS-composite could be predicted by cortical volume (ß = 0.49, p = 0.01) and ΔdFC-DMN (ß = 0.52, p < 0.01). After adding dFC of the DMN to the model, the explained variance in IPS increased with 26% (p < 0.01). Conclusion: On top of conventional brain measures, dFC from RS to task-state explains additional variance in IPS. This highlights the potential importance of the DMN to adapt upon cognitive demands to maintain intact IPS in pwMS.

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.

Aerobic exercise increases hippocampal volume and improves memory in multiple sclerosis: preliminary findings.

Multiple sclerosis leads to prominent hippocampal atrophy, which is linked to memory deficits. Indeed, 50% of multiple sclerosis patients suffer memory impairment, with negative consequences for quality of life. There are currently no effective memory treatments for multiple sclerosis either pharmacological or behavioral. Aerobic exercise improves memory and promotes hippocampal neurogenesis in nonhuman animals. Here, we investigate the benefits of aerobic exercise in memory-impaired multiple sclerosis patients. Pilot data were collected from two ambulatory, memory-impaired multiple sclerosis participants randomized to non-aerobic (stretching) and aerobic (stationary cycling) conditions. The following baseline/follow-up measurements were taken: high-resolution MRI (neuroanatomical volumes), fMRI (functional connectivity), and memory assessment. Intervention was 30-minute sessions 3 times per week for 3 months. Aerobic exercise resulted in 16.5% increase in hippocampal volume and 53.7% increase in memory, as well as increased hippocampal resting-state functional connectivity. Improvements were specific, with no comparable changes in overall cerebral gray matter (+2.4%), non-hippocampal deep gray matter structures (thalamus, caudate: -4.0%), or in non-memory cognitive functioning (executive functions, processing speed, working memory: changes ranged from -11% to +4%). Non-aerobic exercise resulted in relatively no change in hippocampal volume (2.8%) or memory (0.0%), and no changes in hippocampal functional connectivity. This is the first evidence for aerobic exercise to increase hippocampal volume and connectivity and improve memory in multiple sclerosis. Aerobic exercise represents a cost-effective, widely available, natural, and self-administered treatment with no adverse side effects that may be the first effective memory treatment for multiple sclerosis patients.