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.

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.

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.

The neural correlates of cognitive fatigue in traumatic brain injury using functional MRI.

PRIMARY OBJECTIVE: The present study used fMRI (functional magnetic resonance imaging) to objectively assess cognitive fatigue in persons with traumatic brain injury (TBI). It was hypothesized that while performing a cognitive task, TBI participants would show increased brain activity over time, indicative of increased cerebral 'effort' which might manifest as the subjective feeling of cognitive fatigue. METHODS AND PROCEDURES: Functional MRI was used to track brain activity across time while 11 TBI patients with moderate-severe injury and 11 age-matched healthy controls (HCs) performed a modified Symbol Digit Modalities Task (mSDMT). Cognitive fatigue was operationally defined as a relative increase in cerebral activation across time compared to that seen in HCs. ROIs were derived from the Chauduri and Behan model of cognitive fatigue. MAIN OUTCOMES AND RESULTS: While performing the mSDMT, participants with a TBI showed increased activity, while HCs subsequently showed decreased activity in several regions including the middle frontal gyrus, superior parietal cortex, basal ganglia and anterior cingulate. CONCLUSIONS: Increased brain activity exhibited by participants with a TBI might represent increased cerebral effort which may be manifested as cognitive fatigue. Functional MRI appears to be a potentially useful tool for understanding the neural mechanisms associated with cognitive fatigue in TBI.

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.

The relationship between neuropsychological measures and the Timed Instrumental Activities of Daily Living task in multiple sclerosis.

Multiple sclerosis (MS) can result in cognitive deficits and a loss of functional independence. To date, little research has linked the observed cognitive and behavioral deficits in MS, especially those in the processing speed domain, to performance on tasks of everyday functioning. The present study examined the relationship between neuropsychological test performance and performance on the Timed Instrumental Activities of Daily Living task (TIADL) in individuals with MS, and in healthy controls (HCs). The TIADL is a functional measure, which assesses both accuracy and speed in one's performance of everyday activities. The MS group performed significantly worse on the TIADL relative to the HC group. Additionally, TIADL scores of individuals with MS were significantly correlated with neuropsychological measures of processing speed. TIADL scores were not, however, correlated with neuropsychological measures of verbal episodic memory or working memory. These results indicate that the impairments in processing speed may contribute to impairments in activities of everyday living in persons with MS.

Examining lactate in severe TBI using proton magnetic resonance spectroscopy.

PRIMARY OBJECTIVE: Clinical management of acute traumatic brain injury (TBI) has emphasized identification of secondary mechanisms of pathophysiology. An important objective in this study is to use proton magnetic resonance spectroscopy (pMRS) to examine early metabolic disturbance due to TBI. RESEARCH DESIGN: The current design is a case study with repeated measures. METHOD AND PROCEDURE: Proton magnetic resonance imaging was used to examine neurometabolism in this case of very severe brain trauma at 9 and 23 days post-injury. MRI was performed on a clinical 1.5 Tesla scanner. MAIN OUTCOMES AND RESULTS: These data also reveal that pMRS methods can detect lactate elevations in an adult surviving severe head trauma and are sensitive to changes in basic neurometabolism during the first month of recovery. CONCLUSIONS: The current case study demonstrates the sensitivity of pMRS in detecting metabolic alterations during the acute recovery period. The case study reveals that lactate elevations may be apparent for weeks after severe neurotrauma. Further work in this area should endeavour to determine the ideal time periods for pMRS examination in severe TBI as well as the ideal locations of data acquisition (e.g. adjacent or distal to lesion sites).