There is substantial interpatient variation in recovery from upper limb impairment after stroke in patients with severe initial impairment. Defining recovery as a change in the upper limb Fugl-Meyer score (ΔFM), we predicted ΔFM with its conditional expectation (i.e., posterior mean) given upper limb Fugl-Meyer initial impairment (FM(ii)) and a putative functional magnetic resonance imaging (fMRI) recovery measure. Patients with first time, ischemic stroke were imaged at 2.5 ± 2.2 days poststroke with 1.5-T fMRI during a hand closure task alternating with rest (fundamental frequency = 0.025 Hz, scan duration = 172 s). Confirming a previous finding, we observed that the prediction of ΔFM by FM(ii) alone is good in patients with nonsevere initial hemiparesis but is not good in patients with severe initial hemiparesis (96% and 16% of the total sum of squares of ΔFM explained, respectively). In patients with severe initial hemiparesis, prediction of ΔFM by the combination of FM(ii) and the putative fMRI recovery measure nonsignificantly increased predictive explanation from 16% to 47% of the total sum of squares of ΔFM explained. The implications of this preliminary negative result are discussed.

Humans are able to rapidly adapt their movements when a visuomotor or other systematic perturbation is imposed. However, the adaptation is forgotten or unlearned equally rapidly once the perturbation is removed. The ultimate cause of this unlearning remains poorly understood. Unlearning is often considered to be a passive process due to inability to retain an internal model. However, we have recently suggested that it may instead be a process of reversion to habit, without necessarily any forgetting per se. We compared the timecourse and nature of unlearning across a variety of protocols where unlearning is known to occur: error-clamp trials, removal of visual feedback, removal of the perturbation, or simply a period of inactivity. We found that, in agreement with mathematical models, there was no significant difference in the rate of decay between subject who experienced zero-error clamp trials, and subjects who made movements with no visual feedback. Time alone did lead to partial unlearning (over the duration we tested), but the amount of unlearning was inconsistent across subjects. Upon re-exposure to the same perturbation, subjects who unlearned through time or by reverting to veridical feedback exhibited savings. By contrast, no savings was observed in subjects who unlearned by having visual feedback removed or by being placed in a series of error-clamp trials. Thus although these various forms of unlearning can all revert subjects back to baseline behavior, they have markedly different effects on whether long-term memory for the adaptation is spared or is also unlearned. On the basis of these and previous findings, we suggest that unlearning is not due to passive forgetting of an internal model, but is instead an active process whereby adapted behavior gradually reverts to baseline habits.

ObjectiveTo determine which findings on routine clinical EEGs correlate with delirium severity across various presentations and to determine whether EEG findings independently predict important clinical outcomes.MethodsWe prospectively studied a cohort of nonintubated inpatients undergoing EEG for evaluation of altered mental status. Patients were assessed for delirium within 1 hour of EEG with the 3-Minute Diagnostic Interview for Confusion Assessment Method (3D-CAM) and 3D-CAM severity score. EEGs were interpreted clinically by neurophysiologists, and reports were reviewed to identify features such as theta or delta slowing and triphasic waves. Generalized linear models were used to quantify associations among EEG findings, delirium, and clinical outcomes, including length of stay, Glasgow Outcome Scale scores, and mortality.ResultsWe evaluated 200 patients (median age 60 years, IQR 48.5–72 years); 121 (60.5%) met delirium criteria. The EEG finding most strongly associated with delirium presence was a composite of generalized theta or delta slowing (odds ratio 10.3, 95% confidence interval 5.3–20.1). The prevalence of slowing correlated not only with overall delirium severity (R2 = 0.907) but also with the severity of each feature assessed by CAM-based delirium algorithms. Slowing was common in delirium even with normal arousal. EEG slowing was associated with longer hospitalizations, worse functional outcomes, and increased mortality, even after adjustment for delirium presence or severity.ConclusionsGeneralized slowing on routine clinical EEG strongly correlates with delirium and may be a valuable biomarker for delirium severity. In addition, generalized EEG slowing should trigger elevated concern for the prognosis of patients with altered mental status.

There is a great need to develop new approaches for rehabilitation of the upper limb after stroke. Robotic therapy is a promising form of neurorehabilitation that can be delivered in higher doses than conventional therapy. Here we sought to determine whether the reported effects of robotic therapy, which have been based on clinical measures of impairment and function, are accompanied by improved motor control. Patients with chronic hemiparesis were trained for 3 wk, 3 days a week, with titrated assistive robotic therapy in two and three dimensions. Motor control improvements (i.e., skill) in both arms were assessed with a separate untrained visually guided reaching task. We devised a novel PCA-based analysis of arm trajectories that is sensitive to changes in the quality of entire movement trajectories without needing to prespecify particular kinematic features. Robotic therapy led to skill improvements in the contralesional arm. These changes were not accompanied by changes in clinical measures of impairment or function. There are two possible interpretations of these results. One is that robotic therapy only leads to small task-specific improvements in motor control via normal skill-learning mechanisms. The other is that kinematic assays are more sensitive than clinical measures to a small general improvement in motor control.

IMPORTANCE Powassan virus is a rare but increasingly recognized cause of severe neurological disease. OBJECTIVE To highlight the diagnostic challenges and neuropathological findings in a fatal case of Powassan encephalitis caused by deer tick virus (lineage II) in a patient with follicular lymphoma receiving rituximab, with nonspecific anti-GAD65 antibodies, who was initially seen with fever and orchiepididymitis. DESIGN, SETTING, AND PARTICIPANTS Comparison of clinical, radiological, histological, and laboratory findings, including immunohistochemistry, real-time polymerase chain reaction, antibody detection, and unbiased sequencing assays, in a single case report (first seen in December 2016) at an academic medical center. EXPOSURE Infection with Powassan virus. MAIN OUTCOMES AND MEASURES Results of individual assays compared retrospectively. RESULTS In a 63-year-old man with fatal Powassan encephalitis, serum and cerebrospinal fluid IgM antibodies were not detected via standard methods, likely because of rituximab exposure. Neuropathological findings were extensive, including diffuse leptomeningeal and parenchymal lymphohistiocytic infiltration, microglial proliferation, marked neuronal loss, and white matter microinfarctions most severely involving the cerebellum, thalamus, and basal ganglia. Diagnosis was made after death by 3 independent methods, including demonstration of Powassan virus antigen in brain biopsy and autopsy tissue, detection of viral RNA in serum and cerebrospinal fluid by targeted real-time polymerase chain reaction, and detection of viral RNA in cerebrospinal fluid by unbiased sequencing. Extensive testing for other etiologies yielded negative results, including mumps virus owing to prodromal orchiepididymitis. Low-titer anti-GAD65 antibodies identified in serum, suggestive of limbic encephalitis, were not detected in cerebrospinal fluid. CONCLUSIONS AND RELEVANCE Owing to the rarity of Powassan encephalitis, a high degree of suspicion is required to make the diagnosis, particularly in an immunocompromised patient, in whom antibody-based assays may be falsely negative. Unbiased sequencing assays have the potential to detect uncommon infectious agents and may prove useful in similar scenarios.

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Delirium, sometimes referred to as encephalopathy, is an acute confusional state that is both common in hospitalized patients and associated with poor outcomes. For patients, families, and caregivers, delirium can be a traumatic experience. While delirium is one of the most common diagnoses encountered by the consulting neurologist, the majority of the time it will have been previously unrecognized as such by the care team. Neurologic syndromes such as dementia or aphasia can either be misdiagnosed as delirium or may coexist with it, necessitating careful neurologic assessment. Once the diagnosis of delirium has been established, a careful evaluation for predisposing and precipitating factors can help uncover modifiable contributors, which should be addressed as part of a multicomponent, primarily nonpharmacologic intervention. Importantly, delirium management, which begins with comprehensive prevention, should emphasize the humanity of the delirious patient and the challenges of caring for this vulnerable population. When considered, delirium represents an important opportunity for the neurologist to substantially enhance patient care.

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