The translation of brief, millisecond-long pain-eliciting stimuli to the subjective perception of pain is associated with changes in theta, alpha, beta, and gamma oscillations over sensorimotor cortex. However, when a pain-eliciting stimulus continues for minutes, regions beyond the sensorimotor cortex, such as the prefrontal cortex, are also engaged. Abnormalities in prefrontal cortex have been associated with chronic pain states, but conventional, millisecond-long EEG paradigms do not engage prefrontal regions. In the current study, we collected high-density EEG data during an experimental paradigm in which subjects experienced a 4-s, low- or high-intensity pain-eliciting stimulus. EEG data were analyzed using independent component analyses, EEG source localization analyses, and measure projection analyses. We report three novel findings. First, an increase in pain perception was associated with an increase in gamma and theta power in a cortical region that included medial prefrontal cortex. Second, a decrease in lower beta power was associated with an increase in pain perception in a cortical region that included the contralateral sensorimotor cortex. Third, we used machine learning for automated classification of EEG data into low- and high-pain classes. Theta and gamma power in the medial prefrontal region and lower beta power in the contralateral sensorimotor region served as features for classification. We found a leave-one-out cross-validation accuracy of 89.58%. The development of biological markers for pain states continues to gain traction in the literature, and our findings provide new information that advances this body of work. The development of a biological marker for pain continues to gain traction in literature. Our findings show that high- and low-pain perception in human subjects can be classified with 89% accuracy using high-density EEG data from prefrontal cortex and contralateral sensorimotor cortex. Our approach represents a novel neurophysiological paradigm that advances the literature on biological markers for pain.

Bilateral priming combined with the task-oriented approach elicited more improvements in self-reported strength and disability degrees than the task-oriented approach by itself. Further large-scale research with at least 31 participants in each intervention group is suggested to confirm the study findings.

Objective:Determine the relationship between diffusion microstructure and early changes in Alzheimer’s disease (AD) severity as assessed by clinical diagnosis, cognitive performance, dementia severity, and plasma concentrations of neurofilament light chain.Methods:Diffusion MRI scans were collected on cognitively normal participants (CN), patients with early mild cognitive impairment (EMCI), late mild cognitive impairment (LMCI), and AD. Free water (FW) and FW-corrected fractional anisotropy were calculated in the locus coeruleus to transentorhinal cortex tract, four magnocellular regions of the basal forebrain (e.g. nucleus basalis of Meynert), entorhinal cortex, and hippocampus. All patients underwent a battery of cognitive assessments; neurofilament light chain levels were measured in plasma samples.Results:FW was significantly higher in EMCI compared to CN in the locus coeruleus to transentorhinal cortex tract, nucleus basalis of Meynert, and hippocampus (mean Cohen d = 0.54; pfdr<0.05). FW was significantly higher in AD compared to CN in all the examined regions (mean Cohen d = 1.41; pfdr<0.01). Additionally, FW in the hippocampus, entorhinal cortex, nucleus basalis of Meynert, and locus coeruleus to transentorhinal cortex tract positively correlated with all five cognitive impairment metrics, and neurofilament light chain levels (mean r2 = 0.10; pfdr<0.05).Conclusions:These results show that higher FW is associated with greater clinical diagnosis severity, cognitive impairment, and neurofilament light chain. They also suggest that FW elevation occurs in the locus coeruleus to transentorhinal cortex tract, nucleus basalis of Meynert, and hippocampus in the transition from CN to EMCI, while other basal forebrain regions and the entorhinal cortex are not affected until a later stage of AD. FW is a clinically relevant and non-invasive early marker of structural changes related to cognitive impairment.