Predicting Post-operative Pain in Lung Cancer Patients using Pre-operative Peak Alpha Frequency

Aims and Objectives: Experimental models of neuropathic pain suggest that individual peak alpha frequency (PAF), measured using electroencephalography (EEG), can predict future pain sensitivity in experimental settings. Here, we tested whether PAF could predict future pain severity in a clinical setting in patients undergoing thoracotomy. Methods: Recorded using wearable around the ear electrodes (cEEGrids), the feasibility and efficacy of pre-operative PAF as a neuro-marker for post-operative pain was assessed in 16 patients undergoing thoracic surgery for lung cancer (age = 67.53 +/- 4.38 [SD]). Patients also provided numerical ratings (0-10) of current, average, and worst pain pre-operatively as well as within three days post-operatively Results and Significance: Pre-operative PAF of less than 9 Hz was highly sensitive (1.0) and specific (0.86) in identifying patients who would go on to experience severe (>7/10) worst pain. Moreover, PAF was negatively correlated with a patients' current, average, and worst post-operative pain. PAF was significantly higher for those reporting lower pain severity compared to those reporting higher pain severity in the immediate post-operative period. This suggests that PAF is a promising neuro-marker to pre-operatively assess individual susceptibility to severe pain in the immediate post-operative period, possibly enabling a more informed assessment of an individual's suitability for surgery.

Mental State Detection Using Riemannian Geometry on Electroencephalogram Brain Signals

The goal of this study was to implement a Riemannian geometry (RG)-based algorithm to detect high mental workload (MWL) and mental fatigue (MF) using task-induced electroencephalogram (EEG) signals. In order to elicit high MWL and MF, the participants performed a cognitively demanding task in the form of the letter n-back task. We analyzed the time-varying characteristics of the EEG band power (BP) features in the theta and alpha frequency band at different task conditions and cortical areas by employing a RG-based framework. MWL and MF were considered as too high, when the Riemannian distances of the task-run EEG reached or surpassed the threshold of the baseline EEG. The results of this study showed a BP increase in the theta and alpha frequency bands with increasing experiment duration, indicating elevated MWL and MF that impedes/hinders the task performance of the participants. High MWL and MF was detected in 8 out of 20 participants. The Riemannian distances also showed a steady increase toward the threshold with increasing experiment duration, with the most detections occurring toward the end of the experiment. To support our findings, subjective ratings (questionnaires concerning fatigue and workload levels) and behavioral measures (performance accuracies and response times) were also considered.

Behavioural effects of task-relevant neuromodulation by rTMS on giving-up

Recent studies suggest that online repetitive transcranial magnetic stimulation (rTMS) can induce local entrainment of ongoing endogenous oscillatory activity during a task. This effect may impact cognitive performance, depending on the function of the oscillation. In this study, we aimed to investigate the effects of stimulation frequency and target location that are relevant to the cognitive processes of giving-up. We first investigated the correlations between the EEG oscillations and cognitive giving-up processes during problem-solving tasks (Experiment 1). We then conducted online rTMS to examine the frequency-dependent stimulation effects of rTMS on the performance of problem-solving tasks and ongoing oscillations (Experiment 2). The results of Experiment 1 suggested that the frontal theta rhythm is associated with the giving-up processes and that the frontal alpha rhythm is associated with problem-solving behaviour. Accordingly, we hypothesised that rTMS at the theta frequency would induce ongoing theta activity and accelerate the giving-up behaviour, while rTMS at the alpha frequency would induce ongoing alpha activity and slow down the giving-up behaviour in Experiment 2. The results showed that theta-frequency rTMS application induced an increase in theta amplitudes and shortened the giving-up response. Alpha-frequency rTMS application induced an increase in alpha amplitudes, but did not change giving-up responses. Considering the close resemblance between giving-up behaviour and rumination in depression, neuromodulation of cognitive giving-up processes may lead to a new intervention to treat depression by rTMS. Furthermore, this study strengthens the hypothesis that modulating task-relevant oscillations by rTMS could induce behavioural changes related to cognitive performance.

Validating the wearable MUSE headset for EEG spectral analysis and Frontal Alpha Asymmetry

EEG power spectral density (PSD), the individual alpha frequency (IAF) and the frontal alpha asymmetry (FAA) are all EEG spectral measures that have been widely used to evaluate cognitive and attentional processes in experimental and clinical settings, and that can be used for real-world applications (e.g., remote EEG monitoring, brain-computer interfaces, neurofeedback, neuromodulation, etc.). Potential applications remain limited by the high cost, low mobility, and long preparation times associated with high-density EEG recording systems. Low-density wearable systems address these issues and can increase access to larger and diversified samples. The present study tested whether a low-cost, 4-channel wearable EEG system (the MUSE) could be used to quickly measure continuous EEG data, yielding similar frequency components compared to research a grade EEG system (the 64-channel BIOSEMI Active Two). We compare the spectral measures from MUSE EEG data referenced to mastoids to those from BIOSEMI EEG data with two different references for validation. A minimal amount of data was deliberately collected to test the feasibility for real-world applications (EEG setup and data collection being completed in under 5 min). We show that the MUSE can be used to examine power spectral density (PSD) in all frequency bands, the individual alpha frequency (IAF; i.e., peak alpha frequency and alpha center of gravity), and frontal alpha asymmetry. Furthermore, we observed satisfying internal consistency reliability in alpha power and asymmetry measures recorded with the MUSE. Estimating asymmetry on PAF and CoG frequencies did not yield significant advantages relative to the traditional method (whole alpha band). These findings should advance human neurophysiological monitoring using wearable neurotechnologies in large participant samples and increase the feasibility of their implementation in real-world settings.

Preservation of neural synchrony at peak alpha frequency via global synaptic scaling compensates for white matter structural decline over adult lifespan

We propose that preservation of functional integration, estimated from measures of neural synchrony, is a key neurocompensatory mechanism associated with healthy human ageing. To support this proposal, we demonstrate how phase-locking at peak alpha frequency from Magnetoencephalography (MEG) data is invariant over lifespan in a large cohort of human participants, aged 18-88 years. Using empirically derived connection topologies from diffusion tensor imaging (DTI) data, we create an in-silico model of whole-brain alpha dynamics. We show that enhancing inter-areal coupling can cancel the effect of increased axonal transmission delay associated with age-related degeneration of white matter tracts and thus, preserve neural synchrony. Together with analytical solutions for non-biological all-to-all connection scenarios, our model establishes the theoretical principles by which frequency slowing with age, frequently observed in the alpha band in diverse populations, can be viewed as an epiphenomenon of the underlying neurocompensatory mechanisms.

Frequency- and Phase-Dependent Effects of Auditory Entrainment on Attentional Blink

Attentional blink (AB) is the impaired detection of a second target (T2) after a first target has been identified. In this paper, we investigated the functional roles of alpha and theta oscillations on AB by determining how much preceding rhythmic auditory stimulation affected the performance of AB. Healthy young adults participated in the experiment online. We found that when two targets were embedded in rapid serial visual presentation (RSVP) of distractors at 10 Hz (i.e., alpha frequency), the magnitude of AB increased with auditory stimuli. The increase was limited to the case when the frequency and phase of auditory stimuli matched the following RSVP stream. On the contrary, when only two targets were presented without a distractor, auditory stimuli at theta, not alpha, increased the AB magnitude. These results indicate that neural oscillations at two different frequencies, namely alpha and theta, are both involved in attentional blink.

The combination of acute exercise and eye closure has a synergistic effect on alpha activity

Acute aerobic exercise increases the brain cortical activity in alpha frequency. Eye closure also increases alpha activity. However, whether the two have an additive or a synergistic effect on alpha activity has never been explored. This study observed electroencephalography (EEG) from fifteen participants seated on the cycle ergometer before, during, and after a cycling exercise with the eyes open and with them closed. Exercise intensity was set to a target heart rate (120–130 bpm), corresponding to light-to-moderate intensity exercise. Each epoch was 6 min and the last 4 min (eyes closed in the first 2 min and eyes open in the second 2 min) were analyzed. The EEG power spectrum densities were calculated for alpha frequency band activity (8–13 Hz). At rest, alpha activity was significantly greater with the eyes closed than open. Exercise significantly increased alpha activity in both eye conditions. More importantly, in the occipital site, the alpha-increasing effect of their combination was significantly greater than the sum of the effect of each, showing a synergistic effect. We concluded that acute light-to-moderate intensity exercise with the eyes closed has a synergistic effect on alpha activity.

Validation of eyes-closed resting alpha amplitude predicting neurofeedback learning of upregulation alpha activity

Neurofeedback training (NFT) enables users to learn self-control of EEG activity of interest and then to create many benefits on cognitive function. A considerable number of nonresponders who fail to achieve successful NFT have often been reported in the within-session prediction. This study aimed to investigate successful EEG NFT of upregulation alpha activity in terms of trainability, independence, and between-session predictability validation. Forty-six participants completed 12 training sessions. Spectrotemporal analysis revealed the upregulation success on brain activity of 8–12 Hz exclusively to demonstrate trainability and independence of alpha NFT. Three learning indices of between-session changes exhibited significant correlations with eyes-closed resting state (ECRS) alpha amplitude before the training exclusively. Through a stepwise linear discriminant analysis, the prediction model of ECRS’s alpha frequency band amplitude exhibited the best accuracy (89.1%) validation regarding the learning index of increased alpha amplitude on average. This study performed a systematic analysis on NFT success, the performance of the 3 between-session learning indices, and the validation of ECRS alpha activity for responder prediction. The findings would assist researchers in obtaining insight into the training efficacy of individuals and then attempting to adapt an efficient strategy in NFT success.