Behavioral, Physiological and EEG Activities Associated with Conditioned Fear as Sensors for Fear and Anxiety

Music boosts the recovery of attention after mental fatigue in healthy young male subjects: A human auditory event-related potential study

Daily life faces continuous cognitive tasks. Several methods could lessen cognitive fatigue including music. To find out how music functions in recovering cognitive fatigue, twenty-seven participants were randomly assigned to the rest group (N = 12) and the music group (N = 15). To evaluate the effects of Mozart K488 music on attention function after a continuous cognitively demanding task. Participants completed subjective questionnaires and the contingent negative variation (CNV) task before fatigue, after fatigue, and after the rest/musical intervention. EEG and ECG data were also collected during the experiment. The results showed that 5 min of Mozart K488 music resulted in improved CNV task performance in the musical intervention group. For EEG data, recoveries of the initial CNV and terminal CNV amplitude in Cz and CPz electrodes were observed and compared with the values after Mental Fatigue, which music increased the iCNV and tCNV. Alpha-ERD was lower after listening to music than after resting. Moreover, during music playing, compared to other brain regions the EEG alpha power of participants was significantly high in the central frontal region. This study demonstrates a short-term musical intervention can effectively boost the recovery of attention after Mental Fatigue.

Characterizing PTSD Using Electrophysiology: Towards A Precision Medicine Approach

Objective. Resting-state EEG measures have shown potential in distinguishing individuals with PTSD from healthy controls. ERP components such as N2, P3, and late positive potential have been consistently linked to cognitive abnormalities in PTSD, especially in tasks involving emotional or trauma-related stimuli. However, meta-analyses have reported inconsistent findings. The understanding of biomarkers that can classify the varied symptoms of PTSD remains limited. This study aimed to develop a concise set of electrophysiological biomarkers, using neutral cognitive tasks, that could be applied across psychiatric conditions, and to identify biomarkers associated with the anxiety and depression dimensions of PTSD. Approach. Continuous simultaneous recordings of EEG and electrocardiogram (ECG) were obtained in veterans with PTSD (n = 29) and healthy controls (n = 62) during computerized tasks. EEG, ERP, and heart rate measures were evaluated in terms of their ability to discriminate between the groups or correlate with psychological measures. Results. The PTSD cohort exhibited faster alpha oscillations, reduced alpha power, and a flatter power spectrum. Furthermore, stronger reduction in alpha power was associated with higher trait anxiety, while a flatter slope was related to more severe depression symptoms in individuals with PTSD. In ERP tasks of visual memory and sustained attention, the PTSD cohort demonstrated delayed and exaggerated early components, along with attenuated LPP amplitudes. The three tasks revealed distinct and complementary EEG signatures PTSD. Significance. Multimodal individualized biomarkers based on EEG, cognitive ERPs, and ECG show promise as objective tools for assessing mood and anxiety disturbances within the PTSD spectrum.

Neuroscience of the human thalamus related to acute pain and chronic "thalamic" pain

The association of posterior thalamic strokes with the presence of chronic "thalamic" pain was described in the early 1900s and revisited in a recent review of these patients. Acute pain in corporal structures is associated with the spinothalamic tract (STT), which originates in the dorsal horn of the spinal cord, whereas that associated with cranial structures is associated with the spinal division of the trigeminal nucleus. These pathways terminate in the ventral posterior nucleus (VP), including its posterior and inferior subnuclei and its core, which is classically associated with tactile and haptic functions. In medial nuclei (medial dorsal and intralaminar) receptive fields are large and stimulation evokes diffuse unpleasant sensations and pain while neurons in these nuclei subserve cognitive processes of attention, alerting, and conditioning. In the lateral nuclei neurons have small receptive and projected fields and high resolution of responses to somatic stimuli. Neurons in the lateral nuclei respond to stimuli producing pain, temperature, and visceral sensations while stimulation evokes similar sensations. Small strokes in VP core versus structures located inferior and posterior are associated with thalamic pain and decreased tactile, painful, and cold sensations and with decreased evoked potentials for painful (laser) heat and median nerve stimulation (electrical). Lesions of VP, but not ventral medial posterior nucleus (VMpo), are associated with thalamic pain, contrary to the recent "disinhibition" model. We review the evidence that the lateral nuclei are associated with multiple processes including tactile, nociceptive, visceral, and thermal content of stimuli, whereas the medial nuclei are related to cognitions about those stimuli.

Detection of Anxiety-Based Epileptic Seizures in EEG Signals Using Fuzzy Features and Parrot Optimization-Tuned LSTM

In humans, epilepsy is diagnosed through electroencephalography (EEG) signals. Epileptic seizures (ESs) arise due to anxiety. The detection of anxiety-based seizures is challenging for radiologists, and there is a limited availability of anxiety-based EEG signals. Data augmentation methods are required to increase the number of novel samples. An epileptic seizure arises due to anxiety, which manifests as variations in EEG signal patterns consisting of changes in the size and shape of the signal. In this study, anxiety EEG signals were synthesized by applying data augmentation methods such as random data augmentation (RDA) to existing epileptic seizure signals from the Bonn EEG dataset. The data-augmented anxiety seizure signals were processed using three algorithms-(i) fuzzy C-means-particle swarm optimization-long short-term memory (FCM-PS-LSTM), (ii) particle swarm optimization-long short-term memory (PS-LSTM), and (iii) parrot optimization LSTM (PO-LSTM)-for the detection of anxiety ESs via EEG signals. The predicted accuracies of detecting ESs through EEG signals using the proposed algorithms-namely, (i) FCM-PS-LSTM, (ii) PS-LSTM, and (iii) PO-LSTM-were about 98%, 98.5%, and 96%, respectively.

Oscillatory correlates of threat imminence during virtual navigation

The Predatory Imminence Continuum Theory proposes that defensive behaviors depend on the proximity of a threat. While the neural mechanisms underlying this proposal are well studied in animal models, it remains poorly understood in humans. To address this issue, we recorded EEG from 24 (15 female) young adults engaged in a first-person virtual reality Risk-Reward interaction task. On each trial, participants were placed in a virtual room and presented with either a threat or reward conditioned stimulus (CS) in the same room location (proximal) or different room location (distal). Behaviorally, all participants learned to avoid the threat-CS, with most using the optimal behavior to actively avoid the proximal threat-CS (88% accuracy) and passively avoid the distal threat-CS (69% accuracy). Similarly, participants learned to actively approach the distal reward-CS (82% accuracy) and to remain passive to the proximal reward-CS (72% accuracy). At an electrophysiological level, we observed a general increase in theta power (4-8 Hz) over the right posterior channel P8 across all conditions, with the proximal threat-CS evoking the largest theta response. By contrast, distal cues induced two bursts of gamma (30-60 Hz) power over midline-parietal channel Pz (200 msec post-cue) and right frontal channel Fp2 (300 msec post-cue). Interestingly, the first burst of gamma power was sensitive to the distal threat-CS and the second burst at channel Fp2 was sensitive to the distal reward-CS. Together, these findings demonstrate that oscillatory processes differentiate between the spatial proximity information during threat and reward encoding, likely optimizing the selection of the appropriate behavioral response.

Emotion Self-Regulation in Neurotic Students: A Pilot Mindfulness-Based Intervention to Assess Its Effectiveness through Brain Signals and Behavioral Data

Neuroticism has recently received increased attention in the psychology field due to the finding of high implications of neuroticism on an individual’s life and broader public health. This study aims to investigate the effect of a brief 6-week breathing-based mindfulness intervention (BMI) on undergraduate neurotic students’ emotion regulation. We acquired data of their psychological states, physiological changes, and electroencephalogram (EEG), before and after BMI, in resting states and tasks. Through behavioral analysis, we found the students’ anxiety and stress levels significantly reduced after BMI, with p-values of 0.013 and 0.027, respectively. Furthermore, a significant difference between students in emotion regulation strategy, that is, suppression, was also shown. The EEG analysis demonstrated significant differences between students before and after MI in resting states and tasks. Fp1 and O2 channels were identified as the most significant channels in evaluating the effect of BMI. The potential of these channels for classifying (single-channel-based) before and after BMI conditions during eyes-opened and eyes-closed baseline trials were displayed by a good performance in terms of accuracy (~77%), sensitivity (76–80%), specificity (73–77%), and area-under-the-curve (AUC) (0.66–0.8) obtained by k-nearest neighbor (KNN) and support vector machine (SVM) algorithms. Mindfulness can thus improve the self-regulation of the emotional state of neurotic students based on the psychometric and electrophysiological analyses conducted in this study.