Using Electroencephalogram-Extracted Nonlinear Complexity and Wavelet-Extracted Power Rhythm Features during the Performance of Demanding Cognitive Tasks (Aristotle's Syllogisms) in Optimally Classifying Patients with Anorexia Nervosa.

Anorexia nervosa is associated with impaired cognitive flexibility and central coherence, i.e., the ability to provide an overview of complex information. Therefore, the aim of the present study was to evaluate EEG features elicited from patients with anorexia nervosa and healthy controls during mental tasks (valid and invalid Aristotelian syllogisms and paradoxes). Particularly, we examined the combination of the most significant syllogisms with selected features (relative power of the time-frequency domain and wavelet-estimated EEG-specific waves, Higuchi fractal dimension (HFD), and information-oriented approximate entropy (AppEn)). We found that alpha, beta, gamma, theta waves, and AppEn are the most suitable measures, which, when combined with specific syllogisms, form a powerful tool for efficiently classifying healthy subjects and patients with AN. We assessed the performance of triadic combinations of "feature-classifier-syllogism" via machine learning techniques in correctly classifying new subjects in these two groups. The following triads attain the best classifications: (a) "AppEn-invalid-ensemble BT classifier" (accuracy 83.3%), (b) "Higuchi FD-valid-linear discriminant" (accuracy 75%), (c) "alpha amplitude-valid-SVM" (accuracy 83.3%), (d) "alpha RP-paradox-ensemble BT" (accuracy 85%), (e) "beta RP-valid-ensemble" (accuracy 85%), (f) "gamma RP-valid-SVM" (accuracy 85%), and (g) "theta RP-valid-KNN" (accuracy 80%). Our findings suggest that anorexia nervosa has a specific information-processing style across reasoning tasks in the brain as measured via EEG activity. Our findings also contribute to further supporting the view that entropy-oriented, i.e., information-based features (the AppEn measure used in this study) are promising diagnostic tools (biomarkers) in clinical applications related to medical classification problems. Furthermore, the main EEG-specific frequency waves are extremely enhanced and become powerful classification tools when combined with Aristotle's syllogisms.

Early auditory-evoked potentials in body dysmorphic disorder: An ERP/sLORETA study.

Body dysmorphic disorder (BDD) is characterized by excessive preoccupation with imagined or slight physical defects in appearance. BDD is associated with cognitive impairments (attention, visual processing). Our study aims to evaluate the early neural responses (N100, P200) to prepulse inhibition (PPI) and prepulse facilitation (PPF), to investigate attentional processing of BDD in the auditory domain. Fifty-five adults took part: 30 BDD patients and 25 healthy controls. We compared their brain responses to PPI and PPF by analyzing global field power (GFP), event-related potentials (ERPs) and their respective sources. BDD exhibited reduced N100 amplitudes compared to healthy controls in response to the startle tone elicited by both PPI and PPF, potentially suggesting impaired allocation of attention. Interestingly, the lower the GFP at the N100, the higher the BDD severity. Source reconstruction analysis showed reduced activation for BDD during the N100 time window in PPI. Scalp responses and source activations in PPI were decreased overall compared to PPF, confirming the gating effect of PPI. We provided evidence that the N100 may serve as an electrophysiological marker of BDD, predicting its severity. Our study demonstrated the potential of using ERPs combined with behavioural PPI and PPF protocols to advance our understanding of BDD pathophysiology.

Test-retest reliability of brain oscillations in a prepulse inhibition and facilitation paradigm: effects of gender in healthy humans.

There is a growing interest in assessing the reliability of electroencephalographic (EEG) measures in clinical and research settings. Prepulse inhibition (PPI: representing attentional modulation) and facilitation (PPF: reflecting selective attention) paradigms have been used to study inhibitory function and selective attention, respectively. However, to date, little has been known with regards to the stability of brain oscillatory activity during PPI and PPF. We investigated the stability of event-related EEG oscillations during PPI and PPF in healthy humans over two monthly sessions. Power spectral densities were analysed at traditional frequency bands (delta, alpha, beta sub-bands, and gamma). We assessed test-retest reliability by calculating intraclass correlation coefficients (ICCs, absolute agreement definition) and examined potential effects of gender. The results showed good-to-excellent reproducibility of EEG power (both in PPI and PPF) over all frequency bands (ICCs > 0.75), except for delta (ICCs < 0.75), with alpha exhibiting the highest repeatability performance. In addition, females showed reduced reliability compared to males in both PPI and PPF, possibly attributed to menstrual cycle phase across our female participants. Overall, our findings suggest that brain oscillatory activity can be test-retest reliable, while gender needs to be controlled with caution. Finally, event-related EEG oscillations during both PPI and PPF could provide a complementary tool to study psychopathology in clinical practice.