Personality cannot be predicted from the power of resting state EEG

In the present study we asked whether it is possible to decode personality traits from resting state EEG data. EEG was recorded from a large sample of subjects (N = 309) who had answered questionnaires measuring personality trait scores of the 5 dimensions as well as the 10 subordinate aspects of the Big Five. Machine learning algorithms were used to build a classifier to predict each personality trait from power spectra of the resting state EEG data. The results indicate that the five dimensions as well as their subordinate aspects could not be predicted from the resting state EEG data. Finally, to demonstrate that this result is not due to systematic algorithmic or implementation mistakes the same methods were used to successfully classify whether the subject had eyes open or eyes closed and whether the subject was male or female. These results indicate that the extraction of personality traits from the power spectra of resting state EEG is extremely noisy, if possible at all.Comment: 14 pages, 4 figure

Visual mismatch negativity (vMMN): A review and meta-analysis of studies in psychiatric and neurological disorders

The visual mismatch negativity (vMMN) response is an event-related potential (ERP) component, which is automatically elicited by events that violate predictions based on prior events. VMMN experiments use visual stimulus repetition to induce predictions, and vMMN is obtained by subtracting the response to rare unpredicted stimuli from those to frequent stimuli. One increasingly popular interpretation of the mismatch response postulates that vMMN, similar to its auditory counterpart (aMMN), represents a prediction error response generated by cortical mechanisms forming probabilistic representations of sensory signals. Here we discuss the physiological and theoretical basis of vMMN and review thirty-three studies from the emerging field of its clinical applications, presenting a meta-analysis of findings in schizophrenia, mood disorders, substance abuse, neurodegenerative disorders, developmental disorders, deafness, panic disorder and hypertension. Furthermore, we include reports on aging and maturation as they bear upon many clinically relevant conditions. Surveying the literature we found that vMMN is altered in several clinical populations which is in line with aMMN findings. An important potential advantage of vMMN however is that it allows the investigation of deficits in predictive processing in cognitive domains which rely primarily on visual information; a principal sensory modality and thus of vital importance in environmental information processing and response, and a modality which arguably may be more sensitive to some pathological changes. However, due to the relative infancy of research in vMMN compared to aMMN in clinical populations its potential for clinical application is not yet fully appreciated. The aim of this review and meta-analysis therefore is to present, in a detailed systematic manner, the findings from clinically-based vMMN studies, to discuss their potential impact and application, to raise awareness of this measure and to improve our understanding of disease upon fundamental aspects of visual information processing

Reaction time to motion onset and magnitude estimation of velocity in the presence of background motion

AbstractReaction times (RT) to motion onset of a target grating moving at 0.4, 0.6, 0.8, 1.0 or 1.6°/s and magnitude estimation of the same velocities were studied in the presence of the surrounding background motion which was either in the same or opposite direction. Surprisingly, we found no relative motion effect: if the background motion, irrespective of its direction, affected the target, then it delayed the RTs and decreased velocity ratings. The background motion was effective on RTs to motion onset only when the target was relatively small and immediately surrounded by a moving background. Increases in RTs were mostly explained by an apparent slowdown of the target stimulus velocity which was caused by the interference from the moving background. The background motion also affected velocity ratings by decreasing them without systematic effect of the background motion direction