This Research Topic is part of the ‘Visual Mismatch Negativity (vMMN): A Prediction Error Signal in the Visual Modality’ article collection series:
Visual Mismatch Negativity (vMMN): A Prediction Error Signal in the Visual ModalityThe Research Topic, 'Visual Mismatch Negativity (vMMN): A Prediction Error Signal in the Visual Modality', initiated in 2012, generated a large amount of interest in the field of vMMN, as indicated by more than 137, 000 downloads of these articles. Since the publication of these papers in this special issue, we identified approximately 100 research papers, showing that the area of automatic detection of stimuli deviating from the frequent stimuli of visual sequences has become a highly useful research tool. These investigations have been recently connected to the predictive coding framework similar to the auditory MMN.
The scope of papers included successful and unsuccessful replications of previous research, investigations on the reliability of the concept of ‘automatic predictive coding in vision’, brain localization of vMMN, the sensitivity of the memory system underlying vMMN to various types of stimuli, the introduction of new variables like familiarity, meaningfulness, and more frequently, translational research using various samples of participants. Besides the traditional electrophysiological methods (transient event-related potentials), deviant-related activity was successfully recorded in steady-state activity, magnetoencephalography, and fMRI. Due to the increased interest, we are pleased to present a second edition of this Research Topic, ‘Visual mismatch negativity (vMMN): a unique tool in investigating automatic processing’.
This second volume aims to bring together results from normative and clinical populations, different methodological approaches, a variety of stimulus features, and experimental conditions to investigate automatic change detection in the visual modality.
Original Research articles are of main interest, but Brief Research Report, Case Report, Clinical Trial, Data Report, Opinion, Perspective, Review, and Study Protocol articles are also welcome.
