Abstract
Our visual field contains much more information at everymoment than we can attend and consciously process. How isthe multitude of unattended events processed in the brain andselected for the further attentive evaluation? Current theories ofvisual change detection emphasize the importance of consciousattention to detect changes in the visual environment. However,an increasing body of studies shows that the human brain iscapable of detecting even small visual changes if such changesviolate non-conscious probabilistic expectations based on priorexperiences. In other words, our brain automatically representsenvironmental statistical regularities.Since the discovery of the auditory mismatch negativity(MMN) event-related potential (ERP) component, the majorityof research in the field has focused on auditory deviance detec-tion.Suchautomaticchangedetectionmechanismsoperateinthevisual modality too, as indicated by the visual mismatch negativ-ity (vMMN) brain potential to rare changes. vMMN is typicallyelicited by stimuli with infrequent (deviant) features embeddedin a stream of frequent (standard) stimuli, outside the focus ofattention. Information about both simple and more complexcharacteristics of stimuli is rapidly processed and stored by thebrain in the absence of conscious attention.InthisresearchtopicweaimtopresentvMMNasapredictionerror signal and put it in context of the hierarchical predictivecoding framework. Predictive coding theories account for phe-nomena such as MMN and repetition suppression, and placetheminabroadercontextofageneraltheoryofcorticalresponses(Friston,2005,2010).EachpaperinthisResearchTopicisavalu-able contribution to the field of automatic visual change detec-tion and deepens our understanding of the short term plasticityunderlying predictive processes of visual perceptual learning.A wide range of vMMN studies has been presented in sev-enteen articles in this Research Topic. Twelve articles addressroughly four general sub-themes including attention, language,faceprocessing,andpsychiatricdisorders.Additionally,fourarti-cles focused on particular subjects such as the oblique effect,object formation, and development and time-frequency analysisof vMMN. Furthermore, a review paper presented vMMN in ahierarchical predictive coding framework.Four articles investigated the relationship between attentionand vMMN. Kremlaˇcek et al. (2013) presented subjects withradial motion stimuli in the periphery of the visual field usingan oddball paradigm and manipulated the attentional load byvarying the difficulty of a central distractor tasks. They aimedto manipulate the amount of available attentional resources thatmight have been involuntarily captured by the vMMN-evokingstimulipresentedintheperipheryoutsideoftheattentionalfocus.The distractor task had three difficulty levels: (1) a central fix-ation (easy), and a target number detection task with (2) onetarget number (moderate), and (3) three target numbers (diffi-cult). Analysis of deviant minus standard differential waveformsrevealed a significant posterior negativity in the ∼140–200msinterval,whichwasunaffectedbythedifficultyofthecentraltask,indicatingthattheautomaticprocessesunderlyingregistrationofchanges in motion are independent of attentional resources usedto detect target numbers.Kimura and Takeda (2013) investigated whether characteris-tics of vMMN depended on the difficulty of an attended primarytask, i.e., they tested the level of automaticity of the vMMN. Taskdifficulty was manipulated as the magnitude of change of a cir-cle at fixation, and vMMN was elicited by deviant orientationof bar patterns. An equal probability control condition was alsoused. The difference potential between the deviant-related ERPand the ERP elicited by identical orientation pattern in the con-trol condition appeared to be influenced by the difficulty of theattentive task. As a function of task difficulty, the latency of thedifference potential (i.e., the vMMN) increased, indicating thatprocesses underlying vMMN to orientation changes are not fullyindependent of the attention demands of the ongoing tasks.Kuldkepp et al. (2013) used rare changes in direction ofperipheral motion to evoke vMMN applying a novel continuouswhole-display stimulus configuration. The demanding distractortask involved motion onset detection and was presented in thecenter of the visual field. The level of attention to the vMMN-evoking stimuli was varied by manipulating their task-relevanceusing “Ignore” and “Attend” conditions. Deviant minus standardwaveforms in the “Ignore” condition showed significant vMMNin the 100–200, 250–300, and 235–375ms intervals, whereas in
Highlights
Our visual field contains much more information at every moment than we can attend and consciously process
Since the discovery of the auditory mismatch negativity (MMN) event-related potential (ERP) component, the majority of research in the field has focused on auditory deviance detection
Such automatic change detection mechanisms operate in the visual modality too, as indicated by the visual mismatch negativity brain potential to rare changes. vMMN is typically elicited by stimuli with infrequent features embedded in a stream of frequent stimuli, outside the focus of attention
Summary
Our visual field contains much more information at every moment than we can attend and consciously process. Kremlácek et al (2013) presented subjects with radial motion stimuli in the periphery of the visual field using an oddball paradigm and manipulated the attentional load by varying the difficulty of a central distractor tasks.
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