Is it a face of a woman or a man? Visual mismatch negativity is sensitive to gender category

Abstract

The present study investigated whether gender information for human faces was represented by the predictive mechanism indexed by the visual mismatch negativity (vMMN) event-related brain potential (ERP). While participants performed a continuous size-change-detection task, random sequences of cropped faces were presented in the background, in an oddball setting: either various female faces were presented infrequently among various male faces, or vice versa. In Experiment 1 the inter-stimulus-interval (ISI) was 400 ms, while in Experiment 2 the ISI was 2250 ms. The ISI difference had only a small effect on the P1 component, however the subsequent negativity (N1/N170) was larger and more widely distributed at longer ISI, showing different aspects of stimulus processing. As deviant-minus-standard ERP difference, a parieto-occipital negativity (vMMN) emerged in the 200–500 ms latency range (~350 ms peak latency in both experiments). We argue that regularity of gender on the photographs is automatically registered, and the violation of the gender category is reflected by the vMMN. In conclusion the results can be interpreted as evidence for the automatic activity of a predictive brain mechanism, in case of an ecologically valid category.

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

“…These alterations are observed as decreased response amplitude (e.g., K€ ahk€ onen et al, 2007;Takei et al, 2009), delayed latency and different source location of the change detection-related activity (Takei et al, 2010). The previous studies in depressive participants have not found relationship between clinical c o r t e x x x x ( 2 0 1 6 ) 1 e3 7 13 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 ...…”

“…The neural mechanisms underlying disturbances in cognitive functions are poorly understood, and they may be present even at the level of automatic information processing (for a review, see Beck, 2008). Therefore several studies used aMMN (or its magnetic counterpart, MMNm) to study automatic sensorycognitive processes in depression (Iv, Zhao, Gong, Chen, & Miao, 2010;K€ ahk€ onen et al, 2007;Lepist€ o et al, 2004;Pang et al, 2014;Takei et al, 2009) and BP (Andersson, Barder, Hellvin, Løvdahl, & Malt, 2008;Takei et al, 2010). Takei et al applied magnetoencephalography to measure information processing deficit in depression (2009) andBP (2010).…”

“…Especially studies using elementary visual features (e.g., orientation or color changes), abstract or rule-like changes (e.g., Kecskes-Kovacs et al, 2013a) and perhaps also emotional changes like changes in facial expressions in same participant groups would be very informative. In a long run these vMMN studies can be applied for developing diagnostic tools.…”

“…Introduction again similar to aMMN that can be elicited by rare changes in more abstract attributes of the acoustic stimuli than simple physical features, vMMN is also sensitive to higher-level attributes such as sequential regularities (Stefanics, Kimura, et al, 2011), object structure (Mü ller, Widmann, & Schr€ oger, 2013), symmetry (Kecskes-Kovacs, Sulykos, & Czigler, 2013a), laterality of body parts , or attributes of socially more relevant stimuli such as facial emotions (Astikainen & Hietanen, 2009;Fujimura & Okanoya, 2013;Susac, Ilmoniemi, Pihko, Ranken, & Supek, 2010;Susac, Ilmoniemi, Pihko, & Supek, 2004;Zhao & Li, 2006), as well as facial gender (Kecskes-Kovacs, Sulykos, & Czigler, 2013b). Thus, there is ample evidence that automatic perceptual predictive mechanisms operate in the visual modality too, which can be probed by experimentally manipulating statistical properties of a wide variety of stimulus attributes or their relationships.…”

“…This is in line with a recent EEG study where SSA was found to depend critically on statistical context in the auditory cortex (Herrmann, Henry, Fromboluti, McAuley, & Obleser, 2015), and that aMMN itself is a compound response of primary and higher-level cortical areas with longer response latencies. Adaptation has been observed in electrophysiological studies throughout the visual system including the retina (Hosoya, Baccus, & Meister, 2005), thalamus (Solomon, Peirce, Dhruv, & Lennie, 2004), superior colliculus (Boehnke et al, 2011), and several cortical areas (Kaliukhovich & Vogels, 2014;Kremlacek et al, 2007;Meyer, Ramachandran, & Olson, 2014;Motter, 2006;Mü ller, Metha, Krauskopf, & Lennie, 1999;Ramachandran, Meyer, & Olson, 2016; for a review, see Vogels, in press). Although the exact relationship of adaptation at different levels of the visual processing hierarchy to change detection as observed in vMMN studies (e.g., Kimura et al, 2011;Stefanics et al, 2014) is not clear, there is general agreement that the function of adaptation is to match response properties of the sensory system to the current environment (Clifford et al, 2007;Webster, 2011) and thus improve stimulus discrimination or detection of improbable stimuli (Benucci, Saleem & Carandini, 2013;Carandini & Heeger, 2012;Kohn, 2007;Solomon & Kohn, 2014;Wark, Lundstrom, & Fairhall, 2007).…”