Valence processing of first impressions in the dorsomedial prefrontal cortex

Abstract

Previous studies have suggested that the dorsomedial prefrontal cortex (dmPFC) plays a central role in processing first impressions; however, little is known about how dmPFC processes different valences of first impressions. Moreover, it is still unclear as to whether the dmPFC shows lateralization or only induces different levels of activation when processing positive and negative impressions. To address these questions in the present study, the brain activities for the impression judgments expressed by participants were measured with near-infrared spectroscopy. For each real facial picture, participants were asked to evaluate their first impressions on a scale from 'bad' to 'good' using a keyboard. The results showed that although the right dmPFC has a higher sensitivity in processing impressions, both the hemispheres of dmPFC showed a significant trend where the activation of positive impressions was higher than the negative ones. Accordingly, it is proposed that the dmPFC acts as a single mechanism responsible for delineating the processing of first impressions rather than two lateralized systems. Therefore, a 'positivity dominance hypothesis' is also proposed, which states that dmPFC in both hemispheres have a higher sensitivity and priority for positive impressions than negative ones. The present study provides valuable findings with respect to the role of the dmPFC in the processes of first impression formation.

A Dual Route Model of Empathy: A Neurobiological Prospective

“…For example, previous evidence showed that both cognitive and affective empathy-associated brain regions are more activated when people observe familiar friends than unfamiliar strangers in pain (Meyer et al, 2012 ). A number of studies further suggested that the brain regions for impression formation are highly overlapped with the areas supporting cognitive empathy (Mitchell et al, 2004 ; Schiller et al, 2009 ; Yu et al, 2016 ). According to these lines of evidence, the present opinion suggests that our prior knowledge constructs a moderated role on both the lower and higher routes.…”

Multi-time-point analysis: A time course analysis with functional near-infrared spectroscopy

“…Although there was a method for mass univariate analysis to obtain enough power by averaging the original number of time points to a much smaller number of time points (H.-C. Chen et al, 2011;H.-C. Chen et al, 2008;Khan, Hong, & Hong, 2014;Scholkmann, Wolf, & Wolf, 2013;B. Xu et al, 2014;Yu et al, 2016;Zimmermann et al, 2013), we argue that this method may decrease the temporal resolution due to loss of information on the neglected time points. By contrast, without losing any temporal information, MTPA was able to detect a significant difference between conditions with many time points and further led to a conclusion consistent with previous research.…”

“…Also, this choice echoed the rationale of a widely used down-sampling approach (Chen et al, 2011;Chen et al, 2008;Khan, Hong, & Hong, 2014;Scholkmann, Wolf, & Wolf, 2013;B. Xu et al, 2014;Yu et al, 2016;Zimmermann et al, 2013), which typically averages s e v er al n ei gh bo r i ng t i m e p o i n t s to a 5 H z r a t e ( Our sampling rate Bandwidth ¼ 10 Hz 2 ¼ 5 Hz ). Furthermore, implementing larger bandwidths did not provide additional benefit to constitute a significant improvement over a bandwidth of 2 in the present NIRS data set (the results of a bandwidth of 3 are also shown in Supplementary Figure 2 for demonstration purposes).…”

“…In order to obtain the time course information for fNIRS data, researchers usually implement mass univariate analysis. Under the linear model framework, mass univariate analysis can examine the differences between different experimental conditions at each individual time point (H.-C. Chen, Vaid, Boas, & Bortfeld, 2011;H.-C. Chen, Vaid, Bortfeld, & Boas, 2008;Mihara, Miyai, Hatakenaka, Kubota, & Sakoda, 2008;Yu, Wang, & Hu, 2016). For example, H.-C. Chen et al (2011) used the one-sample t test to directly examine whether increases in oxyhemoglobin concentration significantly differed from zero under each sampled time point, and used the paired t test to examine whether increases in oxyhemoglobin concentration differed significantly from one condition to another.…”

Fabric Softener Fragrances Modulate the Impression Toward Female Faces and Frontal Brain Activity

“…Then, the waveform was replotted so that the signal change value at the onset was 0. Based on previous fNIRS studies demonstrating significant oxy‐Hb signal changes around 10–20 s after visual stimulation (Takahashi et al, ; Yu, Wang, & Hu, ), the analysis period was set at 10–20 s after the onset of the facial photograph, and the signal changes during the analysis period were averaged and used as the indices of brain activity for the faces. The mean signal changes were examined by ANOVA.…”