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Social interactions require quick perception, interpretation, and categorization of faces, with facial features offering cues to emotions, intentions, and traits. Importantly, reactions to faces depend not only on their features but also on their processing fluency, with disfluent faces suffering social devaluation. The current research used electrophysiological (EEG) and behavioral measures to explore at what processing stage and under what conditions emotional ambiguity is detected in the brain and how it influences trustworthiness judgments. Participants viewed male and female faces ranging from pure anger, through mixed expressions, to pure happiness. They categorized each face along the experimental dimension (happy vs. angry) or a control dimension (gender). In the emotion-categorization condition, mixed (ambiguous) expressions were classified relatively slower, and their trustworthiness was rated relatively lower. EEG analyses revealed that early brain responses are independent of the categorization condition, with pure faces evoking larger P1/N1 responses than mixed expressions. Some late (728- 880 ms) brain responses from central-parietal sites also were independent of the categorization condition and presumably reflect familiarity of the emotion categories, with pure expressions evoking larger central-parietal LPP amplitude than mixed expressions. Interestingly, other late responses were sensitive to both expressive features and categorization task, with ambiguous faces evoking a larger LPP amplitude in frontal-medial sites around 560-660 ms but only in the emotion categorization task. Critically, these late responses from the frontal-medial cluster correlated with the reduction in trustworthiness judgments. Overall, the results suggest that ambiguity detection involves late, top-down processes and that it influences important social impressions. Electronic supplementary material The online version of this article (10.3758/s13415-020-00778-5) contains supplementary material, which is available to authorized users.

This project has been carried out in the context of recent major developments in botics and more widespread usage of virtual agents in personal and professional sphere. The general purpose of the experiment was to thoroughly examine the character of the human–non-human interaction process. Thus, in the paper, we present a study of human–chatbot interaction, focusing on the affective responses of users to different types of interfaces with which they interact. The experiment consisted of two parts: measurement of psychophysiological reactions of chatbot users and a detailed questionnaire that focused on assessing interactions and willingness to collaborate with a bot. In the first quantitative stage, participants interacted with a chatbot, either with a simple text chatbot (control group) or an avatar reading its responses in addition to only presenting them on the screen (experimental group. We gathered the following psychophysiological data from participants: electromyography (EMG), respirometer (RSP), electrocardiography (ECG), and electrodermal activity (EDA). In the last, declarative stage, participants filled out a series of questionnaires related to the experience of interacting with (chat)bots and to the overall human–(chat)bot collaboration assessment. The theory of planned behaviour survey investigated attitude towards cooperation with chatbots in the future. The social presence survey checked how much the chatbot was considered to be a “real” person. The anthropomorphism scale measured the extent to which the chatbot seems humanlike. Our particular focus was on the so-called uncanny valley effect, consisting of the feeling of eeriness and discomfort towards a given medium or technology that frequently appears in various kinds of human–machine interactions. Our results show that participants were experiencing lesser uncanny effects and less negative affect in cooperation with a simpler text chatbot than with the more complex, animated avatar chatbot. The simple chatbot have also induced less intense psychophysiological reactions. Despite major developments in botics, the user’s affective responses towards bots have frequently been neglected. In our view, understanding the user’s side may be crucial for designing better chatbots in the future and, thus, can contribute to advancing the field of human–computer interaction.

For decades, the frontal alpha asymmetry (FAA) – a disproportion in EEG alpha oscillations power between right and left frontal channels – has been one of the most popular measures of depressive disorders (DD) in electrophysiology studies. Patients with DD often manifest a left-sided FAA: relatively higher alpha power in the left versus right frontal lobe. Recently, however, multiple studies failed to confirm this effect, questioning its reproducibility. Our purpose is to thoroughly test the validity of FAA in depression by conducting a multiverse analysis – running many related analyses and testing the sensitivity of the effect to changes in the analytical approach – on data from five independent studies. Only 13 of the 270 analyses revealed significant results. We conclude the paper by discussing theoretical assumptions underlying the FAA and suggest a list of guidelines for improving and expanding the EEG data analysis in future FAA studies.

Frontal alpha asymmetry (FAA) is one of the most common electrophysiological measures in research on depressive disorders (DD). Many previous studies reported a relatively higher alpha band power in the left versus right frontal channels (left-sided FAA) in people with DD compared to healthy controls. Recently, however, multiple studies failed to replicate this finding and a meta-analysis has cast doubt on the relationship between FFA and DD (van der Vinne et al., 2017). To test the robustness and reproducibility of the relationship between FAA and DD we conducted a multiverse analysis of resting state EEG data from three independent studies with 218 participants in total. We performed 81 analyses altogether - some replicatory and other improving on the methodology used in past FAA studies - differing in: a) channel vs source level signal: using average reference, current source density or DICS beamforming; b) channel pairs selection and correction for multiple comparisons; c) statistical approach: group contrasts vs linear regression. Only two of the 81 analyses revealed significant results - an outcome expected with a 5% type I error rate (p = 0.917, binomial test). Therefore, the conducted analyses do not provide a basis to reject the null hypothesis of no relationship between resting state FAA and DD in spite of (or maybe due to) various methodological improvements. We conclude the paper by discussing theoretical assumptions underlying the FAA and suggest a list of guidelines for improving and expanding the EEG data analysis in future FAA studies.

Electrophysiological investigations have pointed out significant yet weak correlations between intelligence and oscillatory brain activity, including the spectral power, frequency, complexity, synchrony, and coherence of electroencephalographic (EEG) signals, however neglecting the interplay between fast and slow neuronal oscillations underlying information transfer in the brain. We found that fluid intelligence level (gf) depends on the precise synchronization of fast oscillations to a specific time window of slow brain rhythms. Specifically, by examining EEG recordings of 50 people in resting state as well as during performance at two gf tasks we found converging evidence that high-gf participants display stronger Phase-Amplitude Coupling (PAC) related to an increased concentration of gamma (~ 36 Hz) spectral power at the descending phase of delta oscillations (~ 3 Hz). Delta-gamma PAC strength explained 35% variance in scores on multiple gf tests, outperforming six alternative EEG-based predictors including spectral power, complexity and amplitude-amplitude coupling. Present results suggest PAC as a neurophysiological substrate of gf in humans, offering novel insight about the role of slow and fast brain rhytms in high-order cognition, as well as a potential new target for neuromodulatory interventions in the healthy and pathological brain.

Many decisions require sequentially searching through the available alternatives. In these tasks, older adults have been shown to perform worse than younger adults, but the reasons why age differences occur are still unclear. In the present research, we tackle this question by investigating which strategies older and younger adults adopt and how these strategies relate to individual differences in cognitive (mental speed, working memory capacity) and motivational (need for cognitive closure) variables. To achieve this goal, we conducted two studies in which older and younger adults performed a computerized sequential choice task. Study 1 indicated that older adults changed their decision-making strategies throughout the task by reducing the number of options they considered. This change in strategy did not decrease performance because searching less allowed older adults to choose more promising options. In the second study we manipulated whether a long or short search was optimal. In the beginning older adults performed worse than younger adults independent of whether short or long search was adaptive. However, in the second half of the task we found age differences in performance when long search was required, but not when short search was required. In both studies whether or not older adults changed their strategy depended on their need for cognitive closure, suggesting that avoiding cognitive closure facilitates adaptive flexibility. Together, the two studies provide evidence for compensatory strategy adaptations among older adults completing sequential choice tasks. (PsycINFO Database Record (c) 2018 APA, all rights reserved)

Experienced video game players exhibit superior performance in visuospatial cognition when compared to non-players. However, very little is known about the relation between video game experience and structural brain plasticity. To address this issue, a direct comparison of the white matter brain structure in RTS (real time strategy) video game players (VGPs) and non-players (NVGPs) was performed. We hypothesized that RTS experience can enhance connectivity within and between occipital and parietal regions, as these regions are likely to be involved in the spatial and visual abilities that are trained while playing RTS games. The possible influence of long-term RTS game play experience on brain structural connections was investigated using diffusion tensor imaging (DTI) and a region of interest (ROI) approach in order to describe the experience-related plasticity of white matter. Our results revealed significantly more total white matter connections between occipital and parietal areas and within occipital areas in RTS players compared to NVGPs. Additionally, the RTS group had an altered topological organization of their structural network, expressed in local efficiency within the occipito-parietal subnetwork. Furthermore, the positive association between network metrics and time spent playing RTS games suggests a close relationship between extensive, long-term RTS game play and neuroplastic changes. These results indicate that long-term and extensive RTS game experience induces alterations along axons that link structures of the occipito-parietal loop involved in spatial and visual processing.

We have previously shown that beta-band EEG activity is related to attentional modulation in the visual system of cats and humans. In a separate experiment we also observed that some elderly subjects expressed beta-band power decreases during a simple visual attention task, an effect which was accompanied by low behavioral accuracy in this subgroup. Here, we conducted a detailed examination of beta power deficits in elderly subjects in comparison to young controls. In order to do so, we equalized the subjective level of task difficulty by adjusting visual stimuli presentation duration in such a way that elderly and young subjects achieved similar behavioral results. We found that: (1) beta-band power of EEG signals recorded over occipital regions in elderly and young groups is related to visual attention, as judged from increases in beta power preceding correct responses and lack of beta activity change before erroneous responses; (2) despite forming a homogeneous group when screened for dementia (MMSE), age, education level, visual correction, and speed-accuracy trade-off strategy, elderly subjects could be assigned into one of the two subgroups: high performers, who did not differ from young performers in terms of beta-band power increases, and low ;performers, whose beta power decreased during the most difficult attentional conditions (shortest - 3 s and longest - 11 s cue-target delays). These findings posit that the beta-band activity decrease recorded in low performing elderly subjects reflects difficulty in activation and deficits in sustaining attentional processes. (C) 2013 Elsevier B.V. All rights reserved.

We have investigated the interplay between face orientation, eye presence, and N170 amplitude by recording Event Related Potentials. To clarify previous reports of nonlinearity in N170 amplitude changes along rotation angle changes, we adopted Itier et al.'s model (Itier et al., 2007) which links N170 face inversion effects with the presence of eyes. Comparison of N170 amplitude and latency for five stimulus categories (Faces-with-eyes, Faces-without-eyes, Eyes, Cars-with-lights, Cars-without-lights) in five different rotations (0, 45, 90, 135, 180) resulted in mixed conclusions. The main findings of this study are as follows: (1) a strong nonlinear relationship between N170 and angle of rotation that is specific to faces, distinguishing face from car category even when no significant differences were observed between these categories for upright and inverted orientations; and (2) the nonlinear relationship between N170 and angle of rotation does not depend on eye presence. We also propose an alternative model according to which N170 amplitude consists of two related aspects of face processing: (A) incompatibility (relative distance of the stimulus pattern from experience-based hypothetical prototype) and (B) integration (degree to which stimulus is integrated into holistic representation), with the former affecting the latter. Moreover, we suggest two possible neural events underlying these two aspects of face processing: neural population size activated by the stimulus, and synchronization within this population.