The roles of spatial frequency in category‐level visual search of real‐world scenes

Other ethnicity effects in ensemble coding of facial expressions

Cultural difference in ensemble emotion perception is an important research question, providing insights into the complexity of human cognition and social interaction. Here, we conducted two experiments to investigate how emotion perception would be affected by other ethnicity effects and ensemble coding. In Experiment 1, two groups of Asian and Caucasian participants were tasked with assessing the average emotion of faces from their ethnic group, other ethnic group, and mixed ethnicity groups. Results revealed that participants exhibited relatively accurate yet amplified emotion perception of their group faces, with a tendency to overestimate the weight of the faces from the other ethnic group. In Experiment 2, Asian participants were instructed to discern the emotion of a target face surrounded by faces from Caucasian and Asian faces. Results corroborated earlier findings, indicating that while participants accurately perceived emotions in faces of their ethnicity, their perception of Caucasian faces was noticeably influenced by the presence of surrounding Asian faces. These findings collectively support the notion that the other ethnicity effect stems from differential emotional amplification inherent in ensemble coding of emotion perception.

Grounding Context in Embodied Cognitive Robotics

Biological agents are context-dependent systems that exhibit behavioral flexibility. The internal and external information agents process, their actions, and emotions are all grounded in the context within which they are situated. However, in the field of cognitive robotics, the concept of context is far from being clear with most studies making little to no reference to it. The aim of this paper is to provide an interpretation of the notion of context and its core elements based on different studies in natural agents, and how these core contextual elements have been modeled in cognitive robotics, to introduce a new hypothesis about the interactions between these contextual elements. Here, global context is categorized as agent-related, environmental, and task-related context. The interaction of their core elements, allows agents to first select self-relevant tasks depending on their current needs, or for learning and mastering their environment through exploration. Second, to perform a task and continuously monitor its performance. Third, to abandon a task in case its execution is not going as expected. Here, the monitoring of prediction error, the difference between sensorimotor predictions and incoming sensory information, is at the core of behavioral flexibility during situated action cycles. Additionally, monitoring prediction error dynamics and its comparison with the expected reduction rate should indicate the agent its overall performance on executing the task. Sensitivity to performance evokes emotions that function as the driving element for autonomous behavior which, at the same time, depends on the processing of the interacting core elements. Taking all these into account, an interactionist model of contexts and their core elements is proposed. The model is embodied, affective, and situated, by means of the processing of the agent-related and environmental core contextual elements. Additionally, it is grounded in the processing of the task-related context and the associated situated action cycles during task execution. Finally, the model proposed here aims to guide how artificial agents should process the core contextual elements of the agent-related and environmental context to give rise to the task-related context, allowing agents to autonomously select a task, its planning, execution, and monitoring for behavioral flexibility.