The ability to understand how others feel, both in terms of emotional category and intensity, is central to navigating social life. Despite extensive research on emotion recognition, it remains unclear how different communication channels influence this ability, or how accurately people gauge others’ emotional intensity. My research addresses these gaps by examining how individuals interpret emotional signals through auditory, visual, and combined modalities across neurotypical and clinical populations. Using naturalistic paradigms such as the empathic accuracy task with dynamic video stimuli, I examine emotional processing in real-life contexts. My findings challenge assumptions about facial cue dominance, showing that auditory information often carries more emotional insight. Neural data from EEG studies reveal that emotional understanding in visual-only settings relies more heavily on simulation mechanisms, such as mu rhythm suppression. Building on these insights, I am investigating how autistic individuals process emotional cues across different channels to identify optimal communication modalities for their social understanding—representing a paradigmatic shift from deficit-focused research to identifying sensory-informed strengths for tailored interventions. I also explore how accurately people assess the intensity of others’ emotions. Across multiple studies, I found that people systematically overestimate emotional intensity, especially for negative emotions. This bias emerges across modalities and social contexts with meaningful implications for social interactions. I am now investigating how this perception bias manifests in clinical populations, including adults with ADHD and anxiety symptoms. This program integrates behavioral and neural methods to advance deeper, ecologically grounded understanding of emotion perception, ultimately informing more effective clinical interventions.

Supervisor: Prof. Anat Perry