# Investigating Visual Attention Mechanisms During Emotional Inferences

> **NIH NIH F99** · UNIVERSITY OF CALIFORNIA BERKELEY · 2024 · $46,965

## Abstract

Project Summary
Humans move their eyes toward relevant information when making decisions, especially when
making social inferences (e.g. inferences on emotion, trustworthiness, danger, etc.). While
previous research has investigated how human gaze patterns are guided by task demands and
stimulus features, little is known about how humans, especially those with abnormal gaze
patterns, make eye movements toward socially relevant information in a dynamic environment.
This is due to much of the previous literature investigating eye movements in social cognitive
tasks with the use of static stimuli of facial expressions, leaving much to be desired regarding the
generalizability and ecological validity of previous research. Many novel computational and
analytical methods can be used to process dynamic eye-tracking data, such as inter-subject
correlations of gaze patterns between observers that can reveal task engagement and information
processing. Thus, in order to mimic the complex social environment that humans experience in
their everyday lives, more naturalistic experimental designs and stimuli should be implemented
by researchers. Advancements in this area of research can help scientists understand how eye
movements are influenced during dynamic social cognitive tasks, especially in individuals with
known abnormal gaze patterns such as those with depression, autism spectrum disorder, and
schizophrenia.
F99 Phase: The current project uses a novel dynamic emotion tracking task called Inferential
Emotion Tracking in which observers must continuously track the emotion of a target character in
a video (e.g. Hollywood movie, home video, or documentary clip) while observers' eye movements
are recorded. This emotion-tracking paradigm can capture large amounts of data from continuous
emotion ratings and eye-tracking. More importantly, the use of dynamic and context-rich stimuli
to investigate human social cognition can more accurately measure the cognitive mechanisms
that humans use to infer emotion outside of a laboratory setting. Additionally, using eye tracking
while participants complete this emotion perception task will allow us to access where and when
observers look for important emotional cues or information to inform their judgments. Investigating
how humans shift their visual attention during social cognitive tasks will provide valuable insights
into how social visual attention is impacted in vulnerable populations. The training involved in this
phase will include instruction in computational methods related to computer vision models and
the neuroscience of emotion processing to prepare for the K00 phase.
K00 Phase: This phase would include extending my F99 Phase study by investigating the neural
mechanisms of visual attention during complex social cognitive tasks by using fMRI. This
approach could reveal which areas of the brain are involved during the processing of emotions
with the use of dynamic and context-rich stimuli and aims to improve ou...

## Key facts

- **NIH application ID:** 11074881
- **Project number:** 1F99NS141343-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA BERKELEY
- **Principal Investigator:** Jefferson Ortega
- **Activity code:** F99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $46,965
- **Award type:** 1
- **Project period:** 2024-09-15 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11074881

## Citation

> US National Institutes of Health, RePORTER application 11074881, Investigating Visual Attention Mechanisms During Emotional Inferences (1F99NS141343-01). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/11074881. Licensed CC0.

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