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Student Class

2027

Student Affiliation

WISP Intern

First Advisor

Viola Störmer

First Advisor Department

Department of Psychological and Brain Sciences

Second Advisor

Kevin Ortego

Second Advisor Department

Department of Psychological and Brain Sciences

Description

This project seeks to investigate the mechanisms underlying our ability to select relevant and ignore irrelevant information. At any moment, we are confronted with an overwhelming amount of sensory information – far more than we can process at once. Selective attention is the cognitive function that allows us to prioritize processing relevant inputs and ignoring irrelevant or distracting inputs, making selective attention a core cognitive capacity that underlies and constraints information processing in the human brain. Traditionally, attention theory distinguishes between two types of selection: consciously deciding what to focus on (top-down, or endogenous attention), and attentional focus drawn to salient stimuli in the environment (bottom-up, or exogenous attention). More recently, another type of attention has been suggested in the literature, namely learned attention, where the attentional system operates based on statistical regularities in the environment, such that attention is incidentally biased toward information that has been relevant frequently in the past (Awh et al., 2012). To date, it is unclear how this learned attention operates and also how it compares to top-down attentional processes.

A previous study found that explicitly informing participants about an upcoming relevant target or irrelevant distractor feature using attention cues increased performance during a visual search task, but this effect was much stronger for targets than distractors (Addleman & Störmer, 2022). This may suggest that selecting targets and ignoring distractors rely on different cognitive resources. However, unconsciously learned target and distractor features seemed to increase performance at a similar rate, suggesting that they rely on shared selection mechanisms. To measure the neural processes involved in learned attention, I have been conducting research that assesses the changes in visual processing efficiency for learned targets and distractor features using human electroencephalography (EEG). Through this fellowship, I plan to complete the data collection on this project, analyze the behavioral and EEG data, and disseminate the results in the form of a research paper and/or at a conference. With ample time to collect data on the effects of learned feature-based selection and ignoring, I will examine whether previous selection bias for targets and previous suppression bias for distractors utilize the same cognitive resources. This research has the potential to explain visual processing biases that affect attention, changing the way the attentional framework is regarded, integrating not only physical salience and current goals of selection but also selection history.

Publication Date

Spring 2024

Keywords

Visual attention, perception, n2pc, attention, learning

Disciplines

Psychology

Do common distractions help us attend? Effects of unconscious learning on attention

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Available to Dartmouth community via local IP address.

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