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Updated: Jun 27, 2026

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Investigating the Deployment of Visual Attention Before Accurate and Averaging Saccades via Eye Tracking and Assessment of Visual Sensitivity
Published on: March 18, 2019
Normal electrocortical facilitation but abnormal target identification during visual sustained attention in
Brett A Clementz1, Jun Wang, Andreas Keil
1Department of Psychology, BioImaging Research Center, University of Georgia, Athens, Georgia 30602, USA. clementz@uga.edu
Summary
Schizophrenia patients struggle with visual attention tasks due to impaired target detection, not poor attentional selectivity. This study used electroencephalography (EEG) to differentiate these deficits in visual attention.
Area of Science:
- Neuroscience
- Cognitive Psychology
- Psychiatry
Background:
- Visual attention deficits are common in schizophrenia, but the underlying cause remains unclear.
- Previous studies conflated attentional selectivity and target detection, hindering precise diagnosis.
Purpose of the Study:
- To differentiate between attentional selectivity and target detection deficits in schizophrenia.
- To investigate the neural mechanisms underlying visual attention in schizophrenia using electroencephalography (EEG).
Main Methods:
- 17 schizophrenia patients and 17 healthy controls performed a visual attention task with superimposed images.
- Steady-state visual evoked potentials (ssVEPs) measured attention-related neural activity.
- Behavioral performance and event-related potentials (ERPs) assessed target detection.
Main Results:
- Both groups showed enhanced neural activity for attended stimuli and suppressed activity for unattended stimuli.
- Schizophrenia patients exhibited significant impairments in target detection, both behaviorally and neurally.
- Neural and behavioral measures of target detection were strongly correlated in both groups.
Conclusions:
- Deficient target detection, not compromised attentional selectivity, underlies visual attention deficits in schizophrenia.
- EEG measures, including ssVEPs and ERPs, can effectively distinguish these deficits.
