Multimodal assessment of visual attention using the Bethesda Eye & Attention Measure (BEAM)

ABSTRACT

Introduction: Computerized cognitive tests measuring manual response time (RT) and errors are often used in the assessment of visual attention. Evidence suggests that saccadic RT and errors may also provide valuable information about attention. This study was conducted to examine a novel approach to multimodal assessment of visual attention incorporating concurrent measurements of saccadic eye movements and manual responses. Method: A computerized cognitive task, the Bethesda Eye & Attention Measure (BEAM) v.34, was designed to evaluate key attention networks through concurrent measurement of saccadic and manual RT and inhibition errors. Results from a community sample of n = 54 adults were analyzed to examine effects of BEAM attention cues on manual and saccadic RT and inhibition errors, internal reliability of BEAM metrics, relationships between parallel saccadic and manual metrics, and relationships of BEAM metrics to demographic characteristics. Results: Effects of BEAM attention cues (alerting, orienting, interference, gap, and no-go signals) were consistent with previous literature examining key attention processes. However, corresponding saccadic and manual measurements were weakly related to each other, and only manual measurements were related to estimated verbal intelligence or years of education. Conclusions: This study provides preliminary support for the feasibility of multimodal assessment of visual attention using the BEAM. Results suggest that BEAM saccadic and manual metrics provide divergent measurements. Additional research will be needed to obtain comprehensive normative data, to cross-validate BEAM measurements with other indicators of neural and cognitive function, and to evaluate the utility of these metrics within clinical populations of interest.

KEYWORDS:

• Visual attention
• response time
• multimodal assessment
• eye tracking
• inhibition
• saccade

Acknowledgements

The technology described in this paper is included in U.S. Patent Application No. 61/779,801, U.S. Patent Application No. 14/773,987, European Patent Application No. 14780396.9, and International Patent Application No. PCT/US2014/022468 (rights assigned to the Uniformed Services University of the Health Sciences [USUHS]). The views and opinions presented in this manuscript are those of the authors and do not necessarily represent the position of USUHS, the Department of Defense, or the United States government. We owe many thanks to our study participants; to Dmitry Mirochnitchenko, who assisted with study coordination, data collection, and technical assistance; to Lindsay Reinhardt and Katherine Lunsford, who assisted with data collection; to Amanda Devane, who assisted with data screening; and to Doug Girard, who assisted with software development.

ORCID

Mark L. Ettenhofer http://orcid.org/0000-0001-9381-7578

Additional information

Funding

Support for this research was provided by the Uniformed Services University of the Health Sciences (USUHS) [Research Grant number R072LP].