While nearly everyone travels, the ease with which this life-affecting activity is accomplished can be profoundly influenced by physical disabilities (e.g., blindness), traumas (e.g. brain injury), or aging (e.g., Alzheimer's). These populations at risk are growing. As a result, our society will increasingly be faced with more and more citizens who are unable to successfully travel independently. This inevitably results in a profound loss of access to employment, education, and cultural institutions. The long term goal of this project is to develop a methodology that can be applied to understand and improve wayfinding for disabled populations. The novelty of the approach is to combine elements of several areas of expertise to develop a valid, reliable instrument to measure and predict navigation behavior using maps, while exploring its neural underpinnings. This project includes two Specific Aims. The first is to develop a behavioral instrument to measure and predict the wayfinding success of a special-needs population (blind travelers). This instrument will include several subcomponents (each one measuring a separate wayfinding ability or skill), and will assess proficiency in completing tasks that have been shown to be predictors of successful wayfinding. The subcomponents of the wayfinding test will be identified and validated using technology developed in this project. Unobtrusive, wearable devices will record environmental wayfinding behavior for the purpose of 1) identifying the skills that special needs populations (e.g., blind travelers) employ to complete wayfinding tasks, and 2) evaluating the validity of our wayfinding ability measurement (WAM) instrument. The second Specific Aim is to use functional magnetic resonance imaging (fMRI) to investigate the neural basis of successful navigation behavior. FMRI will be used to evaluate the relationship between different spatial components identified by our WAM instrument (as well as other psychometric tests) that are significantly important for successful wayfinding. FMRI data will also be used to uncover neural patterns associated with high-level (successful) vs. low-level (less-successful) navigation behavior as defined by our field-tested and validated predictor instrument. More generally, the use of fMRI technology will allow us to document, for the first time, the cortical reorganization of the blind brain into functional areas important for spatial comprehension and map use. Additionally, we will also be able to compare neural activation patterns for blind subjects in tactile spatial and map tasks to sighted subjects to determine if there are """"""""amodal"""""""" brain regions important for processing spatial information, irrespective of sensory input (visual vs. tactile) or developmental history (presence or absence of visual sensory input). Congenital and, increasingly, age- and trauma-related disabilities present barriers for mobility and travel for a growing number of people with profound effects on quality of living. This project will develop methods and technologies to evaluate and measure individual abilities or skills that affect successful wayfinding in special needs populations. These measures will identify individual's wayfinding abilities and skills amenable to training in order to improve the potential for success.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Exploratory/Developmental Grants (R21)
Project #
5R21DA024293-04
Application #
7922583
Study Section
Special Emphasis Panel (ZDA1-GXM-A (27))
Program Officer
Onken, Lisa
Project Start
2007-09-26
Project End
2013-07-31
Budget Start
2010-08-01
Budget End
2013-07-31
Support Year
4
Fiscal Year
2010
Total Cost
$275,791
Indirect Cost
Name
University of Oregon
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
948117312
City
Eugene
State
OR
Country
United States
Zip Code
97403
Juliani, Arthur W; Bies, Alexander J; Boydston, Cooper R et al. (2016) Navigation performance in virtual environments varies with fractal dimension of landscape. J Environ Psychol 47:155-165
Lehky, Sidney R; Sereno, Margaret E; Sereno, Anne B (2013) Population coding and the labeling problem: extrinsic versus intrinsic representations. Neural Comput 25:2235-64