Faculty Bibliography

OBJECTIVE: This study introduces a rapid picture naming test, the Mobile Universal Lexicon Evaluation System (MULES), as a novel, vision-based performance measure for concussion screening. The MULES is a visual-verbal task that includes 54 original photographs of fruits, objects and animals. We piloted MULES in a cohort of volunteers to determine feasibility, ranges of picture naming responses, and the relation of MULES time scores to those of King-Devick (K-D), a rapid number naming test. METHODS: A convenience sample (n=20, age 34+/-10) underwent MULES and K-D (spiral bound, iPad versions). Administration order was randomized; MULES tests were audio-recorded to provide objective data on temporal variability and ranges of picture naming responses. RESULTS: Scores for the best of two trials for all tests were 40-50s; average times required to name each MULES picture (0.72+/-0.14s) was greater than those needed for each K-D number ((spiral: 0.33+/-0.05s, iPad: 0.36+/-0.06s, 120 numbers), p<0.0001, paired t-test). MULES scores showed the greatest degree of improvement between trials (9.4+/-4.8s, p<0.0001 for trials 1 vs. 2), compared to K-D (spiral 1.5+/-3.3s, iPad 1.8+/-3.4s). Shorter MULES times demonstrated moderate and significant correlations with shorter iPad but not spiral K-D times (r=0.49, p=0.03). CONCLUSION: The MULES test is a rapid picture naming task that may engage more extensive neural systems than more commonly used rapid number naming tasks. Rapid picture naming may require additional processing devoted to color perception, object identification, and categorization. Both tests rely on initiation and sequencing of saccadic eye movements.

This paper proposes a parametric model for saccadic waveforms. The model has a small number of parameters, yet it effectively simulates a variety of physiologic saccade properties. In particular, the model reproduces the established relationship between peak saccadic angular velocity and saccadic amplitude (i.e., the saccadic main sequence). The proposed saccadic waveform model can be used in the evaluation and validation of methods for quantitative saccade analysis. For example, we use the proposed saccade model to evaluate four well-known saccade detection algorithms. The comparison indicates the most reliable algorithm is one by Nystrom et al. We further use the proposed saccade model to evaluate the standard technique used for the estimation of peak saccadic angular velocity. The evaluation shows the occurrence of systematic errors. We thus suggest that saccadic angular velocity values determined by the standard technique (low-pass differentiation) should be interpreted and used with caution.