Faculty Bibliography

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.

OBJECTIVE: The King-Devick (KD) test, which is based on rapid number naming speed, is a performance measure that adds vision and eye movement assessments to sideline concussion testing. We performed a laboratory-based study to characterize ocular motor behavior during the KD test in a patient cohort with chronic concussion to identify features associated with prolonged KD reading times. METHODS: Twenty-five patients with a concussion history (mean age: 31) were compared to control participants with no concussion history (n = 42, mean age: 32). Participants performed a computerized KD test under infrared-based video-oculography. RESULTS: Average intersaccadic intervals for task-specific saccades were significantly longer among concussed patients compared to controls (324.4 +/- 85.6 msec vs. 286.1 +/- 49.7 msec, P = 0.027). Digitized KD reading times were prolonged in concussed participants versus controls (53.43 +/- 14.04 sec vs. 43.80 +/- 8.55 sec, P = 0.004) and were highly correlated with intersaccadic intervals. Concussion was also associated with a greater number of saccades during number reading and larger average deviations of saccade endpoint distances from the centers of the to-be-read numbers (1.22 +/- 0.29 degrees vs. 0.98 +/- 0.27 degrees , P = 0.002). There were no differences in saccade peak velocity, duration, or amplitude. INTERPRETATION: Prolonged intersaccadic intervals, greater numbers of saccades, and larger deviations of saccade endpoints underlie prolonged KD reading times in chronic concussion. The KD test relies upon a diffuse neurocognitive network that mediates the fine control of efferent visual function. One sequela of chronic concussion may be disruption of this system, which may produce deficits in spatial target selection and planning of eye movements.

A coordinate system is composed of an encoding, defining the dimensions of the space, and an origin. We examine the coordinate encoding used to update motor plans during sensory-motor adaptation to center-out reaches. Adaptation is induced using a novel paradigm in which feedback of reach endpoints is perturbed following a sinewave pattern over trials; the perturbed dimensions of the feedback were the axes of a Cartesian coordinate system in one session and a polar coordinate system in another session. For center-out reaches to randomly chosen target locations, reach errors observed at one target will require different corrections at other targets within Cartesian- and polar-coded systems. The sinewave adaptation technique allowed us to simultaneously adapt both dimensions of each coordinate system (x-y, or reach gain and angle), and identify the contributions of each perturbed dimension by adapting each at a distinct temporal frequency. The efficiency of this technique further allowed us to employ perturbations that were a fraction the size normally used, which avoids confounding automatic adaptive processes with deliberate adjustments made in response to obvious experimental manipulations. Subjects independently corrected errors in each coordinate in both sessions, suggesting that the nervous system encodes both a Cartesian- and polar-coordinate-based internal representation for motor adaptation. The gains and phase lags of the adaptive responses are not readily explained by current theories of sensory-motor adaptation.

OBJECTIVE: Concussion is a major public health problem and considerable efforts are focused on sideline-based diagnostic testing to guide return-to-play decision-making and clinical care. The King-Devick (K-D) test, a sensitive sideline performance measure for concussion detection, reveals slowed reading times in acutely concussed subjects, as compared to healthy controls; however, the normal behavior of eye movements during the task and deficits underlying the slowing have not been defined. METHODS: Twelve healthy control subjects underwent quantitative eye tracking during digitized K-D testing. RESULTS: The total K-D reading time was 51.24 (+/-9.7) seconds. A total of 145 saccades (+/-15) per subject were generated, with average peak velocity 299.5 degrees /s and average amplitude 8.2 degrees . The average inter-saccadic interval was 248.4ms. Task-specific horizontal and oblique saccades per subject numbered, respectively, 102 (+/-10) and 17 (+/-4). Subjects with the fewest saccades tended to blink more, resulting in a larger amount of missing data; whereas, subjects with the most saccades tended to make extra saccades during line transitions. CONCLUSIONS: Establishment of normal and objective ocular motor behavior during the K-D test is a critical first step towards defining the range of deficits underlying abnormal testing in concussion. Further, it sets the groundwork for exploration of K-D correlations with cognitive dysfunction and saccadic paradigms that may reflect specific neuroanatomic deficits in the concussed brain.

Healthy individuals appear to use both vector-coded reach plans that encode movements in terms of their desired direction and extent, and target-coded reach plans that encode the desired endpoint position of the effector. We examined whether these vector and target reach-planning codes are differentially affected after stroke. Participants with stroke and healthy controls made blocks of reaches that were grouped by target location (providing target-specific practice) and by movement vector (providing vector-specific practice). Reach accuracy was impaired in the more affected arm after stroke, but not distinguishable for target- versus vector-grouped reaches. Reach velocity and acceleration were not only impaired in both the less and more affected arms poststroke, but also not distinguishable for target- versus vector-grouped reaches. As previously reported in controls, target-grouped reaches yielded isotropic (circular) error distributions and vector-grouped reaches yielded error distributions elongated in the direction of the reach. In stroke, the pattern of variability was similar. However, the more affected arm showed less elongated error ellipses for vector-grouped reaches compared to the less affected arm, particularly in individuals with right-hemispheric stroke. The results suggest greater impairment to the vector-coded movement-planning system after stroke, and have implications for the development of personalized approaches to poststroke rehabilitation: Motor learning may be enhanced by practice that uses the preserved code or, conversely, by retraining the more impaired code to restore function.

We analyze the problem of obstacle avoidance from a Bayesian decision-theoretic perspective using an experimental task in which reaches around a virtual obstacle were made toward targets on an upright monitor. Subjects received monetary rewards for touching the target and incurred losses for accidentally touching the intervening obstacle. The locations of target-obstacle pairs within the workspace were varied from trial to trial. We compared human performance to that of a Bayesian ideal movement planner (who chooses motor strategies maximizing expected gain) using the Dominance Test employed in Hudson et al. (2007). The ideal movement planner suffers from the same sources of noise as the human, but selects movement plans that maximize expected gain in the presence of that noise. We find good agreement between the predictions of the model and actual performance in most but not all experimental conditions.