Daniel Austin


September 2013

Document Type


Degree Name



Dept. of Biomedical Engineering


Oregon Health & Science University


One of the great challenges facing modern science is the ability to measure cognitive function. This is important for making advances in brain research as well as for clinical practice involving diagnosis and treatment. Unfortunately, cognitive function cannot be measured directly and attempts to assess cognitive function through neuropsychological or other testing is based on comparing patient test scores to normative data to determine whether a patient is impaired. While successful for diagnosing disease and detecting brain damage, this methodology has been hampered in assessing cognitive deficits because the tests are not suitable for making inferences about the underlying cognitive processes involved in test performance. Advances in technology, monitoring and computational modeling generated an opportunity to link cognition directly to behavioral data. One very general approach is the use of computational models to build, fit, and test precise relationships that may link behavioral measurements to cognitive processes underlying the behavior, which we exploit to investigate the relationship between cognitive and motor function. There has been increasing evidence that motor function is an important indicator of cognitive and physical function. For example, motor slowing precedes cognitive impairment and is diminished in neurodegenerative diseases. One of the most commonly used assessments of motor speed is the Halstead-Reitan finger tapping test (FTT). The FTT has been repeatedly linked to current levels of cognitive function and future cognitive decline, although it is considered to be a simple motor task with little cognitive involvement. In addition to the apparently disparate role of cognitive function in the task – it is perceived as a non-cognitive task despite other work showing cognition relates to the FTT – the task administration suffers from several shortcomings common to many neuropsychological tests. Specifically, the test is administered infrequently, requires a trained assessor, outputs a final score that is aggregated across trials. These shortcomings make the test unable to distinguish between abrupt change and slower change over time and cause troubles with inter-rater reliability. Further, the test is not specific to different diseases and is not a naturally occurring task in everyday life (i.e., it lacks ecological validity). In this thesis, we demonstrate that finger tapping does, in fact, recruit cognitive resources by explicitly characterizing the role attention plays in the task (as measured by a serial subtraction task known to also require elements of calculation and working memory). We first develop a novel finger tapping decomposition that allows us to statistically characterize the different physical components of the tapping task. Using this characterization, we are able to demonstrate that reduced attention and increased cognitive load both slows the speed and increases the variability in certain behavioral aspects of tapping (referred to as dwell phases). We also show that reduced attention does not modulate the other behavioral aspects of tapping (referred to as transition phases). Additionally, we demonstrate that monitoring typing at the keyboard during normal computer use can be used as a surrogate for the FTT, which overcomes all the normal limitations of finger tapping assessment outlined above. Specifically, this provides an objective and continuous assessment of motor function that not only has face validity to the FTT but also demonstrates the high correlation between tapping and typing speed, suggesting a high degree of overlap between the cognitive and motor function used in the two tasks. Taken together, our results not only indicate that finger tapping is a cognitively demanding task but also provide the first steps toward characterizing the interplay of cognitive, motor and sensory function during the task by characterizing the role of attention in the task. We also provide a novel methodology for obtaining a continuous, unobtrusive, and objective assessment of motor function by means of everyday typing at the computer.




School of Medicine



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