Senior thesis experiences in Computational Neuroscience – Movement Science

Thesis opportunities are designed to provide students with experience in applying quantitative
methods to practical problems in neuroscience and/or movement science. Quantitative approaches include,
but are not limited to, computer modeling and animation, development of mathematical models, and time
series analysis. Students typically come to computational neuroscience via two different routes: 1) those
with strong quantitative backgrounds, e.g. applied mathematics, applied physics, engineering, and computer
science, who wish to obtain “hands on” experience working on a problem with biological and/or medical
interest; and 2) those with strong experimental backgrounds, e.g. neurophysiology, cognitive neuroscience,
and motion studies, who wish to develop appropriate quantitative skills.

Thesis topics are chosen to peak the interests of both the student and the instructor. The only constraint
is the availability of equipment and the timeliness of the project. It is hoped that if the project is
successfully completed, then it would be submitted for publication. It is understood that no student can
be expected to be equally strong in both experimental neuroscience/movement science and quantitative
methods. Thus, many projects will be done by a team of two (or more) students: for example, one who is
a stronger experimentalist, another who is stronger in mathematics, computer programming, electronics,
etc. The composition of these teams will be determined by the instructor on the basis of which skills are
most critically needed to successfully complete the research topic.

Examples of possible research topics are:

Computational Neuroscience

1). Neural control at the edge of stability
2). Dynamic memory storage in small neuronal networks
3). Neuronal membrane noise: Intermittency versus 1/f
4). Data mining techniques for analyzing large multi-electrode array recordings of
neural populations.
5). Dynamics of time-delayed feedback control mechanisms in presence of noise
6). Models of the pupil light reflex
7). Muscle co-activation and the development of expertise

Movement Science

1). Falling in the elderly
2). Biomechanics of the golf swing of elderly and physically challenged
golfers and injury reduction
3). Design and development of wireless technologies to monitor activities of the
nervous system in an outdoor environment
4). Effects of noise on balance control and gait variability
5). Concussion and sports: Balance control and the back to play decision