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Time-frequency analysis of neuro-electrical activity in response to visual stimuli

Patterns observed from neuronal electrical activity during controlled experiments can give insight into how the brain responds to presented stimuli. However, it is possible that current analysis methods are not taking full advantage of noisy data sets. We are investigated wavelet-based techniques to develop noise reduction techniques that retain more of the high-frequency content than is left after the customary time averaging technique is applied. MATLAB is used to explore recorded data sets and trends are communicated graphically. Preliminary results have uncovered little cohesive information about highfrequency neuronal behavior. Continued work aims to refine analysis methods and will hopefully generate further results.