Data Collection Techniques in Neuroscience

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The skills will cover relevant laws of sensory perception (Weber, Fechner, Stevens), and introduce testing procedures for the measurement of detection and discrimination thresholds. These will include constant stimuli methods, and various adaptive testing procedures. In addition, there will be an introduction to Signal Detection Theory and derived measures of detectability or discriminability. In order to make this knowledge concrete, students conduct experiments based on several of these testing procedures. The end goal is to test one of the colleague-students and determine a sensory threshold with provided software. Students will also be familiarized with the analysis (Brainvoyager QX) and interpretation of an fMRI dataset. In addition to the empirical data collection and analysis, relevant literature will be covered on specific testing procedures, and on particularly beautiful examples of current state of the art experiments.