Thesis Project Form
Title (tentative): Novel techniques for neural data analysis of in vivo electrophysiological signalsThesis advisor(s): Chiappalone Michela, Federico Barban (DIBRIS) | E-mail: |
Address: Via Opera Pia 13, 16145 Genova | Phone: |
Description
Motivation and application domain
Electroceutical therapies have been showing promising results in restoration of function after brain damage. However, the underlying neural mechanisms promoting recovery are not well understood. A crucial obstacle in the analysis of neural data recorded during neurostimulation is the presence of a high amplitude stimulation artefacts, which hinders the analysis of the stimulation evoked responses and all around decreases the SNR.
General objectives and main activities
In collaboration with the Cortico-Plasticity Lab at the Kansas University Medical Center, the student will develop novel methods of artifact rejection to be implemented in our shared data analysis pipeline. The newly developed method will be compared and validated against state-of-the-art techniques on semi-synthetic data and will then be applied to a novel intracortical stimulation dataset recorded on nonhuman primates. The student will also apply standard and newly designed analysis techniques on the cleaned data.
Moreover, the student will be introduced to, and gain some expertise in, the topic of electrophysiological data collection and laboratory animal handling.
Moreover, the student will be introduced to, and gain some expertise in, the topic of electrophysiological data collection and laboratory animal handling.
Training Objectives (technical/analytical tools, experimental methodologies)
The thesis will allow training in neuroengineering, experimental neuroscience, neurophysiology, data analysis, code writing, laboratory animal handling.
Place(s) where the thesis work will be carried out: Kansas University Medical Center, Kansas City (Kansas), USA
Additional information
Pre-requisite abilities/skills: Excellent coding skills (Matlab/Python). Excellent English knowledge.
Maximum number of students: 1
Financial support/scholarship: YES