Projects

Classification in sEEG Forced Two-Choice Task

During the NeuralStorm Workshop 2023, Wenqing and I from CCLAB teamed up for a small competition held on the final day. We employed machine learning methods to classify choices made in a sEEG Forced Two-Choice Task based on summary statistics derived from several frequency bands, tying for first place!

Decoding Motor Responses from Neural Spike Activity

This project was assigned to me during my elective course from the Department of Biomedical Engineering at UC Davis. I employed machine learning methods to decode and understand the rats’ neural responses in the motor cortex to a tilting platform.

Functional Connectivity Fingerprints of FEF and IFJ

This was my master’s thesis project at the University of Trento. Under the supervision of Dr. Daniel Baldauf, we investigated the dissociative functional roles of the FEF and IFJ within the prefrontal cortex. We examined the functional phase and power coupling of these regions, in addition to their directed influences. Our findings were later published in the European Journal of Neuroscience!

Object vs Scene Perception

I worked on this project during my internship in Object Vision Group at CIMeC. For a dataset of object and scene images, I used transfer learning to test the feature extraction of several neural networks by applying representational similarity analysis (RSA).

Object Appearance vs Object Category

This project is my final assignment for the Advanced Hands-on fMRI Analysis course during my master’s degree. It was a great experience! I applied multiclass decoding and representational similarity analysis to the fMRI data by using CoSMoMVPA toolbox.

Naturalistic Video Reconstruction From Brain Activity

I worked on this project during my Erasmus+ internship at the Donders Institute. Based on the subject’s eye-tracking data, my research aimed to enable naturalistic video reconstruction from the brain data of participants who have free-viewed movies during fMRI recording.