Said Garcia

Professor Nicolas M. Phielipp, MD

• Performing EEG, EMG, MRI, and TMS procedures
• Utilizing Spike2 for EEG and EMG data collection and analyzing data using MATLAB, including decoding EEG signals
• Conducting clinical research involving Parkinson's patients, assessing motor skills through EEG, EMG, and TMS
• Preparing manuscripts for publication and delivering oral and written presentations
• Future work will involve studying conscious and unconscious movements in patients with functional movement disorders

Professor Christine King

• Exploring efficient methods for detecting and improving P300 signals in EEG-based brain-computer interfaces (BCIs)
• Optimizing hardware, software, and analytical methodologies to enhance P300 signal detection and reduce noise interference
• Investigating advanced filtration techniques, including spatial and temporal filtering, to improve the accuracy of P300 waveform detection and analysis
• Working on integrating these improvements into BCI applications, such as enhancing the functionality of a P300 speller to refine overall BCI performance

Professor Changhuei Yang and Professor Marianne Bronner

• Developed innovative sex identification methods for chicken embryos using laser speckle contrast imaging, LED imaging, and AI analysis
• Validated hypotheses through PCR, gel electrophoresis, and gonad examination
• Aimed to address the yearly culling of 7 billion male chicks by improving identification methods

• Conducted research on brain-computer interfaces (BCIs) for mind-controlled word spelling
• Analyzed event-related potentials (ERPs), focusing on the P300 response in EEG data
• Compared spelling accuracy using icon-based versus letter-based P300 spellers with four subjects
• Explored various BCI types and their applications in neuroscience, including aiding individuals with Parkinson's disease