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Name: Orhan Soyuhos
Type: User
Company: UC Davis Center for Neuroscience
Bio: Graduate Student Researcher at UC Davis Center for Neuroscience.
Twitter: SoyuhosOrhan
Location: Davis
Name: Orhan Soyuhos
Type: User
Company: UC Davis Center for Neuroscience
Bio: Graduate Student Researcher at UC Davis Center for Neuroscience.
Twitter: SoyuhosOrhan
Location: Davis
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.
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The code for my project in a biomedical engineering course. It involves decoding motor responses of rats to tilting events using neural spike activity. Key components include organizing spike time data, creating perievent rasters and histograms, and developing a PSTH classifier enhanced with PCA.
Naturalistic video reconstruction from brain data of participants who freely viewed movies during fMRI recordings.
A short script to predict whether a subject was presented with a number or not, using brain data recorded by commercial EEG devices.
This repository provides MATLAB scripts for simulating neural responses to visual stimuli and calculating population receptive fields (PRF) based on these responses.
This project is my final assignment for the Introduction to MATLAB course, where I used Psychtoolbox to write an interactive learning environment for teaching English to kids.
The analysis pipeline for our paper 'Functional connectivity fingerprints of the frontal eye field and inferior frontal junction suggest spatial versus nonspatial processing in the prefrontal cortex'.
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).
This project is from the NeuralStorm Workshop in 2023. On the final day, we had a small competition to classify choices made in a sEEG Forced Two-Choice Task. Wenqing and I from CCLAB teamed up and tied for first place in the competition! We primarily utilized summary statistics derived from several frequency bands to predict the choices made.
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