upload a page for my project (#374)

* upload a page for my project

* Changed the content of the index.md based on the conversations, added a simple cover image.
Thanks for the suggestions!

* Apply suggestions from code review

Thank you!

Co-authored-by: Lune Bellec <lune.bellec@umontreal.ca>

---------

Co-authored-by: Lune Bellec <lune.bellec@umontreal.ca>

Author: SkyStream5240

content/en/project/Univariate_analysis_on_melody_evaluation_test/image.png

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+---
+type: "project" 
+
+date: "2025-06-12"
+
+title: "Univariate analysis on melody evaluation test"
+
+names: [Hsin-Yu Cheng]
+
+github_repo: https://github.com/SkyStream5240/Hsin-YuCheng_project
+
+tags: [auditory, fmri]
+
+summary: "The project focused on extracting activities from functional images in a previous study about neural representation of melody-transposition. Using parcellated brain atlas as a mask, the BOLD signals underwent univariate analysis to look for effects in error detection or music-like stimulus-related brain regions/"
+
+image: "image.png"
+---
+<!-- This is an html comment and this won't appear in the rendered page. You are now editing the "content" area, the core of your description. Everything that you can do in markdown is allowed below. We added a couple of comments to guide your through documenting your progress. -->
+
+## Project definition
+
+For brainhack school TW-SG 2025
+
+__bhfunc2025.py__ includes some functions are used in other code
+
+__projectVisualizeTest.ipynb__ is the main processing steps I work on extracting the activities and images from preprocessed fMRI images
+
+The exported csv files are plotted to bar graphs in __resultplotting.ipynb__
+
+### Background
+
+Inspired by the previous paper: Y.-­ A. Han and P.J. Hsieh Imaging Neuroscience, Volume 2, 2024 https://doi.org/10.1162/imag_a_00352. I want to understand how simple melody stimuli can induce neuronal activities in the brain.
+
+
+### Tools
+
+The __Univariate analysis on melody evaluation test__ project will rely on the following technologies:
+ * jupyter notebook
+ * python packages - nilearn and nibabel
+ * nilearn.dataset - Spatially constrained parcellation: msdl_rois
+
+### Data
+
+Using the functional fMRI data in the previous paper: Y.-­ A. Han and P.J. Hsieh Imaging Neuroscience, Volume 2, 2024 https://doi.org/10.1162/imag_a_00352.
+Will not be provided when the project is uploaded.
+
+### Deliverables
+
+ - comparison of activity in a set of parcellated brain regions
+
+## Results
+
+### Progress overview
+
+The preprocessed image series went through masking and activities are extracted.
+
+### Tools I learned during this project
+
+ * **Github workflow** 
+ * **dealing with Nifti data** 
+ * **basic data visualization in seaborn** 
+
+### Results
+
+#### Deliverable 1: Comparison of activity difference 
+
+Two subjects, one run each, are analyzed to look for the activation difference in dorsal ACC, dlPFC, and a generalized auditory region. <img width="317" alt="image" src="https://github.com/user-attachments/assets/247a787c-f099-485a-ad7d-fbc159b00b79" />
+Expected effect are seen in one run of one subject but the other doesn't seem obvious.
+
+<img width="301" alt="image" src="https://github.com/user-attachments/assets/88091782-5c86-4533-b52e-9b90b65d3185" />
+<img width="311" alt="image" src="https://github.com/user-attachments/assets/9be9241c-9e34-490a-b75d-aabe95c8ff7d" />
+<img width="297" alt="image" src="https://github.com/user-attachments/assets/c4a09939-0352-42fa-a922-22e0e70bc367" />
+
+<img width="310" alt="image" src="https://github.com/user-attachments/assets/b8f49aa2-2051-4142-ba4a-da26bfe8c6ca" />
+<img width="311" alt="image" src="https://github.com/user-attachments/assets/c6a9d909-0279-48ee-a6a5-216ee57426d5" />
+<img width="305" alt="image" src="https://github.com/user-attachments/assets/5f650b49-855b-483c-b6cc-0ac8a21ff745" />
+
+
+## Conclusion and acknowledgement
+
+We can see the brain activity in different regions vary a lot in different individuals, even in identical test runs. More data needs analysis for a further, more general conclusion.