zitonglu1996 / neurora

A Python Toolbox for Multimode Neural Data Representation Analysis - A Representational Analysis Toolbox for Neuroscience, including Neural Pattern Similarity (NPS), Representational Similarity Analysis (RSA), Spatiotemporal Pattern Similarity (STPS) & Inter-Subject Correlation (ISC)

Hi there 👋

I'm Zitong Lu from 🇨🇳 now in 🇺🇸 !

To be an experimental psychologist, a cognitive neuroscientist, an AI scientist.

• 😉🎓 I am a third-year PhD candidate in cognitive neuroscience working with Dr. Julie Golomb in Vision and Cognitive Neuroscience Lab at The Ohio State University. Also, I am the OSU EEGlab manager！

  I got a graduate Minor degree in statistics in 2023 and a MSci degree in psychology in 2022 from The Ohio State University. And I graduated with a MSci degree in cognitive neuroscience from East China Normal University (Shanghai, China) in 2021. Also, I was a member of Memory and Emotion Lab led by Dr. Yixuan Ku in Sun Yat-sen University (Guangzhou, China) and a research assistant in Peng Cheng National Laboratory (Shenzhen, China). Before that, I received a BEng degree in software engineering from Northeastern University (Shenyang, China) in 2018.

• 👀🔑 Visual Perception, Cognitive Computational Neuroscience, NeuroAI.

• 😅🔆 I’m the author of NeuroRA and PyCTRSA - Two Python toolboxes for representational analysis.

• 😋:📔 I'm also the author of the first Chinese Python EEG data analysis handbook.

• 📧📬 If you have any question about my projects, you can email me: [email protected] / [email protected]

• 😃💡 Research Interests: To understand how we process object information in the complex and dynamics world using behavioral, EEG, fMRI and computational approaches and building more brain-like artificial vision models.

• 😉👻 Focused Topics:

• 1️⃣ Neural and behavioral mechanisms of visual perception: (A) Object-location binding; (B) Depth and 3D perception; (C) Visual and semantic representations; (D) Generally spatial representation.

• 2️⃣ Mapping representations between human brains and artificial neural networks: (A) Representational alignment between human brains and artificial neural networks; (B) Brain encoding models; (C) Inter-individual neural converters; (D) Reverse engineering to interpret neural mechanisms.

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Typical Open-source Projects

• NeuroRA: A Python toolbox of representational analysis from multimode neural data
• Python-EEG-Handbook-CN: A Chinese handbook for EEG data analysis based on Python
• EEG2EEG: A high-performance inter-individual EEG converter

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Languages and Tools

• Python, MATLAB, C, C++, Java, Julia
• 

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neurora's Issues

Permutation test for 2 dependent samples

Will there be the equivalent of permutation_cluster_test in mne?

bhvRDM for representations in CNNs

First of all, thank you so much for making this work open source! It is much appreciated! :)

I am interested in calculating RDMs for representations learned by neural networks. For this, I was looking at your bhvRDM function, since the description of the function includes 'This function can also be used to calculate the RDM for computational simulation data'.

My understanding was that for RDMs, correlation distance (i.e. 1 - r where r refers to the Pearson correlation) was used. However, on line 84 (here), I am not sure why you are simply computing the absolute distance. Can you please help me out?

Thanks once again for your phenomenal work!

why not remove .idea directory

.idea directory is the configuration directory of JetBrains IDEs such as Intellij idea or Pycharm. It's your own configuration, so it's helpless to others.

Could this approach be extended to work on high dimensional spike train data?

First of all, thank you so much for making this work open source! It is much appreciated! :)

Could this approach be extended to work on high dimensional spike train data? If so which classes which would be the best classes to extend and inherit from in developing a new spike train based approach?

I think PySpike is doing something similar to representational similarity analysis of spike trains, but I don't know if it is interoperable with approaches here.

Thanks,