- Associate professor: Psychology department, Shenzhen University, Shenzhen, Guangdong, China
- Ph.D & postdoc: Basque Center for Brain, Cognitive, and Language (BCBL), Donostia, Spain
- Email: meining at szu.edu.cn
- Website: https://github.com/nmningmei/nmningmei
- Open Science Framework: https://osf.io/chav7/
- Openneuro: https://openneuro.org/datasets/ds003927/versions/1.0.1
- Supervisor: Prof. Qi Chen and/or Dr. Ning Mei
- Topic:
\t flexibility of higher-order cognition function, OCD behavior and neural mechanism
\t neual mechanism of attention and the computational modeling of attentions - Contact: chenqi@szu.edu.cn
- Desired experience: experience with MRI, MEG and TMS; coding in Python and R is a plus
- Annual salary: ¥500,000 - 80,000 ($69,000 - 110,000 or EUR64,000 - 103,000)
- Location: Shenzhen, China (South of China, one of metropolitan cities of China, 45 minutes train from Center Hong Kong, 1 hour ship from Macau)
- 2023
Basque Center for Brain, Cognitive, and Language (BCBL), Donostia/San Sebastian, Basque, Spain
Postdoctorate, Generative models of consciousness and metacognition of the human brain - 2022
Basque Center for Brain, Cognitive, and Language (BCBL), Donostia/San Sebastian, Basque, Spain
Ph.D in Cognitive Neuroscience - 2016
New York University (NYU), New York, NY, US
M.A in Psychology (General) - 2014
Arizona State University (ASU), Tempe, AZ, US
B.A. in Psychology (minor in Statistics) - 2012
Guangzhou University of Traditional Chinese Medicine (UTCM), Guangzhou,Guangdong, China
B.S. in Applied Psychology
@article{mei2023using,
title={Using serial dependence to predict confidence across observers and cognitive domains},
author={Mei, Ning and Rahnev, Dobromir and Soto, David},
journal={Psychonomic Bulletin \& Review},
pages={1--13},
year={2023},
publisher={Springer}
}
- Mei, N., Santana, R. & Soto, D. Informative neural representations of unseen contents during higher-order processing in human brains and deep artificial networks. Nat Hum Behav 6, 720–731 (2022). https://doi.org/10.1038/s41562-021-01274-7 biorxiv
@article{mei2022informative,
title={Informative neural representations of unseen contents during higher-order processing in human brains and deep artificial networks},
author={Mei, Ning and Santana, Roberto and Soto, David},
journal={Nature Human Behaviour},
volume={6},
number={5},
pages={720--731},
year={2022},
publisher={Nature Publishing Group}
}
@article{soto2020decoding,
title={Decoding and encoding models reveal the role of mental simulation in the brain representation of meaning},
author={Soto, David and Sheikh, Usman Ayub and Mei, Ning and Santana, Roberto},
journal={Royal Society open science},
volume={7},
number={5},
pages={192043},
year={2020},
publisher={The Royal Society}
}
@article{mei2020similar,
title={Similar history biases for distinct prospective decisions of self-performance},
author={Mei, Ning and Rankine, Sean and Olafsson, Einar and Soto, David},
journal={Scientific reports},
volume={10},
number={1},
pages={1--13},
year={2020},
publisher={Nature Publishing Group}
}
@article{mei2020lateralization,
title={Lateralization in the dichotic listening of tones is influenced by the content of speech},
author={Mei, Ning and Flinker, Adeen and Zhu, Miaomiao and Cai, Qing and Tian, Xing},
journal={Neuropsychologia},
volume={140},
pages={107389},
year={2020},
publisher={Elsevier}
}
@article{mei2017identifying,
title={Identifying sleep spindles with multichannel EEG and classification optimization},
author={Mei, Ning and Grossberg, Michael D and Ng, Kenneth and Navarro, Karen T and Ellmore, Timothy M},
journal={Computers in biology and medicine},
volume={89},
pages={441--453},
year={2017},
publisher={Elsevier}
}
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Ellmore, T. M., Reichert, C. P., Ng, K., & Mei, N. (2017). Visual Continuous Recognition Reveals Widespread Cortical Contributions to Scene Memory. bioRxiv, 234609.
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Teng, X., Mei, N., Tian, X., & Poeppel, D. (2016). Auditory temporal windows revealed by locally reversing Mandarin speech. Society for Neurobiology of Language, Poster (co-first-author), Cognitive Neuroscience Society, 2016
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Kim, T., Mei, N., Poeppel, D., & Flinker, A. (2015). A new acoustic space for hemispheric asymmetries. Society for Neurobiology of Language, Poster (co-first-author), Society for Neuroscience, 2015
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Mei, N., Sheikh, U., Santana, R., & Soto, D. (2019, September). How the brain encodes meaning: Comparing word embedding and computer vision models to predict fMRI data during visual word recognition. Cognitive Computational Neuroscience Conference, Berline, Germany.
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Mei, N., & Soto, D. (2019, September). Predicting human prospective beliefs and decisions to engage using multivariate classification analyses of behavioural data. Cognitive Computational Neuroscience Conference, Berline, Germany.
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Mei, N., Santana, R., & Soto, D. (2021, December). Informative neural representations of unseen contents during higher-order processing in human brains and deep artificial networks. Flash talk: NeuroMatch conference 2021.
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Mei, N., Santana, R., & Soto, D. (June, 2021). Informative neural representations of unseen objects during higher-order processing in human brains and deep artificial networks. Oral presentation at Association for the Scientific Study of Consciousness, Israel, Virtual Conference.
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Mei, N., Santana, R., & Soto, D. (October, 2022). Informative neural representations of unseen contents during higher-order processing in human brains and deep artificial networks. Oral presentation at Scientific Conference about Attention RECA XIII, Granada, Spain.
- Solve probability problems of Reddit
- Comparison of simple parametric and nonparametric statistical methods
- Preprocessing pipelines for M/EEG and fMRI data
- Download EEG sleep data fro open science framework
- BCBL repository of implementing deep learning models on cognitive neuroscience studies
- Introduce of python libraries, i.e. Numpy
- BESA python reader, translated from Matlab scripts
- Simple implementation of openpose library without a GPU
- Arizona State University, Dean’s list 2013, 2014
- Data Science RoAD-Trip Award 2016 - 2017
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David Soto Group Doctoral researcher
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Running psychophysics experiments, fMRI experiments, data analysis (M/EEG, fMRI, behavioral, etc)
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Ongoing project:
a. [Benchmarking decoding models of Spanish/Basque conscious/unconscious noun words in various conditions (i.e. shallow/deep process, social conditions)](https://github.com/nmningmei/METASEMA_encoding_model) b. [How computer vision and semantic representation models provide insights of unconscious processing of object images and their semantic categories](https://github.com/nmningmei/unconfeats) c. How the history of behavioral pattern could predict the future confidence rating, [a](https://github.com/nmningmei/decoding_confidence_dataset), [b](https://github.com/nmningmei/Decode_confidence_dataset) d. [Ecoding-based representational similarity analysis](https://github.com/nmningmei/metasema_encoding_based_RSA)
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Fall 2014 – Fall 2017 David Poeppel Lab (NYU)
MA research assistant- Running psychophysics experiments, MEG experiments, data analysis
- Ongoing project: Investigating hemispheric asymmetry in perceiving Mandarin Tones, in conditions of hums or lexical tones.
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Spring 2015 – Fall 2016 Catherine Good Lab (CUNY-Baruch)
MA research assistant- Experimental subject testing, data collection, data analysis
- Data analysis on how sense of belonging in math moderating self-estimation in different confidence levels
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Spring 2016 – Spring 2018 Timothy Ellmore Lab (CUNY-North)
MA research assistant- Develop python/Matlab Input/Output interacting scripts/protocol for EEG data processing
- Selecting features to detect target brain wave patterns (i.e. spindles, k-complex, sleeping stages) in the signal
- Automatic pipeline of non-supervised models to detect spindles (https://osf.io/fc3u5/ and get the data here)
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Fall 2016 – Spring 2017 Data Science RoAD-Trip (Fund awarded - $4000) The RoAD-Trip Joint Data Science Plan (Mentor: Gaurav Pandey)
- Implementing machine learning algorithms to detect target brain wave patterns (i.e. spindles, k-complex)
- Implementing machine learning algorithm to classify sleeping stages within subjects (https://github.com/adowaconan/Spindle_by_Graphical_Features)
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Spring 2017 – Fall 2017 Denis Pelli Lab
Research assistant- Study of noise dynamic in visual grouping effect
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Spring 2014 American Cancer Society Cancer Prevention Study – 3
Volunteer, Research assistant- Recruiting subjects, social media research
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Fall 2012-Summer 2014 ASU Changemaker center, Tempe, AZ
Volunteer- Creating communities of support around new solutions/ideas
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Fall 2009, Spring 2010 Canton Life Hot Line, Guangzhou, China
Intern- Consulting, recording consulting results
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Fall 2010, Spring 2011 Research team, prisoner emotional health, Guangzhou, China
Intern- Collecting data about prisoners’ mental health assessments
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Fall 2012 to Spring 2018 Varsity Tutor Tutor
- Multivariate Calculus
- Linear Algebra
- Trigonometry
- Statistics (i.e. research methods, analysis methods, simulation, signal detection theory)
- Mandarin
- Programming data analysis (Python, R, and Matlab)
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March 2013 to present
Translator, MCC Translation, Phoenix, AZ
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Excellent – Microsoft Office Word, Excel, Presentation, Poster Design
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Excellent – Matlab
- Parametric tests
- Nonparametric tests
- Factorial analysis
- Principle Component Analysis
- Psychophysics Toolbox
- Signal Processing Toolbox
- Data Visualization
- Scripts of Functions.
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Excellent – Python
- Parametric tests
- Nonparametric tests
- Factorial analysis
- Principle Component Analysis
- Bayesian Model building (PYMC3)
- Model Evaluation, Data Visualization, Lambda Functions,
- Extensions of Python such as MNE-python (specialize in EEG, MEG data analysis), Nipype (specialize in fMRI)
- Pandas
- Deep learning (Tensorflow/Keras, pytorch, JAX)
- Import and export excel, matlab, SPSS, and SAS files. Extract, transform, and load databases.
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Excellent – SPSS
- Parametric tests
- Nonparametric tests
- Factorial Analysis
- Principle Component Analysis
- Independent Component Analysis
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Excellent – R
- Parametric tests
- Nonparametric tests
- Factorial Analysis
- Principle Component Analysis
- probabilistic programming
- Shiny – interactive graphs
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Good – Letax Editor
- Equations and special effects in presentation slides, posters
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Beginner – Julia
- Julia ikernel interacting with Jupyter projects
- Deep learning (FLUX)
- Calculus/Analytic Geometry I – III
- Probability
- Mathematical statistics
- Simulation and Data Analysis
- Mathematical Tools for Psychology and Neuroscience
- Parametric statistics
- Non-parametric statistics
- Factorial Analysis
- Principle Component Analysis
- Independent Component Analysis
- Least square regression
- Multivariate regression
- Step-wise hierarchical regression
- Bayesian Inference
- Machine Learning: general to deep learning