NLTools is a Python package for analyzing neuroimaging data. It is the analysis engine powering neuro-learn There are tools to perform data manipulation and analyses such as univariate GLMs, predictive multivariate modeling, and representational similarity analyses. It is based loosely off of Tor Wager’s object-oriented Matlab toolbox and leverages much code from nilearn and scikit-learn

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Listening through the noise
We are all familiar with the difficulty of trying to pay attention to a person speaking in a noisy environment, something often known as the ‘cocktail party problem’. This can be especially…

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Many people ask me what (NMA) was about, how it worked, how we got there, what we learned etc. And every time I try to provide a concise answer, it feels like I’m not doing it justice. Where to start? What to say? How can one summarize what has been the biggest interactive online neuroscience training event in the history of neuroscience in a few sentences?...

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By the end of this tutorial, you will:
• Be able to provide an example of how linear algebra is used in computational neuroscience
• Be able to describe vectors, their properties (dimensionality/length), and their operations (scalar multiplication, vector addition, dot product) geometrically
• Be able to determine and explain the number of basis vectors necessary for a given vector space

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#NMA_2021

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Online lecture series "Neural Data Science" on how to use #MachineLearning for #neuroscience is now complete

YouTube
GitHub

Ten simple rules for structuring papers:

Overview
Good scientific writing is essential to career development and to the progress of science. A well-structured manunoscript allows readers and reviewers to get excited about the subject matter, to understand and verify the paper’s contributions, and to integrate these contributions into a broader context. However, many scientists struggle with producing high-quality manunoscripts and are typically untrained in paper writing. Focusing on how readers consume information, we present a set of ten simple rules to help you communicate the main idea of your paper. These rules are designed to make your paper more influential and the process of writing more efficient and pleasurable.

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A tutorial video on writing applied-mathematics papers.

In case it is helpful, here it is: https://t.co/OwLNGCmQwS

Dive into Deep Learning
Interactive deep learning book with code, math, and discussions

Implemented with NumPy/MXNet, PyTorch, and TensorFlow

https://d2l.ai/index.html

JOB DESCRIPTION
The EEG-BCI facility of the Fondation Campus Biotech Geneva (FCBG) offers state-of-the-art equipment and high-level expertise in EEG and BCI to these labs to give them the best possible environment to conduct their experiments.

REQUIRED PROFILE
Qualifications
• PhD in computer science, neuroscience or related field
• Strong experience in EEG BCI and/or neurofeedback
• Experience in human EEG research 
• High skills with software development, including graphical interface and multi-OS porting
• High programming skills in Python. Matlab and C++ appreciated.
• Proficiency in English. French appreciated.
Application: Applications should include a CV, a cover letter and reference letters. The application should be sent by email to: administration@fcbg.ch
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#positions

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A young filmmaker sets out to document a brilliant neuroscientist who has become frustrated with his field’s status quo. With time elapsing and millions of dollars on the line, In Silico explores an audacious 10-year quest to simulate the entire human brain on supercomputers. Along the way, it reveals the profound beauty of tiny mistakes and bold predictions — a controversial space where scientific process meets ego, and where the lines between objectivity and ambition blur.

Director: Noah Hutton

#HumanBrainProject

INFO:
The documentary premiered on 30th of April 2021 to a broader audience of US citizens exclusively. In awe of Henry Markram's idealist approach to understand the brain against our better materialist judgement I share the documentary to an european audience for educational purposes.

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It’s become commonplace to record from hundreds of neurons simultaneously. If past trends extrapolate, we might commonly record 10k neurons by 2030. What are we going to do with all this data?
.....
by: Patrick Mineault

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REGULARIZATION: An important concept in Machine Learning

The word regularize means to make things regular or acceptable. This is exactly why we use it for. Regularizations are techniques used to reduce the error by fitting a function appropriately on the given training set and avoid overfitting. Now to get a clear picture of what the above definition means, let’s get into the details.

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#basic_maths

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Mathematical Methods in Computational Neuroscience

Computational Neuroscience and Inference from data are disciplines that extensively use tools from Mathematics and Physics to understand the behavior of model neuronal networks and analyze data from real experiments. Due to its interdisciplinary nature and the complexity of the neuronal networks, the list of techniques that are borrowed from Physics and Mathematics is an extensive one. Although using tools from standard curriculum of Physics, Mathematics and Engineering is common, more advanced research requires methods and techniques that are not usually covered in any single discipline. 
 
To fill in this gap, this summer school covers some of the most important methods used in computational neuroscience research through both main lectures and scientific seminars (5-6 main lectures per topic and  1-2 seminars by each invited seminar speaker)

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