Computational Neuroscience Workshop 2014 – Online and Timeless Material

Hello everyone!

From the feedback I had over the last two weeks and my own feelings, force is to conclude that this year again the workshop has been an exceptional occasion to acquire and share information on computational tools available to neuroscientists. (more…)

Computational Neuroscience Workshop, Online!

Hi guys,

Finally! After several hours of video editing and cursing (ok, it wasn’t that bad), here are the videos of the talks presented during the computational neuroscience workshop, held on May 7th of this year. (more…)

Machine Learning for dummies (just kidding)

Hi guys,

Another semester ended, another to be added the countless number of semesters that we have seen since the beginning of our academic career as professional students. Still, I’m taking the time to share with you what has made this last one particularly significant for me. I was registered in the course Machine Learning (COMP-652) and I had such a great time that I didn’t see the semester flying by, or was it because I was overwhelmed by work, it’s hard to tell. Never mind, this course taught me, and the other students who were registered, about a bunch of tools, not far from being qualified of statistics, that I’m sure you too could benefits from knowing. Unfortunately, there is only one way for you to get the fine details, and it is to register yourself, yet, I’m going to give you an appreciation of two topics covered during this class and maybe you’ll find yourself interested in learning more on the subject. (more…)

Area under the receiver operating characteristic (ROC) curve – A versatile tool, by Jackson Smith*

The method used in classic studies [1, 2] to quantify the discrimination sensitivity of middle temporal (MT) neurones in a two-alternative, forced-choice (2AFC) task has since become an important technique of behavioural neurophysiology. The key question is whether a neurone fired more spikes in one condition than in another. However, traditional parametric methods for answering this question place restrictive assumptions on the statistics of neural activity; for example, neurones do not always resemble a Poisson process [3].



Here’s my little story about how I got involved in CAMBAM. I have joined CAMBAM somewhere around June last year. At the time, I was interested in knowing more about non-linear dynamics, dynamical system theory and their applications, because I had ran into some papers analysing neural networks behavior with these tools. I thought that hanging with the people who play with these mathematics on a daily basis would be helpful and informative. (more…)

What happened at the LBUM?

What to think about the visit of the laboratoire de rhéologie et d’ultrasonographie médicale (LBUM, that took place last Wednesday? The first thing that comes to my mind is how nice these people were. For a full day, François Destrempes and a group of members of the LBUM interrupted their research to receive us and expose us the nature of their work. (more…)

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