This video showcases the aims, research, and possibilities at CAMBAM (Center for Applied Mathematics in Bioscience And Medicine). Get to know some of our research projects and scientists…
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…)
Good day everyone!
Over the course of the last few months, a team of McGill neuroscience students and post-docs have been preparing talks on the topic of computational neuroscience aimed at explaining computational techniques that they are applying to their data, the results of which will be presented at the Computational Neuroscience Workshop 2014.
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…)
Leon Glass, Isadore Rosenfeld Chair in Cardiology and Professor of Physiology at McGill University and CAMBAM member, has recently been awarded the Arthur Winfree prize by the Society for Mathematical Biology: “the Arthur T. Winfree Prize […] will honor a theoretician whose research has inspired significant new biology.” [smb.org] On this occasion we (Thomas Quail and Lennart Hilbert) have posed a few questions to Leon. Again, a reminder that Leon is not only a brilliant theorist, but is hardly found short of experiences, insights, and worthwhile pastimes to talk about. (more…)
Several members of the CAMBAM student community, and professors associated with it, are studying in the field of neuroscience, but CAMBAM only rarely sponsored neuroscience events. It is time for this to change! (more…)
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…)
Dr. Sarah P. (“Sally”) Otto is presently visiting McGill for a couple of days. Yesterday we had two CAMBAM-sponsored events with her; thanks to everybody who turned out for those!
The first was a CAMBAM students’ roundtable lunch with Dr. Otto. A handful of us had pizza and soda with her while talking about our research projects and bouncing around related ideas. This was quite fun for me, since I’m not a CAMBAM member and don’t know much about what you folks do; it was great to hear about heart arrhythmias and neuron chemistry and asthma and actin and myosin and all the rest! I hope it was also fun for the CAMBAM folks to hear about my models of floral morphology and pollen dispersal and reproductive isolation. Mathematical biology contains such a diversity of ideas!
“Lennart, what do you think we do an art show with CAMBAM?”
“But Grace, we are scientists.”
“Some great art has been done by simple minds.”
Lennart, clearly out of arguments: “Ehhhm, I guess we do an art show then?!” (more…)
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 .