Hi all, I've noticed that many computational neuroscience research groups use MATLAB. While it's possible that MATLAB may have some features unavailable in R, I suspect that this may instead simply be a case of costly tradition, where researchers were taught MATLAB as students and pay for it as researchers because it's all they know. I'd like to attempt to break the cycle by offering colleagues resources on using R for computational neuroscience, but I haven't been able to find anything (searched the task view, r-seek, & google). Can anyone direct me to resources on using R for computational neuroscience? Input on my possibly naive assumption that R is a sufficient tool for this field would also be appreciated. Cheers, Mike -- Mike Lawrence Graduate Student Department of Psychology Dalhousie University www.thatmike.com Looking to arrange a meeting? Check my public calendar: http://www.thatmike.com/mikes-public-calendar ~ Certainty is folly... I think. ~
On Fri, 2009-01-23 at 08:53 -0400, Mike Lawrence wrote:> Hi all, > > I've noticed that many computational neuroscience research groups use > MATLAB. While it's possible that MATLAB may have some features > unavailable in R, I suspect that this may instead simply be a case of > costly tradition, where researchers were taught MATLAB as students and > pay for it as researchers because it's all they know. > > I'd like to attempt to break the cycle by offering colleagues > resources on using R for computational neuroscience, but I haven't > been able to find anything (searched the task view, r-seek, & google). > > Can anyone direct me to resources on using R for computational > neuroscience? Input on my possibly naive assumption that R is a > sufficient tool for this field would also be appreciated. > > Cheers, > > MikeMike, I think neuroscience is a term using for a wide group of researchers. The common analysis (hypothesis test, ANOVA, regression models, etc) is perfectly made in R. But the interpretation of mri is need a packages: 1- AnalyzeFMRI -Functions for I/O, visualisation and analysis of functional Magnetic Resonance Imaging (fMRI) datasets stored in the ANALYZE or NIFTI format. 2- fmri - contains R-functions to perform an fmri analysis as described in Tabelow, K., Polzehl, J., Voss, H.U., and Spokoiny, V. Analysing fMRI experiments with structure adaptive smoothing procedures, NeuroImage, 33:55-62 (2006) 3- dti - Diffusion Weighted Imaging is a Magnetic Resonance Imaging modality, that measures diffusion of water in tissues like the human brain. The package contains R-functions to process diffusion-weighted data in the context of the diffusion tensor model (DTI). This includes the calculation of anisotropy measures and, most important, the implementation of our structural adaptive smoothing algorithm as described in K. Tabelow, J. Polzehl, V. Spokoiny, and H.U. Voss, Diffusion Tensor Imaging: Structural Adaptive Smoothing, Neuroimage 39(4), 1763-1773 (2008). -- Bernardo Rangel Tura, M.D,MPH,Ph.D National Institute of Cardiology Brazil
Mike Lawrence <mike <at> thatmike.com> writes:> I've noticed that many computational neuroscience research groups use > MATLAB. While it's possible that MATLAB may have some features > unavailable in R, I suspect that this may instead simply be a case of > costly tradition, where researchers were taught MATLAB as students and > pay for it as researchers because it's all they know. > I'd like to attempt to break the cycle by offering colleagues > resources on using R for computational neuroscience, but I haven't > been able to find anything (searched the task view, r-seek, & google).> Can anyone direct me to resources on using R for computational > neuroscience? Input on my possibly naive assumption that R is a > sufficient tool for this field would also be appreciated. > MikeConsider also, the packages STAR - Spike Train Averaging in R and brainwaver - Basic wavelet analysis of multivariate time series with a visualisation and parametrisation using graph theory which was developed for analyzing fMRI data. Many of the packages developed for analyzing graphs of social networks are equally of use in analyzing connectivity in neural systems. There are also packages for analysing psychophysical data which are relevant for behavioral neuroscience, psyphy, MLDS, sdtalt, etc. Would there be enough for CRAN TASK VIEW? Ken -- Ken Knoblauch Inserm U846 Institut Cellule Souche et Cerveau D?partement Neurosciences Int?gratives 18 avenue du Doyen L?pine 69500 Bron France tel: +33 (0)4 72 91 34 77 fax: +33 (0)4 72 91 34 61 portable: +33 (0)6 84 10 64 10 http://www.sbri.fr