Coming up! PRoNTo(Pattern Recognition for Neuroimaging Toolb) course - September 15th-17th, 2021
15 September 2021–17 September 2021, 1:00 pm–5:30 pm
Join us for the upcoming PRoNTo(*) course - 15th-17th September 2021, online (UK timezone). PRoNTo (Pattern Recognition for Neuroimaging Toolbox) is a software toolbox based on pattern recognition techniques for the analysis of neuroimaging data
This three-day course will offer a comprehensive coverage of all PRoNTo v3.0 features and functionalities, including:
- how to extract features from different data types (sMRI, fMRI, EEG, MEG and other data modalities)
- introduction to pattern recognition concepts
- specific pattern recognition methods for neuroimaging
- PRoNTo demos with single modality and multimodal predictive models
PRoNTo v3.0 accepts different data types and enables building multimodal predictive models.
For further information and registration, please see: http://www.mlnl.cs.ucl.ac.uk/pronto/prtcourses.html
PRoNTo (Pattern Recognition for Neuroimaging Toolbox) is a software toolbox based on pattern recognition techniques for the analysis of neuroimaging data. Statistical pattern recognition is a field within the area of machine learning which is concerned with automatic discovery of regularities in data through the use of computer algorithms, and with the use of these regularities to take actions such as classifying the data into different categories. In PRoNTo, brain scans are treated as spatial patterns and statistical learning models are used to identify statistical properties of the data that can be used to discriminate between experimental conditions or groups of subjects, or to predict a continuous measure/score.
PRoNTo is directly compatible with SPM12 and is freely downloadable from http://www.mlnl.cs.ucl.ac.uk/pronto/
An introductory paper is available here: http://dx.doi.org/10.1007/s12021-013-9178-1 and a more recent paper describing some of the new functionalities in PRoNTo version 2 is available here: https://doi.org/10.1007/s12021-017-9347-8