xff_-_sdm_format
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— | xff_-_sdm_format [2010/06/12 01:46] (current) – created jochen | ||
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+ | ====== SDM (BrainVoyager QX's Single-study design matrix) file format ====== | ||
+ | ===== Motivation ===== | ||
+ | The most common approach to identify brain areas that are active during a specific task is by creating regressors used in a multiple linear regression model (General Linear Model; GLM). BrainVoyager QX uses a text-based file format that, after applying a convolution to the stimulus-based stick- or block functions, stores a set of columns, each representing one of the experimental conditions (or parametric modulations of these) as well as any additional variables added to the model, such as motion parameters, filters, heart-rate or respiratory influences on the hemodynamic BOLD response in the brain. | ||
+ | |||
+ | ===== General setup ===== | ||
+ | The information contained in BrainVoyager QX text files is either given in the form: | ||
+ | |||
+ | < | ||
+ | |||
+ | or, if a short list of values (e.g. an RGB color code triplet) is given, as | ||
+ | < | ||
+ | |||
+ | or yet, in case several values are to be coded, as an array of values (or strings) without any header | ||
+ | |||
+ | < | ||
+ | Row2Col1 Row2Col2 Row2Col3 | ||
+ | ...</ | ||
+ | |||
+ | Text-based tokens (constant values) are generally given **without** quotes, names are given **with** quotes (with exceptions noted where appropriate)! Linebreaks are added for increased readability. They do, however, not impact the actual reading of information from the file! | ||
+ | |||
+ | ===== Example ===== | ||
+ | <file - example.sdm> | ||
+ | |||
+ | FileVersion: | ||
+ | |||
+ | NrOfPredictors: | ||
+ | NrOfDataPoints: | ||
+ | IncludesConstant: | ||
+ | FirstConfoundPredictor: | ||
+ | |||
+ | 255 255 0 0 255 255 255 255 255 | ||
+ | " | ||
+ | 0.000000 | ||
+ | 0.000000 | ||
+ | 0.000000 | ||
+ | 0.000000 | ||
+ | 0.000000 | ||
+ | 0.000000 | ||
+ | 0.000000 | ||
+ | 0.000000 | ||
+ | 0.000000 | ||
+ | 0.003554 | ||
+ | 0.113691 | ||
+ | 0.460896 | ||
+ | 0.831251 | ||
+ | 1.050803 | ||
+ | 1.133200 | ||
+ | 1.138367 | ||
+ | 1.109856 | ||
+ | 1.073621 | ||
+ | 1.039519 | ||
+ | 0.908721 | ||
+ | 0.549604 | ||
+ | 0.173206 | ||
+ | -0.049103 | ||
+ | -0.132650 | ||
+ | -0.138260 | ||
+ | -0.109856 | ||
+ | -0.073621 | ||
+ | -0.043074 | ||
+ | -0.022412 | ||
+ | -0.010500 | ||
+ | -0.004457 | ||
+ | 0.001855 | ||
+ | 0.113141 | ||
+ | 0.460789 | ||
+ | 0.831251 | ||
+ | 1.050803 | ||
+ | 1.133200 | ||
+ | 1.138367 | ||
+ | 1.109856 | ||
+ | 1.073621 | ||
+ | 1.039519 | ||
+ | 0.908721 | ||
+ | 0.549604 | ||
+ | 0.173206 | ||
+ | -0.049103 | ||
+ | -0.132650 | ||
+ | -0.138260 | ||
+ | -0.109856 | ||
+ | -0.073621 | ||
+ | -0.043074 | ||
+ | -0.022412 | ||
+ | -0.010500 | ||
+ | -0.004457 | ||
+ | -0.001700 | ||
+ | -0.000550 | ||
+ | -0.000107 | ||
+ | 0.000000 | ||
+ | 0.000000 | ||
+ | 0.000000 | ||
+ | 0.000000 | ||
+ | </ | ||
+ | |||
+ | ===== Fields ===== | ||
+ | As almost any text-based file format in BrainVoyager QX, a '' | ||
+ | |||
+ | ^ Field name ^ Type ^ Content | ||
+ | | FileVersion | ||
+ | | NrOfPredictors | ||
+ | | NrOfDataPoints | ||
+ | | IncludesConstant | ||
+ | | FirstConfoundPredictor | ||
+ | | PredictorColors | ||
+ | | PredictorNames | ||
+ | | SDMMatrix | ||
+ | |||
+ | ===== Further notes ===== | ||
+ | In addition to HRF-convolved design matrices, two further applications are given for the SDM format: | ||
+ | * deconvolution design matrices - instead of applying a convolution with an assumed response shape, the length of a response function window is specified, which then leads to a series of 0/1-coded predictors, each additional regressor being a shifted copy of the initial stick function impulse response regressor, which allows to estimate the shape of the response (in the resolution of the data); **please note that this model is still regressed in the temporal resolution of the data! that means that event-related models will incur a certain amount of temporal smoothing when the response is estimated** | ||
+ | * storing other regressor data - as pretty much any hypothesis driven test requires a regression of some sort (e.g. a correlation with a behavioral covariate), the SDM format can also be used to store arbitrary regressors (e.g. IQ or average reaction time for different tasks per subject; heart-rate for each time point, etc.) |
xff_-_sdm_format.txt · Last modified: 2010/06/12 01:46 by jochen