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Decoding time by time
- ZAHRAN Saeed (Unlicensed)
In the previous App, we have trained a classifier to discriminate between experimental conditions by using the spatio-temporal patterns of entire trials. Consequently, the classifier was (hopefully!) able to predict which activation patterns belonged to which condition.
However, an interesting neuroscientific is: Exactly when do the brain signals for two conditions differ?
We can try to answer this question by fitting a classifier at every single time point. If the classifier can successfully discriminate between the two conditions, we can conclude that the spatial activation patterns measured by the MEG or EEG sensors differed at this very time point.
Links to the App:
https://github.com/zahransa/app-decoding-time-by-time
Inputs of the App:
File | Format | Datatype | Description |
|---|---|---|---|
Epochs | .fif | neuro/meeg/mne/epochs | Epoched data |
Configuation parameter | Type | Description |
|---|---|---|
event_condition | string | Experiment descriptions. |
Outputs of the App: