... | ... | @@ -23,11 +23,11 @@ To use simBCI, it is helpful to have a basic understanding of BCI systems (i.e. |
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# Features
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The core of simBCI defines the used conventions and provides a simulator that can execute large numbers of experiments. Typically the experiments are defined by specifications for the generative models and the classification (DSP) pipelines. These specifications can contain functions, subfunctions, and parameter sets. The simulator then instantiates these specifications to perform simulated experiments. The distribution includes several example specifications and their functions. On the generative side we include a motor imagery model (Tangermann & al., BCI Competition IV), simple SSVEP and P300 models, various noise and artifact generators, and a volume conduction model. On the signal processing side, we include example pipelines based on e.g. CSP and inverse models (Cincotti & al., Edelman, Baxter & He). The framework can also route data to BCILAB for classification.
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The core of simBCI defines the used conventions and provides a simulator that can execute large numbers of experiments. Typically the experiments are defined by specifications for the generative models and the classification (DSP) pipelines. These specifications can contain functions, subfunctions, and parameter sets. The simulator then instantiates these specifications to perform simulated experiments. The simBCI archive includes several example specifications and the functions they rely on. On the generative side we include a motor imagery model (Tangermann & al., BCI Competition IV), simple SSVEP and P300 models, various noise and artifact generators, and a volume conduction model. On the signal processing side, we include example pipelines based on e.g. CSP and inverse models (Cincotti & al., Edelman, Baxter & He). The framework can also route data to BCILAB for classification.
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![figure1](/uploads/177b690b47bdc41d6ee1c73cffb661ae/figure1.png) Illustration of the signal generation and classification pipelines as modeled by simBCI.
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In typical operation of modeling a BCI session, the framework is used to generate a timeline of events. The timeline is then rendered by specified generators that are configured to react to the events seen as triggers. Generators working inside the cortical volume are projected to the surface by a linear superposition model (leadfield). The signal processing chains in BCI can be seen to be doing inverse operations in the sense that they attempt to predict some of the original events, based on the EEG observations. The system can be asked to iterate different parameters ranges on both generation and testing side.
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In a typical simulated BCI session, the framework is used to generate a timeline of events. The timeline is then rendered by specified generators that are configured to react to the events seen as triggers. If the generators are specified inside the cortical volume, their outputs are projected to the surface by a linear superposition model (leadfield) and mixed additively. The signal processing chains in BCI can be seen to perform inverse operations in the sense that they attempt to predict some of the original events, based on the EEG observations. The system can be asked to iterate different parameters ranges on both generation and testing side.
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# How do I cite it?
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... | ... | @@ -35,11 +35,11 @@ If you use simBCI in your academic work, please cite the following short confere |
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*J.T. Lindgren, A. Merlini, A. Lécuyer and F.P. Andriulli. SimBCI - Tool to simulate EEG and BCI. BCI Meeting, Asilomar/CA, 2018.* (accepted)
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We will provide ref to the journal paper after it has been accepted for publication
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We will provide a reference to the journal paper after it has been accepted for publication.
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# Where is the documentation?
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The code archive contains brief documentation (doc/) about the the code entry points, the main concepts and the used conventions. The platform defines object classes that hopefully correspond to intuitively meaningful concepts (e.g. event timeline, head model, generator, pipeline, signal processor). We provide several simulation examples in the archive, as well as brief Matlab scripts showing how to do different entry-level tasks with the framework.
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The code archive contains brief documentation (*doc/*) about the the code entry points, the main concepts and the used conventions. The platform defines object classes that hopefully correspond to intuitively meaningful concepts (e.g. event timeline, head model, generator, pipeline, signal processor). We provide several simulation examples in the archive, as well as brief Matlab scripts showing how to do different entry-level tasks with the framework.
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The BCI Meeting 2018 abstract (accepted) and the forthcoming journal paper (submitted) will describe the framework on a high level.
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