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Methods for analyzing large neuroimaging datasets  /

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Category: Procedure

Description: Many common analysis methods for task-based functional MRI rely on detailed information about experiment design and events. Event recording and representation during cognitive experiments deserves more attention, as it forms an essential link between neuroimaging data and the cognition we wish to understand. The use of standardized data structures enables tools to directly use event-based metadata for preprocessing and analysis, allowing for more efficient processing and more standardized results. However, the complex paradigms utilized by cognitive neuroscience often have different requirements for event representation. The process of generating event files from experimental logs and to iteratively restructuring these event files is a time-intensive process. Careful planning and effective tools can reduce the burden on the researcher and create better documented and more shareable datasets.This chapter discusses event representation within the BIDS (Brain Imaging Data Structure) framework. We discuss some of the common pitfalls in event representation and introduce tools to easily transform event files to meet specific analysis requirements. We demonstrate these tools and the corresponding analysis by comparing two BIDS datasets in which participants performed a stop-signal task. We work through the required event restructuring, and use Fitlins to calculate several comparable contrasts across the two datasets.


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