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Minicourse EDDA-TH15

Advanced data analysis and theory using the Brain AnalyzIR toolbox

Theodore Huppert

About this course

This course is intended as an advanced version of the toolbox course and will go into detail on the statistical theory behind our analysis models of fNIRS. This will focus on first and second-level statistical models, image reconstruction, ROC analysis, and resting state/hyperscanning methods.

This course will center around the implementation of these methods in the AnalyzIR toolbox, but it is intended as more of a course on statistical theory as applied to fNIRS.

Learning Outcomes

Students will learn:

  • the theory and implementation of corrections for statistical errors in linear models (serially-correlated noise, motion artifacts, stationary noise);
  • how to quantitatively compare analysis methods and pipelines;
  • the extension of group-level analysis to image reconstruction models;
  • a discussion of statistical pitfalls and assumptions in the analysis.

Course Plan

Level: Advanced

Pre-Requisites:
It assumes familiarity with basic fNIRS data analysis.
This course can be sequential to EDDA-TH14 (Introduction to the Brain AnalyzIR Toolbox)
Course Duration: 2 hours

Delivery Plan

N/A.

Why enrol on this course?

This advanced course is intended to teach the statistical methods and assumptions used in the analysis of fNIRS data. This is intended as a more theory-driven course compared to the companion introduction course (also proposed). Both courses can be taken sequentially.