BIRC Workshops

Upcoming Workshops

Spring 2022

Spring 2022 fMRI Analysis Practicals

BIRC and the IBaCS-BIRC Research Assistantships in Neuroimaging (IBRAiN) program are offering a series of four hands-on practical workshops to demonstrate typical steps in the analysis of BOLD fMRI data, particularly task fMRI. These workshops will be held in-person at BIRC in small groups.

Workshop 1: Quality control
Week of February 28th.
Participants will use mriqc to assess the quality of an fMRI dataset.

Workshop 2: Preprocessing
Week of March 21st.
Participants will use fmriprep to preprocess an fMRI dataset.

Workshop 3: GLM
Week of April 4th.
Participants will use FSL to model the BOLD response in a preprocessed task fMRI dataset.

Workshop 4: Statistics
Week of April 18th.
Participants will use FSL to identify group average activations in a task fMRI dataset.

Registration is now closed. The workshop schedule will be confirmed by February 21st. Please contact Roeland Hancock if you have any questions.

FreeSurfer workshop

Dr. Lihong Wang will also offer a FreeSurfer workshop this Spring.

Description: Brain segmentation and morphology measurements are fundamental procedures for neuroimaging data analyses. Changes in brain volume or cortical thickness have been widely examined in clinical related research. In this workshop, I will briefly introduce the FreeSurfer program, a most widely used program in the field for brain structural analysis. An overview of FreeSurfer's volume and surface processing streams, single subject surface-based analysis, and group level analysis will be included. The goal of this workshop is to enable to conduct brain morphology analysis easily following instructions using FreeSurfer.


  1. You will be familiar with FreeSurfer’s capability
  2. You will be familiar with FreeSurfer pipeline procedures
  3. You will be able to conduct brain morphology analyses easily by following simple commands and wiki guidance.

Date: April 8th, 2022

Time: 1:00-3:00pm EST

Location: Virtual

Registration CLOSED


Past Workshops

Fall 2021

1. DWI Part 1: Principles and Data Acquisition - Nabin Koirala, PhD

Overview: In this two module course, Nabin will give an overview on basics of diffusion MRI including the principles of diffusion and how is it used in the (neuro) imaging. The neurobiological meaning hidden behind the magnificent images that we can obtain using this technique, and hands on analysis of the diffusion MRI data to obtain different metrics.

Topics included:

  • Understand diffusion imaging and why many people are beginning to use it
  • Analyzing data and implementing it into research 

2. DWI Part 2: Data Processing and Analyses - Dr. Nabin Koirala, PhD

Overview: This course will cover the practical aspects of Diffusion data analysis with basics of how to analyze it in your personal computer as well as in the high-performance computing (HPC) systems. The toolbox I will use to demonstrate the data analysis will be FSL. Those who are interested in testing it during the class or before, could download and install them following the instructions here: Note: For the registered users, I will provide a sample dataset to try it in the FSL.

Topics included:

  • Learning how to use FSL and learn to run a standard pipeline for dMRI data processing
  • Learning basics of shell scripting and necessary steps needed to run the data analysis in high-performance computing clusters

3. Introduction to MRI - Dr. Roeland Hancock, PhD

Overview: This workshop will introduce participants to the potential benefits of including MRI in their research and the logistics of doing so.

Topics included:

  • Principles of magnetic resonance and common terminology
  • Survey of MRI techniques and applications
  • Logistics of planning an MRI experiment

Spring 2021

1. Introduction to fMRI

Overview: This virtual seminar will introduce the essentials of using functional magnetic resonance imaging (fMRI) to study brain function at the UConn Brain Imaging Research Center (BIRC).

Topics included:

  • How fMRI signals are measured and how this relates to neural activity
  • The principles of designing an fMRI paradigm
  • A survey of common types of fMRI experiments
  • Typical steps in analyzing fMRI data
  • Logistics of planning an fMRI experiment

2. Introduction to fMRI Preprocessing with BIDS Apps

Overview: This virtual seminar will introduce researchers working with fMRI data to the use of the reproducible scientific computing for fMRI preprocessing.

Topics included:

  • Standardizing neuroimaging file organization using the Brain Imaging Data Structure (BIDS)
  • Containers and reproducible computing
  • UConn computing resources
  • Quality assurance using mriqc
  • fMRI preprocessing using fmriprep

Fall 2020

1. Introduction to Neuroimaging Pipelines

Topics included:

  • Interpreting the components of a BIDS file name
  • Selecting a pipeline appropriate for their preprocessing objectives
  • Constructing Docker and Singularity command lines
  • Estimating the computational resources needed for preprocessing their data

Spring 2020

1. Introduction to MRS

Topics included:

  • Describe the tradeoffs of common MRS sequences
  • Evaluate spectral quality using quantitative and qualitative measures
  • Identify potential challenges in voxel placement