BIRC Lectures and Workshops

BIRC is offering four educational sessions over the course of the 2019-2020 academic year. There will be one workshop and three lectures throughout the year. All UConn faculty, staff, and students are invited to attend. All events are held on the Storrs campusRegistration is required and is due two weeks before each event. Please send inquiries to: birc@uconn.edu.


FALL 2019


BIRC.190918. Workshop: FreeSurfer Practical Workshop

Lihong Wang MD PhD; Associate Professor, Department of Psychiatry, UConn Health
Date: Wednesday 09/18/2019
Time: 10am-12pm
Location: Arjona 340
Registration form: https://forms.gle/zywvyufMEV4SYFHH7 
Maximum Capacity: 8

Abstract:
FreeSurfer is a powerful tool for measuring neuroanatomical information such as volume, cortical thickness, surface area and folding. The workshop will provide a short FreeSurfer tutorial that is available on their website. It will include a brief introduction of data preprocessing, analyses, and hands-on practice of QA (e.g., individual and group data analyses, and troubleshooting). DTI data analysis using TRACULA and overlaying fMRI results onto brain surface will also be introduced.

Learning Objectives:
– To obtain a clear idea of what FreeSurfer can do, why and what outputs you can get from recon-all
– Become familiar with data analysis steps and enable to do data analysis on T1 structural images
– Become familiar with Freeview display

Prerequisites: 
A basic knowledge of Linux/Unix is required. Participants need to have an HPC account by Monday, 09/16/2019. An account can be requested at https://hpc.uconn.edu/storrs/account-application/.

BIRC.191106. Lecture: Introduction to Diffusion Weighted Imaging 

Olga Kepinska PhD; Postdoctoral Scholar, Department of Psychological Sciences

Date: Wednesday 11/06/2019
Time: 10am-12pm
Location: BIRC Conference Room (PCSB 141)
Registration form: https://forms.gle/ek2QURUX8EHx3oRh6
Maximum Capacity: 8

Abstract:
Diffusion Weighted Imaging (DWI) is a non-invasive neuroimaging technique aimed at visualizing and quantifying brain network connectivity, i.e. the brain’s white matter. In this lecture, we will discuss the methodological foundations of the technique and its applications to state-of-the-art research into the neural substrates of language processing. In particular, we will explore the basics of DWI imaging acquisition, pre-processing steps, modeling techniques, visualization approaches, and quantitative analyses methodology. Some clinical applications will also be discussed.

Learning Objectives:
– Be familiar with the workflow of DWI: from data acquisition to quantitative analysis
– Identify main applications of DWI
– Describe the strengths and shortcomings of DWI as compared to other imaging modalities
– Identify potential research questions applicable to DWI
– Critically evaluate research employing DWI

Prerequisite:
Familiarity with magnetic resonance imaging is encouraged but not required.
*THIS LECTURE WILL BE AVAILABLE TO VIEW VIA WEBEX*
Registration is required two weeks in advance to view this lecture on Webex. If interested, please register here. Once you reregistration is approved, you will receive an automatically generated email from Webex with the meeting link and password.

SPRING 2020


BIRC.200212. Lecture: Introduction to MRS lecture

Roeland Hancock, PhD; Associate Director, BIRC; Assistant Research Professor, Department of Psychological Sciences

Date: Wednesday 2/12/2020
Time: 10am-12pm
Location: BIRC Conference Room (PCSB 141)
Registration form: https://forms.gle/g9bZwD1uGCgKkvGW8
Maximum Capacity: 8

Abstract:
Magnetic resonance spectroscopy (MRS) is a technique for non-invasive measurement of metabolic products, without the use of radioligands. The technique has applications in basic and translational research, and clinical practice. This lecture will introduce proton magnetic resonance spectroscopy (1H MRS), with a focus on the use of single voxel spectroscopy in the human brain at 3 Tesla. The basic principles of MRS will be introduced, followed by a discussion of common acquisition methods for measuring metabolites of potential interest in the context of cognitive neuroscience, including J-edited gamma-aminobutyric acid measurement. Acquisition and quality control strategies, preprocessing steps, and limitations will also be discussed.

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

Prerequisite:
Familiarity with magnetic resonance imaging or nuclear magnetic resonance is encouraged.

BIRC.200401. Lecture: Introduction to Neuroimaging Pipelines

Roeland Hancock, PhD; Associate Director, BIRC; Assistant Research Professor, Department of Psychological Sciences

Date: Wednesday 4/1/2020
Time: 10am-12pm
Location: Arjona 340
Registration form: https://forms.gle/HtPFmuuZDvQ3UGab9
Maximum Capacity: 12
Abstract:
The Brain Imaging Data Structure (BIDS) and containerized computing using Docker and Singularity have facilitated the development of reproducible, generalized neuroimaging processing pipelines that can be scalably deployed with minimal effort. This lecture will introduce the major steps needed to successfully deploy a pre-packaged pipeline and an overview of common processing strategies for quality control (mriqc) and preprocessing (e.g. fmriprep) of functional and anatomical MRI data.

Learning Objectives:
– Interpret the components of a BIDS file name
– Select a pipeline appropriate for their preprocessing objectives
– Construct Docker and Singularity command lines
– Estimate the computational resources needed for preprocessing their data

Prerequisites:
– Attendees must be comfortable with command line operations, including directory navigation, on a Unix like operating system, such as Linux or macOS.
– Attendees should be familiar with typical fMRI preprocessing stages
– Attendees should be familiar with T1w, T2w, bold, and field map modalities and understand how to identify these in their own data