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Recording Great Physiological Data in 7T Ultra-High Field fMRI

Graph, EDA, EMG, Unfiltered, Filtered, AcqKnowledge

Live data including raw EDA (top line), raw EMG (third line), and filtered EMG (last line) in AcqKnowledge 

7T FMRI, Hand Gripping, Activation, Brain

BIOPAC Systems products were recently used for neurophysiological mapping on a human subject inside a 7T scanner for a study at Auburn University. The study was also coauthored by two of our own BIOPAC members, Ken Graap and Alan Macy, and presented at the recent Society of Psychophysiology Research annual meeting in Atlanta, GA. The experiment aimed to pull physiological measurements (ECG, EDA, & EMG) from a human subject during fMRI data acquisition. Data was acquired using BIOPAC’s suite of MRI-compatible modules, leads, and electrodes including the ECG100C-MRI, EMG100C-MRI, and EDA100C-MRI and all connected to the powerful MP150 system.  The study successfully gathered both high quality, multichannel physiological data and submillimeter fMRI data in an ultra-high field MR environment. This type of data collection can lead to better understanding of the neural and physiological processes that underlie psychological constructs. With both our reliable equipment and passionate staff members, BIOPAC continues our commitment toward aiding and leading innovation in life science research.

Poster presented at the Society for Psychophysiological Research Annual Meeting, Sept. 13, 2014, Atlanta, GA.

Reference: Jennifer L. Robinson1,2,3, Matthew W. Miller1,2, Ron Beyers3, Kirk Grand2, Lauren A. J. Kirby1, Alan Macy4, & Ken Graap4

1 Department of Psychology, Auburn University, Auburn, AL; 2 Department of Kinesiology, Auburn University, Auburn, AL; 3 Department of Electrical and Computer Engineering, Auburn University MRI Research Center, Auburn, AL; 4 BIOPAC Systems, Inc.

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fNIRS Data Analysis

In this fNIRS training, you will see a typical analysis workflow for fNIRS data in experiments featuring both event-based and continuous stimulation. Learn about a powerful yet easy-to-use software package with both a graphical user interface and scripting capability (for automation).

What You Will Learn:
• Preparing data for analysis
• Signal conditioning, noise removal, and managing artifacts
• Best practices for visualizing recorded data
• Block analysis using event markers and/or time
• Further temporal and spatial processing of data, including cell-by-cell processing
• Automation of analysis procedures
• Performing common statistical comparisons (t-test, ANOVA)
• Spatial visualization
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