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Task Performance Changes the Amplitude and Timing of the BOLD Signal
Atae Akhrif1, Maximilian J Geiger2, Marcel Romanos1
1Center of Mental Health, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University of Wuerzburg, Wuerzburg, Germany.
Translational Neuroscience
|January 11, 2018
Summary
Bayesian Adaptive Regression Splines (BARS) successfully modeled human fMRI data, revealing distinct brain activation patterns in good versus bad performers on a cognitive task. Bad performers showed compensatory left prefrontal cortex activity alongside reduced parieto-striatal function.
Area of Science:
- Neuroscience
- Cognitive Science
- Biomedical Imaging
Background:
- Translational studies comparing animal and human imaging data require harmonized analysis.
- Bayesian Adaptive Regression Splines (BARS) have primarily modeled rodent electrophysiology.
- Functional magnetic resonance imaging (fMRI) measures hemodynamic responses to neural activity.
Purpose of the Study:
- To adapt and apply Bayesian Adaptive Regression Splines (BARS) for analyzing human fMRI data.
- To investigate differences in brain activation and hemodynamic responses between good and bad performers on the Attention Network Task.
- To explore the relationship between BOLD signal characteristics and task performance.
Main Methods:
- Applied Bayesian Adaptive Regression Splines (BARS) to fMRI data from 47 healthy subjects performing the Attention Network Task.
- Analyzed fluctuations in the amplitude and timing of the Blood-Oxygen-Level-Dependent (BOLD) response.
- Validated findings against general linear model (GLM) brain activation and task performance (good vs. bad performers).
Main Results:
- Bad performers exhibited reduced bilateral parietal lobule, right prefrontal cortex (PFC), and striatal activation.
- Bad performers showed enhanced left PFC activation and increased BOLD signal amplitude in this region.
- Parieto-striatal regions showed higher temporal dynamics in bad performers, suggesting increased beta-band activity.
Conclusions:
- The enhanced left PFC recruitment in bad performers suggests compensatory gamma-band activity.
- Reduced parieto-striatal activity accompanied by increased beta-band activity in bad performers indicates potential neural conflict.
- BARS is a viable method for analyzing human fMRI data in translational neuroscience research.
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