Biology subjects

Jordan Muraskin

Publications and source records attributed to Jordan Muraskin.

2 recordsLinked to original sources

bioRxiv2016

The Real-time fMRI Neurofeedback Based Stratification of Default Network Regulation Neuroimaging Data Repository.

This data descriptor describes a repository of openly shared data from an experiment to assess inter-individual differences in default mode network (DMN) activity. This repository includes cross-sectional functional magnetic resonance imaging (fMRI) data from the Multi Source Interference Task, to assess DMN deactivation, the Moral Dilemma Task, to assess DMN activation, a resting state fMRI scan, and a DMN neurofeedback paradigm, to assess DMN modulation, along with accompanying behavioral and cognitive measures. We report technical validation from n=125 participants of the final targeted sample of 180 participants. Each session includes acquisition of one whole-brain anatomical scan and whole-brain echo-planar imaging (EPI) scans, acquired during the aforementioned tasks and resting state. The data includes several self-report measures related to perseverative thinking, emotion regulation, and imaginative processes, along with a behavioral measure of rapid visual information processing.\n\nTechnical validation of the data confirms that the tasks deactivate and activate the DMN as expected. Group level analysis of the neurofeedback data indicates that the participants are able to modulate their DMN with considerable inter-subject variability. Preliminary analysis of behavioral responses and specifically self-reported sleep indicate that as many as 73 participants may need to be excluded from an analysis depending on the hypothesis being tested.

Neuroscience↗

bioRxiv2016

Imaging decision-related neural cascades in the human brain

Perceptual decisions depend on coordinated patterns of neural activity cascading across the brain, running in time from stimulus to response and in space from primary sensory regions to the frontal lobe. Measuring this cascade and how it flows through the brain is key to developing an understanding of how our brains function. However observing, let alone understanding, this cascade, particularly in humans, is challenging. Here, we report a significant methodological advance allowing this observation in humans at unprecedented spatiotemporal resolution. We use a novel encoding model to link simultaneously measured electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) signals to infer the high-resolution spatiotemporal brain dynamics taking place during rapid visual perceptual decision-making. After demonstrating the methodology replicates past results, we show that it uncovers a previously unobserved sequential reactivation of a substantial fraction of the pre-response network whose magnitude correlates with decision confidence. Our results illustrate that a temporally coordinated and spatially distributed neural cascade underlies perceptual decision-making, with our methodology illuminating complex brain dynamics that would otherwise be unobservable using conventional fMRI or EEG separately. We expect this methodology to be useful in observing brain dynamics in a wide range of other mental processes.

Neuroscience↗