Perceptual decision making is one of the most basic forms of cognition, for it is how sensory input is mapped to specific behavior. Substantial effort has focused on uncovering the constituent cortical networks involved in this early form of cognition using both single and multi-unit recordings in primates and, more recently, functional neuroimaging in humans. These neuroimaging studies, typically utilizing functional magnetic resonance imaging (fMRI), have identified areas in frontal, parietal, and thalamic cortex in which metabolic activity correlates with decision related variables. However, decision making is a dynamic process, and the localized activations found with fMRI must be a part of cortical networks defined by the relative timing of these activations and their causality. The overall goal of this project is to couple high temporal resolution, single-trial analysis of electroencephalography (EEG) with simultaneously acquired fMRI to infer the constituent cortical networks of perceptual decision making in the human brain.
Specific aims are 1) to replicate and systematically expand upon our prior results showing neural components correlate with task-relevant decision making variables, but for the case of EEG acquired simultaneously with fMRI, 2) to link trial-to-trial variability of EEG components, identified for perceptual decision making, with spatial area simultaneously imaged with fMRI, and 3) to extend our perceptual decision making paradigm from brief stimulus presentation to prolonged and dynamic stimuli and use single-trial analysis of simultaneous EEG/fMRI to differentiate cortical networks involved in evidence accumulation. This project will significantly advance our understanding of decision making in the human brain by providing a more precise cortical network """"""""diagram"""""""" which could be used to better compare differences observed between primate and human data. Finally, this research could lead to a better understanding of cortical processing underlying basic cognitive deficits, linking spatial and temporal changes in activations to specific neurological diseases and disease states.

Public Health Relevance

In this project we will use state-of-the art neuroimaging to map the neural networks underlying decision making in the human brain. This project will both shed light on basic neuroscience questions related to decision making in humans as well as lead to a better understanding of cognitive deficits and neurological disease in which decision making is affected.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
1R01MH085092-01A1
Application #
7653197
Study Section
Cognitive Neuroscience Study Section (COG)
Program Officer
Rossi, Andrew
Project Start
2009-08-05
Project End
2014-05-31
Budget Start
2009-08-05
Budget End
2010-05-31
Support Year
1
Fiscal Year
2009
Total Cost
$364,071
Indirect Cost
Name
Columbia University (N.Y.)
Department
Biomedical Engineering
Type
Schools of Engineering
DUNS #
049179401
City
New York
State
NY
Country
United States
Zip Code
10027
Muraskin, Jordan; Brown, Truman R; Walz, Jennifer M et al. (2018) A multimodal encoding model applied to imaging decision-related neural cascades in the human brain. Neuroimage 180:211-222
Delis, Ioannis; Dmochowski, Jacek P; Sajda, Paul et al. (2018) Correlation of neural activity with behavioral kinematics reveals distinct sensory encoding and evidence accumulation processes during active tactile sensing. Neuroimage 175:12-21
Muraskin, Jordan; Sherwin, Jason; Lieberman, Gregory et al. (2017) Fusing multiple neuroimaging modalities to assess group differences in perception-action coupling. Proc IEEE Inst Electr Electron Eng 105:83-100
Tu, Tao; Schneck, Noam; Muraskin, Jordan et al. (2017) Network Configurations in the Human Brain Reflect Choice Bias during Rapid Face Processing. J Neurosci 37:12226-12237
Ratcliff, Roger; Sederberg, Per B; Smith, Troy A et al. (2016) A single trial analysis of EEG in recognition memory: Tracking the neural correlates of memory strength. Neuropsychologia 93:128-141
Muraskin, Jordan; Dodhia, Sonam; Lieberman, Gregory et al. (2016) Brain dynamics of post-task resting state are influenced by expertise: Insights from baseball players. Hum Brain Mapp 37:4454-4471
Sherwin, Jason Samuel; Muraskin, Jordan; Sajda, Paul (2015) Pre-stimulus functional networks modulate task performance in time-pressured evidence gathering and decision-making. Neuroimage 111:513-25
Walz, Jennifer M; Goldman, Robin I; Carapezza, Michael et al. (2015) Prestimulus EEG alpha oscillations modulate task-related fMRI BOLD responses to auditory stimuli. Neuroimage 113:153-63
Lou, Bin; Hsu, Wha-Yin; Sajda, Paul (2015) Perceptual Salience and Reward Both Influence Feedback-Related Neural Activity Arising from Choice. J Neurosci 35:13064-75
Muraskin, Jordan; Sherwin, Jason; Sajda, Paul (2015) Knowing when not to swing: EEG evidence that enhanced perception-action coupling underlies baseball batter expertise. Neuroimage 123:1-10

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