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      Causal role of frontal-midline theta in cognitive effort: a pilot study

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          Abstract

          We investigated whether frontal-midline theta (FMT) oscillations tracked with cognitive control or cognitive effort by simultaneous manipulation of cognitive control demands in a working memory task and causal perturbation of cognitive effort using glucose consumption. Facilitation of performance from glucose consumption corresponded with decreased FMT amplitude, which provided preliminary causal evidence for a relationship between FMT amplitude with cognitive effort.

          Abstract

          Frontal-midline theta (FMT) oscillations are increased in amplitude during cognitive control tasks. Since these tasks often conflate cognitive control and cognitive effort, it remains unknown if FMT amplitude maps onto cognitive control or effort. To address this gap, we utilized the glucose facilitation effect to manipulate cognitive effort without changing cognitive control demands. We performed a single-blind, crossover human study in which we provided participants with a glucose drink (control session: volume-matched water) to reduce cognitive effort and improve performance on a visuospatial working memory task. Following glucose consumption, participants performed the working memory task at multiple time points of a 3-h window to sample across the rise and fall of blood glucose. Using high-density electroencephalography (EEG), we calculated FMT amplitude during the delay period of the working memory task. Source localization analysis revealed that FMT oscillations originated from bilateral prefrontal cortex. We found that glucose increased working memory accuracy during the high working memory load condition but decreased FMT amplitude. The decrease in FMT amplitude coincided with both peak blood glucose elevation and peak performance enhancement for glucose relative to water. Therefore, the positive association between glucose consumption and task performance provided causal evidence that the amplitude of FMT oscillations may correspond to cognitive effort, rather than cognitive control. Due to the COVID-19 pandemic, data collection was terminated prematurely; the preliminary nature of these findings due to small sample size should be contextualized by rigorous experimental design and use of a novel causal perturbation to dissociate cognitive effort and cognitive control.

          NEW & NOTEWORTHY We investigated whether frontal-midline theta (FMT) oscillations tracked with cognitive control or cognitive effort by simultaneous manipulation of cognitive control demands in a working memory task and causal perturbation of cognitive effort using glucose consumption. Facilitation of performance from glucose consumption corresponded with decreased FMT amplitude, which provided preliminary causal evidence for a relationship between FMT amplitude with cognitive effort.

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          Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

          Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
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            EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis

            We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.
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              Is Open Access

              FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data

              This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages.
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                Author and article information

                Contributors
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                Journal
                Journal of Neurophysiology
                Journal of Neurophysiology
                American Physiological Society
                0022-3077
                1522-1598
                October 01 2021
                October 01 2021
                : 126
                : 4
                : 1221-1233
                Affiliations
                [1 ]Department of Psychiatry, University of North Carolina, Chapel Hill, North Carolina
                [2 ]Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, North Carolina
                [3 ]Division of Endocrinology and Metabolism, University of North Carolina School of Medicine, Chapel Hill, North Carolina
                [4 ]Department of Neurology, University of North Carolina, Chapel Hill, North Carolina
                [5 ]Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, North Carolina
                [6 ]Department of Biomedical Engineering, University of North Carolina, Chapel Hill, North Carolina
                Article
                10.1152/jn.00068.2021
                fb0976bf-1559-44b0-b130-f11bf212f093
                © 2021

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