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Temporal Dynamics of Event-Related Potentials during Inhibitory Control Characterize Age-Related Neural Compensation.

Symmetry | 2021

Aging is accompanied by frontal lobe and non-dominant hemisphere recruitment that supports executive functioning, such as inhibitory control, which is crucial to all cognitive functions. However, the spatio-temporal sequence of processing underlying successful inhibition and how it changes with age is understudied. Thus, we capitalized on the temporal precision of event-related potentials (ERPs) to assess the functional lateralization of N200 (conflict monitoring) and P300 (inhibitory performance evaluation) in young and healthy older adults during comparably performed successful stop-signal inhibition. We additionally used temporal principal components analysis (PCA) to further interrogate the continuous spatio-temporal dynamics underlying N200 and P300 activation for each group. Young adults demonstrated left hemisphere-dominant N200, while older adults demonstrated overall larger amplitudes and right hemisphere dominance. N200 activation was explained by a single PCA factor in both age groups, but with a more anterior scalp distribution in older adults. The P300 amplitudes were larger in the right hemisphere in young, but bilateral in old, with old larger than young in the left hemisphere. P300 was also explained by a single factor in young adults but by two factors in older adults, including distinct parieto-occipital and anterior activation. These findings highlight the differential functional asymmetries of conflict monitoring (N200) and inhibitory evaluation and adaptation (P300) processes and further illuminate unique age-related spatio-temporal recruitment patterns. Older adults demonstrated lateralized recruitment during conflict processing and bilateral recruitment during evaluation and adaptation, with anterior recruitment common to both processes. These fine-grained analyses are critically important for more precise understanding of age-related compensatory activation.

Pubmed ID: 35923222 RIS Download

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Associated grants

  • Agency: NCATS NIH HHS, United States
    Id: TL1 TR001437
  • Agency: NCATS NIH HHS, United States
    Id: UL1 TR001436

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MATLAB (tool)

RRID:SCR_001622

Multi paradigm numerical computing environment and fourth generation programming language developed by MathWorks. Allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, Java, Fortran and Python. Used to explore and visualize ideas and collaborate across disciplines including signal and image processing, communications, control systems, and computational finance.

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EEGLAB (tool)

RRID:SCR_007292

Interactive Matlab toolbox for processing continuous and event-related EEG, MEG and other electrophysiological data incorporating independent component analysis (ICA), time/frequency analysis, artifact rejection, event-related statistics, and several useful modes of visualization of the averaged and single-trial data. First developed on Matlab 5.3 under Linux, EEGLAB runs on Matlab v5 and higher under Linux, Unix, Windows, and Mac OS X (Matlab 7+ recommended). EEGLAB provides an interactive graphic user interface (GUI) allowing users to flexibly and interactively process their high-density EEG and other dynamic brain data using independent component analysis (ICA) and/or time/frequency analysis (TFA), as well as standard averaging methods. EEGLAB also incorporates extensive tutorial and help windows, plus a command history function that eases users'' transition from GUI-based data exploration to building and running batch or custom data analysis scripts. EEGLAB offers a wealth of methods for visualizing and modeling event-related brain dynamics, both at the level of individual EEGLAB ''datasets'' and/or across a collection of datasets brought together in an EEGLAB ''studyset.'' For experienced Matlab users, EEGLAB offers a structured programming environment for storing, accessing, measuring, manipulating and visualizing event-related EEG data. For creative research programmers and methods developers, EEGLAB offers an extensible, open-source platform through which they can share new methods with the world research community by publishing EEGLAB ''plug-in'' functions that appear automatically in the EEGLAB menu of users who download them. For example, novel EEGLAB plug-ins might be built and released to ''pick peaks'' in ERP or time/frequency results, or to perform specialized import/export, data visualization, or inverse source modeling of EEG, MEG, and/or ECOG data. EEGLAB Features * Graphic user interface * Multiformat data importing * High-density data scrolling * Defined EEG data structure * Open source plug-in facility * Interactive plotting functions * Semi-automated artifact removal * ICA & time/frequency transforms * Many advanced plug-in toolboxes * Event & channel location handling * Forward/inverse head/source modeling

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