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Neural Mechanisms of Individuality - EEG Studies in Self and Morality

The need for individual neural markers has been expressed in both basic and clinical neuroscience. To address this, we here designed a novel behavioural paradigm in which to test several measures as possible neural markers of individuality which distinguish participants from each other in how they perceive, feel and perform cognitive tasks. The individualized paradigm for consequentialist moral dilemmas was validated, showing variability across participants in thresholds and reaction times. Next, task-induced activity changes in EEG activity during the time interval of the Late Positive Potential (LPP) in alpha power, along with phase coherence early in the trial, correlated with reaction times and scores of subjective emotional distress. From these findings in study one, in study two we measured trial-to-trial variability (TTV) and found that the TTV index in the alpha and beta bands correlated with reaction time and prestimulus Lempel-Ziv Complexity. These findings, again in the alpha and beta bands, support alpha power during the LPP, variability quenching in these bands, and early intertrial coherence as markers of neural individuality. Finally, measures of scale-free activity in the resting state, along with others, and self-consciousness scale subscores as indices of the self were investigated. It was found that the power-law exponent, autocorrelation window, modulation index and electromagnetic tomography activity in two Default Mode Network areas correlated significantly with the Private subscore of the Self-Consciousness Scale only. These findings indicate that these resting state measures, along with activity in the DMN, may serve as markers of neural individuality in the brain’s spontaneous activity.

Identiferoai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/39017
Date01 April 2019
CreatorsWolff, Anne Marie
ContributorsNorthoff, Georg
PublisherUniversité d'Ottawa / University of Ottawa
Source SetsUniversité d’Ottawa
LanguageEnglish
Detected LanguageEnglish
TypeThesis
Formatapplication/pdf

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