The gamma model analysis: Introducing a novel scoring method of event-related potentials

Research using the event-related potential (ERP) method to investigate cognitive processes has usually focused on the analysis of either individual peaks or the area under the curve as components of interest. These approaches, however, cannot analyse the substantial variation in size and shape across individual waveforms. The aim of my thesis is thus to introduce the gamma model analysis (GMA). The GMA addresses these specific restrictions of the usually applied methods and enables the analysis of additional time-dependent and shape-related information on ERP components by fitting mathematically computed gamma probability density function (PDF) waveforms to an ERP. The advantage of the GMA is demonstrated in a simulation study and a digit flanker task, as well as a force production task. The data of the digit flanker task is also used to examine a potential limitation of the GMA, namely the inability of the gamma PDF to execute a sign change. Finally, the gamma PDF was compared with three other PDFs concerning their goodness of fit. The different gamma model parameters were sensitive to various experimental manipulations across the empirical studies. Moreover, the GMA revealed several additional interrelated but non-redundant parameters compared to the classical methods, which were predictive of different aspects of behaviour, allowing for a more nuanced analysis of the cognitive processes. The GMA provides an elegant method for extracting easily interpretable indices for the rise and decline of the components that complement the classical parameters. This approach, therefore, provides a novel toolset to better understand the exact relationship between ERP components, behaviour, and cognition

Neural correlates of error detection during complex response selection: Introduction of a novel eight-alternative response task

Error processing in complex decision tasks should be more difficult compared to a simple and commonly used two-choice task. We developed an eight-alternative response task (BART), which allowed us to investigate different aspects of error detection. We analysed event-related potentials (ERP; N = 30). Interestingly, the response time moderated several findings. For example, only for fast responses, we observed the well-known effect of larger error negativity (N-e) in signalled and non-signalled errors compared to correct responses, but not for slow responses. We identified at least two different error sources due to post-experimental reports and certainty ratings: impulsive (fast) errors and (slow) memory errors. Interestingly, the participants were able to perform the task and to identify both, impulsive and memory errors successfully. Preliminary evidence indicated that early (N-e-related) error processing was not sensitive to memory errors but to impulsive errors, whereas the error positivity seemed to be sensitive to both error types

Measuring 129Xe transfer across the blood‐brain barrier using MR spectroscopy

Purpose This study develops a tracer kinetic model of xenon uptake in the human brain to determine the transfer rate of inhaled hyperpolarized 129Xe from cerebral blood to gray matter that accounts for the effects of cerebral physiology, perfusion and magnetization dynamics. The 129Xe transfer rate is expressed using a tracer transfer coefficient, which estimates the quantity of hyperpolarized 129Xe dissolved in cerebral blood under exchange with depolarized 129Xe dissolved in gray matter under equilibrium of concentration. Theory and Methods Time‐resolved MR spectra of hyperpolarized 129Xe dissolved in the human brain were acquired from three healthy volunteers. Acquired spectra were numerically fitted with five Lorentzian peaks in accordance with known 129Xe brain spectral peaks. The signal dynamics of spectral peaks for gray matter and red blood cells were quantified, and correction for the 129Xe T1 dependence upon blood oxygenation was applied. 129Xe transfer dynamics determined from the ratio of the peaks for gray matter and red blood cells was numerically fitted with the developed tracer kinetic model. Results For all the acquired NMR spectra, the developed tracer kinetic model fitted the data with tracer transfer coefficients between 0.1 and 0.14. Conclusion In this study, a tracer kinetic model was developed and validated that estimates the transfer rate of HP 129Xe from cerebral blood to gray matter in the human brain

Larger error negativity peak amplitudes for accuracy versus speed instructions may reflect more neuro-cognitive alignment, not more intense error processing

Article number: 2259 (2023

Search for supersymmetry in events with photons, bottom quarks, and missing transverse momentum in proton-proton collisions at a centre-of-mass energy of 7 TeV with the ATLAS detector

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