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Full-Text Articles in Neuroscience and Neurobiology
Multiple Approaches To Auditory Rhythm: Development Of Sustained Musical Beat And The Relation To Language, Development Of Rhythmic Categories Via Iterated Production, And A Meta-Analytic Study Of Neural Entrainment To Beat, Karli Marie Nave
UNLV Theses, Dissertations, Professional Papers, and Capstones
Rhythm is ubiquitous to human communication, coordination, and experience of music. In this dissertation, I address three empirical questions through three different methodologies, all of which contribute to the growing body of literature on human auditory rhythm processing. In Chapter 2, I present a registered report detailing the results of independent conceptual replications of Nozaradan, Peretz, Missal, & Mouraux (2011), all using the same vetted protocol. Listeners performed the same tasks as in Nozaradan et al. (2011), with the addition of behavioral measures of perception. In neuroscience, neural correlates to musical beat perception have been identified, yet little to no …
Deep-Learning-Based Multivariate Pattern Analysis (Dmvpa): A Tutorial And A Toolbox, Karl M. Kuntzelman, Jacob M. Williams, Phui Cheng Lim, Ashtok Samal, Prahalada K. Rao, Matthew R. Johnson
Deep-Learning-Based Multivariate Pattern Analysis (Dmvpa): A Tutorial And A Toolbox, Karl M. Kuntzelman, Jacob M. Williams, Phui Cheng Lim, Ashtok Samal, Prahalada K. Rao, Matthew R. Johnson
Center for Brain, Biology, and Behavior: Faculty and Staff Publications
In recent years, multivariate pattern analysis (MVPA) has been hugely beneficial for cognitive neuroscience by making new experiment designs possible and by increasing the inferential power of functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and other neuroimaging methodologies. In a similar time frame, “deep learning” (a term for the use of artificial neural networks with convolutional, recurrent, or similarly sophisticated architectures) has produced a parallel revolution in the field of machine learning and has been employed across a wide variety of applications. Traditional MVPA also uses a form of machine learning, but most commonly with much simpler techniques based on …
Neural Correlates Of The Dunning-Kruger Effect, Alana Muller, Lindsey A. Sirianni, Richard Addante
Neural Correlates Of The Dunning-Kruger Effect, Alana Muller, Lindsey A. Sirianni, Richard Addante
Psychology Faculty Publications
The Dunning-Kruger effect (DKE) is a metacognitive phenomenon of illusory superiority in which individuals who perform poorly on a task believe they performed better than others, yet individuals who performed very well believe they under-performed compared to others. This phenomenon has yet to be directly explored in episodic memory, nor explored for physiological correlates or reaction times. We designed a novel method to elicit the DKE via a test of item recognition while electroencephalography (EEG) was recorded. Throughout the task, participants were asked to estimate the percentile in which they performed compared to others. Results revealed participants in the bottom …