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Neuroscience and Neurobiology Commons™
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Articles 1 - 6 of 6
Full-Text Articles in Neuroscience and Neurobiology
Inter-Subject Correlation While Listening To Minimalist Music: A Study Of Electrophysiological And Behavioral Responses To Steve Reich’S Piano Phase, Tysen Dauer, Duc T. Nguyen, Nick Gang, Jacek P. Dmochowski, Jonathan Berger, Blair Kaneshiro
Inter-Subject Correlation While Listening To Minimalist Music: A Study Of Electrophysiological And Behavioral Responses To Steve Reich’S Piano Phase, Tysen Dauer, Duc T. Nguyen, Nick Gang, Jacek P. Dmochowski, Jonathan Berger, Blair Kaneshiro
Publications and Research
Musical minimalism utilizes the temporal manipulation of restricted collections of rhythmic, melodic, and/or harmonic materials. One example, Steve Reich’s Piano Phase, offers listeners readily audible formal structure with unpredictable events at the local level. For example, pattern recurrences may generate strong expectations which are violated by small temporal and pitch deviations. A hyper-detailed listening strategy prompted by these minute deviations stands in contrast to the type of listening engagement typically cultivated around functional tonal Western music. Recent research has suggested that the inter-subject correlation (ISC) of electroencephalographic (EEG) responses to natural audio-visual stimuli objectively indexes a state of “engagement,” demonstrating …
Classical Conditioning Of Cognitive States, Arthur Burns
Classical Conditioning Of Cognitive States, Arthur Burns
Neuroscience Presentations
This research sought out to do preliminary testing to prepare for honors research in the 2021 academic year. This research focuses on attempting to classically condition cognitive states. Learning tasks were designed to elicit relaxation or arousal in partisans and a combination of EEG data, pupil dilation data, performance on cognitive tasks, and self-report were used to evaluate the level of cognitive states in participants.
Classical Conditioning Of Cognitive States, Arthur Burns
Classical Conditioning Of Cognitive States, Arthur Burns
Neuroscience Summer Fellows
This research sought out to do preliminary testing to prepare for honors research in the 2021 academic year. This research focuses on attempting to classically condition cognitive states. Learning tasks were designed to elicit relaxation or arousal in partisans and a combination of EEG data, pupil dilation data, performance on cognitive tasks, and self-report were used to evaluate the level of cognitive states in participants.
Performance Of Openbci Eeg Binary Intent Classification With Laryngeal Imagery, Nathan George, Samuel Kuhn
Performance Of Openbci Eeg Binary Intent Classification With Laryngeal Imagery, Nathan George, Samuel Kuhn
Regis University Faculty Publications (comprehensive list)
One of the greatest goals of neuroscience in recent decades has been to rehabilitate individuals who no longer have a functional relationship between their mind and their body. Although neuroscience has produced technologies which allow the brains of paralyzed patients to accomplish tasks such as spell words or control a motorized wheelchair, these technologies utilize parts of the brain which may not be optimal for simultaneous use. For example, if you needed to look at flashing lights to spell words for communication, it would be difficult to simultaneously look at where you are moving. To improve upon this issue, this …
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 …