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Full-Text Articles in Neuroscience and Neurobiology
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 …
An Eeg Study On Loneliness And Recognition Memory, Carmen Jia Wen Chek
An Eeg Study On Loneliness And Recognition Memory, Carmen Jia Wen Chek
Electronic Theses and Dissertations
Loneliness, the perception of unmet social needs, has been shown to relate to recollection-based recognition deficits, but the relationship between loneliness and recognition memory (i.e., recollection and familiarity) has not been thoroughly examined. The current study hypothesized that more lonely individuals would have lower recognition memory performance, specifically recollection, with smaller ERP parietal old-new effects than less lonely individuals. Forty participants, grouped into less (n = 13) and more (n = 9) lonely groups based on their R-UCLA responses, completed an associative memory task. EEG was used to assess recognition memory effects. Results showed no significant difference in …
Eeg Study Of The Featural And Configural Components Of Face Perception, Heather Rose Stegman
Eeg Study Of The Featural And Configural Components Of Face Perception, Heather Rose Stegman
Summer Research
Prior research using functional magnetic resonance imaging (fMRI) suggests that facial features (i.e. eyes, nose, and mouth) and their configuration (i.e. T-shaped arrangement of features) are processed in different face-specific brain regions. However, precise response time of featural and configural face processing is unknown. Featural processing may occur before configural processing, or configural processing may occur before featural processing; conversely, they may occur simultaneously. Here, using the electroencephalography (EEG), we will examine the face-specific event related potential (ERP), the N170, to analyze temporal differences between featural and configural face processing.
The Relationship Between Time Of Day, Mood, And Electroencephalography (Eeg) Asymmetry, Morgan Tantillo
The Relationship Between Time Of Day, Mood, And Electroencephalography (Eeg) Asymmetry, Morgan Tantillo
Honors Projects
Previous researchers have had success in finding a correlation between exercise and an increase in positive mood. Researchers have also found a correlation between time of day and mood. The current study will explore the relationship between time of day, mood, and electroencephalography (EEG) asymmetry. The study utilized a convenient sample of ten undergraduate students at Bowling Green State University. Participants had baseline EEG recordings taken, and then participated in moderate exercise, followed by another EEG recording. Participants’ mood was assessed through a self-reported mood questionnaire before the condition as well as immediately after. Due to multiple statistical tests, the …
Electrophysiological And Behavioral Working Memory Differences Between Musicians And Non-Musicians, Benjamin P. Richardson
Electrophysiological And Behavioral Working Memory Differences Between Musicians And Non-Musicians, Benjamin P. Richardson
All Master's Theses
The current study examines the P300 brainwave and working memory differences between musicians and non-musicians. Differences in aspects of recorded electrical brain activity have been used to quantify differences in updating processes of working memory possibly related to differences in amount of music experience. The current study is designed to partially replicate and enhance a method previously implemented in research describing how music experience may be associated with differences in visual processing as well auditory working memory and executive function. Behavioral data were collected using six standardized subtest measures of the TOMAL – II, followed by ERP recordings during a …