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- Alpha phase (1)
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Articles 1 - 5 of 5
Full-Text Articles in Computational Neuroscience
Change Detection In Rhesus Monkeys And Humans, Deepna T. Devkar, Deepna T. Devkar
Change Detection In Rhesus Monkeys And Humans, Deepna T. Devkar, Deepna T. Devkar
Dissertations & Theses (Open Access)
Visual working memory (VWM) is the temporary retention of visual information and a key component of cognitive processing. The classical paradigm for studying VWM and its encoding limitations has been change detection. Early work focused on how many items could be stored in VWM, leading to the popular theory that humans could remember no more than 4±1 items. More recently, proposals have suggested that VWM is a noisy, continuous resource distributed across virtually all items in the visual field, resulting in diminished memory quality rather than limited quantity. This debate about the nature of VWM has predominantly been studied with …
Rejection Positivity Predicts Trial-To-Trial Reaction Times In An Auditory Selective Attention Task: A Computational Analysis Of Inhibitory Control, Sufen Chen, Robert D. Melara
Rejection Positivity Predicts Trial-To-Trial Reaction Times In An Auditory Selective Attention Task: A Computational Analysis Of Inhibitory Control, Sufen Chen, Robert D. Melara
Publications and Research
A series of computer simulations using variants of a formal model of attention (Melara and Algom, 2003) probed the role of rejection positivity (RP), a slow-wave electroencephalographic (EEG) component, in the inhibitory control of distraction. Behavioral and EEG data were recorded as participants performed auditory selective attention tasks. Simulations that modulated processes of distractor inhibition accounted well for reaction-time (RT) performance, whereas those that modulated target excitation did not. A model that incorporated RP from actual EEG recordings in estimating distractor inhibition was superior in predicting changes in RT as a function of distractor salience across conditions. A …
Eeg-Microstate Dependent Emergence Of Perceptual Awareness, Juliane Britz, Laura Díaz Hernàndez, Tony Ro, Christoph M. Michel
Eeg-Microstate Dependent Emergence Of Perceptual Awareness, Juliane Britz, Laura Díaz Hernàndez, Tony Ro, Christoph M. Michel
Publications and Research
We investigated whether the differences in perceptual awareness for stimuli at the threshold of awareness can arise from different global brain states before stimulus onset indexed by the EEG microstate. We used a metacontrast backward masking paradigm in which subjects had to discriminate between two weak stimuli and obtained measures of accuracy and awareness while their EEG was recorded from 256 channels. Comparing targets that were correctly identified with and without awareness allowed us to contrast differences in awareness while keeping performance constant for identical physical stimuli. Two distinct pre-stimulus scalp potential fields (microstate maps) dissociated correct identification with and …
Optimizing The Analysis Of Electroencephalographic Data By Dynamic Graphs, Mehrsasadat Golestaneh
Optimizing The Analysis Of Electroencephalographic Data By Dynamic Graphs, Mehrsasadat Golestaneh
Electronic Thesis and Dissertation Repository
The brain’s underlying functional connectivity has been recently studied using tools offered by graph theory and network theory. Although the primary research focus in this area has so far been mostly on static graphs, the complex and dynamic nature of the brain’s underlying mechanism has initiated the usage of dynamic graphs, providing groundwork for time sensi- tive and finer investigations. Studying the topological reconfiguration of these dynamic graphs is done by exploiting a pool of graph metrics, which describe the network’s characteristics at different scales. However, considering the vast amount of data generated by neuroimaging tools, heavy computation load and …
Where Do I Know That? A Distributed Multimodal Model Of Semantic Knowledge, Kevin M. Stubbs
Where Do I Know That? A Distributed Multimodal Model Of Semantic Knowledge, Kevin M. Stubbs
Undergraduate Honors Theses
As computers have grown more and more powerful, computational modeling has become an increasingly valuable tool for evaluating real world findings. Likewise, brain imaging has become increasingly powerful as is evidenced by recent fMRI findings which support the exciting possibility that semantic memory is segregated by modality in the brain (Goldberg et al., 2006b). The present study utilizes connectionist modeling to put the distributed multi-modal framework of semantic memory to the test, and represents the next step forward in the line of sensory-functional models. This model, based around the McRae et al. (2005) feature production norms, includes individual implementations of …