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Full-Text Articles in Cognitive Psychology
Visual Modulation Of Resting State Α Oscillations, Kelly Webster, Tony Ro
Visual Modulation Of Resting State Α Oscillations, Kelly Webster, Tony Ro
Publications and Research
Once thought to simply reflect passive cortical idling, recent studies have demonstrated that α oscillations play a causal role in cognition and perception. However, whether and how cognitive or sensory processes modulate various components of the α rhythm is poorly understood. Sensory input and resting states were manipulated in human subjects while electroencephalography (EEG) activity was recorded in three conditions: eyes-open fixating on a visual stimulus, eyes-open without visual input (darkness), and eyes-closed without visual input (darkness). We show that α power and peak frequency increase when visual input is reduced compared to the eyes open, fixating condition. These results …
The Interaction Of Attention And Memory On The Reorienting Negativity, John C. Moses
The Interaction Of Attention And Memory On The Reorienting Negativity, John C. Moses
Dissertations, Theses, and Capstone Projects
The three-stage model of distraction asserts that when we are presented with salient but task-irrelevant information, our sensory systems first detect the distracting stimulus by way of sensory memory buffers, which is indicated electrophysiologically by the mismatch negativity (MMN). Following detection, attentional resources are involuntarily allocated towards the processing of the distraction, as represented by the P3a. Finally, attentional resources are shifted away from the distracting stimulus and returned to the task-relevant information, as indicated by the reorienting negativity (RON). A great deal of research has focused on this last step in the model, largely centering around defining the mechanisms …
Visual Entrainment Of Perception-Related Neural Oscillations As A Mechanism For Maintaining Rhythmic Temporal Expectations Across A Wide Range Of Frequencies, Michael James Gray
Visual Entrainment Of Perception-Related Neural Oscillations As A Mechanism For Maintaining Rhythmic Temporal Expectations Across A Wide Range Of Frequencies, Michael James Gray
Dissertations, Theses, and Capstone Projects
Visual sensitivity fluctuates rhythmically, in-synch with ongoing, EEG-recorded neural oscillations across a wide range of frequencies (~1-25hz). Some recent work has suggested that these perception-related neural oscillations can be entrained by rhythmic visual stimulation. Evidence is also emerging that the entrainment of ongoing oscillations in visual and auditory cortices is involved in rhythmic temporal expectations. In the introduction chapter, I attempt to bridge these bodies of literature and hypothesize that rhythmic visual stimuli automatically entrain ongoing, perception-related neural oscillations and that this mechanism supports the maintenance of rhythmic temporal expectations. Chapters 2 and 3 address this hypothesis from different angles. …
Alpha Oscillations And Feedback Processing In Visual Cortex For Conscious Perception, Tony Ro
Alpha Oscillations And Feedback Processing In Visual Cortex For Conscious Perception, Tony Ro
Publications and Research
Variability in perception between individuals may be a consequence of different inherent neural processing speeds. To assess whether alpha oscillations systematically reflect a feedback pacing mechanism for cortical processing during visual perception, comparisons were made between alpha oscillations, visual suppression from TMS, visual evoked responses, and metacontrast masking. Peak alpha oscillation frequencies, measured through scalp EEG recordings, significantly correlated with the optimum latencies for visual suppression from TMS of early visual cortex. Individuals with shorter alpha periods (i.e., higher peak alpha frequencies) processed visual information faster than those with longer alpha periods (i.e., lower peak alpha frequencies). Moreover, peak alpha …
A Defense Of Pure Connectionism, Alex B. Kiefer
A Defense Of Pure Connectionism, Alex B. Kiefer
Dissertations, Theses, and Capstone Projects
Connectionism is an approach to neural-networks-based cognitive modeling that encompasses the recent deep learning movement in artificial intelligence. It came of age in the 1980s, with its roots in cybernetics and earlier attempts to model the brain as a system of simple parallel processors. Connectionist models center on statistical inference within neural networks with empirically learnable parameters, which can be represented as graphical models. More recent approaches focus on learning and inference within hierarchical generative models. Contra influential and ongoing critiques, I argue in this dissertation that the connectionist approach to cognitive science possesses in principle (and, as is becoming …