{"id":{"repo_id":"denver","oai_identifier":"oai:digitalcommons.du.edu:etd-2966"},"canonical_url":"https://search.dev.ndltd.org/etd/denver/oai:digitalcommons.du.edu:etd-2966","repository":{"repo_id":"denver","name":"University of Denver","base_url":"https://digitalcommons.du.edu/do/oai/"},"display":{"title":"Mechanisms of Sensory Adaptation in the Primate Visual System","abstract":"<p>Under ecological conditions, the luminance impinging on the retina varies within a dynamic range of 220 dB. Stimulus contrast can also vary drastically within a scene, and eye movements leave little time for sampling luminance. In addition, the amount of information reaching our visual system far exceeds the brain’s information processing capacity. Given the limited dynamic range of its neurons and its limited capacity in processing visual information in real-time, the brain deploys both structural and functional solutions that work in tandem to adapt to the surroundings. In this work, employing visual psychophysics and computational neuroscience, we study the mechanisms by which the brain adapts to the sensory signals that it encounters in the natural environment. We found that the processes underlying motion perception in ecological vision are mediated by an adaptive center-surround mechanism that trade-offs spatiotemporal resolution for signal enhancement when the signal is weak. We proposed a new dynamic neural network that can account for adaptive properties of motion integration and segregation under various luminance and contrast conditions. Finally, in order to clarify the implications of attentional mechanisms deployed to select inputs according to the brain’s processing resources, we tested the predictions of a neural model and showed that competitive interactions between parvocellular and magnocellular systems can explain the differential effects of attention on spatial and temporal acuity. This dissertation's results contribute to the important work of reverse-engineering the human brain, with potential clinical and engineering applications.</p>","abstract_html":"&lt;p&gt;Under ecological conditions, the luminance impinging on the retina varies within a dynamic range of 220 dB. Stimulus contrast can also vary drastically within a scene, and eye movements leave little time for sampling luminance. In addition, the amount of information reaching our visual system far exceeds the brain’s information processing capacity. Given the limited dynamic range of its neurons and its limited capacity in processing visual information in real-time, the brain deploys both structural and functional solutions that work in tandem to adapt to the surroundings. In this work, employing visual psychophysics and computational neuroscience, we study the mechanisms by which the brain adapts to the sensory signals that it encounters in the natural environment. We found that the processes underlying motion perception in ecological vision are mediated by an adaptive center-surround mechanism that trade-offs spatiotemporal resolution for signal enhancement when the signal is weak. We proposed a new dynamic neural network that can account for adaptive properties of motion integration and segregation under various luminance and contrast conditions. Finally, in order to clarify the implications of attentional mechanisms deployed to select inputs according to the brain’s processing resources, we tested the predictions of a neural model and showed that competitive interactions between parvocellular and magnocellular systems can explain the differential effects of attention on spatial and temporal acuity. This dissertation&#x27;s results contribute to the important work of reverse-engineering the human brain, with potential clinical and engineering applications.&lt;/p&gt;","abstract_has_math":false,"creators":["Peñaloza Rojas, Boris Isaac"],"institution":null,"degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Haluk Öğmen","Timothy Sweeny","Mohammad Mahoor","Kimon Valavanis"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2021,"date_issued":"2021-01-01T08:00:00Z","date_published":"2021-01-01T08:00:00Z","updated_at":"2026-07-24T02:02:38Z","subjects":["Computational neuroscience","Dynamic-range","Psychophysics","Spatial attention","Biomedical","Electrical and Computer Engineering","Engineering","Neurology","Other Electrical and Computer Engineering","Other Psychology","Psychology"],"languages":["en"],"rights":["<p>Copyright is held by the author. 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In this work, employing visual psychophysics and computational neuroscience, we study the mechanisms by which the brain adapts to the sensory signals that it encounters in the natural environment. We found that the processes underlying motion perception in ecological vision are mediated by an adaptive center-surround mechanism that trade-offs spatiotemporal resolution for signal enhancement when the signal is weak. We proposed a new dynamic neural network that can account for adaptive properties of motion integration and segregation under various luminance and contrast conditions. Finally, in order to clarify the implications of attentional mechanisms deployed to select inputs according to the brain’s processing resources, we tested the predictions of a neural model and showed that competitive interactions between parvocellular and magnocellular systems can explain the differential effects of attention on spatial and temporal acuity. This dissertation's results contribute to the important work of reverse-engineering the human brain, with potential clinical and engineering applications.</p>"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Mechanisms of Sensory Adaptation in the Primate Visual System"]}]}],"canonical_facts":{"dc:contributor":["Haluk Öğmen","Timothy Sweeny","Mohammad Mahoor","Kimon Valavanis"],"dc:creator":["Peñaloza Rojas, Boris Isaac"],"dc:date.available":["2022-02-07T08:00:00Z"],"dc:description.abstract":["<p>Under ecological conditions, the luminance impinging on the retina varies within a dynamic range of 220 dB. Stimulus contrast can also vary drastically within a scene, and eye movements leave little time for sampling luminance. In addition, the amount of information reaching our visual system far exceeds the brain’s information processing capacity. Given the limited dynamic range of its neurons and its limited capacity in processing visual information in real-time, the brain deploys both structural and functional solutions that work in tandem to adapt to the surroundings. In this work, employing visual psychophysics and computational neuroscience, we study the mechanisms by which the brain adapts to the sensory signals that it encounters in the natural environment. We found that the processes underlying motion perception in ecological vision are mediated by an adaptive center-surround mechanism that trade-offs spatiotemporal resolution for signal enhancement when the signal is weak. We proposed a new dynamic neural network that can account for adaptive properties of motion integration and segregation under various luminance and contrast conditions. Finally, in order to clarify the implications of attentional mechanisms deployed to select inputs according to the brain’s processing resources, we tested the predictions of a neural model and showed that competitive interactions between parvocellular and magnocellular systems can explain the differential effects of attention on spatial and temporal acuity. This dissertation's results contribute to the important work of reverse-engineering the human brain, with potential clinical and engineering applications.</p>"],"dc:format":["application/pdf"],"dc:identifier":["https://digitalcommons.du.edu/etd/1973"],"dc:language":["en"],"dc:rights":["<p>Copyright is held by the author. User is responsible for all copyright compliance.</p>"],"dc:subject":["Computational neuroscience","Dynamic-range","Psychophysics","Spatial attention","Biomedical","Electrical and Computer Engineering","Engineering","Neurology","Other Electrical and Computer Engineering","Other Psychology","Psychology"],"dc:title":["Mechanisms of Sensory Adaptation in the Primate Visual System"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."]},"updated_at":"2026-07-24T02:02:38Z"}