{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/152579"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/152579","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Predictive Novelty Detection in Songbird Auditory Cortex","abstract":"In order to make sense of complicated sensory landscapes, the brain privileges the processing of novel stimuli. Detecting novelty is therefore a fundamental problem for the brain to solve. And it turns out to be complicated, as stimuli can be completely novel, or just novel relative to certain certain contexts or expectations. To better understand how the brain detects both types of novelty, we studied an auditory region of the avian brain that performs both absolute and relative novelty detection. We introduce a predictive model, called the Agnotron, that is capable of performing both kinds of novelty detection with the same circuit mechanism. Armed with predictions made by the Agnotron, we perform experiments to confirm the existence of Agnotron-like circuitry in the brain. While we fail to find evidence that the various novelty signals in this brain area are produced by the same mechanism, we do find support for predictive circuitry for some novelty signals. We continue with an advanced investigation of one absolute novelty signal in particular, known as the Song-Specific Adaptation. After recapitulating classical results with state-of-the-art technology, we report novel phenomena that rule out predictive circuit mechanisms for the SSA. Taken together, our results suggest that predictive mechanisms can explain some novelty signals in the avian brain, but not the SSA, which seems to have a more simplistic feed-forward mechanism of generation.","abstract_html":"In order to make sense of complicated sensory landscapes, the brain privileges the processing of novel stimuli. Detecting novelty is therefore a fundamental problem for the brain to solve. And it turns out to be complicated, as stimuli can be completely novel, or just novel relative to certain certain contexts or expectations. To better understand how the brain detects both types of novelty, we studied an auditory region of the avian brain that performs both absolute and relative novelty detection. We introduce a predictive model, called the Agnotron, that is capable of performing both kinds of novelty detection with the same circuit mechanism. Armed with predictions made by the Agnotron, we perform experiments to confirm the existence of Agnotron-like circuitry in the brain. While we fail to find evidence that the various novelty signals in this brain area are produced by the same mechanism, we do find support for predictive circuitry for some novelty signals. We continue with an advanced investigation of one absolute novelty signal in particular, known as the Song-Specific Adaptation. After recapitulating classical results with state-of-the-art technology, we report novel phenomena that rule out predictive circuit mechanisms for the SSA. Taken together, our results suggest that predictive mechanisms can explain some novelty signals in the avian brain, but not the SSA, which seems to have a more simplistic feed-forward mechanism of generation.","abstract_has_math":false,"creators":["Happ, Michael Liu"],"institution":"Massachusetts Institute of Technology","degree_name":"Doctoral","degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences","school":null,"contributors":[],"advisors":["Fee, Michale S."],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-06","date_published":"2023-06","updated_at":"2026-07-22T22:22:07Z","subjects":[],"languages":[],"rights":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"],"rights_urls":["https://rightsstatements.org/page/InC-EDU/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/1721.1/152579","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Fee, Michale S."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. 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Detecting novelty is therefore a fundamental problem for the brain to solve. And it turns out to be complicated, as stimuli can be completely novel, or just novel relative to certain certain contexts or expectations. To better understand how the brain detects both types of novelty, we studied an auditory region of the avian brain that performs both absolute and relative novelty detection. We introduce a predictive model, called the Agnotron, that is capable of performing both kinds of novelty detection with the same circuit mechanism. Armed with predictions made by the Agnotron, we perform experiments to confirm the existence of Agnotron-like circuitry in the brain. While we fail to find evidence that the various novelty signals in this brain area are produced by the same mechanism, we do find support for predictive circuitry for some novelty signals. We continue with an advanced investigation of one absolute novelty signal in particular, known as the Song-Specific Adaptation. After recapitulating classical results with state-of-the-art technology, we report novel phenomena that rule out predictive circuit mechanisms for the SSA. Taken together, our results suggest that predictive mechanisms can explain some novelty signals in the avian brain, but not the SSA, which seems to have a more simplistic feed-forward mechanism of generation."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph.D."]},{"key":"dc:title","label":"Title","values":["Predictive Novelty Detection in Songbird Auditory Cortex"]}]}],"canonical_facts":{"dc:contributor.advisor":["Fee, Michale S."],"dc:contributor.department":["Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences"],"dc:creator":["Happ, Michael Liu"],"dc:date.accessioned":["2023-10-30T20:04:23Z"],"dc:date.available":["2023-10-30T20:04:23Z"],"dc:date.issued":["2023-06"],"dc:description.abstract":["In order to make sense of complicated sensory landscapes, the brain privileges the processing of novel stimuli. Detecting novelty is therefore a fundamental problem for the brain to solve. And it turns out to be complicated, as stimuli can be completely novel, or just novel relative to certain certain contexts or expectations. To better understand how the brain detects both types of novelty, we studied an auditory region of the avian brain that performs both absolute and relative novelty detection. We introduce a predictive model, called the Agnotron, that is capable of performing both kinds of novelty detection with the same circuit mechanism. Armed with predictions made by the Agnotron, we perform experiments to confirm the existence of Agnotron-like circuitry in the brain. While we fail to find evidence that the various novelty signals in this brain area are produced by the same mechanism, we do find support for predictive circuitry for some novelty signals. We continue with an advanced investigation of one absolute novelty signal in particular, known as the Song-Specific Adaptation. After recapitulating classical results with state-of-the-art technology, we report novel phenomena that rule out predictive circuit mechanisms for the SSA. Taken together, our results suggest that predictive mechanisms can explain some novelty signals in the avian brain, but not the SSA, which seems to have a more simplistic feed-forward mechanism of generation."],"dc:description.degree":["Ph.D."],"dc:identifier.uri":["https://hdl.handle.net/1721.1/152579"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["In Copyright - Educational Use Permitted","Copyright retained by author(s)"],"dc:rights.uri":["https://rightsstatements.org/page/InC-EDU/1.0/"],"dc:title":["Predictive Novelty Detection in Songbird Auditory Cortex"],"dc:type":["Thesis"],"thesis:degree_name":["Doctoral","Doctor of Philosophy"]},"updated_at":"2026-07-22T22:22:07Z"}