{"id":{"repo_id":"toronto-retro","oai_identifier":"oai:utoronto.scholaris.ca:1807/97780"},"canonical_url":"https://search.dev.ndltd.org/etd/toronto-retro/oai:utoronto.scholaris.ca:1807/97780","repository":{"repo_id":"toronto-retro","name":"University of Toronto","base_url":"https://utoronto.scholaris.ca/server/oai/request"},"display":{"title":"It’s Not Simple: Brain Signal Complexity as an Index of Neural Information Processing Described via Music Perception, Complexity and Reward","abstract":"The dynamic, integrated, network activity that underlies higher cognition produces complex brain signals with information at multiple timescales. The present body of work represents an effort to demonstrate that brain signal complexity can be an indicator of the information integration in the brain that supports cognition and behaviour. Study 1 establishes that magnetoencephalography signal complexity is higher in adult musicians compared to non-musicians. The difference in complexity between groups was largest in a music note perception task, which also showed the largest behavioural difference between groups. Study 2 extends this approach to a longitudinal study of music training in preschool-aged children. Higher electroencephalography signal complexity was observed in a passive music note perception task following training in brain regions typically implicated in music perception (e.g. superior temporal cortex), as well as supramodal regions (precuneus, superior parietal cortex). Therefore, we suggest that network information processing capacity increases with experience to support concomitant increases in behavioural capacity. Studies 3 and 4 examine how the information inherent in music stimuli is represented as neural information, and how this relates to behavioural outcomes. We calculated the complexity of the song and compare it to the complexity of the signals from the listening brain. We found that the information content of brain signals more closely matches that of the auditory environment when participants were attending to the acoustics of the music, compared to when they were attending to their own emotions induced by music listening. Further examination of this emotional effect in Study 4 revealed that music reward is inversely related to the similarity between internal brain and external music complexities. These results suggest that the information content of the environment can be measured in the brain, and the level of neural ‘mirroring’ is related to the type of cognitive processing conducted. We suggest that emotional experiences are associated with the integration of internal thought processes with perceptual input information.","abstract_html":"The dynamic, integrated, network activity that underlies higher cognition produces complex brain signals with information at multiple timescales. The present body of work represents an effort to demonstrate that brain signal complexity can be an indicator of the information integration in the brain that supports cognition and behaviour. Study 1 establishes that magnetoencephalography signal complexity is higher in adult musicians compared to non-musicians. The difference in complexity between groups was largest in a music note perception task, which also showed the largest behavioural difference between groups. Study 2 extends this approach to a longitudinal study of music training in preschool-aged children. Higher electroencephalography signal complexity was observed in a passive music note perception task following training in brain regions typically implicated in music perception (e.g. superior temporal cortex), as well as supramodal regions (precuneus, superior parietal cortex). Therefore, we suggest that network information processing capacity increases with experience to support concomitant increases in behavioural capacity. Studies 3 and 4 examine how the information inherent in music stimuli is represented as neural information, and how this relates to behavioural outcomes. We calculated the complexity of the song and compare it to the complexity of the signals from the listening brain. We found that the information content of brain signals more closely matches that of the auditory environment when participants were attending to the acoustics of the music, compared to when they were attending to their own emotions induced by music listening. Further examination of this emotional effect in Study 4 revealed that music reward is inversely related to the similarity between internal brain and external music complexities. These results suggest that the information content of the environment can be measured in the brain, and the level of neural ‘mirroring’ is related to the type of cognitive processing conducted. We suggest that emotional experiences are associated with the integration of internal thought processes with perceptual input information.","abstract_has_math":false,"creators":["Carpentier, Sarah McDonough"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Psychology","school":null,"contributors":[],"advisors":["McIntosh, Anthony R"],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-11","date_published":"2018-11","updated_at":"2026-07-27T21:28:22Z","subjects":["brain complexity","information processing","multiscale entropy","music perception","music preferences","reward"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1807/97780","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["McIntosh, Anthony R"]},{"key":"dc:contributor.department","label":"Department","values":["Psychology"]},{"key":"dc:creator","label":"Author","values":["Carpentier, Sarah McDonough"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2018-11"]},{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2019-11-16T05:00:28Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2019-11-16T05:00:28Z"]},{"key":"dc:date.issued","label":"Date","values":["2018-11"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["brain complexity","information processing","multiscale entropy","music perception","music preferences","reward"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1807/97780"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The dynamic, integrated, network activity that underlies higher cognition produces complex brain signals with information at multiple timescales. The present body of work represents an effort to demonstrate that brain signal complexity can be an indicator of the information integration in the brain that supports cognition and behaviour. Study 1 establishes that magnetoencephalography signal complexity is higher in adult musicians compared to non-musicians. The difference in complexity between groups was largest in a music note perception task, which also showed the largest behavioural difference between groups. Study 2 extends this approach to a longitudinal study of music training in preschool-aged children. Higher electroencephalography signal complexity was observed in a passive music note perception task following training in brain regions typically implicated in music perception (e.g. superior temporal cortex), as well as supramodal regions (precuneus, superior parietal cortex). Therefore, we suggest that network information processing capacity increases with experience to support concomitant increases in behavioural capacity. Studies 3 and 4 examine how the information inherent in music stimuli is represented as neural information, and how this relates to behavioural outcomes. We calculated the complexity of the song and compare it to the complexity of the signals from the listening brain. We found that the information content of brain signals more closely matches that of the auditory environment when participants were attending to the acoustics of the music, compared to when they were attending to their own emotions induced by music listening. Further examination of this emotional effect in Study 4 revealed that music reward is inversely related to the similarity between internal brain and external music complexities. These results suggest that the information content of the environment can be measured in the brain, and the level of neural ‘mirroring’ is related to the type of cognitive processing conducted. We suggest that emotional experiences are associated with the integration of internal thought processes with perceptual input information."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph.D."]},{"key":"dc:title","label":"Title","values":["It’s Not Simple: Brain Signal Complexity as an Index of Neural Information Processing Described via Music Perception, Complexity and Reward"]}]}],"canonical_facts":{"dc:contributor.advisor":["McIntosh, Anthony R"],"dc:contributor.department":["Psychology"],"dc:creator":["Carpentier, Sarah McDonough"],"dc:date":["2018-11"],"dc:date.accessioned":["2019-11-16T05:00:28Z"],"dc:date.available":["2019-11-16T05:00:28Z"],"dc:date.issued":["2018-11"],"dc:description.abstract":["The dynamic, integrated, network activity that underlies higher cognition produces complex brain signals with information at multiple timescales. The present body of work represents an effort to demonstrate that brain signal complexity can be an indicator of the information integration in the brain that supports cognition and behaviour. Study 1 establishes that magnetoencephalography signal complexity is higher in adult musicians compared to non-musicians. The difference in complexity between groups was largest in a music note perception task, which also showed the largest behavioural difference between groups. Study 2 extends this approach to a longitudinal study of music training in preschool-aged children. Higher electroencephalography signal complexity was observed in a passive music note perception task following training in brain regions typically implicated in music perception (e.g. superior temporal cortex), as well as supramodal regions (precuneus, superior parietal cortex). Therefore, we suggest that network information processing capacity increases with experience to support concomitant increases in behavioural capacity. Studies 3 and 4 examine how the information inherent in music stimuli is represented as neural information, and how this relates to behavioural outcomes. We calculated the complexity of the song and compare it to the complexity of the signals from the listening brain. We found that the information content of brain signals more closely matches that of the auditory environment when participants were attending to the acoustics of the music, compared to when they were attending to their own emotions induced by music listening. Further examination of this emotional effect in Study 4 revealed that music reward is inversely related to the similarity between internal brain and external music complexities. These results suggest that the information content of the environment can be measured in the brain, and the level of neural ‘mirroring’ is related to the type of cognitive processing conducted. We suggest that emotional experiences are associated with the integration of internal thought processes with perceptual input information."],"dc:description.degree":["Ph.D."],"dc:identifier.uri":["http://hdl.handle.net/1807/97780"],"dc:subject":["brain complexity","information processing","multiscale entropy","music perception","music preferences","reward"],"dc:title":["It’s Not Simple: Brain Signal Complexity as an Index of Neural Information Processing Described via Music Perception, Complexity and Reward"],"dc:type":["Thesis"]},"updated_at":"2026-07-27T21:28:22Z"}