Pub Date : 1900-01-01DOI: 10.32470/ccn.2022.1304-0
Xue L Gong, Alexander G. Huth, F. Theunissen
{"title":"Phonemic representation of narrative speech in human cerebral cortex","authors":"Xue L Gong, Alexander G. Huth, F. Theunissen","doi":"10.32470/ccn.2022.1304-0","DOIUrl":"https://doi.org/10.32470/ccn.2022.1304-0","url":null,"abstract":"","PeriodicalId":341186,"journal":{"name":"2022 Conference on Cognitive Computational Neuroscience","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130268194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.32470/ccn.2022.1123-0
Oren Kobo, Y. Yeshurun, T. Schonberg
{"title":"Studying the Involvement of the Reward System in Language Processing","authors":"Oren Kobo, Y. Yeshurun, T. Schonberg","doi":"10.32470/ccn.2022.1123-0","DOIUrl":"https://doi.org/10.32470/ccn.2022.1123-0","url":null,"abstract":"","PeriodicalId":341186,"journal":{"name":"2022 Conference on Cognitive Computational Neuroscience","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122130423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.32470/ccn.2022.1034-0
Binxu Wang, Carlos R. Ponce
{"title":"Factorized convolution models for interpreting neuron-guided images synthesis","authors":"Binxu Wang, Carlos R. Ponce","doi":"10.32470/ccn.2022.1034-0","DOIUrl":"https://doi.org/10.32470/ccn.2022.1034-0","url":null,"abstract":"","PeriodicalId":341186,"journal":{"name":"2022 Conference on Cognitive Computational Neuroscience","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127573553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.32470/ccn.2022.1092-0
Lukas Neugebauer, C. Büchel
{"title":"Neural Correlates of Model-Based Generalization","authors":"Lukas Neugebauer, C. Büchel","doi":"10.32470/ccn.2022.1092-0","DOIUrl":"https://doi.org/10.32470/ccn.2022.1092-0","url":null,"abstract":"","PeriodicalId":341186,"journal":{"name":"2022 Conference on Cognitive Computational Neuroscience","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125794684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.32470/ccn.2022.1311-0
Maëlle Freteault, B. Pinsard, Julie Boyle, Pierre Bellec, Nicolas Farrugia
{"title":"Using Massive Individual fMRI Movie Data to Align Artificial and Brain Representations in an Auditory Network","authors":"Maëlle Freteault, B. Pinsard, Julie Boyle, Pierre Bellec, Nicolas Farrugia","doi":"10.32470/ccn.2022.1311-0","DOIUrl":"https://doi.org/10.32470/ccn.2022.1311-0","url":null,"abstract":"","PeriodicalId":341186,"journal":{"name":"2022 Conference on Cognitive Computational Neuroscience","volume":"37 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123065560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.32470/ccn.2022.1180-0
Jong-Chun Lim, Sungbeen Park, Sungshin Kim
{"title":"A goal-driven Deep Reinforcement Learning Model Predicts Neural Representations Related to Human Visuomotor Control","authors":"Jong-Chun Lim, Sungbeen Park, Sungshin Kim","doi":"10.32470/ccn.2022.1180-0","DOIUrl":"https://doi.org/10.32470/ccn.2022.1180-0","url":null,"abstract":"","PeriodicalId":341186,"journal":{"name":"2022 Conference on Cognitive Computational Neuroscience","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129450640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.32470/ccn.2022.1126-0
Fabian M. Renz, Shany Grossman, P. Dayan, Christian F. Doeller, Nicolas W. Schuck
: Cognitive maps represent relational structures and are taken to be important for generalization and optimal decision making in spatial as well as non-spatial domains. While many studies have investigated the benefits of cognitive maps, how these maps are learned from experience has remained less clear. We introduce a new graph-structured sequence task to better understand how cognitive maps are learned. Participants observed sequences of episodes followed by a reward, thereby learning about the underlying transition structure and fluctuating reward contingencies. Importantly, the task structure allowed participants to generalize value from some episode sequences to others, and generalizability was either signaled by episode similarity or had to be inferred more indirectly. Behavioral data demonstrated participants ` ability to learn about signaled and unsignaled generalizability with different speed, indicating that the formation of cognitive maps partially relies on exploiting observable similarities across episodes. We hypothesize that a possible neural mechanism involved in learning cognitive maps as described here is experience replay.
{"title":"Representation learning facilitates different levels of generalization","authors":"Fabian M. Renz, Shany Grossman, P. Dayan, Christian F. Doeller, Nicolas W. Schuck","doi":"10.32470/ccn.2022.1126-0","DOIUrl":"https://doi.org/10.32470/ccn.2022.1126-0","url":null,"abstract":": Cognitive maps represent relational structures and are taken to be important for generalization and optimal decision making in spatial as well as non-spatial domains. While many studies have investigated the benefits of cognitive maps, how these maps are learned from experience has remained less clear. We introduce a new graph-structured sequence task to better understand how cognitive maps are learned. Participants observed sequences of episodes followed by a reward, thereby learning about the underlying transition structure and fluctuating reward contingencies. Importantly, the task structure allowed participants to generalize value from some episode sequences to others, and generalizability was either signaled by episode similarity or had to be inferred more indirectly. Behavioral data demonstrated participants ` ability to learn about signaled and unsignaled generalizability with different speed, indicating that the formation of cognitive maps partially relies on exploiting observable similarities across episodes. We hypothesize that a possible neural mechanism involved in learning cognitive maps as described here is experience replay.","PeriodicalId":341186,"journal":{"name":"2022 Conference on Cognitive Computational Neuroscience","volume":"169 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133006078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 1900-01-01DOI: 10.32470/ccn.2022.1044-0
Zhe-Xin Xu, G. DeAngelis
{"title":"Contextual Influences on the Perception of Motion and Depth","authors":"Zhe-Xin Xu, G. DeAngelis","doi":"10.32470/ccn.2022.1044-0","DOIUrl":"https://doi.org/10.32470/ccn.2022.1044-0","url":null,"abstract":"","PeriodicalId":341186,"journal":{"name":"2022 Conference on Cognitive Computational Neuroscience","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129078408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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