Marcolli, Matilde (2021) Topological Model of Neural Information Networks. In: Geometric Science of Information. Lecture Notes in Computer Science. No.12829. Springer , Cham, pp. 623-633. ISBN 9783030802080. https://resolver.caltech.edu/CaltechAUTHORS:20211222-457136400
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Abstract
This is a brief overview of an ongoing research project, involving topological models of neural information networks and the development of new versions of associated information measures that can be seen as possible alternatives to integrated information. Among the goals are a geometric modeling of a “space of qualia” and an associated mechanism that constructs and transforms representations from neural codes topologically. The more mathematical aspects of this project stem from the recent joint work of the author and Yuri Manin [18], while the neuroscience modeling aspects are part of an ongoing collaboration of the author with Doris Tsao.
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Additional Information: | © Springer Nature Switzerland AG 2021. First Online: 14 July 2021. Supported by Foundational Questions Institute and Fetzer Franklin Fund FFF grant number FQXi-RFP-1804, SVCF grant 2018-190467 and FQXi-RFP-CPW-2014, SVCF grant 2020-224047. | ||||||||||||
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Series Name: | Lecture Notes in Computer Science | ||||||||||||
Issue or Number: | 12829 | ||||||||||||
DOI: | 10.1007/978-3-030-80209-7_67 | ||||||||||||
Record Number: | CaltechAUTHORS:20211222-457136400 | ||||||||||||
Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20211222-457136400 | ||||||||||||
Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||||||||
ID Code: | 112640 | ||||||||||||
Collection: | CaltechAUTHORS | ||||||||||||
Deposited By: | Tony Diaz | ||||||||||||
Deposited On: | 22 Dec 2021 21:52 | ||||||||||||
Last Modified: | 22 Dec 2021 21:52 |
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