Published July 14, 2021 | Version public
Book Section - Chapter

Topological Model of Neural Information Networks

  • 1. ROR icon California Institute of Technology

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.

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.

Additional details

Identifiers

Eprint ID
112640
DOI
10.1007/978-3-030-80209-7_67
Resolver ID
CaltechAUTHORS:20211222-457136400

Related works

Funding

Foundational Questions Institute (FQXI)
FQXi-RFP-1804
Silicon Valley Community Foundation
2018-190467
Foundational Questions Institute (FQXI)
RFP-CPW-2014
Silicon Valley Community Foundation
2020-224047
Fetzer Franklin Fund

Dates

Created
2021-12-22
Created from EPrint's datestamp field
Updated
2021-12-22
Created from EPrint's last_modified field

Caltech Custom Metadata

Caltech groups
Mathematics Department
Series Name
Lecture Notes in Computer Science
Series Volume or Issue Number
12829