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      Neurophenomenal structuralism. A philosophical agenda for a structuralist neuroscience of consciousness

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          Abstract

          The program of “neurophenomenal structuralism” is presented as an agenda for a genuine structuralist neuroscience of consciousness that seeks to understand specific phenomenal experiences as strictly relational affairs. The paper covers a broad range of topics. It starts from considerations about neural change detection and relational coding that motivate a solution of the Newman problem of the brain in terms of spatiotemporal relations. Next, phenomenal quality spaces and their Q-structures are discussed. Neurophenomenal structuralism proclaims a homomorphic mapping of the structures of self-organized neural maps in the brain onto Q-structures, and it will be demonstrated how this leads to a new and special version of structural representationalism about phenomenal content. A methodological implication of neurophenomenal structuralism is that it proposes measurement procedures that focus on the relationships between different stimuli (as, for instance, similarity ratings or representational geometry methods). Finally, it will be shown that neurophenomenal structuralism also has strong philosophical implications, as it leads to holism about phenomenal experiences and serves to reject inverted qualia scenarios.

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          Most cited references103

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          Representational Similarity Analysis – Connecting the Branches of Systems Neuroscience

          A fundamental challenge for systems neuroscience is to quantitatively relate its three major branches of research: brain-activity measurement, behavioral measurement, and computational modeling. Using measured brain-activity patterns to evaluate computational network models is complicated by the need to define the correspondency between the units of the model and the channels of the brain-activity data, e.g., single-cell recordings or voxels from functional magnetic resonance imaging (fMRI). Similar correspondency problems complicate relating activity patterns between different modalities of brain-activity measurement (e.g., fMRI and invasive or scalp electrophysiology), and between subjects and species. In order to bridge these divides, we suggest abstracting from the activity patterns themselves and computing representational dissimilarity matrices (RDMs), which characterize the information carried by a given representation in a brain or model. Building on a rich psychological and mathematical literature on similarity analysis, we propose a new experimental and data-analytical framework called representational similarity analysis (RSA), in which multi-channel measures of neural activity are quantitatively related to each other and to computational theory and behavior by comparing RDMs. We demonstrate RSA by relating representations of visual objects as measured with fMRI in early visual cortex and the fusiform face area to computational models spanning a wide range of complexities. The RDMs are simultaneously related via second-level application of multidimensional scaling and tested using randomization and bootstrap techniques. We discuss the broad potential of RSA, including novel approaches to experimental design, and argue that these ideas, which have deep roots in psychology and neuroscience, will allow the integrated quantitative analysis of data from all three branches, thus contributing to a more unified systems neuroscience.
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            Self-organized formation of topologically correct feature maps

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              Integrated information theory: from consciousness to its physical substrate.

              In this Opinion article, we discuss how integrated information theory accounts for several aspects of the relationship between consciousness and the brain. Integrated information theory starts from the essential properties of phenomenal experience, from which it derives the requirements for the physical substrate of consciousness. It argues that the physical substrate of consciousness must be a maximum of intrinsic cause-effect power and provides a means to determine, in principle, the quality and quantity of experience. The theory leads to some counterintuitive predictions and can be used to develop new tools for assessing consciousness in non-communicative patients.
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                Author and article information

                Contributors
                Journal
                Neurosci Conscious
                Neurosci Conscious
                nconsc
                Neuroscience of Consciousness
                Oxford University Press (UK )
                2057-2107
                2022
                23 August 2022
                23 August 2022
                : 2022
                : 1 , Special Issue: Consciousness science and its theories
                : niac012
                Affiliations
                departmentChair for Theoretical Philosophy, University of Magdeburg , Magdeburg, Germany
                departmentCenter for Behavioral Brain Sciences (CBBS), University of Magdeburg , Magdeburg, Germany
                departmentResearch Training Group 2386 “Extrospection”, Humboldt-Universität zu Berlin , Berlin, Germany
                Author notes
                *Correspondence address. Lehrstuhl für Theoretische Philosophie, Otto-von-Guericke-Universität Magdeburg, Universitätsplatz 2, Magdeburg D-39106, Germany. Email: lyre@ 123456ovgu.de
                Author information
                https://orcid.org/0000-0002-6040-0263
                Article
                niac012
                10.1093/nc/niac012
                9396309
                36004320
                a9525f7d-ba76-4c15-b959-48e393480b93
                © The Author(s) 2022. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 03 March 2022
                : 04 July 2022
                : 27 July 2022
                : 20 July 2022
                : 23 August 2022
                Page count
                Pages: 18
                Funding
                Funded by: Deutsche Forschungsgemeinschaft, DOI 10.13039/501100001659;
                Award ID: RTG 2386, DFG Förderkennzeichen 337619223
                Categories
                Research Article
                AcademicSubjects/SCI01870
                AcademicSubjects/SCI01880
                AcademicSubjects/SCI01950
                AcademicSubjects/SCI02120
                AcademicSubjects/SCI02139

                quality spaces,structural similarity,newman problem,structural representation,self-organized neural maps,neurophenomenal holism,structural qualia,qualia inversion

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