TY - JOUR
T1 - Representational systems
AU - Fekete, Tomer
N1 - Funding Information:
Acknowledgments The author wishes to thank Neta Zach, Shimon Edelman, Steve Farkas and Uri Liron for their meticulous reading of earlier versions of this manuscript, and Itamar Pitowsky and Amiram Grinvald for their help and support. This work was supported by the Weizmann Institute of Science, Rehovot, Israel, and the Interdisciplinary center of Neural Computation, the Hebrew university, Jerusalem.
PY - 2010/2/1
Y1 - 2010/2/1
N2 - The concept of representation has been a key element in the scientific study of mental processes, ever since such studies commenced. However, usage of the term has been all but too liberal-if one were to adhere to common use it remains unclear if there are examples of physical systems which cannot be construed in terms of representation. The problem is considered afresh, taking as the starting point the notion of activity spaces-spaces of spatiotemporal events produced by dynamical systems. It is argued that representation can be analyzed in terms of the geometrical and topological properties of such spaces. Several attributes and processes associated with conceptual domains, such as logical structure, generalization and learning are considered, and given analogues in structural facets of activity spaces, as are misrepresentation and states of arousal. Based on this analysis, representational systems are defined, as is a key concept associated with such systems, the notion of representational capacity. According to the proposed theory, rather than being an all or none phenomenon, representation is in fact a matter of degree-that is can be associated with measurable quantities, as is behooving of a putative naturalistic construct.
AB - The concept of representation has been a key element in the scientific study of mental processes, ever since such studies commenced. However, usage of the term has been all but too liberal-if one were to adhere to common use it remains unclear if there are examples of physical systems which cannot be construed in terms of representation. The problem is considered afresh, taking as the starting point the notion of activity spaces-spaces of spatiotemporal events produced by dynamical systems. It is argued that representation can be analyzed in terms of the geometrical and topological properties of such spaces. Several attributes and processes associated with conceptual domains, such as logical structure, generalization and learning are considered, and given analogues in structural facets of activity spaces, as are misrepresentation and states of arousal. Based on this analysis, representational systems are defined, as is a key concept associated with such systems, the notion of representational capacity. According to the proposed theory, rather than being an all or none phenomenon, representation is in fact a matter of degree-that is can be associated with measurable quantities, as is behooving of a putative naturalistic construct.
KW - Computation and mind
KW - Computational neuroscience
KW - Conceptual representation
KW - Curvature
KW - Geometry
KW - Homology
KW - Isomorphism
KW - Learning
KW - Misrepresentation
KW - Persistent homology
KW - Representation
KW - Representational capacity
KW - Similarity
KW - States of consciousness
KW - Topology
UR - http://www.scopus.com/inward/record.url?scp=77950019386&partnerID=8YFLogxK
U2 - 10.1007/s11023-009-9166-2
DO - 10.1007/s11023-009-9166-2
M3 - Article
AN - SCOPUS:77950019386
SN - 0924-6495
VL - 20
SP - 69
EP - 101
JO - Minds and Machines
JF - Minds and Machines
IS - 1
ER -