Linking structure and function: Information processing in the brain
Abstract
Traditionally, theories of function in neuroscience have emerged from physiology. Physiologists have suggested a number of means by which information in the brain can be processed, yet the principles underlying the generation of these phenomena are not well understood. A complex systems approach would be to examine the overall structure and function of the system and to attempt to establish a common framework for information processing interactions. This paper will use the structure-function relationship as a basis for exploring units of information processing. It will examine the brain as a whole, first providing the non-specialists with an short overview of the structure and some of the functions or outputs of the brain. It then very briefly reviews three of the prominent theoretical concepts that have emerged in the last few decades: receptive fields, feature extraction, and parallel processing. Next, it addresses the question of information processing and outlines the structures which have traditionally been proposed to be the basic unit of information processing. An alternative unit on which information processing in the brain might be based is then proposed, and data outlined to support it. Finally, the implications of this different mode of processing are discussed, both for the brainmore »
- Authors:
- Publication Date:
- Research Org.:
- Los Alamos National Lab., NM (USA)
- Sponsoring Org.:
- USDOE; USDOE, Washington, DC (USA)
- OSTI Identifier:
- 6056889
- Report Number(s):
- LA-UR-91-829; CONF-9006299-
ON: DE91009946
- DOE Contract Number:
- W-7405-ENG-36
- Resource Type:
- Conference
- Resource Relation:
- Conference: 1990 Santa Fe Institute summer school on complex systems, Santa Fe, NM (USA), 12-16 Jun 1990
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; BRAIN; STRUCTURE-ACTIVITY RELATIONSHIPS; BEHAVIOR; BIOLOGICAL FUNCTIONS; MOLECULAR STRUCTURE; BODY; CENTRAL NERVOUS SYSTEM; FUNCTIONS; NERVOUS SYSTEM; ORGANS; 551000* - Physiological Systems
Citation Formats
Gremillion, M A.V. Linking structure and function: Information processing in the brain. United States: N. p., 1990.
Web.
Gremillion, M A.V. Linking structure and function: Information processing in the brain. United States.
Gremillion, M A.V. 1990.
"Linking structure and function: Information processing in the brain". United States.
@article{osti_6056889,
title = {Linking structure and function: Information processing in the brain},
author = {Gremillion, M A.V.},
abstractNote = {Traditionally, theories of function in neuroscience have emerged from physiology. Physiologists have suggested a number of means by which information in the brain can be processed, yet the principles underlying the generation of these phenomena are not well understood. A complex systems approach would be to examine the overall structure and function of the system and to attempt to establish a common framework for information processing interactions. This paper will use the structure-function relationship as a basis for exploring units of information processing. It will examine the brain as a whole, first providing the non-specialists with an short overview of the structure and some of the functions or outputs of the brain. It then very briefly reviews three of the prominent theoretical concepts that have emerged in the last few decades: receptive fields, feature extraction, and parallel processing. Next, it addresses the question of information processing and outlines the structures which have traditionally been proposed to be the basic unit of information processing. An alternative unit on which information processing in the brain might be based is then proposed, and data outlined to support it. Finally, the implications of this different mode of processing are discussed, both for the brain and for other complex systems. 40 refs., 4 figs., 2 tabs.},
doi = {},
url = {https://www.osti.gov/biblio/6056889},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Jan 01 00:00:00 EST 1990},
month = {Mon Jan 01 00:00:00 EST 1990}
}