Title
Sensory representation spaces in neuroscience and computation
Abstract
Physics, Neuroscience and Computation are concerned with finding the most appropriate representation spaces to describe the interaction of a dynamic system with its environment. In this work first we review the two basic conceptual approaches to the problem of representing an environment, Marr's ascending ''constructivism'' and Gibson's ''direct perception'' hypothesis. Later we review the basic neural mechanisms associated with creating meaning in both approaches: lateral inhibition and the creation of cortical maps by resonance to patterns of stimuli of families of spatially ordered neurons. We end by considering the usefulness in artificial intelligence of knowledge about the way in which biological systems construct their representation spaces. We stress the idea regarding events as representation entities and, consequently, using an event time, different from physical time. Semantics emerges from the mechanisms that detect these relevant events in each organisational level and their composition rules to specify the constitutive entities of the next level. This semantic is distributed in the cortical maps of the neuron groups that resound to the corresponding events.
Year
DOI
Venue
2009
10.1016/j.neucom.2008.04.054
Neurocomputing
Keywords
Field
DocType
perception,lateral inhibition,dynamic system,semantic gap,biological systems,artificial intelligent
Constructivism (philosophy of education),Neuroscience,Computer science,Semantic gap,Lateral inhibition,Artificial intelligence,Sensory system,Perception,Machine learning,Semantics,Computation
Journal
Volume
Issue
ISSN
72
4-6
0925-2312
Citations 
PageRank 
References 
0
0.34
4
Authors
2
Name
Order
Citations
PageRank
José Mira154371.44
Ana E. Delgado224316.85