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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Juyang Weng |
| Copyright Year | 2009 |
| Description | Author affiliation: Michigan State University, East Lansing, USA (Juyang Weng) |
| Abstract | A great mystery is how the brain abstracts during the process of development. It is also unclear how motor actions alter cortical representation. The architecture theory introduced here indicates that for each cortical area, the bottom-up space and top-down space are two sources of its representation — bridge representation which embeds manifolds of both spaces into a single space. A bridge representation has the following properties (a) responses from developed neurons are relatively less sensitive to irrelevant sensory information (i.e., invariants) but are relatively more sensitive to relevant sensory information for classification (i.e., discriminants), (b) neurons form topographic cortical areas according to abstract classes. Both properties transform meaningless (iconic, pixel like) raw sensory inputs into an internal representation with abstract meanings. The most abstract area can be considered as frontal cortex (or motor area if each firing pattern of the motor represents a unique abstract class). Such a cortical representation system is neither a purely symbolic system nor a monolithic meaning system, but is iconic-abstract two-way: bottom-up attention, top-down attention and recognition are all tightly integrated and highly distributed throughout the developmental network. |
| Starting Page | 1 |
| Ending Page | 8 |
| File Size | 2250817 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424441174 |
| DOI | 10.1109/DEVLRN.2009.5175545 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-06-05 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Information science Computational modeling Biological system modeling Buildings Humans Computational and artificial intelligence Cognitive robotics Intelligent systems Intelligent robots Computational intelligence |
| Content Type | Text |
| Resource Type | Article |
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