---
abstract: 'This paper shows how the relationship between two arrays of artificial neurons, representing different cortical regions, can be learned. The algorithm enables each neural network to self-organise into a topological map of the domain it represents at the same time as the relationship between these maps is found. Unlike previous methods learning is achieved without a separate training phase; the algorithm which learns the mapping is also that which performs the mapping.'
altloc: []
chapter: ~
commentary: ~
commref: ~
confdates: 1998
conference: 6th European Symposium on Artificial Neural Networks (ESANN98)
confloc: Brugges
contact_email: ~
creators_id: []
creators_name:
- family: Spratling
given: Michael
honourific: ''
lineage: ''
- family: Hayes
given: Gillian
honourific: ''
lineage: ''
date: 1998
date_type: published
datestamp: 2000-11-15
department: ~
dir: disk0/00/00/11/06
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editors_id: []
editors_name: []
eprint_status: archive
eprintid: 1106
fileinfo: /style/images/fileicons/application_postscript.png;/1106/2/cort_map.ps
full_text_status: public
importid: ~
institution: ~
isbn: ~
ispublished: pub
issn: ~
item_issues_comment: []
item_issues_count: 0
item_issues_description: []
item_issues_id: []
item_issues_reported_by: []
item_issues_resolved_by: []
item_issues_status: []
item_issues_timestamp: []
item_issues_type: []
keywords: 'sensorimotor control, neural networks'
lastmod: 2011-03-11 08:54:26
latitude: ~
longitude: ~
metadata_visibility: show
note: ~
number: ~
pagerange: 339-344
pubdom: FALSE
publication: ~
publisher: ~
refereed: TRUE
referencetext: ~
relation_type: []
relation_uri: []
reportno: ~
rev_number: 10
series: ~
source: ~
status_changed: 2007-09-12 16:36:24
subjects:
- comp-sci-neural-nets
- comp-sci-robot
- neuro-mod
succeeds: ~
suggestions: ~
sword_depositor: ~
sword_slug: ~
thesistype: ~
title: Learning sensory-motor cortical mappings without training
type: confpaper
userid: 1040
volume: ~