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Using N400-Component for Automatic Thought Identification In a Natural Reading Task

Emilsson, Johan LU (2011) KOGM11 20092
Cognitive Science
Abstract
Recent advances in human brain imaging techniques have shown that it is possible to correctly identify thoughts associated with specific categorises of conceptual knowledge. A semantic space is created through word clustering from a corpus and cross-referenced with words read during a natural reading task while at the same time recording EEG. These results show that it is possible to correctly classify a words category 25% of the time (out of 12 possible categories) based on neural activity within the N400 component with the help of a artifical neural network. Results also visualises the ANN’s black-box behaviour in which electrodes it deem most contributing when classifying. These results contribute to the discussion on how the semantic... (More)
Recent advances in human brain imaging techniques have shown that it is possible to correctly identify thoughts associated with specific categorises of conceptual knowledge. A semantic space is created through word clustering from a corpus and cross-referenced with words read during a natural reading task while at the same time recording EEG. These results show that it is possible to correctly classify a words category 25% of the time (out of 12 possible categories) based on neural activity within the N400 component with the help of a artifical neural network. Results also visualises the ANN’s black-box behaviour in which electrodes it deem most contributing when classifying. These results contribute to the discussion on how the semantic memory is stored in the brain; modularly or connectionisticly, and also how far it is possible to subcategories thoughts and still correctly identify them with brain imagining techniques. (Less)
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author
Emilsson, Johan LU
supervisor
organization
course
KOGM11 20092
year
type
H1 - Master's Degree (One Year)
subject
keywords
EEG, N400, ANN, Artificial Neural Network, Word cluster, PCA, Semantic space, categorisation, reading task
language
English
id
1971007
date added to LUP
2011-06-23 16:25:28
date last changed
2011-06-23 16:25:28
@misc{1971007,
  abstract     = {Recent advances in human brain imaging techniques have shown that it is possible to correctly identify thoughts associated with specific categorises of conceptual knowledge. A semantic space is created through word clustering from a corpus and cross-referenced with words read during a natural reading task while at the same time recording EEG. These results show that it is possible to correctly classify a words category 25% of the time (out of 12 possible categories) based on neural activity within the N400 component with the help of a artifical neural network. Results also visualises the ANN’s black-box behaviour in which electrodes it deem most contributing when classifying. These results contribute to the discussion on how the semantic memory is stored in the brain; modularly or connectionisticly, and also how far it is possible to subcategories thoughts and still correctly identify them with brain imagining techniques.},
  author       = {Emilsson, Johan},
  keyword      = {EEG,N400,ANN,Artificial Neural Network,Word cluster,PCA,Semantic space,categorisation,reading task},
  language     = {eng},
  note         = {Student Paper},
  title        = {Using N400-Component for Automatic Thought Identification In a Natural Reading Task},
  year         = {2011},
}