The discovery of processing stages: analyzing EEG data with hidden semi-Markov models.
Identifieur interne : 000281 ( Main/Exploration ); précédent : 000280; suivant : 000282The discovery of processing stages: analyzing EEG data with hidden semi-Markov models.
Auteurs : Jelmer P. Borst [Pays-Bas] ; John R. Anderson [États-Unis]Source :
- NeuroImage [ 1095-9572 ] ; 2015.
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
- methods : Electroencephalography.
- physiology : Brain, Recognition (Psychology).
- Humans, Markov Chains, Models, Neurological, Signal Processing, Computer-Assisted.
Abstract
In this paper we propose a new method for identifying processing stages in human information processing. Since the 1860s scientists have used different methods to identify processing stages, usually based on reaction time (RT) differences between conditions. To overcome the limitations of RT-based methods we used hidden semi-Markov models (HSMMs) to analyze EEG data. This HSMM-EEG methodology can identify stages of processing and how they vary with experimental condition. By combining this information with the brain signatures of the identified stages one can infer their function, and deduce underlying cognitive processes. To demonstrate the method we applied it to an associative recognition task. The stage-discovery method indicated that three major processes play a role in associative recognition: a familiarity process, an associative retrieval process, and a decision process. We conclude that the new stage-discovery method can provide valuable insight into human information processing.
DOI: 10.1016/j.neuroimage.2014.12.029
PubMed: 25534112
Affiliations:
- Pays-Bas, États-Unis
- Groningue (province), Pennsylvanie
- Groningue, Pittsburgh
- Université Carnegie-Mellon
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Borst</name><affiliation wicri:level="4"><nlm:affiliation>Carnegie Mellon University, Dept. of Psychology, Pittsburgh, USA; University of Groningen, Dept. of Artificial Intelligence, Groningen, The Netherlands. Electronic address: j.p.borst@rug.nl.</nlm:affiliation><country xml:lang="fr">Pays-Bas</country><wicri:regionArea>Carnegie Mellon University, Dept. of Psychology, Pittsburgh, USA; University of Groningen, Dept. of Artificial Intelligence, Groningen</wicri:regionArea><placeName><settlement type="city">Groningue</settlement><region nuts="2" type="province">Groningue (province)</region><settlement type="city">Pittsburgh</settlement></placeName><orgName type="university">Université Carnegie-Mellon</orgName></affiliation></author><author><name sortKey="Anderson, John R" sort="Anderson, John R" uniqKey="Anderson J" first="John R" last="Anderson">John R. Anderson</name><affiliation wicri:level="4"><nlm:affiliation>Carnegie Mellon University, Dept. of Psychology, Pittsburgh, USA. 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Since the 1860s scientists have used different methods to identify processing stages, usually based on reaction time (RT) differences between conditions. To overcome the limitations of RT-based methods we used hidden semi-Markov models (HSMMs) to analyze EEG data. This HSMM-EEG methodology can identify stages of processing and how they vary with experimental condition. By combining this information with the brain signatures of the identified stages one can infer their function, and deduce underlying cognitive processes. To demonstrate the method we applied it to an associative recognition task. The stage-discovery method indicated that three major processes play a role in associative recognition: a familiarity process, an associative retrieval process, and a decision process. We conclude that the new stage-discovery method can provide valuable insight into human information processing.</div></front></TEI><affiliations><list><country><li>Pays-Bas</li><li>États-Unis</li></country><region><li>Groningue (province)</li><li>Pennsylvanie</li></region><settlement><li>Groningue</li><li>Pittsburgh</li></settlement><orgName><li>Université Carnegie-Mellon</li></orgName></list><tree><country name="Pays-Bas"><region name="Groningue (province)"><name sortKey="Borst, Jelmer P" sort="Borst, Jelmer P" uniqKey="Borst J" first="Jelmer P" last="Borst">Jelmer P. Borst</name></region></country><country name="États-Unis"><region name="Pennsylvanie"><name sortKey="Anderson, John R" sort="Anderson, John R" uniqKey="Anderson J" first="John R" last="Anderson">John R. Anderson</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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