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- Publisher Website: 10.1016/j.cortex.2020.10.016
- Scopus: eid_2-s2.0-85096973706
- PMID: 33276306
- WOS: WOS:000607303200010
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Article: Mechanisms of face specificity – Differentiating speed and accuracy in face cognition by event-related potentials of central processing
Title | Mechanisms of face specificity – Differentiating speed and accuracy in face cognition by event-related potentials of central processing |
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Authors | |
Keywords | Face cognition P300 RIDE Individual differences Performance speed |
Issue Date | 2021 |
Publisher | Elsevier Masson. The Journal's web site is located at http://www.cortex-online.org/ |
Citation | Cortex, 2021, v. 134, p. 114-133 How to Cite? |
Abstract | Given the crucial role of face recognition in social life, it is hardly surprising that cognitive processes specific for faces have been identified. In previous individual differences studies, the speed (measured in easy tasks) and accuracy (difficult tasks) of face cognition (FC, involving perception and recognition of faces) have been shown to form distinct abilities, going along with divergent factorial structures. This result has been replicated, but remained unexplained. To fill this gap, we first parameterized the sub-processes underlying speed vs. accuracy in easy and difficult memory tasks for faces and houses in a large sample. Then, we analyzed event-related potentials (ERPs) extracted from the EEG by using residue iteration decomposition (RIDE), yielding a central (C) component that is comparable to a purified P300. Structural equation modeling (SEM) was applied to estimate face specificity of C component latencies and amplitudes. If performance in easy tasks relies on purely general processes that are insensitive to stimulus content, there should be no specificity of individual differences in the latency recorded in easy tasks. However, in difficult tasks specificity was expected. Results indicated that, contrary to our predictions, specificity occurred in the C component latency of both speed-based and accuracy-based measures, but was stronger in accuracy. Further analyses suggested specific relationships between the face-related C latency and FC ability. Finally, we detected specificity in RTs of easy tasks when single tasks were modeled, but not when multiple tasks were jointly modeled. This suggests that the mechanisms leading to face specificity in performance speed are distinct across tasks. |
Persistent Identifier | http://hdl.handle.net/10722/305919 |
ISSN | 2023 Impact Factor: 3.2 2023 SCImago Journal Rankings: 1.330 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Meyer, K | - |
dc.contributor.author | Nowparast Rostami, H | - |
dc.contributor.author | Ouyang, G | - |
dc.contributor.author | Debener, S | - |
dc.contributor.author | Sommer, W | - |
dc.contributor.author | Hildebrandt, A | - |
dc.date.accessioned | 2021-10-20T10:16:12Z | - |
dc.date.available | 2021-10-20T10:16:12Z | - |
dc.date.issued | 2021 | - |
dc.identifier.citation | Cortex, 2021, v. 134, p. 114-133 | - |
dc.identifier.issn | 0010-9452 | - |
dc.identifier.uri | http://hdl.handle.net/10722/305919 | - |
dc.description.abstract | Given the crucial role of face recognition in social life, it is hardly surprising that cognitive processes specific for faces have been identified. In previous individual differences studies, the speed (measured in easy tasks) and accuracy (difficult tasks) of face cognition (FC, involving perception and recognition of faces) have been shown to form distinct abilities, going along with divergent factorial structures. This result has been replicated, but remained unexplained. To fill this gap, we first parameterized the sub-processes underlying speed vs. accuracy in easy and difficult memory tasks for faces and houses in a large sample. Then, we analyzed event-related potentials (ERPs) extracted from the EEG by using residue iteration decomposition (RIDE), yielding a central (C) component that is comparable to a purified P300. Structural equation modeling (SEM) was applied to estimate face specificity of C component latencies and amplitudes. If performance in easy tasks relies on purely general processes that are insensitive to stimulus content, there should be no specificity of individual differences in the latency recorded in easy tasks. However, in difficult tasks specificity was expected. Results indicated that, contrary to our predictions, specificity occurred in the C component latency of both speed-based and accuracy-based measures, but was stronger in accuracy. Further analyses suggested specific relationships between the face-related C latency and FC ability. Finally, we detected specificity in RTs of easy tasks when single tasks were modeled, but not when multiple tasks were jointly modeled. This suggests that the mechanisms leading to face specificity in performance speed are distinct across tasks. | - |
dc.language | eng | - |
dc.publisher | Elsevier Masson. The Journal's web site is located at http://www.cortex-online.org/ | - |
dc.relation.ispartof | Cortex | - |
dc.subject | Face cognition | - |
dc.subject | P300 | - |
dc.subject | RIDE | - |
dc.subject | Individual differences | - |
dc.subject | Performance speed | - |
dc.title | Mechanisms of face specificity – Differentiating speed and accuracy in face cognition by event-related potentials of central processing | - |
dc.type | Article | - |
dc.identifier.email | Ouyang, G: ouyangg@hku.hk | - |
dc.identifier.authority | Ouyang, G=rp02315 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.cortex.2020.10.016 | - |
dc.identifier.pmid | 33276306 | - |
dc.identifier.scopus | eid_2-s2.0-85096973706 | - |
dc.identifier.hkuros | 327224 | - |
dc.identifier.volume | 134 | - |
dc.identifier.spage | 114 | - |
dc.identifier.epage | 133 | - |
dc.identifier.isi | WOS:000607303200010 | - |
dc.publisher.place | Italy | - |