The Assessment of Eyewitness Memory Using Electroencephalogram: Application of Machine Learning Algorithm / 대한법의학회지
Korean Journal of Legal Medicine
; : 62-70, 2018.
Article
em Ko
| WPRIM
| ID: wpr-917777
Biblioteca responsável:
WPRO
ABSTRACT
This study was conducted to investigate whether memory accuracy can be assessed by analyzing electrophysiological responses (i.e., electroencephalography [EEG]) for retrieval cues related to the witnessed scene. Specifically, we examined the different patterns of EEG signals recorded during witnessed (target) and unwitnessed (lure) stimuli using event-related potential (ERP) analysis. Moreover, using multivariate pattern analysis, we also assessed how accurately single-trial EEG signals can classify target and lure stimuli. Participants watched a staged-crime video (theft crime), and the EEG signals evoked by the objects shown in the video were analyzed (n=56). Compared to the target stimulus, the lure stimulus elicited larger negative ERPs in frontal brain regions 300 to 500 milliseconds after the retrieval cue was presented. Furthermore, the EEG signals observed 450 to 500 milliseconds after the retrieval cue was presented showed the best classification performance related to eyewitness memory, with the mean classification accuracy being 56%. These results suggest that the knowledge and techniques of cognitive neuroscience can be used to estimate eyewitness memory accuracy.
Texto completo:
1
Base de dados:
WPRIM
Tipo de estudo:
Prognostic_studies
Idioma:
Ko
Revista:
Korean Journal of Legal Medicine
Ano de publicação:
2018
Tipo de documento:
Article