Directional information flow analysis in memory retrieval: a comparison between exaggerated and normal pictures

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Publicado en:Medical and Biological Engineering and Computing vol. 63, no. 1 (Jan 2025), p. 89
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Springer Nature B.V.
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245 1 |a Directional information flow analysis in memory retrieval: a comparison between exaggerated and normal pictures 
260 |b Springer Nature B.V.  |c Jan 2025 
513 |a Journal Article 
520 3 |a Working memory plays an important role in cognitive science and is a basic process for learning. While working memory is limited in regard to capacity and duration, different cognitive tasks are designed to overcome these difficulties. This study investigated information flow during a novel visual working memory task in which participants respond to exaggerated and normal pictures. Ten healthy men (mean age 28.5 ± 4.57 years) participated in two stages of the encoding and retrieval tasks. The electroencephalogram (EEG) signals are recorded. Moreover, the adaptive directed transfer function (ADTF) method is used as a computational tool to investigate the dynamic process of visual working memory retrieval on the extracted event-related potentials (ERPs) from the EEG signal. Network connectivity and P300 sub-components (P3a, P3b, and LPC) are also extracted during visual working memory retrieval. Then, the nonparametric Wilcoxon test and five classifiers are applied to network properties for features selection and classification between exaggerated-old and normal-old pictures. The Z-values of Ge is more distinctive rather than other network properties. In terms of the machine learning approach, the accuracy, F1-score, and specificity of the k-nearest neighbors (KNN), classifiers are 81%, 77%, and 81%, respectively. KNN classifier ranked first compared with other classifiers. Furthermore, the results of in-degree/out-degree matrices show that the information flows continuously in the right hemisphere during the retrieval of exaggerated pictures, from P3a to P3b. During the retrieval of visual working memory, the networks associated with attentional processes show greater activation for exaggerated pictures compared to normal pictures. This suggests that the exaggerated pictures may have captured more attention and thus required greater cognitive resources for retrieval. 
653 |a K-nearest neighbors algorithm 
653 |a Memory 
653 |a Visual tasks 
653 |a Memory tasks 
653 |a Visual perception 
653 |a Visual discrimination learning 
653 |a EEG 
653 |a Visual signals 
653 |a Information flow 
653 |a Information retrieval 
653 |a Mental task performance 
653 |a Visual evoked potentials 
653 |a Event-related potentials 
653 |a Electroencephalography 
653 |a Information processing 
653 |a Pictures 
653 |a Machine learning 
653 |a Cognitive tasks 
653 |a Software 
653 |a Hemispheric laterality 
653 |a Transfer functions 
653 |a Biomedical engineering 
773 0 |t Medical and Biological Engineering and Computing  |g vol. 63, no. 1 (Jan 2025), p. 89 
786 0 |d ProQuest  |t ABI/INFORM Global 
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