:: Volume 3, Number 9 (Spring 2017) ::
Caspian.J.Neurol.Sci 2017, 3(9): 60-65 Back to browse issues page
Predicting Normal People’s Reaction Time based on Hippocampal Local Efficiency During a Memory-Guided Attention Task
Fereshteh Saliminia , Milad Amini-Masouleh
MSc in Cognitive Science, AzarbaijanShahidMadani University, Tabriz, Iran; Fereshte.saliminia@gmail.com
Abstract:   (211 Views)

Background: There are some convincing shreds of evidence indicating that memory can direct attention. The local efficiency of an area in the brain, as a quantitative feature in a complex network, indicates how the surrounding nodes can transfer the information when a specific node is omitted. This feature is a scale for measuring efficient integration of information in the brain.

Objectives: The purpose of the present study is to predict the reaction time using the local efficiency variable while doing memory-guided attention task. Materials and Methods: The fMRI database of a research done in New York University during a visual search task was used for this study. Thirty-five right-handed healthy participants (51% female, mean age= 21.7 years) were recruited at New York University. SPM was used for pre-processing fMRI images, and CONN was used for calculating the values of local efficiency. SPSS was also used for statistical analysis of the study.

Results: Results of the study revealed that local efficiency of the right hippocampus can positively predict the reaction time during memory-guided attention tasks.

Conclusion: The findings of the study demonstrated that the hippocampus area has a significant role in the performance of memory-guided attention, and this significant role of the hippocampus reveals that long-term memory uses the hippocampus and affects the movement and attention of eyes on the target.

Keywords: Reaction Time, Memory, Hippocampus, Attention, Functional Neuroimaging
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Type of Study: Research | Subject: Special

DOI: 10.18869/acadpub.cjns.3.9.60

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Volume 3, Number 9 (Spring 2017) Back to browse issues page