Volume 23, Issue 1 (Spring 2021)                   Advances in Cognitive Sciences 2021, 23(1): 128-139 | Back to browse issues page

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Arab M R, Nadjafi M, Khosrowabadi R, Setoudeh F, Tavakoli M B. Organization the memory processes in the brain based on fractal analysis. Advances in Cognitive Sciences 2021; 23 (1) :128-139
URL: http://icssjournal.ir/article-1-1212-en.html
1- PhD Student of Electrical Engineering, Department of Electrical Engineering, Faculty of Engineering, Islamic Azad University, Arak Branch, Arak, Iran
2- Assistant Professor, Faculty of Electrical and Computer Engineering, Arak University of Technology, Arak, Iran
3- Assistant Professor, Institute for Cognitive and Brain Science, Shahid Beheshti University, Tehran, Iran
4- Assistant Professor, Department of Electrical Engineering, Faculty of Engineering, Islamic Azad University, Arak, Iran
Abstract:   (3768 Views)
Introduction: Learning and memory processes are two essential cognitive functions that have no meaning without the other. The learning and memory mechanisms are faced with many challenges due to the complexity of many challenges. It is believed that the brain organizes the information using the coexistence of scale-free and oscillatory activities. Nevertheless, previous studies have mainly focused on neural oscillations during memory formation, while our understanding of scale-free behavior has remained limited. So, the memory content can also be considered in the case of stimulus. Despite research into the effect of stimuli on human EEG signal and memory formation, nothing has been done about behavioral learning tests and nonlinear analysis of EEG signals simultaneously to measure changes in auditory memory content. Such that, in previous studies, learning and memory processes only would lead to transient sensory memory.
One of the tools for investigating self-organizing dynamics during learning is EEG signals analysis. The purpose of this study is to investigate the dynamics of learning and memory processes (coding, maintenance, and retrieval) in the brain. For this purpose in this research, the researchers used the Ray auditory verbal learning test (RAVLT) to create learning and memory processes and evaluate related functions.
Methods: Eighteen volunteer healthy subjects age range 18-23 assigned to evaluate Ray auditory verbal learning test (RAVLT). All of them are university students and right-handed. EEG signals are recorded during five stages of RAVLT and so before and after the behavioral test. Simultaneous to estimate learning rate and memory process through RAVLT cognitive and behavioral assessment, the dynamics of these changes are investigated by Higuchi fractal dimension (HFD) estimation EEG signals.
Results: In this study, for the first time, the specific dynamics of brain activity in learning conditions in the human brain have been modeled by fractal analysis of EEG signals and the extent of self-organizing function or the effect of brain components, including fractal and oscillating has been investigated. From this research, we have shown changes in brain signals in the learning process. The input information that is audibly passed through the sensory memory related to hearing in the behavioral test, and activating the working memory, encodes the input information and places it in the semantic memory, the output of which is as a reminder of this information through verbal memory is provided.
The results of this study showed that increasing the number of words recalled or increasing the learning rate of participants is inversely proportional to the Higuchi fractal dimensionality of the EEG signals. The power spectrum obtained show an increase in the overall frequency spectrum of the EEG.
Approximation entropy confirms reducing the chaotic behavior of signals due to decreasing the complexity of signals the during memory process increases.
Conclusion: The fractal and oscillatory components behavior of the EEG signals present brain organization during learning and memory processes. It is possible to compare the results with a healthy community, which can be used to study people with learning disabilities such as Alzheimer's disease, attention deficit hyperactivity disorder (ADHD), and autism.
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Type of Study: Research |
Received: 2020/11/10 | Accepted: 2021/01/18 | Published: 2021/03/14

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