Neuroplasticity Changes in Brain Networks after Morse Code Training
Poster No:
858
Submission Type:
Abstract Submission
Authors:
Zhongyang He1, Ying Zeng1, Changfu Pei1, Yuanlong Gao1, Li Tong1, Bin Yan1
Institutions:
1Information Engineering University, Zhengzhou, Henan
First Author:
Co-Author(s):
Introduction:
The human brain is plastic, and the physiological structures and functions of the central nervous system, such as synapses and neuronal cells, change with the internal and external environment[1]. Recent studies have shown that second language learning can exercise the reaction speed of brain and improve concentration and memory significantly[2,3]. However, learning process requires a significant investment of time and energy. Morse code (MC) provides a suitable alternative due to its ease of acquisition and similar brain plasticity effects[4]. To investigate the impact of MC training on brain plasticity, this paper designed an EEG experimental paradigm to analyze the differences in brain networks before and after MC training. The research result showed that the brain plasticity changes after MC training as the increased synaptic efficiency in related brain areas, which will have a positive impact on the reaction speed of brain, concentration, and memory.
Methods:
An experimental paradigm tailored was designed, utilizing actual MC communication signals as stimulus materials. The experiment consisted of 3 sessions, namely A-Data Collection, B-MC Training and C-Data Collection, as shown in Figure 1. Among them, the session B ran for a minimum of 20 hours of MC basic knowledge and recognition training. 12 participants (all male, average age 22.5±0.96 years) were recruited, and all of them had no prior knowledge of MC before. Each participant completed the data collection twice before (Pre) and after (Post) the MC training, which corresponded to session A and session C. The data collection was conducted in two phases: practice and experimental. The practice phase aimed to acclimate participants to the procedures, while the experimental phase was divided into three blocks, each designed for a specific code speed. Each block comprised 52 trials, with each trial featuring a MC audio stimulus for an English character. The 26 characters were randomly presented twice, totaling 52 MC audio stimuli per block. This study utilized 21 typical EEG electrodes across the entire brain[5]. PLV (Phase Locking Value) was calculated between any two EEG channels for all participants and blocks, yielding 96 connection matrices of size 21*21. Using these matrices, PLV network difference maps were generated for different code speeds and averages pre- and post-training, with a differential threshold set at 0.05. Additionally, 4 network attributes (CC, CPL, Ge, and Le) were calculated for each participant to assess changes in network characteristics, using methods consistent with Zhang et al.[6].
·Figure 1 Schematic diagram of experimental process.
Results:
The changes in network patterns pre- and post-training under different coding speeds as well as the average across all coding speeds (p<0.05, FDR corrected), as shown in Figure 2. The results indicated that the right hemisphere brain network connections after the training were significantly enhanced around the temporal lobe T8 electrode. Especially, a key activation area for auditory attention, acting as a hub node, showed a clear right hemisphere lateralization effect. It was the first time that the neural plasticity change was shown in the MC training, which might be related to the rhythmic characteristics of MC, mainly involving primary processing in the brain.
·Figure 2 The experimental results were analyzed using brain networks(Character Per Minute ,CPM)
Conclusions:
In this paper, an EEG experimental paradigm was designed to investigates the effects of MC training on brain plasticity using brain network analysis innovatively. The experiment results showed that the MC identification abilities of subjects were improved expectedly after training, and more importantly, the brain network connections in the regions associated with the brain reaction speed, concentration and memory were enhanced significantly. This paper provides a new way to verify the positive effects of MC training on brain plasticity, and has the potential to provide guidance for the training of brain response speed concentration and memory.
Learning and Memory:
Neural Plasticity and Recovery of Function 1
Learning and Memory Other 2
Keywords:
Electroencephaolography (EEG)
Language
Plasticity
1|2Indicates the priority used for review
Abstract Information
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3. Bialystok, E., Craik, F. I. M., Klein, R., & Viswanathan, M. (2004). Bilingualism, aging, and cognitive control: Evidence from the Simon task. Psychology and Aging, 19(2), 290–303.
4. Schlaffke, L., Rüther, N. N., Heba, S., Haag, L. M., Schultz, T., Rosengarth, K., Tegenthoff, M., Bellebaum, C., & Schmidt‐Wilcke, T. (2015). From perceptual to lexico‐semantic analysis—Cortical plasticity enabling new levels of processing. Human Brain Mapping, 36(11), 4512–4528.
5. Jiang, L., Wang, J., Dai, J., Li, F., Chen, B., He, R., Liao, Y., Yao, D., Dong, W., & Xu, P. (2022). Altered temporal variability in brain functional connectivity identified by fuzzy entropy underlines schizophrenia deficits. Journal of Psychiatric Research, 148, 315–324.
6. Zhang, X., Jiang, Y., Zhang, S., Li, F., Pei, C., He, G., Ao, M., Yao, D., Zhao, Y., & Xu, P. (2021). Correlation Analysis of EEG Brain Network With Modulated Acoustic Stimulation for Chronic Tinnitus Patients. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 29, 156–162.