The increase in medical expenses, which is a side effect of the aging society caused by the increase in the aging population, has provided us an opportunity to change from a treatment-oriented medical paradigm to a prevention-oriented medical paradigm that can manage patients and older persons at a much lower cost than treatment costs. Accordingly, various countries are making efforts to prevent and predict degenerative brain diseases known to have a high economic and social burden. Degenerative brain disease is known to be caused by genetic and environmental problems and neurodegeneration that can damage normal cells with aging, thus greatly increasing the prevalence of various degenerative brain diseases such as Alzheimer's, Parkinson's, and multiple sclerosis [29]. Degenerative brain disease causes cognitive impairment, a neurological complication that impairs intellectual functions such as memory, concentration, judgment, and language skills. Cognitive impairment can cause various deficits in neuropsychological function in the initial mild state, eventually leading to severe cognitive impairment [30]. In this study, a total of 8 training contents were developed based on neuropsychology to prevent cognitive decline. Their clinical effects and changes were derived by subdividing components to classify brain regions.
Through MMSE-K, the cognitive rehabilitation training effect of a total of 8 training contents was confirmed. As a cognitive function test, the MMSE-K, revised according to the characteristics of Korean society, has been proven the validity of attention, computational power, language, memory registration and memory recall, and visual composition evaluation methods[31]. In this study, through training conducted on 24 subjects aged 60.58 ± 3.96 years for 3 weeks, the initial score was 27.88 ± 1.70. It was changed to 28.63 ± 1.69, showing an increase of 0.75 ± 2.42. In previous studies, cognitive rehabilitation and control training were conducted for about 9 weeks for 15.95 ± 6.46 subjects with an average age of 73.70 ± 3.72 years. The initial subject's MMSE score was 22.19 ± 2.5. However, the difference in MMSE after training was 0.10, which showed an insignificant training effect [32]. In other words, it is judged that the computerized training program proposed in this study to prevent cognitive decline will have a greater expected effect if it is used for the normal elderly population rather than for the mild patient group. Based on these results, the computerized cognitive rehabilitation training programis expected to be used as a method to prevent aging and functional deterioration of cranial nerves, rather than treating already damaged cranial nerves [33].
The main purpose of segmented contents is to represent regions of the brain. The brain has one large mass of cells. The brain maintains various physical coordination and homeostasis. It is responsible for functions necessary for life activities. It is also responsible for cognition, emotion, memory, and learning. The brain is largely divided into three parts: cerebrum, cerebellum, and brainstem. The cerebrum is the center of mental activity. The outer layer of the cerebrum is composed of four lobes. In this study, language, number, color, and training method were designated as the temporal lobe, parietal lobe, occipital lobe, and frontal lobe, respectively. Accordingly, this study focused on brain atrophy and functional decline that would occur during natural aging [34]. Atrophy, the most common aging process in the brain, represents morphological changes due to a decrease in brain volume. It is very difficult to find atrophic patterns in the brain. However, brain atrophy can be predicted based on a decrease in various functions responsible for specific brain regions[35].
The developed content included each element with words, numbers, and colors. The error rate increased in the order of words, numbers, and colors according to training results. These results were expected to have a specific relationship in the temporal lobe, parietal lobe, and occipital lobe through segmentation of brain regions. The local gyrification index, which determines cortical complexity, is known to be a potential factor for predicting cognitive decline due to brain atrophy. In this study, the local gyrification index corresponding to each brain region was analyzed. According to previous research papers, the local gyrification index is low in the order of the temporal lobe, parietal lobe, and occipital lobe. In addition, the local gyrification index of the occipital lobe is 22% lower than that of the temporal lobe. For this reason, the order of error rate is listed. It was judged that higher error rates occurred in color elements than in word and number elements. Additionally, number concentration and memory content showed greater training effect than other trainings [36]. That is, it is expected that nerve activation according to stimulation occurred significantly in a state in which functions such as memorizing and calculating numbers were deteriorated.
Based on the relationship between the subdivided element and the local gyrification index, it was confirmed that the element used for the content directly or indirectly reflected and affected the brain region. This study proposed the following final effects and characteristics according to elements. Color recognition and memory in the occipital lobe, which has a low basic local gyrification index, might be difficult. However, since the occipital lobe has the temporal lobe in charge of words and the parietal lobe in charge of numbers with pathways, it seems that the color element can be used in combination with one additional element. In other words, it will be possible to develop and utilize more difficult training contents. The number element is judged to be the most effective training element to be performed in older persons. With aging, the existing functions and new learning functions of the parietal lobe are decreased compared to those in young adults. These functions show a decrease in subjective experience [37]. Words and color elements are in the form of presenting what they already know. However, numbers can suggest a variety of new problems through new combinations and calculations. It was determined that existing known calculations and recognition methods could be utilized.
Finally, it is expected that word elements can be used as a prediction of cognitive decline. The brain regions responsible for memory include the medial temporal lobe, the frontal lobe, and the hippocampus. In this study, the role of the medial lateral lobe was emphasized. The reason is that the medial temporal lobe is not the ultimate storage location for memories, it is a temporary storage location[38]. That is, it was determined that the role of the medial temporal lobe would be large because word memory is a content that solves problems using temporary memory. In word memory contents using words, the change in incorrect answer rate was insignificant compared to other contents. For this reason, it is presumed that word learning using nameable objects observed and used in daily life can stimulate the medial temporal lobe and affect the memory process and the processing of memory processes in the brain, suggesting that they are functioning normally at the normal age of 60.58 ± 3.96 years. Finally, based on results of various studies in which the function and volume of the medial temporal lobe are decreased in those with mild cognitive disorders such as Alzheimer's disease [42-44], the occurrence and change of a large error rate of content using word element can to be utilized as a predictor of degenerative brain disease.
Although there was a slight difference depending on the factors, the training effect also differed according to the method of choosing the correct answer and the method of presenting the problem. In this study, it was assumed that these training methods were related to the prefrontal area. The frontal lobe regulates brain functions. It is an area involved in complex cognitive function-related processes such as solving new problems. Also, the frontal lobe is associated with the memory of events and temporal sequences [45]. In this study, events were set as a method of presenting problems at the same time and the temporal order was set as a method of presenting sequential problems. In this study, the method of presenting sequential problems produced more errors. The method of presenting sequential problems was judged to be related to the network function of the frontal lobe and it was confirmed through various studies.
A study on frontal lobe injury has been confirmed that actual frontal lobe injury patients can perform routine memory tests normally [46]. However, it was confirmed that there was a disability in the study focusing on the strategic process test using tactical aspects such as the memory of temporal sequence [47-48]. Results of previous studies and the present study confirmed that the problem presentation method was related to the frontal lobe. It was judged that the strategic process function of subjects who were 60.58 ± 3.96 years old was somewhat weakened. Finally, training using the sequential problem presentation method for frontal lobe activation requires at least three weeks of training time and training using color elements can create a greater effect (Fig. 7A).
Existing training and evaluation have used paper equipment. However, this study performed a computerized training program using computers. Accordingly, the effect of using a computer and training device was additionally confirmed. As older people lose concentration and increase fatigue due to aging, the training time of the content used for training should be taken into account. The gradual increase in the training effect by week and the sharp increase in the incorrect answer rate in the 3rd week decreased. That is, in training using a computer and training device, a solution time of 45 seconds or more may cause a decrease in concentration and an increase in fatigue. In addition, through the satisfaction survey, it was found that repeated training had an additional effect on incorrect answers and concentration or fatigue since repeated training could decrease test subject's training satisfaction when an incorrect answer was selected.
However, this study has some limitations. First, the period of training was short. In a previous study, the cognitive rehabilitation training and adjustment period lasted an average of 9 weeks. Accordingly, final results were presented when training and adjustment were carried out and changes were completed. In this study, although the effect and specificity of training were suggested, the final change was not quantified numerically. In addition, as shown in FIGS. 6C and 6D , a reduction effect after the increased error rate was not confirmed. Nevertheless, compared to the previous study, subjects who were younger than the previous study participated in this study. Results confirmed that cognitive function could be improved by 3 weeks of training for subjects with normal cognitive function, thereby preventing cognitive decline. Second, the condition of the subject could not be maintained the same. The effect of training is expected to vary depending on concentration and fatigue. However, in this study, physical or bio-signal data measurements other than verbal confirmation could not be used to check the condition of these subjects. Thus, the analysis was carried out by removing the occurrence of serious errors through the process of Figure 4.
In summary, this study analyzed clinical effects and characteristics of content elements that could help develop a computerized instructional program for preventing cognitive decline in line with the prevention and prediction-centered medical paradigm. Through this study, it is expected that customized content production will be possible using elements and training methods suitable for each characteristic in the program used for degenerative brain disease prevention contents and devices developed in a variety of ways. It is expected to be helpful in clinical research and planning. Results of this study are expected to contribute to the development of a computerized cognitive rehabilitation training program that can predict and prevent degenerative brain diseases occurring in a rapidly changing aging society, thereby contributing to a prevention-oriented medical paradigm.