透過不同的教學與學習計劃探索認知能力的提升

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(1)國立臺灣師範大學理學院科學教育研究所博士論文 Graduate Institute of Science Education College of Science. National Taiwan Normal University Doctoral Dissertation. 透過不同的教學與學習計劃探索認知能力的提升. Exploring Cognitive Enhancement through Different Teaching and Learning Programs. 鄭泳松 Cheng, John Yung-Sung. 指導教授: 張俊彥博士 Advisor: Chang, Chun-Yen, Ph.D. 中華民國 109年8月 August 2020.

(2) 謝辭 Acknowledgement 1. I would like to express my most sincere gratitude to Professor Chang for his guidance and support to my research of Ph.D. for years. 2. I also want to thank my family for all the considerations and support.. I.

(3) 英文摘要 English Abstract The possibilities of cognitive enhancement have won popularity among commons and academic circles in recent decades. Cognitive enhancement has often been associated with advances in neuroscientific technologies aimed to improve cognitive and intellectual capacities of the brain. It focuses on the improvement of cognitive functions, such as attention, reasoning, memory and executive function. Traditionally, enhancement of cognitive performance could be achieved through conventional way such as structured classroom teaching, individual learning, training (ex. abacus, foreign language, exercise), as well as the use of external information-processing devices. Contemporary attempts to improve cognitive performance often involve the consumptions of drugs, such as amphetamine, methylphenidate, and modafinil, or utilization of electrical brain stimulators. Throughout the whole life span, the adaptations to the diverse contexts and changing social environments are very important to individuals. Capabilities of significant changes of brain and neural system in the complex environments have been referred to as neuroplasticity. During recent years, the literature on cognitive training has been growing rapidly. Neuroplasticity can be observed in mind and brain after training intervention, and the scope and pattern of training effects can be measured to identify the underling mechanism. In general, this study aims to develop teaching and learning programs to enhance cognitive performance through the application of educational neuroscience into the optimization, generalization and integration of instructional techniques. Optimization refers to the improvement of existing techniques to achieve better results. Generalization refers to the application of existing techniques to different domains and integration refers to the combination of several existing techniques to create more effective techniques. Topic One: Exploring Cognitive Enhancement through Teaching Programs. The design of new teaching model of neuroanatomy to prevent neurophobia in preclinical medical students. Topic Two: Exploring Cognitive Enhancement through Learning Programs. Six-month abacus training improves working memory performance in children: a functional MRI and behavior study. Exam the effects of short term abacus training on brain structure, activation pattern and behavior, as a potential learning program to improve working memory. Keywords: cognitive enhancement, cognitive training, neuroplasticity, teaching programs, neurophobia, learning programs, abacus training, working memory. II.

(4) Table of contents Acknowledgement……………………………………………………...........................................I Abstract………………………………………………………………………………...................II 【Chapter 1】Introduction…..………………………………………………………………........1 References……........................................................................................................................7 【Chapter 2】Exploring Cognitive Enhancement through Teaching Programs………………….9 The Design of New Teaching Model of Neuroanatomy to Prevent Neurophobia in Preclinical Medical Students Introduction……....................................................................................................................10 Methods…….........................................................................................................................12 Result…….............................................................................................................................13 Discussion…………………………………………………………………………………..16 Conclusion…….....................................................................................................................17 References……......................................................................................................................18 【Chapter 3】Exploring Cognitive Enhancement through Learning Programs………...............19 Six-month abacus training improves working memory performance in children: a functional MRI and behavior study Introduction……....................................................................................................................20 Methods…….........................................................................................................................21 Result…….............................................................................................................................25 Discussion…………………………………………………………………………………..33 Conclusion…….....................................................................................................................39 References……......................................................................................................................40 Appendix…………………………………………………………………………………………42 1. Oral paper: The Design of New Teaching Model of Neuroanatomy to Prevent Neurophobia in Preclinical Medical Students. 2. 台灣醫學 Formosan J Med 2015;19 : 從大體解剖實驗到虛擬實境：談解剖學教學之新趨勢. The New Approach of Teaching Anatomy: From Cadaver Dissection to Virtual 3. 4.. Reality. An SSVEP-Based BCI Using High Duty-Cycle Visual Flicker. IEEE Transactions on Biomedical Engineering 58.12 (2011): 3350-3359. Oral paper: The nature of abacus is one kind of working memory training: a functional MRI and behavior study. References……......................................................................................................................80 III.

(5) 【Chapter 1】 Introduction Current knowledge has enabled interdisciplinary collaboration to explore the correlation between brain and learning process (Meltzoff et al. 2009, Varma et al. 2008, Goswami et al. 2006). Each regions of the brain has its own functions which associated to certain task. More complex tasks often involve different combination of tasks and require the integration of neural activity. Multiple neural circuits are involved in cognitive processes, such as selective attention, concentration, symbol processing, pattern recognition, working memory and problem solving (Colvin et al. 2016). The integration of these cognitive processes will form the basis of academic abilities, such as critical thinking, reading, writing, higher mathematics, social interactions, long term planning and decision-making, etc. (Figure1). At the structural level, brain is often regarded as the integrated network of regions (grey matter) connected by the neural tracts (white matter). The neural activity associated with certain task might mainly take place in certain brain areas and be transmitted by the white matter to another part of the brain. These patterns of activity are called activation pattern. These activation patterns can be observed by functional magnetic resonance imaging (fMRI) and the functional connectivity can be observed by using resting state functional magnetic resonance imaging (rsfMRI).. Figure1. The generation of higher level academic abilities from basic neural process, adapted from Colvin (2016). Cognitive processes are emerged from basic neural process and integrated to solve higher level academic tasks.. 1.

(6) Cognitive enhancement The possibilities of cognitive enhancement have won popularity among commons and academic circles in recent decades. Cognitive enhancement has often been associated with advances in neuroscientific technologies aimed to improve cognitive and intellectual capacities of the brain. It focuses on the improvement of cognitive functions, such as attention, reasoning, memory and executive function (the ability to monitor direct and coordinate various mental operations). Critical reflections on the pros and cons are essential in the booming era of cognitive enhancement. General intelligence and cognitive performance are often associated with professional achievement. Cognitive enhancement will make more people able to meet the higher standards and potentially beneficial for people from wide range of occupational background, such as white collar worker, students, people who work in high risk, high stress environment, and shift work occupations which required extended awareness. Advancement in cognitive performance will improve quality of life and ability to contribute to society (Beddington et al. 2008). Enhanced cognitive abilities will lead to the emergence of new jobs and development of old occupations. While the benefits might seem to be individual, in the long run cognitive enhancement will eventually contribute across society by reducing cost and increasing productivity (Savulescu et al. 2011). Traditionally, enhancement of cognitive performance could be achieved through conventional way such as structured classroom teaching, individual learning, training ( ex. abacus, foreign language, exercise ), as well as the use of external information-processing devices. They are often well established and culturally acceptable. On the other hand, methods to enhance cognition through unconventional means may include consumption of nootropic drugs, gene therapy, or neural implants. Contemporary attempts to improve cognitive performance often involve the consumptions of drugs, such as amphetamine, methylphenidate, and modafinil, or utilization of electrical brain stimulators, such as transcranial direct current stimulation (tDCS), transcranial alternating current stimulation (tACS), transcranial random noise stimulation (tRNS), and transcranial pulsed current stimulation (tPCS) (Farah 2015). There are numbers of obstacles regarding to the development and applications of cognitive enhancement despite its potential economic and social benefits, such as the current medical system which regulate interventions for disease treatment. This system is still inadequate to regulate the application of medical treatments for enhancement purposes. The intervention that is aimed to correct certain disorder or defect of cognitive domains may be characterized as therapeutic. On the other hand, enhancement is the intervention that improves the function of the system rather than repairing specific dysfunction of certain disease. Nevertheless, therapy and enhancement is often difficult to differentiate practically (Savulescu et al. 2011). Currently, every drug available on the market that have the potential to improve cognitive performance were developed and to treat certain pathological condition. 2.

(7) Furthermore, the applications for cognitive enhancement need to be regular and long term but there was still not enough evidence regarding the efficacy of the cognitive enhancing drugs to improve well-being, happiness and achievements in healthy individuals and the drugs might even pose some risks (Teter et al. 2010). In addition to addiction, there are significant psychiatric, cardiovascular, and other medical risks of using drugs like modafinil and methylphenidate for cognitive enhancement. The improvement in one cognitive domain might also lead to the decrease of the performance in other cognitive domains. Therefore, proper assessment is required to determine the limits of acceptable risks and tradeoffs, such as government regulation for addictive drug for memory improvement. People also argued that enhancements through conventional, cultural or evolutionary process are ethically not the same as enhancement using technology or medications, because they represent a new and different methodology (Schermer 2012). There are people who agree with such efforts and believe that it’s the duty of each individual to enhance themselves. On the other hand, some people argue that the use of medical technologies for human enhancement may erode important human values such as dignity (Kass 2002) and solidarity with weaker groups in our society (Fukuyama 2003). It is difficult to formulate useful guidelines and policy without sufficient knowledge regarding the safety and efficacy of brain interventions. Therefore, safer and more efficient cognitive enhancement methods need to be further explored and developed. Cognitive training Throughout the whole life span, the adaptations to the diverse contexts and changing social environments are very important to individuals. Capabilities of significant changes of brain and neural system in the complex environments have been referred to as neuroplasticity. Interestingly, scientific findings show that the brain and mind can be plastic by training in older adults, as well as in young adults. During recent years, the literature on cognitive training has been growing rapidly. Neuroplasticity can be observed in mind and brain after training intervention, and the scope and pattern of training effects can be measured to identify the underling mechanism. Educational neuroscience Educational neuroscience is one of the fields that address this issue of cognitive training. It is an interdisciplinary field that integrates neuroscientific research to educational practice and policy (Figure2). It studies the mechanisms between education and its associated changes in the brain and behavior. These changes are not only observable in the behavioral level, but lead to brain reorganization in the functional, anatomical, cellular, and molecular levels. The changes might include the change in synaptic strength (Feldman et al 2012), through the growth of new neurons (Murphy et al 1991, Vulkovic et al 2013), or changes in the neuron themselves (Buonomano et al 1995). They can occur in grey matter as well as white matter. These cumulative changes may improve the processing speed within regions, communication speed between regions and 3.

(8) eventually lead to enhancement of cognitive performance.. Figure2. Three major themes of educational neuroscience: (a) application of neuroscience discoveries in the classroom, (b) overlapping and interdisciplinary collaboration of psychology, neuroscience, and education, and (c) a bridge that translates between education and neuroscience, adapted from Feiler et al. (2018). Neuroscience and education can interact directly by considering the brain as an organ with certain requirements for it to learn and reorganize optimally or indirectly as neuroscience shape psychological theory and psychology influence educational practices (Feiler et al. 2018). Successful learning often requires complex processes and attention to multiple domains such as cognitive, affective (emotion, motivation), social (interpersonal interaction), environmental (location and condition) as well as metacognitive domains (Young et al. 2014). Cognitive Load theory Cognitive Load Theory (CLT) is one of the theories that have been suggested to overcome these challenges of successful learning. CLT aims to integrate memory systems (sensory, working and long-term memory) and the cognitive load imposed on working memory (WM) into the learning process (Sweller 1988). This theory recognized the limited capacity of WM as obstruction to long term memory formation and focus to improve the learning process by optimizing the utilization of WM. CLT suggests that there are three types of load imposed on the WM during the learning process which include intrinsic, extrinsic and germane load (Figure3, 4). Intrinsic load refers to the load associated with the learning task. The knowledge of the individual, number of information elements need to be learned and the interaction between those elements can affect the intrinsic load. Higher number of elements and lower elements interactivity will increase the intrinsic load on WM. Intrinsic load can be managed by simplifying the information to be learned or enhancing the expertise of the learners by providing preparatory training prior to the task. Extraneous load refers to the load imposed upon the trainee’s WM but not necessary for learning 4.

(9) the task at hand. This load can emerge from insufficient guidance that caused the learners need to use their own ineffective methods to learn or find information. It can emerge from the separation of teaching materials into several places, time (across different lectures) or when the visual or auditory channel is overloaded. Finally, the distractions or tasks unrelated to the learning process can also be the source of extraneous load. Germane load refers to the load imposed by the mental processes necessary for learning to occur, such as the schemata and automation formation. Germane load can be viewed as the learner’s level of concentration devoted to learning in addition to the intrinsic load associated with holding the relevant interacting elements in WM. Germane load is regulated by the individual and when the extraneous and intrinsic load are too high there will be insufficient WM resources available for learning. Most importantly, cognitive loads are additive, cognitive performance will be impaired and learning process will be harmed if the total load exceed the WM capacity. Therefore, better teaching and learning programs need to be developed to help students to overcome this problem.. Figure3. Composition of cognitive load imposed to working memory, adapted from Inkster (2018).. Figure4. Human learning process, adapted from Clark (2008).. Specific Aims of Thesis In general, this study aims to develop teaching and learning programs to enhance cognitive performance through the application of educational neuroscience into the optimization, generalization and integration of instructional techniques. Optimization refers to the 5.

(10) improvement of existing techniques to achieve better results. Generalization refers to the application of existing techniques to different domains and integration refers to the combination of several existing techniques to create more effective techniques. Aim One: Exploring Cognitive Enhancement through Teaching Programs 1. Topic: The Design of New Teaching Model of Neuroanatomy to Prevent Neurophobia in Preclinical Medical Students. 2. This study aimed to further explore cognitive enhancement effects through the implementation of virtual reality technology into the teaching curriculum of neuroanatomy, especially to overcome neurophobia. Aim Two: Exploring Cognitive Enhancement through Learning Programs 1. Topic: Six-month abacus training improves working memory performance in children: a functional MRI and behavior study. 2. Exam the effects of short term abacus training on brain structure, activation pattern and behavior, as a potential learning program to improve working memory.. 6.

(11) References Buonomano, D. V. & Merzenich, M. M. Temporal information transformed into a spatial code by a neural network with realistic properties. Science 267, 1028–1030 (1995). Clark, Ruth C. Building expertise: Cognitive methods for training and performance improvement. John Wiley & Sons, 2008. Colvin, Robert. "Optimising, generalising and integrating educational practice using neuroscience." npj Science of Learning 1.1 (2016): 1-4. Farah, Martha J. "The unknowns of cognitive enhancement." Science 350.6259 (2015): 379-380. Feiler, Jacob B., and Maureen E. Stabio. "Three pillars of educational neuroscience from three decades of literature." Trends in neuroscience and education 13 (2018): 17-25. Feldman Daniel, E. “The spike-timing dependence of plasticity.” Neuron 75, 556–571 (2012). Goswami, Usha. "Neuroscience and education: from research to practice?." Nature reviews neuroscience 7.5 (2006): 406-413. Meltzoff, Andrew N., et al. "Foundations for a new science of learning." science 325.5938 (2009): 284-288. Murphy, M., Reid, K., Hilton, D. J. & Bartlett, P. F. “Generation of sensory neurons is stimulated by leukemia inhibitory factor.” Proc. Natl Acad. Sci. USA 88, 3498–3501 (1991). Sachdev, Perminder S., et al. "Classifying neurocognitive disorders: the DSM-5 approach." Nature Reviews Neurology 10.11 (2014): 634. Savulescu, J., R. ter Meulen, and G. Kahane, eds. 2011. Enhancing human capacities. Oxford: Wiley Blackwell. Sweller, John. "Cognitive load during problem solving: Effects on learning." Cognitive science 12.2 (1988): 257-285. Varma, Sashank, Bruce D. McCandliss, and Daniel L. Schwartz. "Scientific and pragmatic challenges for bridging education and neuroscience." Educational researcher 37.3 (2008): 140-152. Vukovic, J. et al. Immature doublecortin-positive hippocampal neurons are important for learning but not for remembering. J. Neurosci. 33, 6603–6613 (2013). Young, John Q., et al. "Cognitive load theory: implications for medical education: AMEE Guide No. 86." Medical teacher 36.5 (2014): 371-384. Savulescu, Julian, Ruud Ter Meulen, and Guy Kahane, eds. Enhancing human capacities. John Wiley & Sons, 2011.. 7.

(12) Beddington, J., Cooper, C.L., Field, J., Goswami, U., Huppert, F.A., Jenkins, R. et al. (2008). The mental wealth of nations. Nature, 455, 1057–60. Schermer, M. 2012. Van genezen naar verbeteren. Inaugural lecture. Rotterdam: Erasmus Medical Centre. Kass, L. 2002. Life, liberty and the defense of dignity. San Francisco, CA: Encounter Books. Fukuyama, F. 2003. Our posthuman future: Consequences of the biotechnology revolution. London: Profile Books.. 8.

(13) 【Chapter 2】Exploring Cognitive Enhancement through Teaching Programs The Design of New Teaching Model of Neuroanatomy to Prevent Neurophobia in Preclinical Medical Students. Abstract Human anatomy has been regarded as the keystone of medical knowledge for centuries. Cadaver dissection is the prevailing pedagogy adopted in most medical schools for anatomy learning. However, with the rise of new computer technology, radiology and digital medical images provide an alternative perspective to approach human anatomy. Hence, “Can traditional cadaver dissection be replaced by new computer-based anatomy teaching?” must be inquired. Here, we also try to explore the role of virtual reality in anatomy teaching. This study reviews and analyzes the current literatures in terms of anatomy education worldwide. We aim to look into the challenges most medical students confront in learning anatomy, and further provide a valid teaching strategy to diminish the current gap in between basic and clinical anatomy. Background: Neurophobia, being described as “a fear of the clinical neurosciences”, is a longstanding problem among preclinical medical students. The lack of knowledge in the complexity of neuroanatomy is regarded as one of the most important reasons. Therefore, a new teaching model of neuroanatomy was developed. Summary of work: We combined traditional method and contemporary virtual reality technologies to design this new teaching model of neuroanatomy, including anatomical atlas sketch, pretest and posttest of reading brain computed tomography scans, and teaching with dextroscope. During July 2009 and July 2010, fifty-five medical students in Taipei Medical University Hospital were enrolled in our study. Summary of results: The significant improvement between the mean scores of pretest and posttest was observed. Questionnaire results revealed that most of the students express strong positive attitude toward learning in dextroscope, and the teaching model of neuroanatomy. Moreover, they also showed more confidence on learning neuroanatomy after being taught with dextroscope. Conclusion: A carefully designed teaching model of neuroanatomy could possibly help medical students to overcome neurophobia. Besides, dextroscope is a friendly learning environment of virtual reality. Take-home messages: The traditional method of teaching neuroanatomy could be integrated with new virtual reality technologies to innovate a curriculum of the future. Keywords: anatomy education, cadaver, computer, clinical anatomy, virtual reality 9.

(14) Introduction Anatomy has been the fundamental medical knowledge for centuries since renaissance, but the teaching of anatomy is facing significant challenges in recent years. A great leap in the development of digital medical images has provided new ways to see through the structure of the human body. With the rapid advances in information technology, the role of diagnostic radiography in anatomy education is expanding [1]. Many reports had pointed out the potential roles of digital medical images to enhance the teaching and learning of anatomy [1, 2]. However, there is a developing debate on methods of teaching anatomy. The use of cadaver dissection is still a traditional and important part in the Anatomy course for medical students. But, could it be totally replaced by computerized anatomy resources, (including diverse software and websites)? Rapid evolution of three-dimensional images technologies has made virtual environments (VEs) possible in recent years. The applications of virtual reality (VR) on health care are diverse, including surgical planning and simulation, medical education, patient simulator, psychological assessment, rehabilitation, bronchoscopy, et al [4]. The applications of virtual reality (VR) in surgery include anatomy education, preoperative planning and simulation, and assessment of surgical skills. The results of applications of VR techniques in preoperative planning and simulation are promising, especially for laparoscopic surgery and neurosurgery [4, 5, 6]. The task performance in simulator is strongly correlated to daily surgical performance [7]. The implementation of VR in anatomy education also has great potential, but could it influence the learning of reading skills of diagnostic images for medical students? Moreover, the role of virtual reality (VR) in the teaching of anatomy is revolutionary and with great potential [3, 4]. Since the Visible Human Project (VHP) launched by the US National Library of Medicine in 1988[11], it allowed the developments of various VR 3-D models. The most renown is the Visible Human 3D Anatomical Structure Viewer (EPA Lausanne) [12]. 3-D visualization of clinical diagnostic images allows a deeper understanding of spatial relationships between deep structures that hardly can be achieved by other teaching methods [4]. Taking brain neuroanatomy as an example, trainees thus can see the sophisticated and delicate neural structures by dynamic dissections from various directions with the help of VR. VR definitely improve the learning of anatomy. But, could the VR techniques influence the learning of reading skills of radiological anatomy (diagnostic images) for medical students? Radiological anatomy is totally different from gross anatomy. Medical images are another representation of gross anatomy, and anatomy knowledge gathered from dissections always needs being translated into cross-sectional views of clinical images [11]. That is why students often feel frustrated while reading cross-sectional clinical images (such as, brain computed tomography scans) at the first moment.. 10.

(15) Therefore, appropriate learning scaffolds are needed as the bridges of knowledge among those different representations of anatomy. The learning of reading brain computed tomography (CT) scans is a critical step in studying clinical neuroscience, but it seems to be a major obstacle to medical students. The most difficult parts are lack of the acquaintance of medical terms and 3-D concepts of neuroanatomy. Therefore, we are developing a new model of teaching clinical neuroanatomy for preclinical medical students. The teaching model includes sketch of atlas of neuroanatomy, self-directed learning of reading brain computed tomography (CT) scans, and implement of dextroscope. We are in the hope to teach gross anatomy in the context of clinical setting. Sketch is an unique skill commonly used in medicine, and it is especially important in the training of surgery. Students have to recognize what structures they are going to sketch, and allocate them in a proper position after knowing the spatial relationship between neural structures. Sketch could help students to recall the unfamiliar and difficult neuroanatomical terms, and restructures 3-D concepts of neuroanatomy inside students’ minds. Dextroscope (Volume Interactions, Ltd., Singapore) is a virtual reality system for preoperative planning and simulation of surgery. Patient-oriented and fused medical images are presented stereoscopically and the fused images can be manipulated freely from various dimensions. Some degree of simulation of bone drilling and brain retraction can be implemented in the dextroscope. With the help of dextroscope, students can trace vascular and neural structures in dynamic serial images, and further establish a deep understanding of the spatial relationships between individual structures. This new model of teaching clinical neuroanatomy definitely encourage students to learn clinical neuroanatomy in a more interesting and promising way. However, we also want to see if we could improve the learning of reading skills of brain computed tomography (CT) scans with the help of dextroscope ? Part of the aim of our study is to see if VR can improve students’ confidence of reading brain CT scans. What is Neurophobia? Neurophobia is described as “the fear of clinical neurosciences”. It is a worldwide phenomenon among medical students [13]. Neurological diseases are becoming more and more popular. Brain computed tomography (CT) scans gave become a regular and screening scans for diagnosing neurological problems. Learning to read brain CT scans is the crucial first step to learn clinical neurosciences. However, atlas in anatomical textbooks and brain CT images are different representations of neural structures. Medical Students’ memory battery for neuroanatomy is very poor. Students have difficulty to have far transfer of anatomical knowledge, which was learned years ago. Therefore, an integrated program is needed to path the ways for the learning of basic and radiological neuroanatomy. The aim of this study was to evaluate the impact of dextroscope on. 11.

(16) the learning of radiological neuroanatomy, and to verify that if virtual reality simulator, dextroscope, could help the learning of reading brain computed tomography scans.. Methods Sixty-five preclinical medical students in Taipei Medical University Hospital were enrolled in this study. All of the successive students rotate in the department of neurosurgery for two weeks, and they are divided into two groups. The implement of dextroscope is used as a treatment for the students of the group one. Thirty-five students are in the group one, and the timetable of teaching activities is as the following. On day1, and day 2 of the rotation, students are asked to sketch atlas of basal ganglia and brain stem, and the terms of neuroanatomy structures will be indicated. Then they need to complete a self-study brain CT scans test (including fifty questions), as the pretest, during the first week rotation, and their answers will be discussed with teacher on the 8th day. Dextroscope will be taught for one hour on day 5 and another hour on day 13 of the rotation. The post-test of brain CT scans is held on day 13 after the teaching of dextroscope finished. Thirty students are in the group two, and the timetable of teaching activities is as the following. On day1, and day 2 of the rotation, students are asked to sketch atlas of basal ganglia and brain stem, and the terms of neuroanatomy structures will be indicated. Then they need to complete a self-study brain CT scans test (including 50 questions), as the pretest, during the first week rotation, and their answers will be discussed with teacher on the 8th day. The post-test of brain CT scans is held on day 13. Dextroscope will be taught for one hour, as salvage instruction, only after the post-test of brain CT scans being finished. Learning attitude questionnaire and self-confidence questionnaire are completed after the rotation. Degree of satisfaction is divided into five grades. The fifty questions of pretest of brain CT scans include thirty questions of neuroanatomy and twenty basic clinical questions. Full score of the fifty questions is one hundred. The composition of the fifty post-test questions is slightly different from the pretest’s. Seven advanced clinical questions are added, and they are deployed to indicate the problem-solving ability of students. Therefore, the fifty post-test questions are composed of twenty-six questions of neuroanatomy, seventeen basic clinical questions, and seven advanced clinical questions. Full score of the post-test is also one hundred.. 12.

(17) Results Table 1. Results of sixty-five students Mean SD. Rate of correct Answers. Pre-test. 71.29. 8.4. Post-test. 89.91. 6.3. Clin. A (7tests). 8.46. 2.42. 60%. Clin. B (17tests). 31.94. 2.74. 94%. Anat. (26tests). 49.24. 3.47. 95%. Full mark : 100. E.S. (Cohen’s D): 2.53 : huge effect size.. Table 2. Results of different groups. Treatment. Pretest score. Post-test score. Score Increment. Group one. With Dextroscope (35 students). 71.9. 90.0. 18.1. Group two. Without Dextroscope (30 students). 66.8. 87.9. 21.0. 13.

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(20) Discussion Besides cadavers and dissecting room, there are emerging methods of teaching gross anatomy with the generalization and advance of computer technology [1, 2, 3, 4]. But, could cadaver dissection be totally replaced by computerized anatomy resources? Biasutto et al. (2006) argued that there were no objective and scientific data to prove the superiority of computerized resources over cadaver dissection, and demonstrated that the best way of teaching anatomy is the combination of cadaver dissection and computerized materials [2]. There are three major applications of virtual reality (VR) on health care: anatomy education, simulation of operation, and radiology education. The application of virtual reality (VR) has led anatomy education into different horizon [3, 4, 5]. Through interactive 3-D graphics, students can explore internal structures in various dimensions. Anatomical structures are represented in dynamic images, and it allows trainees to trace all kinds of tissues from multiple viewpoints [4]. Therefore, students can attain a deeper understanding of spatial relationships between different structures that cannot be achieved by other teaching methods. The simulation of operation in virtual reality (VR) environments has been introduced successfully in recent years, especially in laparoscopic surgery and neurosurgery [4, 5, 6, 8, 9, 10]. With the advances of endovascular techniques and radiosurgery, there are more alternative methods of treating cerebral aneurysms or skull base tumors. The decrease of open operative cases is making young neurosurgeons more difficult to develop their surgical skills [8]. VR technologies provide a no-risk environment for preoperative rehearsal, and it allows residents to simulate operation preoperatively. Therefore, neurosurgeon can somehow keep experienced in those rare and complicated surgeries with the implement of VR technologies. Nonetheless, virtual reality is never like actual surgery. It allows some degree of rehearsal of bone drilling, brain retraction, and simulation of possible trajectory and probable difficulties encountered during operation. However, all of these advantages are the initial steps of performing surgery. In real life, the unpredictability during actual operation is more challenging. The experience in computerized simulator could not offer similar tactile and emotional training from the real world experience. Significant progresses in medical imaging in recent years have enhanced the potential role of radiology over anatomy education. Since the introduction of Visible Human Project (VHP) by National Library of Medicine (NLM) in 1988[26], digital diagnostic images can be processed in various ways. Medical images are restructured in 3D style, and it has made virtual reality resources available for radiology education. Students now can see the structures in a more comprehensive way, and spatial relationships between structures could be realized nearly without any limitation. But, could the VR techniques improve the learning of reading skills of clinical images, ex. brain CT scans, for trainees?. 16.

(21) The design of our new teaching model for neuroanatomy adopted sketch (the traditional learning method) and dextroscope (VR technology) to facilitate students’ learning of reading brain CT scans. From our preliminary results, there are no differences of average marks and improvement between study and control group. The treatment for this teaching model, dextroscope, seems to have no role on the learning of reading brain CT scans. However, based on the primitive results of the learning attitude questionnaire and self-confidence questionnaire, students do feel direct help and deeper understanding of spatial relationships between structures from the teaching of dextroscope, and they also show more confidences on the following learning of clinical neuroscience. The significant improvement between the mean scores of pretest and posttest was observed. Questionnaire results revealed that most of the students express strong positive attitude toward learning in dextroscope, and the teaching model of neuroanatomy. Moreover, they also showed more confidence on learning neuroanatomy after being taught with dextroscope.. Conclusion Our new teaching model for neuroanatomy seems to enhance the learning of reading brain CT scans. A carefully designed teaching model of neuroanatomy could possibly help medical students to overcome neurophobia. Besides, dextroscope is a friendly learning environment of virtual reality. Therefore, the traditional method of teaching neuroanatomy could be integrated with new virtual reality technologies to innovate a curriculum of the future.. 17.

(22) References 1. Miles, R.A. (2005). Diagnostic imaging in undergraduate medical education: an expanding role. Clin Radiol., 60(7):742-5. 2. Biasutto S.N. et al. (2006). Teaching anatomy: cadavers vs. computers? Ann Anat., 188(2):187-90. 3. Dobson HD, Pearl RK, Orsay CP, Rasmussen M, Evenhouse R, Ai Z, et al. Virtual reality: new method of teaching anorectal and pelvic floor anatomy. Dis Colon Rectum 2003; 46 (3):349-52. 4. Riva G. Applications of Virtual Environments in Medicine. Methods Inf Med 2003; 42: 524–3 5. Hart R. and Karthigasu K. The benefits of virtual reality simulator training for laparoscopic surgery. Current Opinion in Obstetrics and Gynecology 2007, 19:297–302 6. Stadie, A.T. Virtual reality system for planning minimally invasive neurosurgery. J Neurosurg 108:382–394, 2008 7. Gorman P.J. et al. Simulation and Virtual Reality in Surgical Education Real or Unreal? Arch Surg. 1999;134:1203-1208 8. Anil S.M. et al. (2005). Virtual 3-dimensional preoperative planning with the dextroscope for excision of a 4th ventricular ependymoma. Minim Invas Neurosurg 50: 65 – 70 9. Wong G.K.C. et al. (2007). Craniotomy and clipping of intracranial aneurysm in a stereoscopic virtual reality environment. Neurosurgery 61:564–569 10. Kockro R.A. et al. (2009).Virtual temporal bone: an interactive 3-dimentional learning aid for cranial base surgery. Neurosurgery 64[ONS Suppl 2]:ons216–ons230 11. Visible Human Project (VHP) page of the NLM: (http://www.nlm.nih.gov/research/visible/) 12. Visible Human 3D Anatomical Structure Viewer (EPA Lausanne):http://visiblehuman. epfl.ch/applet3D.php 13. Zinchuk A.V. et al. (2010). Attitudes of US medical trainees towards neurology education: "Neurophobia" - a global issue. BMC Medical Education, 10:49. 18.

(23) 【Chapter 3】Exploring Cognitive Enhancement through Learning Programs Six-month abacus training improves working memory performance in children: a functional MRI and behavior study. Abstract Abacus experts have demonstrated extraordinary potential of mental calculation. It was reported that non-experts mainly showed activity in the prefrontal and perisylvian areas, while experts with long-term training of at least three to five years, showed more activation over premotor and parietal regions. It has also been reported that abacus-based mental calculation (AMC) training was able to improve the working memory. Nevertheless, most of previous studies adopted cross-sectional designs to evaluate the results. The aims of our study are to evaluate the relatively short term effect of a six-month abacus-based mental calculation (AMC) training on the functional connectivity network, and to investigate the possibility of AMC training effect transferring to untrained working memory tasks. A total of 70 human subjects were assigned to abacus (ABA) or control (CON) groups. The ABA group received 3.5 h AMC training per week for 25 weeks, whereas the control group performed general reading exercises. The total effective training time was 87.5 hours. This longitudinal study utilized standardized tests, including functional MRI (fMRI), and resting state fMRI. The validity and scale of this change were evaluated on both the behavioral level and the functional level under a relatively short-term training curriculum. The results from post-training abacus (ABA) group showed that there were significant improvements in working memory index and serial addition reaction time. Functional MRI results revealed tendency of a shift in the activation when performing mental calculation task from prefrontal to the parietal regions. Regression analysis of functional connectivity and working memory index revealed that there was a significant correlation between working memory index and functional connectivity of left Broca area and left angular gyrus (n = 21, r (19) = 0.429, p = 0.041). The correlation between working memory index and functional connectivity of left Broca area and left inferior frontal gyrus (proximal) also trended toward significance from (n = 21, r (19) = 0.085, p = 0.666) to (n = 21, r (19) = 0.386, p = 0.069). These combined results suggested that six months of AMC training can generalize to improvement on untrained working memory tests, and a midway paradigm shift (paradigm drift) can be expected along the fronto-parietal circuitry within the relatively long time required to become an expert. Compared to the common practice of task repetition, AMC training is a more complex and interesting method of working memory training with a stronger sense of self-accomplishment through its step-by-step training curriculum. AMC is not only an arithmetic operation, but it might also be an appropriate learning tool to improve working memory capabilities by exercising 19.

(24) visuo-motor and visuo-spatial skills, as partially evidenced by the current study. As a result of this educational neuroscience study, we might be able to start taking a different perspective on the traditional Chinese tool for not only calculation but also learning potential in the modern age. Keywords: abacus, abacus-based mental calculation, functional connectivity, resting state, working memory, working memory training. Introduction With a history tracing back various millenniums in different cultures, the abacus is an essential tool to human civilization growth and development. It is also a significant symbol in Chinese culture for trade and calculation. Inscription of Chinese abacus on the Representative List of the Intangible Cultural Heritage of Humanity was announced on December 2013 by UNESCO for its cultural significance and "training in abacus-based mental arithmetic is thought to improve a child’s attention span, memory and mental capability." (1). Abacus experts have demonstrated extraordinary potential of mental calculation (2), and even beginner youths are often expected to improve in attention and mental focus abilities. Past imaging studies show a significant difference between experts and non-experts in brain functional areas when performing mathematical tasks (2-5). Non-experts show activity in the prefrontal and perisylvian areas, while experts with long-term training show more activation over premotor and parietal regions. Most abacus-related studies in the past have cross-sectional designs, comparing abacus experts with non-experts. However, in the current Chinese social norm, with the availability of more active or creative extracurricular courses, very few children have the opportunity or willingness to pursue further abacus training after the initial one to two years, far less than the necessary training to become an expert. Therefore, we are curious about the effects of short-term abacus training on functional and behavioral levels. More importantly, how soon can we expect change after initializing training on the functional level and the behavioral level? Children in Chinese society are encouraged to study for at least six months to one year to become acquainted with abacus-based mental calculation (AMC) and express significant behavioral improvement. The Chinese Abacus Association in Taiwan states that according to past experience, the greatest level of behavioral improvement is shown after six months to one year. Irwing et al. suggested in 2008 a general intelligence improvement after receiving only 34 weeks of abacus training (6). Hu et al. suggested in 2011 potential enhancement on white matter integrity after abacus training for 3 years (7). Takeuchi et al. showed in 2013 that cognitive training can have probable effects on intrinsic brain activity and connectivity (8). Therefore, in this study, we hypothesize potential midway paradigm drift, significant change in visuo-motor and visuo-spatial regional connectivity, and working memory behavioral 20.

(25) improvement within a six-month abacus training period. After deploying standardized tests, functional MRI (fMRI), and resting state MRI (rsMRI), we evaluate the validity and scale of this change on both the behavioral level and the functional level under a relatively short-term training curriculum.. Methods The fMRI scanning experiment of this study was performed in Taipei Wanfang Hospital. The total number of subjects was 70. The duration of this study was about half a year and two fMRI scans will be performed in total. Twenty-seven children in total were excluded from the data analysis due poor quality MR images ( n=27). A total of forty-three healthy right-handed children data were analyzed in this study. The subjects are split into two groups: abacus training (ABA, n=21, 17 females, mean age = 9.61 years) and reading control (CON, n=22, 16 females, mean age = 10.57).. 研究程序:. Figure 1. Research procedures. Two abacus-based mental calculation (AMC) teachers were recruited to provide training for the ABA group over a six-month period. The group received 3.5 hours of training per week (2 hours of teacher-student lessons and 1.5 hours of practice homework) for 25 weeks. The CON group performed general reading exercises for 3.5 hours per week for 25 weeks. The total effective training time was 87.5 hours. 在每次fMRI影像掃描之前，會先在萬芳醫院，進行核磁共振攝影試驗前說明，約需二十分鐘。每次的功能性核磁共振fMRI影像掃描約需四十分鐘，包括第一部分的腦部結構檢查與第二部分執行心算任務時的掃描。在影像掃瞄時所進行的任務 ( task )有兩種，包括簡單與複雜的十個數目字的累加計算能力檢測，以及空間能力檢測。珠心算訓練為期6個月，在受訓期間，每個星期需接受2小時的珠心算訓練，且每天您須自 21.

(26) 主練習由試驗主持人所提供的珠心算練習題，每天20分鐘至30分鐘。且在受訓期間，您不能接受其他心智或學術的訓練課程。在珠心算訓練六個月後，將立即進行第二次的功能性核磁共振fMRI攝影。. 試驗程序 □ 第一次核磁共振攝影試驗前說明：約需 20 分鐘 □ 第一次核磁共振攝影：約需 40 分鐘 □ 第一次數算能力及空間能力測驗：約需 30 分鐘 □ 第一次工作記憶能力測驗：約需 30 分鐘 □ 家庭與學習背景問卷調查：約需 20 分鐘 □ 珠心算訓練：6 個月 □ □ □ □. 第二次核磁共振攝影試驗前說明：約需 20 分鐘第二次核磁共振攝影：約需 40 分鐘第二次數算能力及空間能力測驗：約需 30 分鐘第二次工作記憶能力測驗：約需 30 分鐘. MRI 試驗程序 Table 1. MRI experiment procedures. The subjects were examined with fMRI, rs-fMRI functional connectivity (FC), and behavioral exams before and after the six-month training period. Abacus rating exams for the ABA group were provided at the end of the training period by the Chinese Abacus Association.. Image acquisition and preprocessing The subjects were asked to perform a simple serial addition task (SSA) during the fMRI scan. The task initialized with the presentation of a crosshair of 15 seconds, followed by a control or 22.

(27) task period of 24 seconds. There were four control and four task blocks in a run. The control block included ten eight-digit random numbers presented in series with frequency of 0.5 Hz and subjects were required to gaze at the numbers without calculation. The block was then ended by a 4-s period of presenting two numbers and the subjects were asked to randomly select one number by a mouse-click. The task session presented ten random one-digit numbers with the same frequency and the subjects were instructed to sum the presented digits. At the end of each task block, the subjects were asked to select by mouse-click the correct sum from a 4-s queue of two numbers. During the rs-fMRI scan, subjects were instructed to keep their eyes closed, remain clear-minded, and think of nothing in particular.. Table 2. Experimental design of the task.. The fMRI images were acquired with a 1.5 T MAGNETOM Avanto system (Siemens Healthcare, Erlangen, Germany) using a T2*-weighted gradient-echo echo-planar imaging (EPI) sequence (TR/TE/FA = 3000 ms/50 ms/90°). For each subject, 104 volumes of 20 axial slices per volume were acquired. Resting state acquisitions were performed with the same sequence and parameters except TR = 2000 ms and total volume = 180. Functional images analyses were performed by using SPM5 (9) and REST (10). The EPI data was realigned and spatially normalized into MNI template, then smoothed with a Gaussian kernel of 6 mm. Functional activations were obtained by modeling the data with GLM and group results were analyzed using one sample t-test. For rs-fMRI, after preprocessing, FC images underwent seed-based correlation analysis. Left prefrontal seeds were selected from the results of a task-related fMRI pilot study (11) (Table 1) including left fronto-insular cortex and left Broca area (LBA). The correlated results were transformed to approximate Gaussian distribution using Fisher’s z transformation. Between-group and within-group comparisons were assessed by two-sample and paired t-tests, respectively. For regression analysis, the ROIs were selected from 23.

(28) activated prefrontal and parietal clusters within left inferior frontal gyrus (LIFG) and left angular gyrus (LAG), respectively, as determined using the anatomical automatic labeling (AAL) template (12).. Behavioral measures. After each image acquisition, the WISC-IV exam’s working memory subtasks (including digit span, letter-number sequencing, and arithmetic subtests) were deployed to examine the subjects’ working memory capabilities, and an anxiety score questionnaire was used to evaluate the level of anxiety the subjects felt towards mathematical processing and towards the MRI examination.. Statistical analysis Paired two-tailed t-tests were performed to compare the differences of means between pre- and post-intervention tests. Meanwhile, the effect size is specifically computed by using Cohen’s d coefficient. Behavioral and functional conectivity correlations were performed using Spearman’s rank correlation.. 24.

(29) Results Behavioral results Table 3. Working memory performance results of the ABA and CON group Memory span. Number sequence. Math.. WM Index. ABA, Pren=21 intervention. 10.38 ± 3.07. 9.43 ± 3.88. 9.35 ± 2.68. 125.00 ± 23.77. Postintervention. 10.90 ± 2.81. 10.33 ± 2.48 9.95 ± 2.65. 131.35 ± 19.14. ∆. 0.52. 0.90. 0.60. 6.35. ∆ (%). 5.05 %. 9.60 %. 6.42 %. 5.08 %. P-value. 0.2129. 0.1811. 0.1020. 0.0369. Cohen’s d. 0.09. 0.28. 0.23. 0.30. 10.32 ± 3.54. 10.00 ± 3.01 8.82 ± 3.20. 126.68 ± 22.92. 10.82 ± 3.30. 10.50 ± 2.50 9.32 ± 3.15. 129.95 ± 21.62. CON, n=22. Preintervention Postintervention ∆. 0.50. 0.50. 0.50. 2.91. ∆ (%). 4.85 %. 5.00 %. 5.67 %. 2.30 %. P-value. 0.2207. 0.4026. 0.5807. 0.4475. Cohen’s d. 0.15. 0.18. 0.16. 0.15. On the IQ test WISC-IV exam’s working memory subsection, the Abacus group (n = 21) advanced 6.35 marks (from 125 to 131.35) on working memory index (WMI). The WMI results revealed significant change after training (p = 0.0369 < 0.05, Cohen's d = 0.30). Meanwhile, the control group did not revealed significant change(p = 0.4475, Cohen's d = 0.15), and it advanced only 2.91 marks (126.68 to 129.59) on WMI (Table 1). Furthermore, the abacus group expressed 1.8 times higher improvement, compared to the control group, in the word-number sequencing subtest, and it makes a 9.60% increase (9.43 to 10.33,) while the CON group made a 5.00% improvement (10.00 to 10.50). 25.

(30) The ABA group also demonstrated greater growth in the arithmetic subtest than the control group. Additionally, neither group showed significant improvement in the memory span subtest. ABA group (n = 21) showed more concentrated distribution on box-plot, compared to CON group. (Fig. 2) In conclusion, the abacus group showed to have a better working memory performance after abacus training for six months, and expresses significant improvement on working memory index (WMI). The abacus group showed a higher post-intervention improvement in the word-number sequencing subtest, which contributes mostly to the better working memory performance, compared to the other two subtests.. Figure 2. WISC-IV exam’s working memory subsection (working memory percentile). In working memory expression, the ABA group exhibited more concentrated distribution on the boxplot after 6-month intervention.. 26.

(31) Serial addition Table 4. Simple Serial Addition (SSA) and Complex Serial Addition (CSA) assessment results of the ABA and CON group. SSA Accuracy ABA, n=21. SSA Reaction time. CSA Accuracy. CSA Reaction time. Pre68 % ± 23 % 1990.56 ± 497.83 62% ± 27 % 2096.85 ± 544.71 intervention Post79 % ± 21 % 1618.83 ± 447.76 62% ± 26 % 2034.21 ± 556.00 intervention. CON, n=22. ∆. 10.53 %. -371.73. 0%. -62.64. ∆ (%). 15.38 %. -18.67 %. 0%. -2.99 %. P-value. 0.1489. 0.0082. 0.8770. 0.5153. Cohen’s d. 0.51. 0.81. 0. 0.12. Pre66 % ± 27 % 1886.94 ± 703.03 59 % ± 27 % 2078.03 ± 715.62 intervention Post78 % ± 19 % 1876.33 ± 566.84 70 % ± 20 % 2275.22 ± 406.64 intervention ∆. 12.50 %. -10.60. 11 %. 197.19. ∆ (%). 18.97 %. -0.56 %. 19.23 %. 9.49 %. P-value. 0.0873. 0.406. 0.1828. 0.5446. Cohen’s d. 0.53. 0.02. 0.47. 0.35. There was major improvement in SSA accuracy in both abacus (p=0.1489; Cohen’s d=0.51) and control group (p=0.0873; Cohen’s d=0.53) and significant improvement of SSA reaction time in abacus group (p=0.0082<0.05; Cohen’s d=0.81). On the other hand, for the control group there was an 19.23% improvement in the CSA accuracy (p = 0.1828; Cohen’s d=0.47), but also 9.49% increment of the reaction time (p=0.5446; Cohen’s d=0.35). Furthermore, the abacus group showed an 2.99% improvement in CSA reaction time (p=0.5153; Cohen’s d=0.12).. 27.

(32) Anxiety score (AS) Table 5. Anxiety score assessment result of ABA and CON group AS (Prescan) ABA, n=21. CON, n=22. AS (Math). AS (Total). Pre4.55 ± 2.70 intervention. 3.15 ± 3.08. 7.33 ± 5.22. Post2.81 ± 2.56 intervention. 2.52 ± 2.60. 5.33 ± 3.95. Δ. -1.74. -0.626. -2. Δ%. -38.24 %. -19.87 %. -27.27 %. P-value. 0.0081. 0.3506. 0.0513. Cohen’s d. 0.68. 0.23. 0.44. Pre4.26 ± 3.07 intervention. 3.29 ± 2.26. 6.83 ± 4.53. Post2.18 ± 2.65 Intervention. 3.45 ± 3.62. 5.64 ± 5.60. Δ. -2.08. 0.17. -1.20. Δ%. -48.82 %. 5.02 %. -17.52 %. P-value. 0.0131. 0.6170. 0.4571. Cohen’s d. 0.74. 0.05. 0.24. Generally, there was a reduction of anxiety score in both abacus and control group which include all tested prescan, math and total anxiety score, except for the math anxiety score of the control group. There were also significant reductions on the prescan anxiety score in both abacus (p=0.0081, Cohen’s d=0.68) and control group (p=0.0131, Cohen’s d=0.74).. 28.

(33) Neuroimage fMRI: Pre-training data suggested bilateral prefrontal activation during the SSA task, specifically activation over bilateral insular cortices were shown. Post-training data showed similar regional results, and the abacus training group showed increased parietal activation (Table 7). However, when 2-sample paired t-test was performed to verify this change, no significance was found (Fig. 3). rs-fMRI-FC: Functional connectivity analysis of the resting state data showed fairly similar connection network among specific fronto-parietal ROIs. Paired t-test of the ABA group revealed increased connectivity between left Broca area and inferior parietal lobe after AMC training intervention (Fig. 4, Table 8). Table 6. Significant prefrontal activations during BOLD serial addition task in the pilot study pre-AMC training intervention. Table 7. Significant activations of the prefrontal-prefrontal- parasylvian network during BOLD serial addition task in ABA and CON groups before and after AMC training invention.. The MNI coordinates and t-values correspond to the local maxima of the voxel clusters. The statistical threshold was set at p < 0.005 using Alphasim correction (with combination of threshold of p < 0.001 and minimum cluster size of 12 voxels) for the ABA group pre-intervention, p < 0.05 using FDR correction for the others.. 29.

(34) Table 8. Significant clusters of the two-sample paired T-test within the ABA group before and after AMC training intervention. The functional connectivity seed was placed at the left Broca area (x=-39, y=24, z=15, radius = 5 mm). The MNI coordinates and t-values correspond to the local maxima of the centers of voxel clusters. The statistical threshold was set at p < 0.05 using AlphaSim correction (with combination of threshold of p < 0.001 and minimum cluster size of 12 voxels).. Figure 3. General pattern of activity during the serial addition task for ABA and CON groups. (A) Pre-intervention activity is mainly in the prefrontal region. (B) A general increase in post-intervention activity can be found. (C) When the within group analysis is performed with FDR correction, a shift in post-intervention activation to the parietal regions is suggested in the ABA group. However, no significance is found when two-sample paired t-test is performed. The 30.

(35) statistical threshold was set up at p < 0.05 using AlphaSim correction (with combination of threshold of p<0.001 and minimum cluster size of 12 voxels) and set at p < 0.05 using FDR correction.. Figure 4. Resting state functional connectivity findings. The pattern of significant positive correlations between the Broca area seed (x=-39, y=24, x=15, radius=5 mm) and the fronto-parietal network is seen in both the ABA and CON groups. Significance in two-sample paired t-test indicates increased functional connectivity between LBA and bilateral inferior parietal lobules in the ABA group after AMC training intervention. The statistical threshold was set up p < 0.05 FWE correction for the within group analyses and using AlphaSim correction (with combination of threshold p < 0.001 and minimum cluster size of 12 voxels) for the two sample paired t-test.. 31.

(36) Figure 5. Correlations of functional connectivity and working memory index. Scatterplots show the relationship between working memory scores and functional connectivity of left Broca area with two different cortical areas, both for the abacus and control groups. The vertical axis measures the values of functional connectivity, and the horizontal axis represents the raw scores of working memory index. Proximal (pre-training and post-training) represents functional connectivity between left Broca area and left inferior frontal gyrus. Distal (pre-training and post-training) represents functional connectivity between left Broca area and left angular gyrus. (A and C) Functional connectivity of pre-training groups did not correlate with working memory performance. (B) In post-training abacus group, correlation between working memory index and functional connectivity of left Broca area and left inferior frontal gyrus 〔n = 21, r (19) = 0.386, p = 0.069〕 trended toward significance. (D) There is a significant correlation between working memory index and functional connectivity of left Broca area and left angular gyrus 〔n = 21, r (19) = 0.429, p = 0.041〕in post-training abacus group.. 32.

(37) Table 9. Correlations between functional connectivity and working memory index WMI, ABA group Functional connectivity. WMI, CON group. Coefficient P-value Coefficient P-value 0.085. 0.666. 0.135. 0.502. Proximal-Post training (max) 0.386. 0.069. 0.038. 0.849. Proximal-Pre training (max). Distal-Pre training (max). -0.019. 0.925. 0.281. 0.156. Distal-Post training (max). 0.429. 0.041. -0.249. 0.201. Functional connectivity of left broca area and left inferior frontal gyrus (proximal). Functional connectivity of left broca area and left angular gyrus (distal). In the abacus group there was a significant increase of correlation between working memory index and post-training functional connectivity of left Broca area and left angular gyrus (distal) (Table 1). It increased from (n = 21, r (19) = -0.019, p = 0. 925) to (n = 21, r (19) = 0.429, p = 0.041). The correlation between working memory index and functional connectivity of left Broca area and left inferior frontal gyrus (proximal) in post-training abacus group also trended toward significance (Table 1) from (n = 21, r (19) = 0.085, p = 0.666) to (n = 21, r (19) = 0.386, p = 0.069). Comparatively, the control group revealed limited to no change in correlation between functional connectivity and working memory index after intervention.. Discussion The goals of our study are as following: (1) to evaluate the relatively short term effect of six-months abacus-based mental calculation (AMC) training on the functional connectivity network, and (2) to prove the possibility of AMC training effect transfer to the untrained working memory task. In the past decade, several reports of training on AMC have demonstrated distinct brain activations differences between experts and novices (2-5). All of the abacus-related reports are cross-sectional designs. On functional MRI results, non-experts show activity in the prefrontal and perisylvian areas, while experts with long-term training show more activation over premotor and superior parietal regions. In recent years, structural and functional connectivity were deployed to study brain intrinsic integrity in children with 3-year training of the AMC (7,13). Increased integrity in white matter 33.

(38) tracts were observed over right premotor cortex, corpus callosum, and left occipito-temporal junction. The findings also suggested long-term abacus training may improve working memory capacity (7). Resting state MRI (rsMRI) revealed enhanced connectivity between right supplementary motor area (SMA), and right inferior frontal gyrus (IFG), suggesting more extensive engagement of visuo-spatial-attention networks in trained subjects while performing numerical working memory task (13). Multiple cortices on functional MRI were involved, including IFG, SMA, posterior superior parietal gyrus (PSP), and superior occipital gyrus, and it implied the long-term abacus training effects could be transferred to the untrained working memory task. Most past studies focus on cross-sectional analysis of abacus experts and non-experts, but neglect the potential midway paradigm shift (paradigm drift) within the relatively long time required to become an expert. But, how soon can we expect changes after initializing training on the functional level and the behavioral level? The Chinese Abacus Association in Taiwan states that in past experience, the initial greatest level of behavioral improvement can be expected in training periods between six months to one year, implying functional changes may be in place before physical changes become detectable. Our current study seems to corroborate the aforementioned the self-evident observation in terms of brain functionality and connectivity. Stigler's study in 1986 revealed children after one year AMC training could develop the ability of mental abacus (14). Irwing's report in 2008 suggested a general intelligence improvement after receiving only 34 weeks of abacus training (6). Therefore, we assume that 6 months is the minimum period required for the change. In present study, a uniquely longitudinal study was deployed, and we hypothesized significant changes in visuo-motor and visuo-spatial regional (fronto-parietal) functional connectivity and working memory behavioral expression within a six-month abacus training period. The WISC-IV exam’s working memory subsection was used to examine the trained subjects’ working memory capabilities, and to evaluate the possibility of transfer of AMC training effect. After deploying a longitudinal study, utilizing standardized behavioral tests, functional MRI, and resting state MRI, we evaluate the validity and scale of this potential change on both the behavioral level and the functional level under a relatively short-term training curriculum. Elaboration of results Behaviorally, the ABA group children exhibited significant improvement in working memory test after training, comparing to no improvement in control group, and showed significantly decreased reaction time when presented with the serial addition task. Younger subjects showed stronger advances in digit span and letter-number sequencing, as well as greater overall working memory competency improvement. Subjects who performed more poorly on pre-intervention tests experienced significantly stronger improvement in the letter-number sequencing subtest, arithmetic subtest, and overall working memory placement as a whole. Additionally, the ABA group children expressed a decrease in anxiety towards arithmetic processing. 34.

(39) On the functional level, the ABA group expressed stronger activations post-training, and within-group analysis confirms our hypothesis of a partial paradigm shift (paradigm drift) of activation zones to the inferior parietal region. Functional connectivity analysis revealed increased connectivity between the left Broca area (LBA) and the inferior parietal lobe. Association between behavioral expression and neuroimages showed increased correlation between LBA-LIFG connectivity and working memory grading after training, and LBA-LAG connectivity increases greatly in correlation to working memory grading. Our results demonstrated improvements on both neuroimages and behavioral level could be observed in a relative short term (6 months) intervention, compared to the necessary training time to become an expert or experienced practitioner of AMC. Furthermore, the AMC training effect can be generalized to the untrained task, the WISC-IV exam’s working memory subsection. What the nature of AMC training entails? Traditionally, abacus training was taken as a training of mental calculation, focusing on both computation speed and accuracy. AMC training in Taiwan is also a step-by-step process and its learning can be described through three stages of advancement. Stages of AMC training: i. The stage of basic abacus operation (1~3 months): Oral formulas and principles of beads movement were given by instructors, and actual abacus operation was practiced repeatedly. Thus, the mental model of calculation with an abacus physical aide is introduced gradually. The operator usually become acquainted with and ii.. iii.. experienced with the physical operation within the initial three months. The stage of beginner mental abacus (6~12 months): “Beginners at mental abacus calculation move their fingers in the air to aid in moving the mentally imaged beads.”14 Intermediate operators are highly reliant on motor movements of fingers to aid in mental calculation, and the limitation of motor movements or oral distractions greatly affect the response accuracy15. Within timely practice, operators become able to add and subtract without the instrument, but the size of their mental abacus is limited16. Children usually reach this stage after about 6-12 months of training. Paper abacus? The stage of advanced mental abacus (≧12 months): As they progress, experienced operators are able to perform mental calculations by imaginary movements of beads. The operation is exactly as they would do on a real abacus, involving only visual representation without physical or motor assistance15. This progress can usually be seen after one year of training14.. After the student is experienced in the practice of a mental abacus without motor aide, the series size of computation and number of digits are gradually increased. Eventually, abacus experts 35.

(40) become capable of executing extraordinary volumes of computation with great accuracy in compressed time. Traditionally, AMC training is viewed as a training of mental calculation, focused on computation speed and accuracy, but a glance at the steps of learning and performance progression of AMC operators and a modern knowledge of cognitive functions show the training scheme as focused on two main abilities, the initial a visuo-motor coding scheme for transforming numbers into images of beads (17), then the visuo-spatial ability focused on proceduralizing and expanding the operator’s memory span. Simply put, memory span is increased gradually during the progress of AMC training. Thus, AMC should be viewed as a unique method of working memory training, and its operation process involves greatly with visuo-motor and visuo-spatial ability. Paradigm drift in mental calculation after abacus training In the local Chinese and Japanese cultural background, speed and accuracy of mental calculation is crucial to daily life and an important aspect of academic success. The “number sense” greatly depends on the parietal, prefrontal, and cingulate areas, with the HIPS playing a key part in the manipulation of quantity (18). Neuroimaging studies revealed the activation of different neural pathways between untrained children mental calculation and trained experts: the mental calculation task in children mainly activate prefrontal and perisylvian zones of the left hemisphere, with differences shown while performing simple and complex calculation; in sharp contrast, when children are trained in AMC, the activation shifts focus to visuo-motor and visuo-spatial pathways. This is consistent with our knowledge of how AMC is trained in its steps: with each cognitive focus, a change in the underlying functional network can be witnessed in the end results. With knowledge of the training methods and its end result reflected in neuroimaging, we ask ourselves: what changes can be expected in the relatively short-term training of six months? Research show functional differences between three-year experts and untrained subjects, physical properties can be expected to change after long-term training, and general improvements are noted in time as short as thirty-four weeks. But the greatest behavioral improvements are suggested within six months to one year of training, and we proposed the intrinsic functional circuits should rightfully reflect this change. Past studies suggest a shift of activation from frontal lobes to parietal lobes was observed with the gain of arithmetic competence, and intra-parietal shift of activation from HIPS to angular gyrus were also reported (19). Evidence for developmental change in mental arithmetic revealed a shift of activations with ages from prefrontal cortex to left inferior parietal lobe. The increased functional specialization of left inferior parietal cortex in mental arithmetic was accompanied by decreased dependence on memory and attention resources with development (20). Our results demonstrated shift in activation region consistent with our expectation along the fronto-parietal network, but not to the extent of further parietal regions, such as angular gyrus 36.