826 research outputs found

    Efficacy and Moderators of Virtual Reality for Cognitive Training in People with Dementia and Mild Cognitive Impairment: A Systematic Review and Meta-Analysis

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    Background: Mild cognitive impairment (MCI) and dementia result in cognitive decline which can negatively impact everyday functional abilities and quality of life. Virtual reality (VR) interventions could benefit the cognitive abilities of people with MCI and dementia, but evidence is inconclusive. Objective: To investigate the efficacy of VR training on global and domain-specific cognition, activities of daily living and quality of life. To explore the influence of priori moderators (e.g., immersion type, training type) on the effects of VR training. Adverse effects of VR training were also considered. Methods: A systematic literature search was conducted on all major databases for randomized control trial studies. Two separate meta-analyses were performed on studies with people with MCI and dementia. Results: Sixteen studies with people with MCI and four studies with people with dementia were included in each meta-analysis. Results showed moderate to large effects of VR training on global cognition, attention, memory, and construction and motor performance in people with MCI. Immersion and training type were found to be significant moderators of the effect of VR training on global cognition. For people with dementia, results showed moderate to large improvements after VR training on global cognition, memory, and executive function, but a subgroup analysis was not possible. Conclusion: Our findings suggest that VR training is an effective treatment for both people with MCI and dementia. These results contribute to the establishment of practical guidelines for VR interventions for patients with cognitive decline

    ๊ฐ€์ƒํ˜„์‹ค ๋‚ด ์ •๋ณด ๋ถˆ์ผ์น˜๋ฅผ ํ™œ์šฉํ•œ ์ธ์ง€๊ธฐ๋Šฅ ํ‰๊ฐ€: ํƒ์ƒ‰์  ๊ณ ์ฐฐ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ์ธ๋ฌธ๋Œ€ํ•™ ํ˜‘๋™๊ณผ์ • ์ธ์ง€๊ณผํ•™์ „๊ณต, 2022.2. ์ด๊ฒฝ๋ฏผ.๋ณธ ๋ฐ•์‚ฌ๋…ผ๋ฌธ์˜ ๋ชฉ์ ์€ ๊ฐ€์ƒํ˜„์‹ค ๋‚ด์—์„œ ๋ฐœ์ƒํ•˜๋Š” ์ •๋ณด๋ถˆ์ผ์น˜์— ๋Œ€ํ•ด์„œ ์•Œ์•„๋ณด๊ณ , ์ •๋ณด ๋ถˆ์ผ์น˜๋กœ ์ธํ•œ ์ธ์ง€์  ๋ฐ˜์‘์„ ์ธ์ง€๊ธฐ๋Šฅ ํ‰๊ฐ€์— ํ™œ์šฉํ•  ์ˆ˜ ์žˆ๋Š” ๋ฐฉ์•ˆ์„ ๊ณ ์ฐฐํ•˜๊ณ ์ž ํ•จ์ด๋‹ค. ๊ฐ€์ƒํ˜„์‹ค ์ฃผ๋ฐฉ๊ณผ์ œ๋ฅผ ๊ตฌํ˜„ํ•˜์—ฌ ๊ณผ์ œ ์ˆ˜ํ–‰ ์ค‘ ๋‚˜ํƒ€๋‚˜๋Š” ์›€์ง์ž„๊ณผ ์ธ์ง€์ž‘์šฉ์˜ ํŠน์„ฑ์„ ์•Œ์•„๋ณด๊ณ ์ž ํ•˜์˜€๋‹ค. ๋˜ํ•œ VR์—์„œ ๊ณผ์ œ์ˆ˜ํ–‰ ์‹œ ๋‚˜ํƒ€๋‚˜๋Š” ์ธ์ง€ ๋ถ€ํ•˜์˜ ์š”์ธ์„ ํƒ์ƒ‰ํ•˜์˜€๋‹ค. ํŠนํžˆ, ๊ฐ๊ฐ์šด๋™ ์กฐ์ ˆ ์ธก๋ฉด์—์„œ ๊ฐ€์ƒํ˜„์‹ค ๋‚ด ๋ฐœ์ƒํ•˜๋Š” ์ •๋ณด๋ถˆ์ผ์น˜๋กœ ์ธํ•œ ์ธ์ง€ ๊ณผ๋ถ€ํ•˜๋ฅผ ์‚ดํŽด๋ณด์•˜๋‹ค. ์ฒซ์งธ, ๊ฐ€์ƒํ˜„์‹ค๊ณผ ์‹ค์ œํ™˜๊ฒฝ์—์„œ ์ž‘๋™ํ•˜๋Š” ์ธ์ง€๊ณผ์ •์ด ์–ด๋–ป๊ฒŒ ๋‹ค๋ฅธ์ง€ ์•Œ์•„๋ณด๊ธฐ ์œ„ํ•ด ๋‘ ํ™˜๊ฒฝ ๊ฐ„์˜ ๊ณผ์ œ ์ˆ˜ํ–‰ ์ฐจ์ด๋ฅผ ๋น„๊ตํ•˜์˜€๋‹ค. ์ Š์€ ์„ฑ์ธ ๊ทธ๋ฃน์—์„œ๋Š” ์–ด๋ ค์šด ์ฃผ๋ฐฉ๊ณผ์ œ ์ˆ˜ํ–‰ ์‹œ ๊ฐ€์ƒํ˜„์‹ค๊ณผ ์‹ค์ œํ™˜๊ฒฝ ๊ฐ„์˜ ์ˆ˜ํ–‰์‹œ๊ฐ„์— ์œ ์˜ํ•œ ์ฐจ์ด๊ฐ€ ์žˆ์—ˆ์ง€๋งŒ ์‰ฌ์šด ์ฃผ๋ฐฉ ๊ณผ์ œ์—์„œ๋Š” ์ฐจ์ด๊ฐ€ ์—†์—ˆ๋‹ค. ๋ฐ˜๋ฉด ๋…ธ์ธ ์ง‘๋‹จ์—์„œ๋Š” ๊ณผ์ œ์˜ ๋‚œ์ด๋„์™€ ๊ด€๊ณ„์—†์ด ๋‘ ํ™˜๊ฒฝ ๊ฐ„์˜ ์ˆ˜ํ–‰ ์‹œ๊ฐ„์— ์ƒ๋‹นํ•œ ์ฐจ์ด๊ฐ€ ์žˆ์—ˆ๋‹ค. ๋…ธ์ธ์˜ ๊ฒฝ์šฐ ๊ฐ€์ƒํ˜„์‹ค์—์„œ ๊ฐ๊ฐ์šด๋™ ์กฐ์ ˆ์˜ ์–ด๋ ค์›€์„ ๋ณด์˜€๋‹ค. ์ฆ‰ ๋…ธ์ธ์˜ ๊ฒฝ์šฐ ์ Š์€ ์„ฑ์ธ์— ๋น„ํ•ด ๊ฐ€์ƒํ˜„์‹ค ๋‚ด์—์„œ์˜ ๊ฐ๊ฐ์šด๋™ ์กฐ์ ˆ์ด ๋” ์–ด๋ ต๊ธฐ ๋•Œ๋ฌธ์— ์ด๋กœ ์ธํ•œ ์ธ์ง€์  ๋ถ€ํ•˜๊ฐ€ ๊ณผ์ œ ์ˆ˜ํ–‰ ์ž์ฒด์˜ ์ธ์ง€์  ๋ถ€ํ•˜์— ๊ฐ€์ค‘๋˜์–ด ๊ณผ์ œ ๋‚œ์ด๋„๊ฐ€ ์–ด๋ ค์›Œ์ง€๋ฉด ์ธ์ง€์šฉ๋Ÿ‰์˜ ํ•œ๊ณ„๋ฅผ ์ดˆ๊ณผํ•˜๊ฒŒ ๋œ๋‹ค. ๋‘˜์งธ, ๊ฐ€์ƒ ์ฃผ๋ฐฉ๊ณผ์ œ ์ˆ˜ํ–‰ ์‹œ ์ธ์ง€๊ธฐ๋Šฅ์ด ์ €ํ•˜๋จ์— ๋”ฐ๋ผ ๊ฐ‘์ž๊ธฐ ํœ™ ์›€์ง์ด๋Š”(jerky) ํŒจํ„ด์„ ๋ณด์ด๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ด๋Š” ์ธ์ง€๊ธฐ๋Šฅ์ด ์ €ํ•˜๋œ ๋…ธ์ธ์˜ ๊ฒฝ์šฐ ํ™˜๊ฒฝ์— ๋Œ€ํ•œ ์˜ˆ์ธก๋ ฅ์ด ์ €ํ•˜๋˜์–ด ์ตœ์†Œ ์ €ํฌ์šด๋™ ์กฐ์ ˆ(minimal jerk movement control)์— ์–ด๋ ค์›€์ด ์žˆ์Œ์„ ์‹œ์‚ฌํ•œ๋‹ค. ๋˜ํ•œ ์ธ์ง€๊ธฐ๋Šฅ์ด ๋†’์€ ๊ทธ๋ฃน๋ณด๋‹ค ์ธ์ง€๊ธฐ๋Šฅ์ด ๋‚ฎ์€ ๋…ธ์ธ ๊ทธ๋ฃน์˜ ๊ฒฝ์šฐ ๊ณผ์ œ๊ฐ€ ์™„๋ฃŒ๋  ๋•Œ๊นŒ์ง€์˜ ์ผ๋ จ์˜ ์›€์ง์ž„ ๋‹จ๊ณ„๊ฐ€ ๋” ๋งŽ์•˜๋‹ค. ์ธ์ง€๊ธฐ๋Šฅ์ด ์ €ํ•˜๋จ์— ๋”ฐ๋ผ ๋น„ํšจ์œจ์ ์ด๊ณ  ๋ถ„์ฃผํ•œ ์›€์ง์ž„์„ ๋ณด์ธ๋‹ค๊ณ  ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋˜ํ•œ ๋‹ค์ค‘ํšŒ๊ท€๋ถ„์„ ๊ฒฐ๊ณผ, ๋…ธ์ธ์ด ๊ฐ€์ƒํ˜„์‹ค ์ฃผ๋ฐฉ๊ณผ์ œ๋ฅผ ํšจ์œจ์ ์œผ๋กœ ์ˆ˜ํ–‰ํ•จ์— ์žˆ์–ด ์—ฐ๋ น ๋ฐ ํ•™๋ ฅ ๋ณด๋‹ค๋Š” ์ธ์ง€๊ธฐ๋Šฅ์ด ๊ฐ€์žฅ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์š”์ธ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ฆ‰ ๊ฐ€์ƒํ˜„์‹ค ๊ธฐ๋ฐ˜ ๊ณผ์ œ์ˆ˜ํ–‰์€ ์ˆœ์ˆ˜ ์ธ์ง€๊ธฐ๋Šฅ๋งŒ์„ ํ‰๊ฐ€ํ•˜๋Š” ์ƒˆ๋กœ์šด ๋Œ€์•ˆ์œผ๋กœ ์ œ์‹œํ•  ์ˆ˜ ์žˆ๋‹ค. ๋งˆ์ง€๋ง‰์œผ๋กœ ๊ฐ๊ฐ์šด๋™ ํ”ผ๋“œ๋ฐฑ์˜ ์˜ˆ์ธก๋ถˆ๊ฐ€๋Šฅ์„ฑ(unpredictability)์ด ๊ฐ€์ƒํ˜„์‹ค์—์„œ ์ธ์ง€๋ถ€ํ•˜๋ฅผ ์œ ๋ฐœํ•˜๋Š” ๋ฐฉ์‹์„ ์•Œ์•„๋ณด๊ณ ์ž ํ•˜์˜€๋‹ค. ์„ญ๋™์˜ ์˜ˆ์ธก ๊ฐ€๋Šฅ์„ฑ์— ๋”ฐ๋ฅธ ๋ฐ˜์‘ ์‹œ๊ฐ„๊ณผ ์ด๋™ ์†๋„๋ฅผ ์•”๋ฌต์  5ยฐ์™€ ๋ช…์‹œ์  15ยฐ ์„ญ๋™ ์กฐ๊ฑด์—์„œ ๊ฐ๊ฐ ์ธก์ •ํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ ์•”๋ฌต์  ์šด๋™ ์ œ์–ด ์‹œ ์„ญ๋™์˜ ๋ณ€ํ™”๋ฅผ ์˜ˆ์ธกํ•  ์ˆ˜ ์—†์„ ๋•Œ ์›€์ง์ž„์˜ ์ •ํ™•๋„๋ฅผ ๋†’์ด๊ธฐ ์œ„ํ•ด ์›€์ง์ž„์ด ๋Š๋ ค์ง€๋Š” ์ „๋žต(accuracy and speed trade-off)์„ ์‚ฌ์šฉํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ฆ‰, ๊ฐ๊ฐ์šด๋™์กฐ์ ˆ ๊ณผ์ • ์ƒ์—์„œ ์ •๋ณด ๋ถˆ์ผ์น˜๋กœ ์ธํ•œ ์˜ˆ์ธก ๋ถˆ๊ฐ€๋Šฅ์„ฑ์— ๋Œ€ํ•ด ์šฐ๋ฆฌ์˜ ๋‡Œ๋Š” ๋‹ค๋ฅธ ์ธ์ง€์ „๋žต์„ ์ทจํ•œ๋‹ค๊ณ  ์„ค๋ช…ํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ฒฐ๋ก ์ ์œผ๋กœ ๊ฐ€์ƒํ˜„์‹ค์€ ๊ธฐ์ˆ ์  ์ถฉ์‹ค๋„(fidelity) ๋ฌธ์ œ๋กœ ์ธํ•ด ๊ฐ๊ฐ ํ”ผ๋“œ๋ฐฑ์ด ์˜ˆ์ธก ๋ถˆ๊ฐ€๋Šฅํ•˜๊ณ  ๊ฐ€๋ณ€์ ์ด๊ธฐ ๋•Œ๋ฌธ์— ์‹ค์ œ ํ™˜๊ฒฝ๋ณด๋‹ค ๋” ๋งŽ์€ ์ธ์ง€ ๋ถ€ํ•˜๋ฅผ ์œ ๋ฐœํ•œ๋‹ค. ํŠนํžˆ ๊ฐ€์ƒํ˜„์‹ค์—์„œ์˜ ๊ฐ๊ฐ์šด๋™ ์กฐ์ ˆ์€ ์‹ค์ œํ™˜๊ฒฝ์—์„œ ์ธ๊ฐ„์˜ ์šด๋™ ์‹œ์Šคํ…œ์ด ์ ์‘๋œ ๋ฐฉ์‹๊ณผ๋Š” ๋‹ค๋ฅด๋‹ค๊ณ  ๋ณผ ์ˆ˜ ์žˆ๋‹ค. ์ฆ‰ ๊ฐ€์ƒํ˜„์‹ค ๋‚ด์—์„œ๋Š” ๊ฐ๊ฐ์šด๋™ ์‹œ์Šคํ…œ์ด ์˜ˆ์ธกํ•  ์ˆ˜ ์—†๋Š” ํ™˜๊ฒฝ์— ์ ์‘ํ•˜๊ธฐ ์œ„ํ•ด ๋‹ค๋ฅธ ์ธ์ง€ ์ „๋žต์„ ์ทจํ•˜๊ฒŒ ๋œ๋‹ค. ํ™˜๊ฒฝ์— ๋”ฐ๋ฅธ ํšจ์œจ์ ์ธ ์ธ์ง€์ „๋žต์˜ ์ „ํ™˜์€ ์ค‘์•™ ์ง‘ํ–‰๊ธฐ๋Šฅ(central executive)๊ณผ ๊ด€๋ จ ์žˆ์œผ๋ฉฐ, ์ด๋Ÿฌํ•œ ํŠน์ง•์„ ํ™œ์šฉํ•œ ๊ฐ€์ƒํ˜„์‹ค๊ธฐ๋ฐ˜ ๊ณผ์ œ๋Š” ์ƒˆ๋กœ์šด ์ธ์ง€๊ธฐ๋Šฅ ํ‰๊ฐ€์˜ ๋Œ€์•ˆ์œผ๋กœ ์ œ์‹œํ•  ์ˆ˜ ์žˆ๋‹ค.The purpose of this dissertation was to investigate information mismatch in virtual reality (VR) and explore the possibility of using the cognitive reaction arising from information mismatch for cognitive evaluation. The virtual kitchen task was used to observe the subjectsโ€™ behaviors while performing the task, and to investigate the characteristics of movement and cognitive processes appearing during the performance of the virtual task. In addition, an attempt was made to explore the factors of cognitive overload in VR that determine the difference compared to a performance in the real environment. In particular, this study aimed to investigate how information mismatch occurring in VR causes cognitive overload in terms of sensorimotor control. First, it questioned how the cognitive process in VR differs from the real environment and also investigated the factors affecting the performance of tasks in VR. In the young adult group, while there was a significant difference between the execution time in VR and in the real environment in the difficult kitchen task, there was no such difference in the easy kitchen task. Meanwhile, among the elderly, there was a significant difference between the execution time in VR and in the real environment regardless of whether the task was difficult or easy. It was thought that cognitive load was caused due to difficulties in sensorimotor control in VR. It was found that the cognitive capacity is challenged when the task is difficult because the load of task performance itself and the load of sensorimotor control are doubling. Second, it was found that as the cognitive function decreased, an abrupt and jerky movement pattern was exhibited during the virtual kitchen task. The number of sequences in movement until the task was completed was also busier in the elderly group with lower cognitive function in contrast with those with higher cognitive function. In the case of the elderly with deteriorated cognitive function, it is suggested that there is difficulty in minimal jerk movement control because the predictive ability responding to environment is decreased. In addition, according to the results of multiple regression, cognitive function of the elderly is the most influential factor in performing VR tasks, other than age and educational background, which means that purely evaluating cognitive function may be suggested. Third, an attempt was made to verify how the unpredictability of sensorimotor feedback causes cognitive load in VR. The reaction time and speed of movement depending on the predictability of perturbation were measured in implicit 5 degrees and explicit 15 degrees perturbation. When the subject was unable to predict the variation of perturbation only in implicit motor control, reaching became slower and it took more time due to the accuracy and speed trade-off. In other words, unpredictability due to information mismatch leads to the use of different cognitive strategies in brain mechanisms. In conclusion, VR induces more cognitive load than the real environment because the sensory feedback is unpredictable and variable due to technical fidelity problems. The sensorimotor control in VR is challenged by the way the human motor system is adapted. Further, it was found that an unpredictable environment requires different cognitive strategies for the sensorimotor system to adapt to it. The manner in which effective cognitive strategies are taken represents an efficient central executive function. From this perspective, VR-based cognitive evaluation, using such attributes, is thought to be an alternative method for early screening of cognitive decline.Chapter 1. Introduction 7 1.1 Research motivation and introductory overview 7 1.2 Research goal and questions 7 1.2.1 Overall research goal 7 1.2.2 Research questions 8 1.2.3 Research contributions 8 1.3 Thesis structure 8 Chapter 2. Literature Review 10 2.1 Virtual Reality (VR) as ecological method for cognitive evaluation 10 2.2 Sub-types of VR based tasks according to target cognitive function 12 2.2.1. VR task for spatial navigation 13 2.2.2. VR task for memory 14 2.2.3. VR task for executive function 16 2.3 Factors affecting on VR performance 19 2.3.1. General 19 2.3.2. Age effects on VR performance 20 2.3.3. Cognitive challenges in VR 21 2.3.4. Feasibility of VR task for dementia 22 2.4 Cognitive load in VR 23 2.4.1. Immersive versus non-immersive VR 23 2.4.2. Sense of presence and situated cognition 26 2.4.3. Sensorimotor adaptation in VR 28 2.5 Sensorimotor control in VR 29 2.5.1 Predictive brain and internal model for motor control 29 2.5.2 Explicit and implicit process in motor control 31 2.5.3 Accuracy & speed tradeoff in cognitive control 31 2.6 Executive control for information mismatch in information processing 32 Chapter 3. Differences in Cognitive Load Between Real and VR Environment 34 3.1 Introduction 34 3.2 Method 37 3.3 Results 40 3.4 Discussion 45 Chapter 4. The Efficiency of Movement Trajectory and Sequence in VR According to Cognitive Function in the Elderly 50 4.1 Introduction 50 4.2 Method 52 4.3 Results 53 4.4 Discussion 56 Chapter 5. Factors that Affect the Performance of Immersive Virtual Kitchen Tasks in the Elderly 59 5.1 Introduction 59 5.2 Method 62 5.3 Results 64 5.4 Discussion 70 Chapter 6. Effect of Predictability of Sensorimotor Feedback on Cognitive Load in VR 74 6.1 Introduction 74 6.2 Method 77 6.3 Results 79 6.4 Discussion 84 Chapter 7. Conclusion 88 7.1 Summary of findings 88 7.2 Future direction of research 90 References 92๋ฐ•

    Use of Immersive Virtual Reality in the Assessment and Treatment of Alzheimerโ€™s Disease: A Systematic Review

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    Background: Immersive virtual reality (iVR) allows seamless interaction with simulated environments and is becoming an established tool in clinical research. It is unclear whether iVR is acceptable to people with Alzheimerโ€™s disease (AD) dementia or useful in their care. We explore whether iVR is a viable research tool that may aid the detection and treatment of AD. Objectives: This review examines the use of iVR in people with AD or mild cognitive impairment (MCI). Methods: Medline, PsycINFO, Embase, CINAHL, and Web of Science databases were searched from inception. PRISMA guidelines were used with studies selected by at least two researchers. Results: Nine studies were eligible for inclusion. None reported any issues with iVR tolerability in participants with MCI and AD on assessment or treatment tasks. One study demonstrated capability for detecting prodromal AD and correlated with neuroanatomical substrates. Two studies showed iVR to have high accuracy in differentiating participants with AD from controls but were not hypothesis driven or with adequate controls measures. In a small validation study and two longitudinal case studies, iVR cognitive training was positively rated but did not demonstrate reliable benefit. Conclusion: iVR is emerging as a viable method of assessing older adults and people with AD. Strongest benefits were seen when closely integrated with theoretical models of neurodegeneration and existing screening methods. Further randomized controlled trials integrated with clinical populations are required. This will consolidate the power of iVR for assessment of MCI and clarify treatment efficacy beyond current applications in physical rehabilitation

    Use of Immersive Virtual Reality in the Assessment and Treatment of Alzheimer's Disease: A Systematic Review.

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    BACKGROUND: Immersive virtual reality (iVR) allows seamless interaction with simulated environments and is becoming an established tool in clinical research. It is unclear whether iVR is acceptable to people with Alzheimer's disease (AD) dementia or useful in their care. We explore whether iVR is a viable research tool that may aid the detection and treatment of AD. OBJECTIVES: This review examines the use of iVR in people with AD or mild cognitive impairment (MCI). METHODS: Medline, PsycINFO, Embase, CINAHL, and Web of Science databases were searched from inception. PRISMA guidelines were used with studies selected by at least two researchers. RESULTS: Nine studies were eligible for inclusion. None reported any issues with iVR tolerability in participants with MCI and AD on assessment or treatment tasks. One study demonstrated capability for detecting prodromal AD and correlated with neuroanatomical substrates. Two studies showed iVR to have high accuracy in differentiating participants with AD from controls but were not hypothesis driven or with adequate controls measures. In a small validation study and two longitudinal case studies, iVR cognitive training was positively rated but did not demonstrate reliable benefit. CONCLUSION: iVR is emerging as a viable method of assessing older adults and people with AD. Strongest benefits were seen when closely integrated with theoretical models of neurodegeneration and existing screening methods. Further randomized controlled trials integrated with clinical populations are required. This will consolidate the power of iVR for assessment of MCI and clarify treatment efficacy beyond current applications in physical rehabilitation

    Measuring Memory in an Alzheimer's Treatment Trial Using a Visual Search Task

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    Alzheimerโ€™s Disease (AD) is characterized by episodic memory deficits attributed to damage to the hippocampal formation. AD therapies specifically targeting hippocampal function may be best evaluated through the use of selective hippocampal tasks. I used a nonverbal hippocampal-dependent target-in-scene detection task to determine if task performance shows age-related decline and/or AD-related impairments. Participants located objects (โ€˜targetsโ€™) that appeared/disappeared in flickering natural scenes, yielding faster search times for remembered targets than for forgotten ones. AD patients took longer and required more fixations to detect targets, indicating impaired memory. Furthermore, the AD and aged populations exhibited slower pupillary responses. As part of a clinical trial, I next asked whether deep-brain stimulation of the extended hippocampal circuit would modify memory performance in patients with early AD. The double-blind treatment trial is still underway, thus treatment efficacy is yet to be evaluated, however, trial participants showed a measurable, progressive memory impairment in this task

    Cognitive stimulation and cognitive results in older adults: A systematic review and meta-analysis

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    Background and Purpose The lack of cognitive activity accelerates age cognitive decline. Cognitive stimulation (CS) tries to enhance cognitive functioning. The purpose of this systematic review and meta-analysis was to evaluate the effects of CS on cognitive outcomes (general cognitive functioning and specific cognitive domains) in older adults (aged 65 years or older, cognitively healthy participants, or with mild cognitive impairment, or dementia). Methods PubMed, Scopus and Web of Science databases were examined from inception to October 2021. A total of 1,997 studies were identified in these databases, and. 33 studies were finally included in the systematic review and the meta-analysis. Raw means and standard deviations were used for continuous outcomes. Publication bias was examined by Egger's Regression Test for Funnel Plot Asymmetry and the quality assessment tools from the National Institutes of Health. Results CS significantly improves general cognitive functioning (mean difference=MD = 1.536, 95%CI, 0.832 to 2.240), memory (MD = 0.365, 95%CI, 0.300 to 0.430), orientation (MD = 0.428, 95%CI, 0.306 to 0.550), praxis (MD = 0.278, 95%CI, 0.094 to 0.462) and calculation (MD = 0.228, 95%CI, 0.112 to 0.343). Conclusion CS seems to increase general cognitive functioning, memory, orientation, praxis, and calculation in older adults
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