Nörobilişsel Yaşlanma Modelleri: Kaybedilenin Telafisi Mümkün mü?

Elif Güldemir; Handan Can

doi:10.52642/susbed.1225337

TR EN

Öz

Anahtar Kelimeler

yaşlanma, telafi, nörobilişsel modeller, aynılaşma.

Öz

Anahtar Kelimeler

yaşlanma, telafi, nörobilişsel modeller, aynılaşma.

Nörobilişsel Yaşlanma Modelleri: Kaybedilenin Telafisi Mümkün mü?

Öz

Yaşlanma sürecinde bilişsel işlevlerin birçoğunda düşüş görülmektedir. Yaşlanmayla birlikte bilişsel işlevlerde ortaya çıkan bu değişim ile nöral süreçler arasındaki ilişkinin incelenmesine olanak sağlayan nörobilişsel modeller, beyindeki aktivasyon artışına bağlı olarak ortaya çıkan telafi (compensation) mekanizmalarına odaklanmaktadır. Beyin aktivasyonundaki bu artışın, bilişsel performanstaki yaşa bağlı düşüşü dengelemek ve korumak yönünde harekete geçen telafi mekanizmalarını yansıttığı düşünülmektedir. Bu derleme çalışmasının amacı sağlıklı yaşlanma ile birlikte ortaya çıkan telafi mekanizmalarını açıklamak için geliştirilen nörobilişsel modellerden en etkili dört modeli incelemek; bu modellerin katkıları ve sınırlılıklarını tartışmaktır. Bu kapsamda mevcut derlemede Yaşlı Yetişkinlerde Hemisferik Asimetri Azalması (HAROLD) Modeli, Yaşlanmada Posterior-Anterior Kayma (PASA) Teorisi, Nöral Devrelerin Telafiyle İlgili Kullanımı Hipotezi (CRUNCH), Yaşlanma ve Bilişin İskele Teorisi (STAC; STAC-r) ele alınmıştır. Buna karşın nörobilişsel modellerden önce geliştirilen bilişsel modeller yaşa bağlı olarak ortaya çıkan bilişsel farklılıkları açıklamada yaşlanmaya bağlı bozukluklara odaklanmışlardır. Bu nedenle bilişsel değişimi kapsamlı bir şekilde açıklamakta yetersiz kalmışlardır. Nörobilişsel modeller ise, telafi mekanizmalarının harekete geçmesi için nöral ağların kullanımına odaklanmış ve telafi sürecinin daha çok frontal bölgelerde gerçekleştiğine vurgu yapmışlardır. Dolayısıyla nörobilişsel modeller yaşlanmanın nörobilişsel temellerini açıklamak açısından daha kapsamlı modellerdir; ancak bu modeller de bazı sınırlılıklar içermektedir. Türkiye’de ve tüm dünyada yaşlanan nüfus ve buna paralel olarak gelişen demans vaka sayıları giderek artmaktadır. Bu bağlamda, nörobilişsel modelleri test eden çalışmaların artması ve bunlardan elde edilecek sonuçlarla yaşlanmayı açıklayan yeni ve daha kapsamlı modellerin geliştirilmesi, yaşlanma sürecinin doğasının anlaşılması açısından önem arz etmektedir.

Anahtar Kelimeler

Yaşlanma, Telafi, Nörobilişsel Modeller, Aynılaşma.

Neurocognitive Models of Aging: Is It Possible to Compensate for Loss?

Öz

Aging is characterized decrease in many cognitive abilities in this stage. Neurocognitive models focus on the compensation mechanisms associated with overactivation in the brain. This overactivation may reflect compensatory mechanisms acting to balance and protect the age-related decline in cognitive performance. The aim of this review is to examine the four most effective neurocognitive models developed to explain the compensatory mechanisms that emerge with healthy aging, and to discuss their contributions and limitations. In this context, the reviewed models include the Hemispheric Asymmetry Reduction in Older Adults (HAROLD) Model, the Posterior-Anterior Shift in Aging (PASA) Theory, the Compensation-Related Utilization of Neural Circuits Hypothesis (CRUNCH), and the scaffolding theory of aging and cognition (STAC; STAC-r). However, cognitive models developed prior to neurocognitive models have explained age-related cognitive differences and focused on age-related impairments. Thus, they fall short of providing a comprehensive explanation of cognitive change. Neurocognitive models, on the other hand, focus on the use of neural networks to activate compensatory mechanisms and emphasize that the compensation process predominantly occurs in frontal regions. Therefore, neurocognitive models are more comprehensive in explaining the neurocognitive foundations of aging; however, they are still insufficient due to some limitations. The aging population is increasing both in Turkey and worldwide, leading to a rise in dementia cases. In this context, increasing the number of studies that test neurocognitive models and developing new and more comprehensive models based on the results obtained from these studies are important for understanding the nature of the aging process.

Anahtar Kelimeler

Aging, Compensation, Neurocognitive Models, Dedifferentiation.

Kaynakça

Agrigoroaei, S., & Lachman, M. E. (2011). Cognitive functioning in midlife and old age: Combined effects of psychosocial and behavioral factors. The Journals of Gerontology: Series B, 66B(suppl_1), i130-i140. https://doi.org/10.1093/geronb/gbr017
Albinet, C. T., Boucard, G., Bouquet, C. A., & Audiffren, M. (2012). Processing speed and executive functions in cognitive aging: How to disentangle their mutual relationship? Brain and Cognition, 79(1), 1-11. https://doi.org/10.1016/j.bandc.2012.02.001
Alperin, B. R., Mott, K. K., Rentz, D. M., Holcomb, P. J., & Daffner, K. R. (2014). Investigating the age-related “anterior shift” in the scalp distribution of the P3b component using principal component analysis. Psychophysiology, 51(7), 620-633. https://doi.org/10.1111/psyp.12206
Alperin, B. R., Tusch, E. S., Mott, K. K., Holcomb, P. J., & Daffner, K. R. (2015). Investigating age-related changes in anterior and posterior neural activity throughout the information processing stream. Brain and Cognition, 99, 118-127. https://doi.org/10.1016/j.bandc.2015.08.001
Angel, L., Bastin, C., Genon, S., Salmon, E., Fay, S., Balteau, E., Maquet, P., Luxen, A., Isingrini, M., & Collette, F. (2016). Neural correlates of successful memory retrieval in aging: Do executive functioning and task difficulty matter? Brain Research, 1631, 53-71. https://doi.org/10.1016/j.brainres.2015.10.009
Angel, L., Fay, S., Bouazzaoui, B., & Isingrini, M. (2011). Two hemispheres for better memory in old age: Role of executive functioning. Journal of Cognitive Neuroscience, 23(12), 3767-3777. https://doi.org/10.1162/jocn_a_00104
Ansado, J., Monchi, O., Ennabil, N., Faure, S., & Joanette, Y. (2012). Load-dependent posterior–anterior shift in aging in complex visual selective attention situations. Brain Research, 1454, 14-22. https://doi.org/10.1016/j.brainres.2012.02.061
Asken, B. M., VandeVrede, L., Rojas, J. C., Fonseca, C., Staffaroni, A. M., Elahi, F. M., Lindbergh, C. A., Apple, A. C., You, M., Weiner-Light, S., Brathaban, N., Fernandes, N., Boxer, A. L., Miller, B. L., Rosen, H. J., Kramer, J. H., & Casaletto, K. B. (2022). Lower white matter volume and worse executive functioning reflected in higher levels of plasma GFAP among older adults with and without cognitive impairment. Journal of the International Neuropsychological Society, 28(6), 588-599. https://doi.org/10.1017/S1355617721000813
Badre, D. (2008). Cognitive control, hierarchy, and the rostro–caudal organization of the frontal lobes. Trends in Cognitive Sciences, 12(5), 193-200. https://doi.org/10.1016/j.tics.2008.02.004
Banich, M. T. (1998). The missing link: The role of interhemispheric interaction in attentional processing. Brain and Cognition, 36(2), 128-157. https://doi.org/10.1006/brcg.1997.0950

Bender, A. R., & Raz, N. (2012). Age-related differences in memory and executive functions in healthy APOE ɛ4 carriers: The contribution of individual differences in prefrontal volumes and systolic blood pressure. Neuropsychologia, 50(5), 704-714. https://doi.org/10.1016/j.neuropsychologia.2011.12.025
Berlingeri, M., Danelli, L., Bottini, G., Sberna, M., & Paulesu, E. (2013). Reassessing the HAROLD model: Is the hemispheric asymmetry reduction in older adults a special case of compensatory-related utilisation of neural circuits? Experimental Brain Research, 224(3), 393-410. https://doi.org/10.1007/s00221-012-3319-x
Birren, J. E. (1965). Age Changes in Speed of Behavior: Its Central Nature and Physiological Correlates. Içinde A. T. Welford & J. E. Birren (Ed.), Behavior, Aging and The Nervous System: Biological Determinants of Speed and Behavior (ss. 191-216). Charles C. Thomas.
Burke, D. M., & Osborne, G. (2007). Aging and Inhibition Deficits: Where are the Effects? Içinde D. S. Gorfein & C. M. MacLeod (Ed.), Inhibition in Cognition. (ss. 163-183). American Psychological Association. https://doi.org/10.1037/11587-009
Cabeza, R. (2002). Hemispheric asymmetry reduction in older adults: The HAROLD model. Psychology and Aging, 17(1), 85-100. https://doi.org/10.1037/0882-7974.17.1.85
Cabeza, R., Anderson, N. D., Locantore, J. K., & McIntosh, A. R. (2002). Aging gracefully: Compensatory brain activity in high-performing older adults. NeuroImage, 17(3), 1394-1402. https://doi.org/10.1006/nimg.2002.1280
Cabeza, R., Daselaar, S. M., Dolcos, F., Prince, S. E., Budde, M., & Nyberg, L. (2004). Task-independent and task-specific age effects on brain activity during working memory, visual attention and episodic retrieval. Cerebral Cortex, 14(4), 364-375. https://doi.org/10.1093/cercor/bhg133
Cabeza, R., & Dennis, N. A. (2012). Frontal Lobes and Aging: Deterioration and Compensation. Içinde D. T. Stuss & R. T. Knight (Ed.), Principles of Frontal Lobe Function (2. bs, ss. 628-652). Oxford University Press.
Cabeza, R., Grady, C. L., Nyberg, L., McIntosh, A. R., Tulving, E., Kapur, S., Jennings, J. M., Houle, S., & Craik, F. I. M. (1997a). Age-related differences in neural activity during memory encoding and retrieval: A positron emission tomography study. The Journal of Neuroscience, 17(1), 391-400. https://doi.org/10.1523/JNEUROSCI.17-01-00391.1997
Cabeza, R., McIntosh, A. R., Tulving, E., Nyberg, L., & Grady, C. L. (1997b). Age-related differences in effective neural connectivity during encoding and recall. NeuroReport, 8(16). https://doi.org/10.1097/00001756-199711100-00013
Cappell, K. A., Gmeindl, L., & Reuter-Lorenz, P. A. (2010). Age differences in prefontal recruitment during verbal working memory maintenance depend on memory load. Cortex, 46(4), 462-473. https://doi.org/10.1016/j.cortex.2009.11.009
Carp, J., Gmeindl, L., & Reuter-Lorenz, P. A. (2010). Age differences in the neural representation of working memory revealed by multi-voxel pattern analysis. Frontiers in Human Neuroscience, 4. https://doi.org/10.3389/fnhum.2010.00217
Carp, J., Park, J., Polk, T. A., & Park, D. C. (2011). Age differences in neural distinctiveness revealed by multi-voxel pattern analysis. NeuroImage, 56(2), 736-743. https://doi.org/10.1016/j.neuroimage.2010.04.267
Cerella, J. (1985). Information processing rates in the elderly. Psychological Bulletin, 98(1), 67-83. https://doi.org/10.1037/0033-2909.98.1.67
Craik, F. I. M., & Byrd, M. (1982). Aging and Cognitive Deficits. Içinde F. I. M. Craik & S. Trehub (Ed.), Aging and Cognitive Processes (ss. 191-211). Springer US. https://doi.org/10.1007/978-1-4684-4178-9_11
Daselaar, S. M., Iyengar, V., Davis, S. W., Eklund, K., Hayes, S. M., & Cabeza, R. E. (2015). Less wiring, more firing: Low-performing older adults compensate for impaired white matter with greater neural activity. Cerebral Cortex, 25(4), 983-990. https://doi.org/10.1093/cercor/bht289
Davis, S. W., Dennis, N. A., Daselaar, S. M., Fleck, M. S., & Cabeza, R. (2008). Que PASA? The posterior-anterior shift in aging. Cerebral Cortex, 18(5), 1201-1209. https://doi.org/10.1093/cercor/bhm155
Davis, S. W., Kragel, J. E., Madden, D. J., & Cabeza, R. (2012). The architecture of cross-hemispheric communication in the aging brain: Linking behavior to functional and structural connectivity. Cerebral Cortex, 22(1), 232-242. https://doi.org/10.1093/cercor/bhr123
de Chastelaine, M., Wang, T. H., Minton, B., Muftuler, L. T., & Rugg, M. D. (2011). The effects of age, memory performance, and callosal integrity on the neural correlates of successful associative encoding. Cerebral Cortex, 21(9), 2166-2176. https://doi.org/10.1093/cercor/bhq294
de Frias, C. M., Schaie, K. W., & Willis, S. L. (2014). Hypertension moderates the effect of APOE on 21-year cognitive trajectories. Psychology and Aging, 29(2), 431-439. https://doi.org/10.1037/a0036828
Dennis, N. A., & Cabeza, R. (2008). Neuroimaging of Healthy Cognitive Aging. Içinde F. I. M. Craik & T. A. Salthouse (Ed.), The Handbook of Aging and Cognition (3. bs, ss. 1-54). Lawrence Erlbaum.
Dennis, N. A., & Cabeza, R. (2011). Age-related dedifferentiation of learning systems: an fMRI study of implicit and explicit learning. Neurobiology of Aging, 32(12), 2318.e17-2318.e30. https://doi.org/10.1016/j.neurobiolaging.2010.04.004
Di, X., Rypma, B., & Biswal, B. B. (2014). Correspondence of executive function related functional and anatomical alterations in aging brain. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 48, 41-50. https://doi.org/10.1016/j.pnpbp.2013.09.001
Du, Y., Buchsbaum, B. R., Grady, C. L., & Alain, C. (2016). Increased activity in frontal motor cortex compensates impaired speech perception in older adults. Nature Communications, 7(1), 12241. https://doi.org/10.1038/ncomms12241
Düzel, E., Schütze, H., Yonelinas, A. P., & Heinze, H.-J. (2010). Functional phenotyping of successful aging in long-term memory: Preserved performance in the absence of neural compensation. Hippocampus, 21(8), 803-814. https://doi.org/10.1002/hipo.20834
Economou, A. (2009). Memory score discrepancies by healthy middle-aged and older individuals: The contributions of age and education. Journal of the International Neuropsychological Society, 15(6), 963-972. https://doi.org/10.1017/S1355617709990580
Festini, S. B., Zahodne, L., & Reuter-Lorenz, P. A. (2018). Theoretical Perspectives on Age Differences in Brain Activation: HAROLD, PASA, CRUNCH—How Do They STAC Up? Içinde Oxford Research Encyclopedia of Psychology. https://doi.org/10.1093/acrefore/9780190236557.013.400
Fiske, A., Wetherell, J. L., & Gatz, M. (2009). Depression in older adults. Annual Review of Clinical Psychology, 5(1), 363-389. https://doi.org/10.1146/annurev.clinpsy.032408.153621
Grady, C. (2012). Trends in neurocognitive aging. Nature Reviews. Neuroscience, 13(7).
Grady, C. L., McIntosh, A. R., Horwitz, B., Maisog, J. Ma., Ungerleider, L. G., Mentis, M. J., Pietrini, P., Schapiro, M. B., & Haxby, J. v. (1995). Age-related reductions in human recognition memory due to impaired encoding. Science, 269(5221), 218-221. https://doi.org/10.1126/science.7618082
Grady, C., Maisog, J., Horwitz, B., Ungerleider, L., Mentis, M., Salerno, J., Pietrini, P., Wagner, E., & Haxby, J. (1994). Age-related changes in cortical blood flow activation during visual processing of faces and location. The Journal of Neuroscience, 14(3), 1450-1462. https://doi.org/10.1523/JNEUROSCI.14-03-01450.1994
Grossman, M., Cooke, A., DeVita, C., Alsop, D., Detre, J., Chen, W., & Gee, J. (2002). Age-related changes in working memory during sentence comprehension: An fMRI study. NeuroImage, 15(2), 302-317. https://doi.org/10.1006/nimg.2001.0971
Haalanda, K. Y., Price, L., & Larue, A. (2003). What does the WMS–III tell us about memory changes with normal aging? Journal of the International Neuropsychological Society, 9(1), 89-96. https://doi.org/10.1017/S1355617703910101
Harada, C. N., Natelson Love, M. C., & Triebel, K. L. (2013). Normal cognitive aging. Clinics in Geriatric Medicine, 29(4), 737-752. https://doi.org/10.1016/j.cger.2013.07.002
Hasher, L., & Zacks, R. T. (1988). Working memory, comprehension, and aging: A review and a new view. Psychology of Learning and Motivation - Advances in Research and Theory, 22(C). https://doi.org/10.1016/S0079-7421(08)60041-9
Höller-Wallscheid, M. S., Thier, P., Pomper, J. K., & Lindner, A. (2017). Bilateral recruitment of prefrontal cortex in working memory is associated with task demand but not with age. Proceedings of the National Academy of Sciences, 114(5), E830-E839. https://doi.org/10.1073/pnas.1601983114
Huang, C.-M., Polk, T. A., Goh, J. O., & Park, D. C. (2012). Both left and right posterior parietal activations contribute to compensatory processes in normal aging. Neuropsychologia, 50(1), 55-66. https://doi.org/10.1016/j.neuropsychologia.2011.10.022
Iidaka, T., Okada, T., Murata, T., Omori, M., Kosaka, H., Sadato, N., & Yonekura, Y. (2002). Age-related differences in the medial temporal lobe responses to emotional faces as revealed by fMRI. Hippocampus, 12(3), 352-362. https://doi.org/10.1002/hipo.1113
Kalpouzos, G., Persson, J., & Nyberg, L. (2012). Local brain atrophy accounts for functional activity differences in normal aging. Neurobiology of Aging, 33(3), 623.e1-623.e13. https://doi.org/10.1016/j.neurobiolaging.2011.02.021
Kensinger, E. A. (2009). Cognition in Aging and Age Related Disease. Içinde P. R. Hof & C. v. Mobbs (Ed.), Handbook of the Neuroscience of Aging (ss. 249-256), Elsevier Press.
Kerchner, G. A., Racine, C. A., Hale, S., Wilheim, R., Laluz, V., Miller, B. L., & Kramer, J. H. (2012). Cognitive processing speed in older adults: Relationship with white matter integrity. PLoS ONE, 7(11), e50425. https://doi.org/10.1371/journal.pone.0050425
Lezak, M. D., Howieson, D. B., Loring, D. W., Fischer, J. S., Hannay, J. H., & Fischer, J. S. (2004). Neuropsychological Assessment: Oxford University Press. New York.
Li, H.-J., Hou, X.-H., Liu, H.-H., Yue, C.-L., Lu, G.-M., & Zuo, X.-N. (2015). Putting age-related task activation into large-scale brain networks: A meta-analysis of 114 fMRI studies on healthy aging. Neuroscience & Biobehavioral Reviews, 57, 156-174. https://doi.org/10.1016/j.neubiorev.2015.08.013
Lindenberger, U., & Baltes, P. B. (1994). Sensory functioning and intelligence in old age: A strong connection. Psychology and Aging, 9(3), 339-355. https://doi.org/10.1037/0882-7974.9.3.339
Logan, J. M., Sanders, A. L., Snyder, A. Z., Morris, J. C., & Buckner, R. L. (2002). Under-recruitment and nonselective recruitment. Neuron, 33(5), 827-840. https://doi.org/10.1016/S0896-6273(02)00612-8
Lubitz, A. F., Niedeggen, M., & Feser, M. (2017). Aging and working memory performance: Electrophysiological correlates of high and low performing elderly. Neuropsychologia, 106, 42-51. https://doi.org/10.1016/j.neuropsychologia.2017.09.002
Luo, L., & Craik, F. I. (2008). Aging and memory: A cognitive approach. The Canadian Journal of Psychiatry, 53(6), 346-353. https://doi.org/10.1177/070674370805300603
Lustig, C., Shah, P., Seidler, R., & Reuter-Lorenz, P. A. (2009). Aging, training, and the brain: A review and future directions. Neuropsychology Review, 19(4), 504-522. https://doi.org/10.1007/s11065-009-9119-9
Madden, D. J., Costello, M. C., Dennis, N. A., Davis, S. W., Shepler, A. M., Spaniol, J., Bucur, B., & Cabeza, R. (2010). Adult age differences in functional connectivity during executive control. NeuroImage, 52(2), 643-657. https://doi.org/10.1016/j.neuroimage.2010.04.249
Madden, D. J., Gottlob, L. R., Denny, L. L., Turkington, T. G., Provenzale, J. M., Hawk, T. C., & Coleman, R. E. (1999). Aging and recognition memory: changes in regional cerebral blood flow associated with components of reaction time distributions. Journal of Cognitive Neuroscience, 11(5), 511-520. https://doi.org/10.1162/089892999563571
Madden, D. J., Spaniol, J., Whiting, W. L., Bucur, B., Provenzale, J. M., Cabeza, R., White, L. E., & Huettel, S. A. (2007). Adult age differences in the functional neuroanatomy of visual attention: A combined fMRI and DTI study. Neurobiology of Aging, 28(3), 459-476. https://doi.org/10.1016/j.neurobiolaging.2006.01.005
Maillet, D., & Rajah, M. N. (2014). Age-related differences in brain activity in the subsequent memory paradigm: A meta-analysis. Neuroscience & Biobehavioral Reviews, 45, 246-257. https://doi.org/10.1016/j.neubiorev.2014.06.006
Mattay, Venkata. S., Fera, F., Tessitore, A., Hariri, A. R., Berman, K. F., Das, S., Meyer-Lindenberg, A., Goldberg, T. E., Callicott, J. H., & Weinberger, D. R. (2006). Neurophysiological correlates of age-related changes in working memory capacity. Neuroscience Letters, 392(1-2), 32-37. https://doi.org/10.1016/j.neulet.2005.09.025
Meulenbroek, O., Petersson, K. M., Voermans, N., Weber, B., & Fernández, G. (2004). Age differences in neural correlates of route encoding and route recognition. NeuroImage, 22(4), 1503-1514. https://doi.org/10.1016/j.neuroimage.2004.04.007
Nielson, K. A., Langenecker, S. A., & Garavan, H. (2002). Differences in the functional neuroanatomy of inhibitory control across the adult life span. Psychology and Aging, 17(1), 56-71. https://doi.org/10.1037/0882-7974.17.1.56
Nyberg, L., Cabeza, R., & Tulving, E. (1996). PET studies of encoding and retrieval: The HERA model. Psychonomic Bulletin & Review, 3(2), 135-148. https://doi.org/10.3758/BF03212412
Nyberg, L., Lövdén, M., Riklund, K., Lindenberger, U., & Bäckman, L. (2012). Memory aging and brain maintenance. Trends in Cognitive Sciences, 16(5), 292-305. https://doi.org/10.1016/j.tics.2012.04.005
Park, D. C., & Festini, S. B. (2017). Theories of memory and aging: A look at the past and a glimpse of the future. The Journals of Gerontology Series B: Psychological Sciences and Social Sciences, 72(1), 82-90. https://doi.org/10.1093/geronb/gbw066
Park, D. C., & Reuter-Lorenz, P. (2009). The adaptive brain: Aging and neurocognitive scaffolding. Annual Review of Psychology, 60(1), 173-196. https://doi.org/10.1146/annurev.psych.59.103006.093656
Park, D., & Minear, M. (2004). Cognitive Aging: New Directions for Old Theories. Içinde R. A. Dixon, L. Backman, & L. G. Nilsson (Ed.), New Frontiers in Cognitive Aging (ss. 19-40). Oxford University Press.
Park, H., Kennedy, K. M., Rodrigue, K. M., Hebrank, A., & Park, D. C. (2013). An fMRI study of episodic encoding across the lifespan: Changes in subsequent memory effects are evident by middle-age. Neuropsychologia, 51(3), 448-456. https://doi.org/10.1016/j.neuropsychologia.2012.11.025
Persson, J., Nyberg, L., Lind, J., Larsson, A., Nilsson, L.-G., Ingvar, M., & Buckner, R. L. (2006). Structure–function correlates of cognitive decline in aging. Cerebral Cortex, 16(7), 907-915. https://doi.org/10.1093/cercor/bhj036
Qualls, S. H., & Abeles, N. (Ed.). (2000). Psychology and the aging revolution: How we adapt to longer life. American Psychological Association. https://doi.org/10.1037/10363-000
Raji, C. A., Lopez, O. L., Kuller, L. H., Carmichael, O. T., Longstreth, W. T., Gach, H. M., Boardman, J., Bernick, C. B., Thompson, P. M., & Becker, J. T. (2012). White matter lesions and brain gray matter volume in cognitively normal elders. Neurobiology of Aging, 33(4), 834.e7-834.e16. https://doi.org/10.1016/j.neurobiolaging.2011.08.010
Reuter-Lorenz, P. A., & Cappell, K. A. (2008). Neurocognitive aging and the compensation hypothesis. Current Directions in Psychological Science, 17(3), 177-182. https://doi.org/10.1111/j.1467-8721.2008.00570.x
Reuter-Lorenz, P. A., Jonides, J., Smith, E. E., Hartley, A., Miller, A., Marshuetz, C., & Koeppe, R. A. (2000). Age differences in the frontal lateralization of verbal and spatial working memory revealed by PET. Journal of Cognitive Neuroscience, 12(1), 174-187. https://doi.org/10.1162/089892900561814
Reuter-Lorenz, P. A., & Mikels, J. A. (2006). The Aging Mind and Brain: Implications of Enduring Plasticity for Behavioral and Cultural Change. Içinde P. B. Baltes, P. A. Reuter-Lorenz, & F. Roesler (Ed.), Lifespan Development and the Brain: The Perspective of Biocultural Co-Constructivism (ss. 255-276), Cambridge University Press.
Reuter-Lorenz, P. A., & Park, D. C. (2014). How does it STAC up? Revisiting the scaffolding theory of aging and cognition. Neuropsychology Review, 24(3), 355-370. https://doi.org/10.1007/s11065-014-9270-9
Reuter-Lorenz, P. A., Stanczak, L., & Miller, A. C. (1999). Neural recruitment and cognitive aging: Two hemispheres are better than one, especially as you age. Psychological Science, 10(6), 494-500. https://doi.org/10.1111/1467-9280.00195
Rieckmann, A., Fischer, H., & Bäckman, L. (2010). Activation in striatum and medial temporal lobe during sequence learning in younger and older adults: Relations to performance. NeuroImage, 50(3), 1303-1312. https://doi.org/10.1016/j.neuroimage.2010.01.015
Rong, H., Lai, X., Jing, R., Wang, X., Fang, H., & Mahmoudi, E. (2020). Association of sensory impairments with cognitive decline and depression among older adults in China. JAMA Network Open, 3(9), e2014186-e2014186. https://doi.org/10.1001/jamanetworkopen.2020.14186
Rönnlund, M., Nyberg, L., Bäckman, L., & Nilsson, L.-G. (2005). Stability, growth, and decline in adult life span development of declarative memory: Cross-sectional and longitudinal data from a population-based study. Psychology and Aging, 20(1), 3-18. https://doi.org/10.1037/0882-7974.20.1.3
Rosen, A. C., Prull, M. W., O’Hara, R., Race, E. A., Desmond, J. E., Glover, G. H., Yesavage, J. A., & Gabrieli, J. D. E. (2002). Variable effects of aging on frontal lobe contributions to memory. NeuroReport, 13(18). https://doi.org/10.1097/00001756-200212200-00010
Salthouse, T. A. (1996). The processing-speed theory of adult age differences in cognition. Psychological Review, 103(3), 403-428. https://doi.org/10.1037/0033-295X.103.3.403
Salthouse, T. A. (2010). Selective review of cognitive aging. Journal of the International Neuropsychological Society, 16(5), 754-760. https://doi.org/10.1017/S1355617710000706
Schneider, B. A., & Pichora-Fuller, M. K. (2000). Implications of Perceptual Deterioration for Cognitive Aging Research. Içinde F. I. M. Craik & T. A. Salthouse (Ed.), Handbook of Cognitive Aging II (ss. 155-219). Lawrence Erlbaum Associates, Inc.
Schneider-Garces, N. J., Gordon, B. A., Brumback-Peltz, C. R., Shin, E., Lee, Y., Sutton, B. P., Maclin, E. L., Gratton, G., & Fabiani, M. (2010). Span, CRUNCH, and beyond: working memory capacity and the aging brain. Journal of Cognitive Neuroscience, 22(4), 655-669. https://doi.org/10.1162/jocn.2009.21230
Spaniol, J., & Grady, C. (2012). Aging and the neural correlates of source memory: over-recruitment and functional reorganization. Neurobiology of Aging, 33(2), 425.e3-425.e18. https://doi.org/10.1016/j.neurobiolaging.2010.10.005
Stebbins, G. T., Carrillo, M. C., Dorfman, J., Dirksen, C., Desmond, J. E., Turner, D. A., Bennett, D. A., Wilson, R. S., Glover, G., & Gabrieli, J. D. E. (2002). Aging effects on memory encoding in the frontal lobes. Psychology and Aging, 17(1), 44-55. https://doi.org/10.1037/0882-7974.17.1.44
Townsend, J., Adamo, M., & Haist, F. (2006). Changing channels: An fMRI study of aging and cross-modal attention shifts. NeuroImage, 31(4), 1682-1692. https://doi.org/10.1016/j.neuroimage.2006.01.045
Tulving, E., Kapur, S., Craik, F. I., Moscovitch, M., & Houle, S. (1994). Hemispheric encoding/retrieval asymmetry in episodic memory: positron emission tomography findings. Proceedings of the National Academy of Sciences, 91(6), 2016-2020. https://doi.org/10.1073/pnas.91.6.2016
Türkiye Alzheimer Derneği. (2020, Ağustos 29). Türkiye’de 600.000 aile Alzheimer hastalığı ile mücadele ediyor. Eylül 22, 2022 tarihinde https://Www.Alzheimerdernegi.Org.Tr/Turkiyede-600-000-Aile-Alzheimer-Hastaligi-Ile-Mucadele-Ediyor/ adresinden alındı.
Whiting, W. L., & Smith, A. D. (1997). Differential age-related processing limitations in recall and recognition tasks. Psychology and Aging, 12(2), 216-224. https://doi.org/10.1037/0882-7974.12.2.216
Wisdom, N. M., Mignogna, J., & Collins, R. L. (2012). Variability in Wechsler Adult Intelligence Scale-IV subtest performance across age. Archives of Clinical Neuropsychology, 27(4), 389-397. https://doi.org/10.1093/arclin/acs041
Zanjani, F., Downer, B. G., Kruger, T. M., Willis, S. L., & Schaie, K. W. (2013). Alcohol effects on cognitive change in middle-aged and older adults. Aging & Mental Health, 17(1), 12-23. https://doi.org/10.1080/13607863.2012.717254.

Ayrıntılar

Birincil Dil

Türkçe

Konular

Bilim ve Teknoloji Sosyolojisi ve Sosyal Bilimler

Bölüm

Derleme

Yazarlar

Elif Güldemir ^*
0000-0002-0532-7577
Türkiye

Handan Can Bu kişi benim
0000-0003-4991-9803
Türkiye

Yayımlanma Tarihi

31 Ağustos 2023

Gönderilme Tarihi

27 Aralık 2022

Kabul Tarihi

3 Temmuz 2023

Yayımlandığı Sayı

Yıl 2023 Sayı: 51

DOI

https://doi.org/10.52642/susbed.1225337

IZ

https://izlik.org/JA25GN99XH

APA

Güldemir, E., & Can, H. (2023). Nörobilişsel Yaşlanma Modelleri: Kaybedilenin Telafisi Mümkün mü? Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 51, 437-453. https://doi.org/10.52642/susbed.1225337

AMA

1.Güldemir E, Can H. Nörobilişsel Yaşlanma Modelleri: Kaybedilenin Telafisi Mümkün mü? SUSBED. 2023;(51):437-453. doi:10.52642/susbed.1225337

Chicago

Güldemir, Elif, ve Handan Can. 2023. “Nörobilişsel Yaşlanma Modelleri: Kaybedilenin Telafisi Mümkün mü?”. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, sy 51: 437-53. https://doi.org/10.52642/susbed.1225337.

EndNote

Güldemir E, Can H (01 Ağustos 2023) Nörobilişsel Yaşlanma Modelleri: Kaybedilenin Telafisi Mümkün mü? Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 51 437–453.

IEEE

[1]E. Güldemir ve H. Can, “Nörobilişsel Yaşlanma Modelleri: Kaybedilenin Telafisi Mümkün mü?”, SUSBED, sy 51, ss. 437–453, Ağu. 2023, doi: 10.52642/susbed.1225337.

ISNAD

Güldemir, Elif - Can, Handan. “Nörobilişsel Yaşlanma Modelleri: Kaybedilenin Telafisi Mümkün mü?”. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi. 51 (01 Ağustos 2023): 437-453. https://doi.org/10.52642/susbed.1225337.

JAMA

1.Güldemir E, Can H. Nörobilişsel Yaşlanma Modelleri: Kaybedilenin Telafisi Mümkün mü? SUSBED. 2023;:437–453.

MLA

Güldemir, Elif, ve Handan Can. “Nörobilişsel Yaşlanma Modelleri: Kaybedilenin Telafisi Mümkün mü?”. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, sy 51, Ağustos 2023, ss. 437-53, doi:10.52642/susbed.1225337.

Vancouver

1.Elif Güldemir, Handan Can. Nörobilişsel Yaşlanma Modelleri: Kaybedilenin Telafisi Mümkün mü? SUSBED. 01 Ağustos 2023;(51):437-53. doi:10.52642/susbed.1225337

24108 28027

Bu eser Creative Commons Attribution-NonCommercial 4.0 International Lisansı ile lisanslanmıştır.

Öz

Anahtar Kelimeler

Öz

Anahtar Kelimeler

Nörobilişsel Yaşlanma Modelleri: Kaybedilenin Telafisi Mümkün mü?

Öz

Anahtar Kelimeler

Neurocognitive Models of Aging: Is It Possible to Compensate for Loss?

Öz

Anahtar Kelimeler

Kaynakça

Ayrıntılar

Birincil Dil

Konular

Bölüm

Yazarlar

Yayımlanma Tarihi

Gönderilme Tarihi

Kabul Tarihi

Yayımlandığı Sayı

DOI

IZ

Kaynak Göster