Structural brain changes after traditional and robot-assisted multi-domain cognitive training in community-dwelling healthy elderly

Geon Ha Kim, Seun Jeon, Kiho Im, Hunki Kwon, Byung Hwa Lee, Ga Young Kim, Hana Jeong, Noh Eul Han, Sang Won Seo, Hanna Cho, Young Noh, Sang Eon Park, Hojeong Kim, Jung Won Hwang, Cindy W Yoon, Hee Jin Kim, Byoung Seok Ye, Ju Hee Chin, Jung-Hyun Kim, Mee Kyung Suh, Jong Min Lee, Sung Tae Kim, Mun-Taek Choi, Mun Sang Kim, Kenneth M Heilman, Jee Hyang Jeong, Duk L Na, Geon Ha Kim, Seun Jeon, Kiho Im, Hunki Kwon, Byung Hwa Lee, Ga Young Kim, Hana Jeong, Noh Eul Han, Sang Won Seo, Hanna Cho, Young Noh, Sang Eon Park, Hojeong Kim, Jung Won Hwang, Cindy W Yoon, Hee Jin Kim, Byoung Seok Ye, Ju Hee Chin, Jung-Hyun Kim, Mee Kyung Suh, Jong Min Lee, Sung Tae Kim, Mun-Taek Choi, Mun Sang Kim, Kenneth M Heilman, Jee Hyang Jeong, Duk L Na

Abstract

The purpose of this study was to investigate if multi-domain cognitive training, especially robot-assisted training, alters cortical thickness in the brains of elderly participants. A controlled trial was conducted with 85 volunteers without cognitive impairment who were 60 years old or older. Participants were first randomized into two groups. One group consisted of 48 participants who would receive cognitive training and 37 who would not receive training. The cognitive training group was randomly divided into two groups, 24 who received traditional cognitive training and 24 who received robot-assisted cognitive training. The training for both groups consisted of daily 90-min-session, five days a week for a total of 12 weeks. The primary outcome was the changes in cortical thickness. When compared to the control group, both groups who underwent cognitive training demonstrated attenuation of age related cortical thinning in the frontotemporal association cortices. When the robot and the traditional interventions were directly compared, the robot group showed less cortical thinning in the anterior cingulate cortices. Our results suggest that cognitive training can mitigate age-associated structural brain changes in the elderly.

Trial registration: ClnicalTrials.gov NCT01596205.

Conflict of interest statement

Competing Interests: Dr. S.W. Seo received research support from the Ministry for Health, Welfare and Family Affairs, Korea. Dr. D.L. Na received research support from Gaha Corporation through a research grant to Samsung Medical Center, and a grant from the Ministry for Health, Welfare and Family Affairs, Korea. All other authors report no disclosures. We do not have any other relevant relationships including employment, consultancy, products in development, marketed products or patent rights from Gaha Corporation. Although Samsung Medical Center has made a contract with Gaha Corporation to receive a royalty from Robocare for the software programs fitted in the robot, none of the authors including Dr. Na benefit from this personally. The authors declare that neither funding from Gaha Corporation nor the reception of royalty from Robocare alters the authors' adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1. Flow of participants in this…
Fig 1. Flow of participants in this study.
The similarity index was defined as follows:similarity index = 2 * nnz(A and B)/(nnz(A) + nnz(B)) where A and B are the baseline and post-intervention connectivity from binary matrices, respectively and nnz refers to the number of non-zero elements in a matrix. If the two binary matrices were the same, the similarity index was assigned a value of 1. We excluded subjects with a similarity index lower than 0.5 in our statistical analyses to reduce the artifactual effects related to the different times of scanning.
Fig 2. Topographical changes in cortical thickness.
Fig 2. Topographical changes in cortical thickness.
(A) Compared to the control group, the intervention group shows attenuated cortical thinning on heteromodal association cortices such as the bilateral medial prefrontal and right middle temporal gyrus. (B) When the traditional and robot groups were directly compared, significantly reduced cortical thinning on the bilateral anterior cingulate cortices and right inferior temporal cortex was evident in the robot group. No area demonstrated less cortical thinning in the traditional group than the robot group.
Fig 3. Topographical changes in nodal strength.
Fig 3. Topographical changes in nodal strength.
(A) There are no significant differences in regional nodal strength between the control and the intervention group. (B)The robot group shows increased nodal strength in the rectus gyrus than the traditional group.
Fig 4. Correlation of changes in cognitive…
Fig 4. Correlation of changes in cognitive functions and changes in cortical thickness.
(A) In the traditional group, changes in the raw scores of visual memory are positively correlated with those of cortical thickness in the right inferior temporalgyrus and right subgenual cingulate region (uncorrected P < 0.001). (B) For the robot group, changes in the raw scores of executive function are positively correlated with those of left temoporo-parietal junction as well as left inferior temporal gyrus (uncorrected P <0.001).

References

    1. Smith GE, Housen P, Yaffe K, Ruff R, Kennison RF, Mahncke HW, et al. A cognitive training program based on principles of brain plasticity: results from the Improvement in Memory with Plasticity-based Adaptive Cognitive Training (IMPACT) study. J Am Geriatr Soc. 2009;57: 594–603. 10.1111/j.1532-5415.2008.02167.x
    1. Valenzuela M, Sachdev P. Can cognitive exercise prevent the onset of dementia? Systematic review of randomized clinical trials with longitudinal follow-up. Am J Geriatr Psychiatry. 2009;17: 179–187. 10.1097/JGP.0b013e3181953b57
    1. Salat DH, Buckner RL, Snyder AZ, Greve DN, Desikan RS, Busa E, et al. Thinning of the cerebral cortex in aging. Cereb Cortex. 2004;14: 721–730.
    1. Engvig A, Fjell AM, Westlye LT, Moberget T, Sundseth O, Larsen VA, et al. Effects of memory training on cortical thickness in the elderly. Neuroimage. 2010;52: 1667–1676. 10.1016/j.neuroimage.2010.05.041
    1. Wenger E, Schaefer S, Noack H, Kuhn S, Martensson J, Heinze HJ, et al. Cortical thickness changes following spatial navigation training in adulthood and aging. Neuroimage. 2012;59: 3389–3397. 10.1016/j.neuroimage.2011.11.015
    1. Eckroth-Bucher M, Siberski J. Preserving cognition through an integrated cognitive stimulation and training program. Am J Alzheimers Dis Other Demen. 2009;24: 234–245. 10.1177/1533317509332624
    1. Cheng Y, Wu W, Feng W, Wang J, Chen Y, Shen Y, et al. The effects of multi-domain versus single-domain cognitive training in non-demented older people: a randomized controlled trial. BMC Med. 2012;10: 30 10.1186/1741-7015-10-30
    1. Gates N, Valenzuela M. Cognitive exercise and its role in cognitive function in older adults. Curr Psychiatry Rep. 2010;12: 20–27. 10.1007/s11920-009-0085-y
    1. Rebok GW, Carlson MC, Langbaum JB. Training and maintaining memory abilities in healthy older adults: traditional and novel approaches. J Gerontol B Psychol Sci Soc Sci. 2007;62 Spec No 1: 53–61.
    1. Kueider AM, Parisi JM, Gross AL, Rebok GW. Computerized cognitive training with older adults: a systematic review. PLoS One. 2012;7: e40588 10.1371/journal.pone.0040588
    1. Gates NJ, Sachdev P. Is cognitive training an effective treatment for preclinical and early Alzheimer's disease? J Alzheimers Dis. 2014;42 Suppl 4: S551–559. 10.3233/JAD-141302
    1. Pieramico V, Esposito R, Sensi F, Cilli F, Mantini D, Mattei PA, et al. Combination training in aging individuals modifies functional connectivity and cognition, and is potentially affected by dopamine-related genes. PLoS One. 2012;7: e43901 10.1371/journal.pone.0043901
    1. Reddy R. Robotics and intelligent systems in support of society. IEEE Intell Syst. 2006;21: 24–31.
    1. Han C, Jo SA, Jo I, Kim E, Park MH, Kang Y. An adaptation of the Korean mini-mental state examination (K-MMSE) in elderly Koreans: demographic influence and population-based norms (the AGE study). Arch Gerontol Geriatr. 2008;47: 302–310.
    1. Kang Y, Na DL. Seoul neurophsychological screening battery: professional manual. Incheon: Human Brain Research & Consulting Co; 2003.
    1. Barnard ND, Bush AI, Ceccarelli A, Cooper J, de Jager CA, Erickson KI, et al. Dietary and lifestyle guidelines for the prevention of Alzheimer's disease. Neurobiol Aging. 2014;35 Suppl 2: S74–78. 10.1016/j.neurobiolaging.2014.03.033
    1. Lee Y, Back JH, Kim J, Kim SH, Na DL, Cheong HK, et al. Systematic review of health behavioral risks and cognitive health in older adults. Int Psychogeriatr. 2010;22: 174–187. 10.1017/S1041610209991189
    1. Ko HJ, Youn CH. Effects of laughter therapy on depression, cognition and sleep among the community-dwelling elderly. Geriatr Gerontol Int. 2011;11: 267–274. 10.1111/j.1447-0594.2010.00680.x
    1. Chun MY. Validity and reliability of korean version of international physical activity questionnaire short form in the elderly. Korean J Fam Med. 2012;33: 144–151. 10.4082/kjfm.2012.33.3.144
    1. Im K, Lee JM, Lee J, Shin YW, Kim IY, Kwon JS, et al. Gender difference analysis of cortical thickness in healthy young adults with surface-based methods. Neuroimage. 2006;31: 31–38.
    1. Bullmore E, Sporns O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat Rev Neurosci. 2009;10: 186–198. 10.1038/nrn2575
    1. Youn JC, Lee DY, Kim KW, Lee JH, Jhoo JH, Lee KU, et al. Development of the Korean version of Alzheimer's Disease Assessment Scale (ADAS-K). Int J Geriatr Psychiatry. 2002;17: 797–803.
    1. Im K, Lee JM, Seo SW, Yoon U, Kim ST, Kim YH, et al. Variations in cortical thickness with dementia severity in Alzheimer's disease. Neurosci Lett. 2008;436: 227–231. 10.1016/j.neulet.2008.03.032
    1. Seo SW, Im K, Lee JM, Kim ST, Ahn HJ, Go SM, et al. Effects of demographic f actors on cortical thickness in Alzheimer's disease. Neurobiol Aging. 2011;32: 200–209. 10.1016/j.neurobiolaging.2009.02.004
    1. Collins DL, Neelin P, Peters TM, Evans AC. Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J Comput Assist Tomogr. 1994;18: 192–205.
    1. Sled JG, Zijdenbos AP, Evans AC. A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging. 1998;17: 87–97.
    1. Zijdenbos AP, Evans AC, Riahi F, Sled JG, Chui J, Kollokian V. Automatic quantification of multiple sclerosis lesion volume using stereotaxic space In: Höhne KH, Kikinis R, editors. Visualization in biomedical computing. Lecture Notes in Computer Science. 1131 Berlin: Springer; 1996. pp. 439–448.
    1. Kim JS, Singh V, Lee JK, Lerch J, Ad-Dab'bagh Y, MacDonald D, et al. Automated 3-D extraction and evaluation of the inner and outer cortical surfaces using a Laplacian map and partial volume effect classification. Neuroimage. 2005;27: 210–221.
    1. Lerch JP, Pruessner JC, Zijdenbos A, Hampel H, Teipel SJ, Evans AC. Focal decline of cortical thickness in Alzheimer's disease identified by computational neuroanatomy. Cereb Cortex. 2005;15: 995–1001.
    1. Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, et al. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage. 2002;15: 273–289.
    1. Gong G, He Y, Concha L, Lebel C, Gross DW, Evans AC, et al. Mapping anatomical connectivity patterns of human cerebral cortex using in vivo diffusion tensor imaging tractography. Cereb Cortex. 2009;19: 524–536. 10.1093/cercor/bhn102
    1. Cho H, Jeon S, Kang SJ, Lee JM, Lee JH, Kim GH, et al. Longitudinal changes of cortical thickness in early- versus late-onset Alzheimer's disease. Neurobiol Aging. 2013;34: 1921.e9–1921.e15. 10.1016/j.neurobiolaging.2013.01.004
    1. Nichols TE, Holmes AP. Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum Brain Mapp. 2002;15: 1–25.
    1. Hurtz S, Woo E, Kebets V, Green AE, Zoumalan C, Wang B, et al. Age effects on cortical thickness in cognitively normal elderly individuals. Dement Geriatr Cogn Dis Extra. 2014;4: 221–227. 10.1159/000362872
    1. Mesulam MM. From sensation to cognition. Brain. 1998;121 (Pt 6): 1013–1052.
    1. Fjell AM, Westlye LT, Amlien I, Espeseth T, Reinvang I, Raz N, et al. High consistency of regional cortical thinning in aging across multiple samples. Cereb Cortex. 2009;19: 2001–2012. 10.1093/cercor/bhn232
    1. Ilg R, Wohlschlager AM, Gaser C, Liebau Y, Dauner R, Woller A, et al. Gray matter increase induced by practice correlates with task-specific activation: a combined functional and morphometric magnetic resonance imaging study. J Neurosci. 2008;28: 4210–4215. 10.1523/JNEUROSCI.5722-07.2008
    1. Muotri AR, Gage FH. Generation of neuronal variability and complexity. Nature. 2006;441: 1087–1093.
    1. Chapman SB, Aslan S, Spence JS, Defina LF, Keebler MW, Didehbani N, et al. Shorter term aerobic exercise improves brain, cognition, and cardiovascular fitness in aging. Front Aging Neurosci. 2013;5: 75 10.3389/fnagi.2013.00075
    1. Holroyd CB, Yeung N. Motivation of extended behaviors by anterior cingulate cortex. Trends Cogn Sci. 2012;16: 122–128. 10.1016/j.tics.2011.12.008
    1. Levy R, Dubois B. Apathy and the functional anatomy of the prefrontal cortex-basal ganglia circuits. Cereb Cortex. 2006;16: 916–928.
    1. Tun PA, Lachman ME. The association between computer use and cognition across adulthood: use it so you won't lose it? Psychol Aging. 2010;25: 560–568. 10.1037/a0019543
    1. Heilman KM, Valenstein E. Frontal lobe neglect in man. Neurology. 1972;22: 660–664.
    1. Watson RT, Heilman KM, Cauthen JC, King FA. Neglect after cingulectomy. Neurology. 1973;23: 1003–1007.
    1. Liu Y, Bengson J, Huang H, Mangun GR, Ding M. Top-down Modulation of Neural Activity in Anticipatory Visual Attention: Control Mechanisms Revealed by Simultaneous EEG-fMRI. Cereb Cortex. 2014. (In Press).
    1. Wu K, Taki Y, Sato K, Kinomura S, Goto R, Okada K, et al. Age-related changes in topological organization of structural brain networks in healthy individuals. Hum Brain Mapp. 2012;33: 552–568. 10.1002/hbm.21232
    1. Zhu W, Wen W, He Y, Xia A, Anstey KJ, Sachdev P. Changing topological patterns in normal aging using large-scale structural networks. Neurobiol Aging. 2012;33: 899–913. 10.1016/j.neurobiolaging.2010.06.022
    1. Ballmaier M, Toga AW, Blanton RE, Sowell ER, Lavretsky H, Peterson J, et al. Anterior cingulate, gyrus rectus, and orbitofrontal abnormalities in elderly depressed patients: an MRI-based parcellation of the prefrontal cortex. Am J Psychiatry. 2004;161: 99–108.
    1. Szatkowska I, Szymanska O, Marchewka A, Soluch P, Rymarczyk K. Dissociable contributions of the left and right posterior medial orbitofrontal cortex in motivational control of goal-directed behavior. Neurobiol Learn Mem. 2011;96: 385–391. 10.1016/j.nlm.2011.06.014
    1. Krain AL, Wilson AM, Arbuckle R, Castellanos FX, Milham MP. Distinct neural mechanisms of risk and ambiguity: a meta-analysis of decision-making. Neuroimage. 2006;32: 477–484.
    1. Kringelbach ML. The human orbitofrontal cortex: linking reward to hedonic experience. Nat Rev Neurosci. 2005;6: 691–702.
    1. Morecraft RJ, Geula C, Mesulam MM. Cytoarchitecture and neural afferents of orbitofrontal cortex in the brain of the monkey. J Comp Neurol. 1992;323: 341–358.
    1. Luciana M, Nelson CA. Assessment of neuropsychological function through use of the Cambridge Neuropsychological Testing Automated Battery: performance in 4- to 12-year-old children. Dev Neuropsychol. 2002;22: 595–624.
    1. Nouchi R, Taki Y, Takeuchi H, Hashizume H, Akitsuki Y, Shigemune Y, et al. Brain training game improves executive functions and processing speed in the elderly: a randomized controlled trial. PLoS One. 2012;7: e29676 10.1371/journal.pone.0029676
    1. McKee JL, Riesenhuber M, Miller EK, Freedman DJ. Task dependence of visual and category representations in prefrontal and inferior temporal cortices. J Neurosci. 2014;34: 16065–16075. 10.1523/JNEUROSCI.1660-14.2014
    1. Nieuwenhuis IL, Takashima A. The role of the ventromedial prefrontal cortex in memory consolidation. Behav Brain Res. 2011;218: 325–334. 10.1016/j.bbr.2010.12.009
    1. Rudebeck PH, Putnam PT, Daniels TE, Yang T, Mitz AR, Rhodes SE, et al. A role for primate subgenual cingulate cortex in sustaining autonomic arousal. Proc Natl Acad Sci U S A. 2014;111: 5391–5396. 10.1073/pnas.1317695111
    1. Hellige JB. Hemispheric asymmetry for visual information processing. Acta Neurobiol Exp (Wars). 1996;56: 485–497.
    1. Vossel S, Geng JJ, Fink GR. Dorsal and ventral attention systems: distinct neural circuits but collaborative roles. Neuroscientist. 2014;20: 150–159. 10.1177/1073858413494269
    1. Tanji J, Shima K, Mushiake H. Concept-based behavioral planning and the lateral prefrontal cortex. Trends Cogn Sci. 2007;11: 528–534.
    1. Jiang J, Sachdev P, Lipnicki DM, Zhang H, Liu T, Zhu W, et al. A longitudinal study of brain atrophy over two years in community-dwelling older individuals. Neuroimage. 2014;86: 203–211. 10.1016/j.neuroimage.2013.08.022
    1. Bemelmans R, Gelderblom GJ, Jonker P, de Witte L. Socially assistive robots in elderly care: a systematic review into effects and effectiveness. J Am Med Dir Assoc. 2012;13: 114–120. e1 10.1016/j.jamda.2010.10.002

Source: PubMed

3
購読する