Neuroimaging Outcomes in Studies of Cognitive Training in Mild Cognitive Impairment and Early Alzheimer’s Disease: A Systematic Review

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Abstract

Background: Cognitive Training (CT) has demonstrated some benefits to cognitive and psychosocial function in Mild Cognitive Impairment (MCI) and early dementia, but the certainty related to those findings remains unclear. Therefore, understanding the mechanisms by which CT improves cognitive functioning may help to understand the relationships between CT and cognitive function.

The purpose of this review was to identify the evidence for neuroimaging outcomes in studies of CT in MCI and early Alzheimer’s Disease (AD).

Methods: Medline, Embase, Web of Science, PsycINFO, CINAHL, and The Cochrane Library were searched with a predefined search strategy, which yielded 1778 articles. Studies were suitable for inclusion where a CT program was used in patients with MCI or AD, with a structural or functional Magnetic Resonance Imaging (MRI) outcome. Studies were assessed for quality using the Downs and Black criteria.

Results: A total of 19 studies met the inclusion criteria. Quality of the included studies was variable and there was significant heterogeneity for studies included in this review. Task activation was generally increased post-training, but functional connectivity was both increased and decreased after training. Results varied by diagnosis, type of CT program, and brain networks examined. No effects were seen on hippocampal volumes post-training, but cortical thickening and increased grey matter volumes were demonstrated.

Conclusions: CT resulted in variable functional and structural changes in dementia, and conclusions are limited by heterogeneity and study quality. Larger, more robust studies are required to correlate these findings with clinical benefits from CT.

Keywords: Cognitive impairment, brain training, brain imaging, MCI, Alzheimer’s disease, vascular cognitive impairment.

[1]
Petersen RC. Mild cognitive impairment as a diagnostic entity. J Intern Med 2004; 256(3): 183-94.
[http://dx.doi.org/10.1111/j.1365-2796.2004.01388.x] [PMID: 15324362]
[2]
Cummings J, Lee G, Ritter A, Zhong K. Alzheimer's disease drug development pipeline: 2018 Alzheimer's & dementia (New York, NY) 2018; 4: 195-214.
[3]
Martin M, Clare L, Altgassen AM, Cameron MH, Zehnder F. Cognition-based interventions for healthy older people and people with mild cognitive impairment. Cochrane Database Syst Rev 2011; (1): CD006220
[http://dx.doi.org/10.1002/14651858.CD006220.pub2] [PMID: 21249675]
[4]
Belleville S. Cognitive training for persons with mild cognitive impairment. Int Psychogeriatr 2008; 20(1): 57-66.
[http://dx.doi.org/10.1017/S104161020700631X] [PMID: 17958927]
[5]
Gates NJ, Sachdev P. Is cognitive training an effective treatment for preclinical and early Alzheimer’s disease? J Alzheimers Dis 2014; 42(4): S551-9.
[http://dx.doi.org/10.3233/JAD-141302] [PMID: 25171716]
[6]
Bahar-Fuchs A, Clare L, Woods B. Cognitive training and cognitive rehabilitation for persons with mild to moderate dementia of the Alzheimer’s or vascular type: A review. Alzheimers Res Ther 2013; 5(4): 35.
[http://dx.doi.org/10.1186/alzrt189] [PMID: 23924584]
[7]
Bahar-Fuchs A, Martyr A, Goh AM, Sabates J, Clare L. Cognitive training for people with mild to moderate dementia. Cochrane Database Syst Rev 2019; 3 CD013069
[http://dx.doi.org/10.1002/14651858.CD013069.pub2] [PMID: 30909318]
[8]
Hill NT, Mowszowski L, Naismith SL, Chadwick VL, Valenzuela M, Lampit A. computerized cognitive training in older adults with mild cognitive impairment or dementia: A systematic review and meta-analysis. Am J Psychiatry 2017; 174(4): 329-40.
[http://dx.doi.org/10.1176/appi.ajp.2016.16030360] [PMID: 27838936]
[9]
ten Brinke LF, Davis JC, Barha CK, Liu-Ambrose T. Effects of computerized cognitive training on neuroimaging outcomes in older adults: A systematic review. BMC Geriatr 2017; 17(1): 139.
[http://dx.doi.org/10.1186/s12877-017-0529-x]
[10]
Belleville S, Bherer L. Biomarkers of cognitive training effects in aging. Curr Transl Geriatr Exp Gerontol Rep 2012; 1(2): 104-10.
[http://dx.doi.org/10.1007/s13670-012-0014-5] [PMID: 23864998]
[11]
Ikram MA, Vrooman HA, Vernooij MW, et al. Brain tissue volumes in relation to cognitive function and risk of dementia. Neurobiol Aging 2010; 31(3): 378-86.
[http://dx.doi.org/10.1016/j.neurobiolaging.2008.04.008] [PMID: 18501994]
[12]
Westman E, Cavallin L, Muehlboeck JS, et al. AddNeuroMed consortium. Sensitivity and specificity of medial temporal lobe visual ratings and multivariate regional MRI classification in Alzheimer’s disease. PLoS One 2011; 6(7) e22506
[http://dx.doi.org/10.1371/journal.pone.0022506] [PMID: 21811624]
[13]
Narayanan L, Murray AD. What can imaging tell us about cognitive impairment and dementia? World J Radiol 2016; 8(3): 240-54.
[http://dx.doi.org/10.4329/wjr.v8.i3.240] [PMID: 27029053]
[14]
Lehmann M, Koedam EL, Barnes J, et al. Alzheimer’s Disease Neuroimaging Initiative. Visual ratings of atrophy in MCI: Prediction of conversion and relationship with CSF biomarkers. Neurobiol Aging 2013; 34(1): 73-82.
[http://dx.doi.org/10.1016/j.neurobiolaging.2012.03.010] [PMID: 22516280]
[15]
Hosseini SM, Kramer JH, Kesler SR. Neural correlates of cognitive intervention in persons at risk of developing Alzheimer’s disease. Front Aging Neurosci 2014; 6: 231.
[http://dx.doi.org/10.3389/fnagi.2014.00231] [PMID: 25206335]
[16]
Park DC, Bischof GN. The aging mind: Neuroplasticity in response to cognitive training. Dialogues Clin Neurosci 2013; 15(1): 109-19.
[PMID: 23576894]
[17]
Park DC, Reuter-Lorenz P. The adaptive brain: Aging and neurocognitive scaffolding In Annu Rev Psychol 2009; 173-96.
[18]
Hagmann P, Jonasson L, Maeder P, Thiran JP, Wedeen VJ, Meuli R. Understanding diffusion MR imaging techniques: From scalar diffusion-weighted imaging to diffusion tensor imaging and beyond. Radiographics 2006; 26(1): S205-23.
[http://dx.doi.org/10.1148/rg.26si065510] [PMID: 17050517]
[19]
Health Quality Ontario. The appropriate use of neuroimaging in the diagnostic work-up of dementia: An evidence-based analysis. Ont Health Technol Assess Ser 2014; 14(1): 1-64.
[PMID: 24592296]
[20]
Grieve SM, Williams LM, Paul RH, Clark CR, Gordon E. Cognitive aging, executive function, and fractional anisotropy: A diffusion tensor MR imaging study. Am J Neuroradiol 2007; 28(2): 226-35.
[PMID: 17296985]
[21]
Glover GH. Overview of functional magnetic resonance imaging. Neurosurg Clin N Am 2011; 22(2): 133-139[vii.].
[http://dx.doi.org/10.1016/j.nec.2010.11.001] [PMID: 21435566]
[22]
Grade M, Hernandez Tamames JA, Pizzini FB, Achten E, Golay X, Smits M. A neuroradiologist’s guide to arterial spin labeling MRI in clinical practice. Neuroradiology 2015; 57(12): 1181-202.
[http://dx.doi.org/10.1007/s00234-015-1571-z] [PMID: 26351201]
[23]
Petcharunpaisan S, Ramalho J, Castillo M. Arterial spin labeling in neuroimaging. World J Radiol 2010; 2(10): 384-98.
[http://dx.doi.org/10.4329/wjr.v2.i10.384] [PMID: 21161024]
[24]
Rogers BP, Morgan VL, Newton AT, Gore JC. Assessing functional connectivity in the human brain by fMRI. Magn Reson Imaging 2007; 25(10): 1347-57.
[http://dx.doi.org/10.1016/j.mri.2007.03.007] [PMID: 17499467]
[25]
Vermeij A, Kessels RPC, Heskamp L, Simons EMF, Dautzenberg PLJ, Claassen JAHR. Prefrontal activation may predict working-memory training gain in normal aging and mild cognitive impairment. Brain Imaging Behav 2016; 11(1): 141-54.
[PMID: 26843001]
[26]
Belleville S, Clément F, Mellah S, Gilbert B, Fontaine F, Gauthier S. Training-related brain plasticity in subjects at risk of developing Alzheimer’s disease. Brain 2011; 134(6): 1623-34.
[http://dx.doi.org/10.1093/brain/awr037] [PMID: 21427462]
[27]
Chhatwal JP, Sperling RA. Functional MRI of mnemonic networks across the spectrum of normal aging, mild cognitive impairment, and Alzheimer’s disease. J Alzheimers Dis 2012; 31(3): S155-67.
[28]
Sala-Llonch R, Bartrés-Faz D, Junqué C. Reorganization of brain networks in aging: A review of functional connectivity studies. Front Psychol 2015; 6(663): 663.
[http://dx.doi.org/10.3389/fpsyg.2015.00663] [PMID: 26052298]
[29]
Morcom AM, Henson RNA. Increased prefrontal activity with aging reflects nonspecific neural responses rather than compensation. J Neurosci 2018; 38(33): 7303-13.
[http://dx.doi.org/10.1523/JNEUROSCI.1701-17.2018] [PMID: 30037829]
[30]
Moher D, Liberati A, Tetzlaff J, Altman DG. PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Med 2009; 6(7) e1000097
[http://dx.doi.org/10.1371/journal.pmed.1000097] [PMID: 19621072]
[31]
Gates NJ, Sachdev PS, Fiatarone Singh MA, Valenzuela M. Cognitive and memory training in adults at risk of dementia: A systematic review. BMC Geriatr 2011; 11: 55.
[http://dx.doi.org/10.1186/1471-2318-11-55] [PMID: 21942932]
[32]
Downs SH, Black N. The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non-randomised studies of health care interventions. J Epidemiol Community Health 1998; 52(6): 377-84.
[http://dx.doi.org/10.1136/jech.52.6.377] [PMID: 9764259]
[33]
Huntley JD, Hampshire A, Bor D, Owen A, Howard RJ. Adaptive working memory strategy training in early Alzheimer’s disease: Randomised controlled trial. Br J Psychiatry 2017; 210(1): 61-6.
[http://dx.doi.org/10.1192/bjp.bp.116.182048] [PMID: 27758836]
[34]
Barban F, Mancini M, Cercignani M, et al. A pilot study on brain plasticity of functional connectivity modulated by cognitive training in mild Alzheimer’s disease and mild cognitive impairment. Brain Sci 2017; 7(5) E50
[http://dx.doi.org/10.3390/brainsci7050050] [PMID: 28468232]
[35]
Yang H, Leaver AM, Siddarth P, et al. Neurochemical and neuroanatomical plasticity following memory training and yoga interventions in older adults with mild cognitive impairment. Front Aging Neurosci 2016; 8: 277.
[http://dx.doi.org/10.3389/fnagi.2016.00277]
[36]
Feng W, Wang D, Tang L, et al. Effects of different cognitive trainings on amnestic mild cognitive impairment in the elderly: A one-year longitudinal functional magnetic resonance imaging (MRI) study. Med Sci Monit 2018; 24: 5517-27.
[http://dx.doi.org/10.12659/MSM.908315] [PMID: 30089102]
[37]
Suo C, Singh MF, Gates N, et al. Therapeutically relevant structural and functional mechanisms triggered by physical and cognitive exercise. Mol Psychiatry 2016; 21(11): 1645.
[http://dx.doi.org/10.1038/mp.2016.57] [PMID: 27090304]
[38]
Na HR, Lim JS, Kim WJ, et al. Multimodal Assessment of neural substrates in computerized cognitive training: A preliminary study. J Clin Neurol 2018; 14(4): 454-63.
[http://dx.doi.org/10.3988/jcn.2018.14.4.454] [PMID: 30198220]
[39]
Zhang H, Wang Z, Wang J, et al. Computerized multi-domain cognitive training reduces brain atrophy in patients with amnestic mild cognitive impairment. Transl Psychiatry 2019; 9(1): 48.
[http://dx.doi.org/10.1038/s41398-019-0385-x] [PMID: 30705261]
[40]
Hampstead BM, Stringer AY, Stilla RF, Giddens M, Sathian K. Mnemonic strategy training partially restores hippocampal activity in patients with mild cognitive impairment. Hippocampus 2012; 22(8): 1652-8.
[http://dx.doi.org/10.1002/hipo.22006] [PMID: 22368035]
[41]
Rosen AC, Sugiura L, Kramer JH, Whitfield-Gabrieli S, Gabrieli JD. Cognitive training changes hippocampal function in mild cognitive impairment: A pilot study. J Alzheimers Dis 2011; 26(3): 349-57.
[http://dx.doi.org/10.3233/JAD-2011-0009] [PMID: 21971474]
[42]
Hampstead BM, Stringer AY, Stilla RF, et al. Activation and effective connectivity changes following explicit-memory training for face-name pairs in patients with mild cognitive impairment: A pilot study. Neurorehabil Neural Repair 2011; 25(3): 210-22.
[http://dx.doi.org/10.1177/1545968310382424] [PMID: 20935339]
[43]
Simon SS, Hampstead BM, Nucci MP, et al. Cognitive and brain activity changes after mnemonic strategy training in amnestic mild cognitive impairment: Evidence from a randomized controlled trial. Front Aging Neurosci 2018; 10: 342.
[http://dx.doi.org/10.3389/fnagi.2018.00342] [PMID: 30483113]
[44]
Hampstead BM, Stringer AY, Stilla RF, Sathian K. Mnemonic strategy training increases neocortical activation in healthy older adults and patients with mild cognitive impairment. Int J Psychophysiol 2020; 154: 27-36.
[http://dx.doi.org/10.1016/j.ijpsycho.2019.04.011]] [PMID: 31067489]
[45]
De Marco M, Meneghello F, Pilosio C, Rigon J, Venneri A. Up-regulation of DMN connectivity in mild cognitive impairment via network-based cognitive training. Curr Alzheimer Res 2018; 15(6): 578-89.
[http://dx.doi.org/10.2174/1567205015666171212103323] [PMID: 29231140]
[46]
Lin F, Heffner KL, Ren P, et al. Cognitive and neural effects of vision-based speed-of-processing training in older adults with amnestic mild cognitive impairment: A pilot study. J Am Geriatr Soc 2016; 64(6): 1293-8.
[http://dx.doi.org/10.1111/jgs.14132] [PMID: 27321608]
[47]
Lin F, Heffner KL, Ren P, Tadin D. A role of the parasympathetic nervous system in cognitive training. Curr Alzheimer Res 2017; 14(7): 784-9.
[http://dx.doi.org/10.2174/1567205014666170203095128] [PMID: 28164771]
[48]
Eyre HA, Acevedo B, Yang H, et al. Changes in neural connectivity and memory following a yoga intervention for older adults: a pilot study. J Alzheimers Dis 2016; 52(2): 673-84.
[http://dx.doi.org/10.3233/JAD-150653] [PMID: 27060939]
[49]
Li BY, He NY, Qiao Y, et al. Computerized cognitive training for Chinese mild cognitive impairment patients: A neuropsychological and fMRI study. Neuroimage Clin 2019; 22 101691
[http://dx.doi.org/10.1016/j.nicl.2019.101691] [PMID: 30708349]
[50]
Pantoni L, Poggesi A, Diciotti S, et al. Effect of attention training in mild cognitive impairment patients with subcortical vascular changes: The RehAtt study. J Alzheimers Dis 2017; 60(2): 615-24.
[http://dx.doi.org/10.3233/JAD-170428] [PMID: 28869475]
[51]
Reuter-Lorenz PA, Cappell KA. Neurocognitive aging and the compensation hypothesis. Curr Dir Psychol Sci 2008; 17(3): 177-82.
[http://dx.doi.org/10.1111/j.1467-8721.2008.00570.x]
[52]
Berlingeri M, Danelli L, Bottini G, Sberna M, Paulesu E. Reassessing the HAROLD model: Is the hemispheric asymmetry reduction in older adults a special case of compensatory-related utilisation of neural circuits? Exp Brain Res 2013; 224(3): 393-410.
[http://dx.doi.org/10.1007/s00221-012-3319-x] [PMID: 23178904]
[53]
Cabeza R. Hemispheric asymmetry reduction in older adults: the HAROLD model. Psychol Aging 2002; 17(1): 85-100.
[http://dx.doi.org/10.1037/0882-7974.17.1.85] [PMID: 11931290]
[54]
Goh JO, Park DC. Neuroplasticity and cognitive aging: The scaffolding theory of aging and cognition. Restor Neurol Neurosci 2009; 27(5): 391-403.
[http://dx.doi.org/10.3233/RNN-2009-0493] [PMID: 19847066]
[55]
Schneider-Garces NJ, Gordon BA, Brumback-Peltz CR, et al. Span, CRUNCH, and beyond: Working memory capacity and the aging brain. J Cogn Neurosci 2010; 22(4): 655-69.
[http://dx.doi.org/10.1162/jocn.2009.21230] [PMID: 19320550]
[56]
Festini SB, Zahodne L, Reuter-Lorenz PA. Theoretical perspectives on age differences in brain activation: HAROLD, PASA, CRUNCH-how do they stac up?. Oxford University Press 2018.
[57]
Reuter-Lorenz PA, Park DC. How does it STAC up? Revisiting the scaffolding theory of aging and cognition. Neuropsychol Rev 2014; 24(3): 355-70.
[http://dx.doi.org/10.1007/s11065-014-9270-9] [PMID: 25143069]
[58]
Myrum C. Is PASA Passé? Rethinking compensatory mechanisms in cognitive aging. J Neurosci 2019; 39(5): 786-7.
[http://dx.doi.org/10.1523/JNEUROSCI.2348-18.2018] [PMID: 30700526]
[59]
Mevel K, Chételat G, Eustache F, Desgranges B. The default mode network in healthy aging and Alzheimer’s disease. Int J Alzheimers Dis 2011; 2011 535816
[http://dx.doi.org/10.4061/2011/535816]
[60]
Weiler M, Casseb RF, De Ligo Teixeira CV, et al. Alzheimer’s disease patients with higher cognitive reserve present more efficient network topology. Alzheimers Dement 2017; 13(7): 584.
[http://dx.doi.org/10.1016/j.jalz.2017.07.209]
[61]
Sheline YI, Raichle ME. Resting state functional connectivity in preclinical Alzheimer’s disease. Biol Psychiatry 2013; 74(5): 340-7.
[http://dx.doi.org/10.1016/j.biopsych.2012.11.028] [PMID: 23290495]
[62]
Brier MR, Thomas JB, Snyder AZ, et al. Loss of intranetwork and internetwork resting state functional connections with Alzheimer’s disease progression. J Neurosci 2012; 32(26): 8890-9.
[http://dx.doi.org/10.1523/JNEUROSCI.5698-11.2012] [PMID: 22745490]
[63]
Brier MR, Thomas JB, Ances BM. Network dysfunction in Alzheimer’s disease: Refining the disconnection hypothesis. Brain Connect 2014; 4(5): 299-311.
[http://dx.doi.org/10.1089/brain.2014.0236] [PMID: 24796856]
[64]
Bakker A, Krauss GL, Albert MS, et al. Reduction of hippocampal hyperactivity improves cognition in amnestic mild cognitive impairment. Neuron 2012; 74(3): 467-74.
[http://dx.doi.org/10.1016/j.neuron.2012.03.023] [PMID: 22578498]
[65]
Li M, Zheng G, Zheng Y, et al. Alterations in resting-state functional connectivity of the default mode network in amnestic mild cognitive impairment: An fMRI study. BMC Med Imaging 2017; 17(1): 48.
[http://dx.doi.org/10.1186/s12880-017-0221-9] [PMID: 28814282]
[66]
Das SR, Pluta J, Mancuso L, et al. Increased functional connectivity within medial temporal lobe in mild cognitive impairment. Hippocampus 2013; 23(1): 1-6.
[http://dx.doi.org/10.1002/hipo.22051] [PMID: 22815064]
[67]
Lampit A, Hallock H, Valenzuela M. Computerized cognitive training in cognitively healthy older adults: A systematic review and meta-analysis of effect modifiers. PLoS Med 2014; 11(11) e1001756
[http://dx.doi.org/10.1371/journal.pmed.1001756] [PMID: 25405755]
[68]
Cheng Y, Wu W, Feng W, 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.
[http://dx.doi.org/10.1186/1741-7015-10-30] [PMID: 22453114]
[69]
Motter JN, Devanand DP, Doraiswamy PM, Sneed JR. Clinical trials to gain FDA approval for computerized cognitive training: What is the ideal control condition? Front Aging Neurosci 2016; 8: 249.
[http://dx.doi.org/10.3389/fnagi.2016.00249] [PMID: 27853432]
[70]
McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer’s disease: Report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 1984; 34(7): 939-44.
[http://dx.doi.org/10.1212/WNL.34.7.939] [PMID: 6610841]
[71]
Organisation WH. International classification of diseases. WHO 2010.
[72]
Organisation WH. International classification of diseases 11. WHO 2018.
[73]
Association AP. Diagnostic and statistical manual of mental health disorders (DSM-IV). APA 2000.
[74]
Association AP. Diagnostic and statistical manual of mental health disorders (DSM-V). APA 2013.
[http://dx.doi.org/10.1176/appi.books.9780890425596]
[75]
McKhann GM, Knopman DS, Chertkow H, et al. The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 2011; 7(3): 263-9.
[http://dx.doi.org/10.1016/j.jalz.2011.03.005] [PMID: 21514250]
[76]
Petersen RC, Caracciolo B, Brayne C, Gauthier S, Jelic V, Fratiglioni L. Mild cognitive impairment: A concept in evolution. J Intern Med 2014; 275(3): 214-28.
[http://dx.doi.org/10.1111/joim.12190] [PMID: 24605806]
[77]
Winblad B, Palmer K, Kivipelto M, et al. Mild cognitive impairment--beyond controversies, towards a consensus: Report of the International Working Group on Mild Cognitive Impairment. J Intern Med 2004; 256(3): 240-6.
[http://dx.doi.org/10.1111/j.1365-2796.2004.01380.x] [PMID: 15324367]
[78]
Román GC, Tatemichi TK, Erkinjuntti T, et al. Vascular dementia: Diagnostic criteria for research studies. Report of the NINDS-AIREN International Workshop. Neurology 1993; 43(2): 250-60.
[http://dx.doi.org/10.1212/WNL.43.2.250] [PMID: 8094895]