Multimodal Assessment of Neural Substrates in Computerized Cognitive Training: A Preliminary Study

Abstract

Background and PurposeSeveral studies have validated the clinical efficacy of computerized cognitive training applications. However, few studies have investigated the neural substrates of these training applications using simultaneous multimodal neuroimaging modalities. We aimed to determine the effectiveness of computerized cognitive training and corresponding neural substrates through a multimodal approach.MethodsTen patients with mild cognitive impairment (MCI), six patients with subjective memory impairment (SMI), and 10 normal controls received custom-developed computerized cognitive training in the memory clinic of a university hospital. All of the participants completed 24 sessions of computerized cognitive training, each lasting 40 minutes and performed twice weekly. They were assessed using neuropsychological tests (both computerized and conventional), electroencephalography, fluorodeoxyglucose positron-emission tomography (FDG-PET), volumetric magnetic resonance imaging (MRI), and diffusion-tensor imaging (DTI) at pre- and posttraining.ResultsThe patients with MCI exhibited significant improvements in the trail-making test–black & white-B, and memory domain of the computerized cognitive assessment. Subjects with normal cognition exhibited significant improvements in scores in the language and attention-/psychomotor-speed domains. There were no significant changes in subjects with SMI. In the pre- and posttraining evaluations of the MCI group, FDG-PET showed focal activation in the left anterior insula and anterior cingulate after training. Volumetric MRI showed a focal increase in the cortical thickness in the rostral anterior cingulate. DTI revealed increased fractional anisotropy in several regions, including the anterior cingulate.ConclusionsThe anterior cingulate and anterior insula, which are parts of the salience network, may be substrates for the improvements in cognitive function induced by computerized cognitive training.

Functional MRI-Specific Alterations in Salience Network in Mild Cognitive Impairment: An ALE Meta-Analysis

“…The insula, especially the anterior insula, is a critical node of the SN which connects many areas including the prefrontal cortex and the parietal lobe and engages in the transformation between cognitive domains (Cerliani et al, 2012 ). A study by Na et al reported that the MCI subgroup revealed focal activation in the left anterior insula and ACC after 24 sessions of computerized cognitive training (Na et al, 2018 ). The PreCG, which overlaps with the SMA, is involved in producing and controlling the movement (Cai et al, 2017 ).…”

Effects of preventive interventions on neuroimaging biomarkers in subjects at-risk to develop Alzheimer's disease: A systematic review

“…The populations with nCI exhibited one of the following risk factors: (1) subjective memory complaints/impairment (SMC/SMI) ( n = 3; Youn et al, 2009 ; Risacher et al, 2015 ; Na et al, 2018 ); (2) “probable MCI” defined by a mini-mental state examination (MMSE) score within normal range but a reduced Montreal cognitive assessment (MoCA) score ( n = 1; ten Brinke et al, 2015 ); (3) at-risk for dementia based on the CAIDE score (Cardiovascular Risk Factors, Aging, and Incidence of Dementia; Kivipelto et al, 2006 ) with cognitive performance at average or slightly lower level than expected according to Finnish population norms for Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neuropsychological battery (Moms et al, 1989 ) ( n = 2; Stephen et al, 2019 , 2020 ); (4) limitations in one instrumental activity of daily living or slow gait speed or spontaneous memory complaints ( n = 1; Delrieu et al, 2020 ); (5) high systolic blood pressure ( n = 1; van Dalen et al, 2017 ); (6) elevated amyloid load or subthreshold amyloid levels [cerebral-to-cerebellar standard uptake value ratio (SUVR) threshold > 1.0; n = 1; Vidoni et al, 2021 ], or (7) hypertension and elevated amyloid load or subthreshold amyloid levels (SUVR > 1.0, see Vidoni et al, 2021 ) ( n = 1; Kaufman et al, 2021 ).…”

“…Various CT were used, computerized ( n = 5) or non-computerized ( n = 8), uni- or multi-domain and aimed at improving domains such as memory, attention or executive functions. Over the five computerized CT, four targeted multiple cognitive domains (Barban et al, 2017 ; Na et al, 2018 ; Li et al, 2019 ; Zhang et al, 2019 ) while only one focussed on solely improving working memory (Vermeij et al, 2016 ). Among the eight non-computerized CT, two used multi-domain CT (Ciarmiello et al, 2015 ; Park et al, 2019 ), one included both multi-domain and uni-domain (Feng et al, 2018 ), and five tested single domains (Belleville et al, 2011 ; Yang et al, 2016 ; Hohenfeld et al, 2017 ; Simon et al, 2018 ; Youn et al, 2019 ).…”

“…A decrease of WM mean diffusivity was observed, usually associated with increased myelination and axon density, while GMV was not impacted (Youn et al, 2019 ). Conversely, a 12 weeks multi-domain computerized CT did not affect WM nor integrity of GMV in SCI participants, however no sham condition was examined (Na et al, 2018 ). For patients with CI—no matter what the type of neuroimaging biomarker considered and for trials with sham interventions—positive results outweighed null results.…”

“…All trials examining the effect of multiple CT on brain morphology presented positive results, especially on GMV ( Table 5 ). For participants with MCI, GMV was increased and WM integrity preserved by 12 weeks of computerized CT targeting multiple domains (Na et al, 2018 ).…”