Cognitive Improvement and Brain Changes after Real-Time Functional MRI Neurofeedback Training in Healthy Elderly and Prodromal Alzheimer’s Disease

Abstract

BackgroundCognitive decline is characteristic for Alzheimer’s disease (AD) and also for healthy ageing. As a proof-of-concept study, we examined whether this decline can be counteracted using real-time fMRI neurofeedback training. Visuospatial memory and the parahippocampal gyrus (PHG) were targeted.MethodsSixteen healthy elderly subjects (mean age 63.5 years, SD = 6.663) and 10 patients with prodromal AD (mean age 66.2 years, SD = 8.930) completed the experiment. Four additional healthy subjects formed a sham-feedback condition to validate the paradigm. The protocol spanned five examination days (T1–T5). T1 contained a neuropsychological pre-test, the encoding of a real-world footpath, and an anatomical MRI scan of the brain. T2–T4 included the fMRI neurofeedback training paradigm, in which subjects learned to enhance activation of the left PHG while recalling the path encoded on T1. At T5, the neuropsychological post-test and another anatomical MRI brain scan were performed. The neuropsychological battery included the Montreal Cognitive Assessment (MoCA); the Visual and Verbal Memory Test (VVM); subtests of the Wechsler Memory Scale (WMS); the Visual Patterns Test; and Trail Making Tests (TMT) A and B.ResultsHealthy elderly and patients with prodromal AD showed improved visuospatial memory performance after neurofeedback training. Healthy subjects also performed better in a working-memory task (WMS backward digit-span) and in the MoCA. Both groups were able to elicit parahippocampal activation during training, but no significant changes in brain activation were found over the course of the training. However, Granger-causality-analysis revealed changes in cerebral connectivity over the course of the training, involving the parahippocampus and identifying the precuneus as main driver of activation in both groups. Voxel-based morphometry showed increases in grey matter volumes in the precuneus and frontal cortex. Neither cognitive enhancements, nor parahippocampal activation were found in the control group undergoing sham-feedback.ConclusionThese findings suggest that cognitive decline, either related to prodromal AD or healthy ageing, could be counteracted using fMRI-based neurofeedback. Future research needs to determine the potential of this method as a treatment tool.

A Guide to Literature Informed Decisions in the Design of Real Time fMRI Neurofeedback Studies: A Systematic Review

“…The ability for one rt-fMRI neurofeedback session to make lasting changes to neural processes and symptomology is less credible. Limited work suggests that patients with schizophrenia benefited from two sessions of neurofeedback, and that a third did not add to their ability to regulate (Dyck et al, 2016), but Hohenfeld et al (2017) found that older adults didn't improve in their ability to regulate after the first session. Neither of these studies were designed to evaluate the influence of number of sessions on sustained behavior or symptom changes at follow-up.…”

“…The ability to regulate activity associated with cognition with the aid of rt-fMRI neurofeedback have also been investigated, with 12 published studies using various tasks. Individuals are able to use neurofeedback to improve sustained attention (Debettencourt et al, 2015), working memory (Zhang et al, 2013), and visual memory (Hohenfeld et al, 2017). There may also be potential to use this technique in prodromal stages of Alzheimer's, individuals with schizophrenia (Cordes et al, 2015), adults with ADHD (Zilverstand et al, 2017), and major depressive disorder (Schnyer et al, 2015).…”

Neurofeedback with fMRI: A critical systematic review

“…Another study demonstrated that neurofeedback participants could regulate the DLPFC and improve working memory performance compared to a mental rehearsal control . In a more recent study, participants failed to regulate their parahippocampal gyrus, but improved on 3 of 14 memory tests (Hohenfeld et al, 2017); however, the researchers make no mention of accounting for multiple comparison and they used an underpowered placebo-nf group with four participants, compared to the 16 receiving genuine-nf.…”

“…Biofeedback of real-time functional magnetic resonance imaging data from t SMA supplementary motor area Hanlon et al, (2013) . Reduction of cue-induced craving through realtime neurofeedback in nicotine use PMC premotor cortex Harmelech et al, (2015) Hohenfeld, C., Nellessen, N., Dogan, I., Kuhn, H., Müller, C., Papa, F., et al (2017). Cognitive improvement and brain changes after real-time functional MRI neurofeedback PHC parahippocampal cortex Hui et al, (2014); Xie et al, Karch, S., Keeser, D., Hümmer, S., Paolini, M., Kirsch, V., Karali, T., et al (2015).…”

Tonic resting-state hubness supports high-frequency activity defined verbal-memory encoding network in epilepsy

“…In the first study of its kind, applying an integrated IEEG-fMRI method, we have shown that established markers of memory encoding correspond to meaningful network differences captured by rsfMRI. In clinical terms, knowing a region is a hub, playing an important role in multi-regional and multi-functional connectivity, may inform technologies trying to identify the most effective targets to electrically or pharmacologically stimulate for cognitive enhancement in areas such as memory Ezzyat Y et al, 2018;Kucewicz MT et al, 2018), or perhaps be used to identify the areas with sufficient influence over targets to generate effective neuro-feedback loops (Hohenfeld C et al, 2017;Murphy AC et al, 2017).…”