EP 131. Real-time fMRI neurofeedback training in elderly leads to cognitive improvement and changes in cerebral connectivity. Issue 9 (September 2016)

• Record Type: Journal Article
• Authors: Hohenfeld, C.; Nellessen, N.; Dogan, I.; Kuhn, H.; Müller, C.; Papa, F.; Ketteler, S.; Shah, N.J.; Schulz, J.; Reske, M.; Reetz, K.
• Is Part Of: Clinical neurophysiology. Volume 127:Issue 9(2016:Sep.)
• Page Start: e295
• Page End: e296
• Publication Date: 2016-09
• Subjects: Neurophysiology -- Periodicals; Electroencephalography -- Periodicals; Electromyography -- Periodicals; Neurology -- Periodicals; 612.8
• DOI: 10.1016/j.clinph.2016.05.171
• Languages: English
• ISSNs: 1388-2457

Abstract

Abstract : Introduction: During past years real-time functional MRI (rtfMRI) has been shown to be a feasible tool for neurofeedback (NFB). This is a technique, which aims at subjects learning to voluntarily modulate activation of specific brain regions. It has already been applied successfully clinically and non-clinically. We conducted rtfMRI NFB training of the left parahippocampal gyrus (PHG) in healthy elderly with the hypothesis subjects are indeed able to modulate left PHG activation and that this training leads to increased cognitive performance. Here, we also focus on brain connectivity over the course of the training. Methods: 16 subjects (mean age 63.5 y, 9 male) completed the protocol of five examination days (T1–T5). On T1 the neuropsychological pre-test was done (see table), followed by the encoding of a real-world footpath (one out of three variants). On T2–T4 the rtfMRI NFB training was carried out. Activation of the left PHG was fed back visually by a thermometer bar. The task alternated between upregulation (recalling the path encoded on T1) and baseline (counting backwards). Three rtfMRI NFB runs were done per day. On T5 the neuropsychological post-test was done. For analysis of neuropsychological data ANCOVAs with examination day and variant of the footpath as factors and age, education and gender as covariates were calculated. For fMRI data a general linear model with upregulation as predictor was computed with BrainVoyager QX for each NFB run and the activation was then averaged across all runs. Activation was limited to a threshold of Bonferroni-corrected p < . 05 and two voxels of cluster size. To conduct an analysis of connectivity, activation time courses were extracted from clusters active during upregulation and averaged for each day and region. With the statistical software R, a Granger-Causality-Analysis (GCA) for each training day was conducted for each combination of active regions (306 connections) with a lag size of 1 volume (2000 ms). P -values were corrected using the Bonferroni-Holm method. Results: Subjects showed improvements in the following neuropsychological tests: a visuo-spatial-memory task from the VVM ( F (1, 13) = 8.378, p = .013), the backward-digit-span task from the WMS ( F (1, 13) = 6.919, p = .021) and the MoCA ( F (1, 13) = 12.204, p = .004). Functional MRI analysis revealed that during NFB training the left PHG was indeed activated. Activation was further found in the right PHG, the left posterior cingulate, bilaterally in the precuneus, superior occipital lobe, middle frontal gyrus and the cerebellum. GCA revealed 133 connections on T2, 206 on T3 and 156 on T4. The main findings were: (1) activation was chiefly driven by both anterior lobes of the cerebellum, the left posterior cingulate and a cluster within the right precuneus, but these regions received only few input from other regions; (2) there was no connectivity between both PHG; (3) the amount of connections to both PHG increased over time, while the amount of connections from both PHG to other regions such as the right cerebellum and the right precuneus tended to decrease. Conclusions: The neuropsychological, activation and connectivity data from our NFB training in elderly suggest the following: (1) subjects were able to modulate left PHG activation; (2) the conducted training lead to increased cognitive performance; (3) GCA revealed a complex underlying neuronal network, mainly driven by a small number of regions and with a changing role of the target region of the training over time.