P 20 fMRI-associations with performance increase by mental imagery training of finger sequence. Issue 10 (October 2017)

• Record Type: Journal Article
• Authors: Lebon, F.; Horn, U.; Domin, M.; Lotze, M.
• Is Part Of: Clinical neurophysiology. Volume 128:Issue 10(2017:Oct.)
• Page Start: e336
• Page End: e337
• Publication Date: 2017-10
• Subjects: Neurophysiology -- Periodicals; Electroencephalography -- Periodicals; Electromyography -- Periodicals; Neurology -- Periodicals; 612.8
• DOI: 10.1016/j.clinph.2017.06.099
• Languages: English
• ISSNs: 1388-2457

Abstract

Abstract : Objective: Motor imagery (MI) is the mental simulation of action frequently used by professionals in different fields. The knowledge about changes in functional representation of motor patterns trained with mental imagery is sparse. In addition, we do not know how changes in functional representation during imagery training are associated with preciseness of imagined performance. We therefore intended to investigate changes in functional representation going along with performance changes (error, velocity) during a highly controlled (for intensity and temporal accuracy) mental imagery training (finger sequence performance) in 51 healthy young volunteers. Methods: fMRI: mental imagery was measured with fMRI (3 Tesla, EPI with TR: 2 s) over 170 s pre and post training. Executed movements before and after training served for the assessment of training gain. Participants were instructed to move or to imagine moving the fingers of the right hand in a specific order in time with a 2 Hz blinking dot. Participants were given a key pad and were instructed to combine kinesthetic and visual imagery strategies. We tested the temporal congruence of the imagined finger sequence 10 times during training and rated imagery vividness on a 7-point Likert scale. Imaging analysis was performed using a full factorial design with SPM8 and a significance level of p < . 05, corrected for the whole brain volume (FWE). Linear regression (ROI-analysis for hippocampus, fusiform gyrus, BA 6, BA 44, parietal sulcus, cerebellar hemisphere; FWE; p < . 05 ) was performed for performance changes over training (error, velocity) and scores during training for the changes for the MI-task over time. In addition, we tested whether training outcome (error, velocity) could be predicted by MI-pre-measurement. Results: Performance increased for spatial accuracy (less errors; ( t (47) = 1.99; p (one sided) = .026)) and velocity of finger movements ( t (47) = 4.01; p = .001). For fMRI we found expected differences between the EX and MI task (Fig. 1, top left). Only the MI task showed fMRI-changes over time (Fig. 1, top right). fMRI-activation change in the fusiform gyrus went along with rated intensity of imagery during training (Fig. 1, bottom left). fMRI-activation intensity of left hippocampus during MI pre predicted spatial accuracy after training (error number low;Fig. 1, bottom right). Conclusion: Mental imagery minus execution of finger sequence showed increased intraparietal sulcus activation comparable to previous studies (Boecker et al., 2002 ). Inferior left parietal activation during MI was increasing over training. The anterior hippocampus and the fusiform gyrus have been identified as important for spatial imagery before (Jahn et al., 2009 ). Here we showed that the right anterior hippocampus during pre-training MI is predictive for spatial accuracy after training - a finding also reported before (Huijbers et al., 2011 ). Only fMRI was capable of predicting spatial preciseness outcome but not imagery scores (MIQ, vividness). However, MI vividness rated during training was associated with increase of fusiform gyrus activation over training indicating high visual imagery strategies (Huijbers et al., 2011 ).