Introduction

Action Observation Training (AOT) is being studied as a promising tool to improve upper limb function and it has been suggested that is likely to act by modulating the recruitment of the mirror neuron system.¹ Previous analyses in multiple sclerosis (MS) patients suggested that AOT is able to induce specific structural and functional brain changes within the motor and mirror neuron system.² Action Observation Training (AOT) facilitates motor functional recovery, possibly through a functional modulation of brain networks. The aim of this study is to assess whether AOT modifies brain dynamic functional network connectivity (dFNC) in healthy controls (HC) and multiple sclerosis (MS) patients with right (R) upper limb impairment. Applying a novel method of analysis, which allows a time-varying (dynamic) assessment of resting state functional connectivity, this study might improve our understanding of the functional substrates underlying motor deficit recovery in MS patients and contribute to develop individualized treatment strategies.

Methods

In this blind, controlled study, 87 R-handed subjects were randomized into 2 experimental groups (HC-AOT n=23; MS-AOT n=20) and 2 control groups (HC-C n=23; MS-C n=21). The 2-weeks training consisted of 10 sessions of 45 minutes. AOT-groups watched 3 daily-life actions videos alternated by their execution with the R hand; C-groups performed the same tasks watching landscape videos. At baseline (t0) and after 2 weeks (w2), resting state fMRI was obtained. Independent component analysis identified 41 FC networks (Figure 1).³ Between-group differences and dFNC changes over-time in each group were evaluated using a dynamic approach, i.e., assessing FC on small temporal segments using sliding windows, and then grouping FC correlation matrices into recurrent FC states.⁴

Results

After training, MS groups improved in right upper limb functions. Two recurrent FC states were detected: State1, showing strong inter-network connectivity; and State2, with weak inter-network connectivity. At t0, MS patients showed a consistent dFNC decrease vs HC (Figure 2), especially in State1, mainly involving basal ganglia, cerebellar and default mode networks (DMN), and some increase of dFNC of visual, executive and attention networks (Figure 3). DFNC was significantly increased over time in both MS groups, especially in State1, with more effects in MS-AOT than in MS-C, and an involvement of sensorimotor, visual, basal ganglia, DMN and attention networks. Conversely, HC-groups showed a decrease of dFNC at w2 vs t0, with a prevalent involvement of sensorimotor, basal ganglia, cerebellar and attention networks in HC-AOT, and of DMN and attention network in HC-C.

Discussion

Two weeks of motor training modulated dFNC of several functional networks with stronger effects in the MS-AOT than in the MS-C group. The significant increases over time involving sensorimotor, visual, basal ganglia, default mode and attention networks of MS-AOT are probably related to AOT specific characteristics.

Conclusions

Our findings might improve the understanding of the functional substrates underlying motor deficits recovery in MS patients and to develop individualized treatment strategies.

Acknowledgements

Partially supported by grants from Fondazione Italiana Sclerosi Multipla (FISM2012/R/15) and Italian Ministry of Health (RF-2011-02350374).

References

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