• Alexander Thiel, Alexander Hartmann, Ilona Rubi-Fessen, Carole Anglade, Lutz Kracht, Nora Weiduschat, Josef Kessler, Thomas Rommel, and Wolf-Dieter Heiss.
• Department of Neurology and Neurosurgery, McGill University, Montreal, Canada. alexander.thiel@mcgill.ca
• Stroke. 2013 Aug 1;44(8):2240-6.

Background And PurposeModulation of activity in language networks using repetitive transcranial magnetic stimulation (rTMS) may possibly support recovery from poststroke aphasia. Case series and feasibility studies seem to indicate a therapeutic effect; however, randomized sham-controlled, proof-of-principle studies relating clinical effects to activation patterns are missing.MethodsTwenty-four patients with subacute poststroke aphasia were randomized to a 10-day protocol of 20-minute inhibitory 1 Hz rTMS over the right triangular part of the posterior inferior frontal gyrus or sham stimulation, followed by 45 minutes of speech and language therapy. Activity in language networks was measured with O-15-water positron emission tomography during verb generation before and after treatment. Language performance was assessed using the Aachen Aphasia Test battery.ResultsThe primary outcome measure, global Aachen Aphasia Test score change, was significantly higher in the rTMS group (t test, P=0.003). Increases were largest for subtest naming (P=0.002) and tended to be higher for comprehension, token test, and writing (P<0.1). Patients in the rTMS group activated proportionally more voxels in the left hemisphere after treatment than before (difference in activation volume index) compared with sham-treated patients (t test, P=0.002).There was a moderate but significant linear relationship between activation volume index change and global Aachen Aphasia Test score change (r2=0.25; P=0.015).ConclusionsTen sessions of inhibitory rTMS over the right posterior inferior frontal gyrus, in combination with speech and language therapy, significantly improve language recovery in subacute ischemic stroke and favor recruitment of left-hemispheric language networks.

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