[ARTICLE] Interindividual differences in motor network connectivity and behavioral response to iTBS in stroke patients – Full Text


Multimodal assessment of motor system integrity for predicting iTBS-aftereffects

Effective connectivity of M1 predicts behavioral iTBS-aftereffects

No association between iTBS-aftereffects and BOLD activity or RMT/AMT/SICI

Effects of brain stimulation strongly influenced by connectivity of stimulated region


Cerebral plasticity-inducing approaches like repetitive transcranial magnetic stimulation (rTMS) are of high interest in situations where reorganization of neural networks can be observed, e.g., after stroke. However, an increasing number of studies suggest that improvements in motor performance of the stroke-affected hand following modulation of primary motor cortex (M1) excitability by rTMS shows a high interindividual variability. We here tested the hypothesis that in stroke patients the interindividual variability of behavioral response to excitatory rTMS is related to interindividual differences in network connectivity of the stimulated region. Chronic stroke patients (n = 14) and healthy controls (n = 12) were scanned with functional magnetic resonance imaging (fMRI) while performing a simple hand motor task. Dynamic causal modeling (DCM) was used to investigate effective connectivity of key motor regions. On two different days after the fMRI experiment, patients received either intermittent theta-burst stimulation (iTBS) over ipsilesional M1 or control stimulation over the parieto-occipital cortex. Motor performance and TMS parameters of cortical excitability were measured before and after iTBS. Our results revealed that patients with better motor performance of the affected hand showed stronger endogenous coupling from supplemental motor area (SMA) onto M1 before starting the iTBS intervention. Applying iTBS to ipsilesional M1 significantly increased ipsilesional M1 excitability and decreased contralesional M1 excitability as compared to control stimulation. Individual behavioral improvements following iTBS specifically correlated with neural coupling strengths in the stimulated hemisphere prior to stimulation, especially for connections targeting the stimulated M1. Combining endogenous connectivity and behavioral parameters explained 82% of the variance in hand motor performance observed after iTBS. In conclusion, the data suggest that the individual susceptibility to iTBS after stroke is influenced by interindividual differences in motor network connectivity of the lesioned hemisphere.

1. Introduction

Recovery of function after stroke is driven by reorganization of neural networks in both the lesioned and unaffected hemispheres (Cramer, 2008). However, spontaneous recovery after stroke often remains incomplete (Kolominsky-Rabas et al., 2006). One strategy to improve the functional outcome of patients suffering from brain lesions is to modulate cerebral plasticity by means of non-invasive brain stimulation such as, e.g., repetitive transcranial magnetic stimulation (rTMS) (Ridding and Rothwell, 2007). Although to date a direct proof is missing, increasing evidence exist that rTMS-effects are mediated by changes in synaptic transmission (Funke and Benali, 2011 ;  Hoogendam et al., 2010). One specific strategy to ameliorate motor impairments in stroke patients is to enhance cortical excitability of the motor cortex in the lesioned hemisphere (Khedr et al., 2005). An effective protocol of rTMS to induce such increase in excitability of the motor cortex following a relatively short (i.e., 3.5 min) stimulation period is intermittent theta-burst stimulation (iTBS) (Huang et al., 2005).

Consequently, proof-of-principle studies have been able to demonstrate that iTBS applied to ipsilesional M1 improve hand motor function in stroke patients (Ackerley et al., 2010Hsu et al., 2012 ;  Talelli et al., 2007b). A major issue, however, with rTMS (including iTBS) induced cerebral plasticity is high inter-individual variability of the effects induced in both healthy subjects (Daskalakis et al., 2006Hamada et al., 2013 ;  Muller-Dahlhaus et al., 2008) and stroke patients (Ameli et al., 2009 ;  Grefkes and Fink, 2012). For example, Hamada et al. (2013) demonstrated that application of iTBS in healthy subjects leads to an increase of motor-cortical excitability in only 52% subjects, while the other half responded in an opposite way with a decrease of excitability. Likewise, Ameli et al. (2009) reported that in patients suffering from cortical strokes, only half of them showed behavioral improvements after 10 Hz rTMS while the other half even deteriorated with their stroke affected hands. Such opposed stimulation after-effects are likely to contribute to absent overall effects across the entire group (Hamada et al., 2013).

Apart from known sources of response variability following iTBS like age (Freitas et al., 2011), genetic polymorphisms of the brain-derived neurotrophic factor (Cheeran et al., 2008 ;  Kleim et al., 2006) and technical aspects such as the direction of current flow, the intensity of stimulation and the number of pulses applied (Gamboa et al., 2010Gentner et al., 2008 ;  Talelli et al., 2007a), clinical factors like lesion location, degree of neurological impairment and time since stroke are also likely to impact on the response to rTMS (Grefkes and Fink, 2012). For example, several studies demonstrated that patients with subcortical lesions have a higher probability to improve after rTMS than patients with cortical lesions (Ameli et al., 2009 ;  Hsu et al., 2012). Moreover, the pathomechanisms underlying stroke-induced motor deficits do not only depend on direct tissue damage due to ischemia, but might also comprise network disturbances remote from the stroke lesion (Grefkes and Fink, 2011 ;  Grefkes and Fink, 2014). Thus, changes in network interactions are likely to constitute another important factor for the evolution of rTMS-aftereffects as TMS does not only interfere with neural tissue of the stimulated hemisphere but also with neural activity levels of regions that are interconnected with the stimulation site (Bestmann et al., 2005).

Hence, there is good reason to assume that specific inter-individual differences (or abnormalities post-stroke) in network connectivity might – at least in part – influence response to rTMS. Support for this hypothesis stems from studies with patients suffering from dystonia in which reduced functional connectivity between premotor cortex and M1 was indicative for responding to rTMS (Huang et al., 2010 ;  Quartarone et al., 2003). Furthermore, changes in motor-evoked potential (MEP) amplitudes following rTMS have been shown to be associated with higher effective connectivity between supplementary motor area (SMA), ventral premotor cortex (vPMC) and M1 of the stimulated hemisphere (Cardenas-Morales et al., 2014).

Therefore, in stroke patients, the variability of the individual response to plasticity-inducing intervention might depend on how the stimulation interacts with the pre-existing connectivity in a given functional network, e.g., the motor system. In order to identify factors that are associated with a positive behavioral effect in response to intermittent theta burst stimulation (here: iTBS) applied to ipsilesional M1, we used a multimodal approach consisting of clinical scales, electrophysiological parameters measured using single- and paired-pulse TMS, as well as functional magnetic resonance imaging (fMRI) and dynamic causal modeling (DCM) to assess effective connectivity of the cortical motor network. We reasoned that the systems level perspective offered by DCM might be useful for identifying predictors that indicate whether or not a patient will respond to non-invasive brain stimulation given that (i) focal brain stimulation also impacts on activity levels of areas connected to the stimulation site (Bestmann et al., 2003 ;  Grefkes et al., 2010) and (ii) recovery of motor function depends on changes in the entire motor network rather than changes in M1 only (Rehme et al., 2012 ;  Ward et al., 2003). Here, especially the coupling strengths between ipsilesional M1 and premotor areas might be indicative for the behavioral after-effect of iTBS given the role of these connections in motor performance in both healthy subjects and stroke (Pool et al., 2013Pool et al., 2014 ;  Rehme et al., 2011a). […]

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Fig. 4

Fig. 4. Neural activity when patients and controls moved the affected or unaffected hand. Fist closures were conducted at a fixed movement frequency of 0.8 Hz and at a frequency adjusted to individual performance levels. Compared to controls, patients featured enhanced activity in both hemispheres during movements of the affected hand. Movements of the unaffected hand yielded a similar activation pattern in patients and controls. T-values are represented by the color bar. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)




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