Behavioral and neuroanatomical correlates of facial emotion processing in post-stroke depression.

BACKGROUND: Emotion processing deficits are known to accompany depressive symptoms and are often seen in stroke patients. Little is known about the influence of post-stroke depressive (PSD) symptoms and specific brain lesions on altered emotion processing abilities and how these phenomena develop over time. This potential relationship may impact post-stroke rehabilitation of neurological and psychosocial function. To address this scientific gap, we investigated the relationship between PSD symptoms and emotion processing abilities in a longitudinal study design from the first days post-stroke into the early chronic phase. METHODS: Twenty-six ischemic stroke patients performed an emotion processing task on videos with emotional faces ('happy,' 'sad,' 'anger,' 'fear,' and 'neutral') at different intensity levels (20%, 40%, 60%, 80%, 100%). Recognition accuracies and response times were measured, as well as scores of depressive symptoms (Montgomery-Åsberg Depression Rating Scale). Twenty-eight healthy participants matched in age and sex were included as a control group. Whole-brain support-vector regression lesion-symptom mapping (SVR-LSM) analyses were performed to investigate whether specific lesion locations were associated with the recognition accuracy of specific emotion categories. RESULTS: Stroke patients performed worse in overall recognition accuracy compared to controls, specifically in the recognition of happy, sad, and fearful faces. Notably, more depressed stroke patients showed an increased processing towards specific negative emotions, as they responded significantly faster to angry faces and recognized sad faces of low intensities significantly more accurately. These effects obtained for the first days after stroke partly persisted to follow-up assessment several months later. SVR-LSM analyses revealed that inferior and middle frontal regions (IFG/MFG) and insula and putamen were associated with emotion-recognition deficits in stroke. Specifically, recognizing happy facial expressions was influenced by lesions affecting the anterior insula, putamen, IFG, MFG, orbitofrontal cortex, and rolandic operculum. Lesions in the posterior insula, rolandic operculum, and MFG were also related to reduced recognition accuracy of fearful facial expressions, whereas recognition deficits of sad faces were associated with frontal pole, IFG, and MFG damage. CONCLUSION: PSD symptoms facilitate processing negative emotional stimuli, specifically angry and sad facial expressions. The recognition accuracy of different emotional categories was linked to brain lesions in emotion-related processing circuits, including insula, basal ganglia, IFG, and MFG. In summary, our study provides support for psychosocial and neural factors underlying emotional processing after stroke, contributing to the pathophysiology of PSD.

Neuroanatomy of post-stroke depression: the association between symptom clusters and lesion location.

Post-stroke depression affects about 30% of stroke patients and often hampers functional recovery. The diagnosis of depression encompasses heterogeneous symptoms at emotional, motivational, cognitive, behavioural or somatic levels. Evidence indicates that depression is caused by disruption of bio-aminergic fibre tracts between prefrontal and limbic or striatal brain regions comprising different functional networks. Voxel-based lesion-symptom mapping studies reported discrepant findings regarding the association between infarct locations and depression. Inconsistencies may be due to the usage of sum scores, thereby mixing different symptoms of depression. In this cross-sectional study, we used multivariate support vector regression for lesion-symptom mapping to identify regions significantly involved in distinct depressive symptom domains and global depression. MRI lesion data were included from 200 patients with acute first-ever ischaemic stroke (mean 0.9 ± 1.5 days of post-stroke). The Montgomery-Åsberg Depression Rating interview assessed depression severity in five symptom domains encompassing motivational, emotional and cognitive symptoms deficits, anxiety and somatic symptoms and was examined 8.4 days of post-stroke (±4.3). We found that global depression severity, irrespective of individual symptom domains, was primarily linked to right hemispheric lesions in the dorsolateral prefrontal cortex and inferior frontal gyrus. In contrast, when considering distinct symptom domains individually, the analyses yielded much more sensitive results in regions where the correlations with the global depression score yielded no effects. Accordingly, motivational deficits were associated with lesions in orbitofrontal cortex, dorsolateral prefrontal cortex, pre- and post-central gyri and basal ganglia, including putamen and pallidum. Lesions affecting the dorsal thalamus, anterior insula and somatosensory cortex were significantly associated with emotional symptoms such as sadness. Damage to the dorsolateral prefrontal cortex was associated with concentration deficits, cognitive symptoms of guilt and self-reproach. Furthermore, somatic symptoms, including loss of appetite and sleep disturbances, were linked to the insula, parietal operculum and amygdala lesions. Likewise, anxiety was associated with lesions impacting the central operculum, insula and inferior frontal gyrus. Interestingly, symptoms of anxiety were exclusively left hemispheric, whereas the lesion-symptom associations of the other domains were lateralized to the right hemisphere. In conclusion, this large-scale study shows that in acute stroke patients, differential post-stroke depression symptom domains are associated with specific structural correlates. Our findings extend existing concepts on the neural underpinnings of depressive symptoms, indicating that differential lesion patterns lead to distinct depressive symptoms in the first weeks of post-stroke. These findings may facilitate the development of personalized treatments to improve post-stroke rehabilitation.

To engage or not engage: Early incentive motivation prevents symptoms of chronic post-stroke depression - A longitudinal study.

BACKGROUND: Although post-stroke depression (PSD) is known to disrupt motor rehabilitation after stroke, PSD is often undertreated and its relationship with motor impairment remains poorly understood. METHODS: In a longitudinal study design we investigated, which factors at the early post-acute stage may increase the risk for PSD symptoms. We were especially interested in whether interindividual differences in the motivational drive to engage in physically demanding tasks indicate PSD development in patients suffering from motor impairments. Accordingly, we used a monetary incentive grip force task where participants were asked to hold their grip force for high and low rewards at stake to maximize their monetary outcome. Individual grip force was normalized according to the maximal force prior to the experiment. Experimental data, depression, and motor impairment were assessed from 20 stroke patients (12 male; 7.7 ± 6.78 days post-stroke) with mild-to-moderate hand motor impairment and 24 age-matched healthy participants (12 male). RESULTS: Both groups showed incentive motivation as indicated by stronger grip force for high versus low reward trials and the overall monetary outcome in the task. In stroke patients, severely impaired patients showed stronger incentive motivation, whereas early PSD symptoms were associated with reduced incentive motivation in the task. Larger lesions in corticostriatal tracts correlated with reduced incentive motivation. Importantly, chronic motivational deficits were preceded by initially reduced incentive motivation and larger corticostriatal lesions in the early stage post-stroke. CONCLUSIONS: More severe motor impairment motivates reward-dependent motor engagement, whereas PSD and corticostriatal lesions potentially disturb incentive motivational behavior, thereby increasing the risk of chronic motivational PSD symptoms. Acute interventions should address motivational aspects of behavior to improve motor rehabilitation post-stroke.

Dynamic connectivity predicts acute motor impairment and recovery post-stroke.

Thorough assessment of cerebral dysfunction after acute lesions is paramount to optimize predicting clinical outcomes. We here built random forest classifier-based prediction models of acute motor impairment and recovery post-stroke. Predictions relied on structural and resting-state fMRI data from 54 stroke patients scanned within the first days of symptom onset. Functional connectivity was estimated via static and dynamic approaches. Motor performance was phenotyped in the acute phase and 6 months later. A model based on the time spent in specific dynamic connectivity configurations achieved the best discrimination between patients with and without motor impairments (out-of-sample area under the curve, 95% confidence interval: 0.67 ± 0.01). In contrast, patients with moderate-to-severe impairments could be differentiated from patients with mild deficits using a model based on the variability of dynamic connectivity (0.83 ± 0.01). Here, the variability of the connectivity between ipsilesional sensorimotor cortex and putamen discriminated the most between patients. Finally, motor recovery was best predicted by the time spent in specific connectivity configurations (0.89 ± 0.01) in combination with the initial impairment. Here, better recovery was linked to a shorter time spent in a functionally integrated configuration. Dynamic connectivity-derived parameters constitute potent predictors of acute impairment and recovery, which, in the future, might inform personalized therapy regimens to promote stroke recovery.

Early motor network connectivity after stroke: An interplay of general reorganization and state-specific compensation.

Motor recovery after stroke relies on functional reorganization of the motor network, which is commonly assessed via functional magnetic resonance imaging (fMRI)-based resting-state functional connectivity (rsFC) or task-related effective connectivity (trEC). Measures of either connectivity mode have been shown to successfully explain motor impairment post-stroke, posing the question whether motor impairment is more closely reflected by rsFC or trEC. Moreover, highly similar changes in ipsilesional and interhemispheric motor network connectivity have been reported for both rsFC and trEC after stroke, suggesting that altered rsFC and trEC may capture similar aspects of information integration in the motor network reflecting principle, state-independent mechanisms of network reorganization rather than state-specific compensation strategies. To address this question, we conducted the first direct comparison of rsFC and trEC in a sample of early subacute stroke patients (n = 26, included on average 7.3 days post-stroke). We found that both rsFC and trEC explained motor impairment across patients, stressing the clinical potential of fMRI-based connectivity. Importantly, intrahemispheric connectivity between ipsilesional M1 and premotor areas depended on the activation state, whereas interhemispheric connectivity between homologs was state-independent. From a mechanistic perspective, our results may thus arise from two distinct aspects of motor network plasticity: task-specific compensation within the ipsilesional hemisphere and a more fundamental form of reorganization between hemispheres.

Connectivity-Related Roles of Contralesional Brain Regions for Motor Performance Early after Stroke.

Hemiparesis after stroke is associated with increased neural activity not only in the lesioned but also in the contralesional hemisphere. While most studies have focused on the role of contralesional primary motor cortex (M1) activity for motor performance, data on other areas within the unaffected hemisphere are scarce, especially early after stroke. We here combined functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS) to elucidate the contribution of contralesional M1, dorsal premotor cortex (dPMC), and anterior intraparietal sulcus (aIPS) for the stroke-affected hand within the first 10 days after stroke. We used "online" TMS to interfere with neural activity at subject-specific fMRI coordinates while recording 3D movement kinematics. Interfering with aIPS activity improved tapping performance in patients, but not healthy controls, suggesting a maladaptive role of this region early poststroke. Analyzing effective connectivity parameters using a Lasso prediction model revealed that behavioral TMS effects were predicted by the coupling of the stimulated aIPS with dPMC and ipsilesional M1. In conclusion, we found a strong link between patterns of frontoparietal connectivity and TMS effects, indicating a detrimental influence of the contralesional aIPS on motor performance early after stroke.

Bringing proportional recovery into proportion: Bayesian modelling of post-stroke motor impairment.

Accurate predictions of motor impairment after stroke are of cardinal importance for the patient, clinician, and healthcare system. More than 10 years ago, the proportional recovery rule was introduced by promising that high-fidelity predictions of recovery following stroke were based only on the initially lost motor function, at least for a specific fraction of patients. However, emerging evidence suggests that this recovery rule is subject to various confounds and may apply less universally than previously assumed. Here, we systematically revisited stroke outcome predictions by applying strategies to avoid confounds and fitting hierarchical Bayesian models. We jointly analysed 385 post-stroke trajectories from six separate studies-one of the largest overall datasets of upper limb motor recovery. We addressed confounding ceiling effects by introducing a subset approach and ensured correct model estimation through synthetic data simulations. Subsequently, we used model comparisons to assess the underlying nature of recovery within our empirical recovery data. The first model comparison, relying on the conventional fraction of patients called 'fitters', pointed to a combination of proportional to lost function and constant recovery. 'Proportional to lost' here describes the original notion of proportionality, indicating greater recovery in case of a more severe initial impairment. This combination explained only 32% of the variance in recovery, which is in stark contrast to previous reports of >80%. When instead analysing the complete spectrum of subjects, 'fitters' and 'non-fitters', a combination of proportional to spared function and constant recovery was favoured, implying a more significant improvement in case of more preserved function. Explained variance was at 53%. Therefore, our quantitative findings suggest that motor recovery post-stroke may exhibit some characteristics of proportionality. However, the variance explained was substantially reduced compared to what has previously been reported. This finding motivates future research moving beyond solely behaviour scores to explain stroke recovery and establish robust and discriminating single-subject predictions.

Invasive versus non-invasive mapping of the motor cortex.

Precise and comprehensive mapping of somatotopic representations in the motor cortex is clinically essential to achieve maximum resection of brain tumours whilst preserving motor function, especially since the current gold standard, that is, intraoperative direct cortical stimulation (DCS), holds limitations linked to the intraoperative setting such as time constraints or anatomical restrictions. Non-invasive techniques are increasingly relevant with regard to pre-operative risk-assessment. Here, we assessed the congruency of neuronavigated transcranial magnetic stimulation (nTMS) and functional magnetic resonance imaging (fMRI) with DCS. The motor representations of the hand, the foot and the tongue regions of 36 patients with intracranial tumours were mapped pre-operatively using nTMS and fMRI and by intraoperative DCS. Euclidean distances (ED) between hotspots/centres of gravity and (relative) overlaps of the maps were compared. We found significantly smaller EDs (11.4 ± 8.3 vs. 16.8 ± 7.0 mm) and better spatial overlaps (64 ± 38% vs. 37 ± 37%) between DCS and nTMS compared with DCS and fMRI. In contrast to DCS, fMRI and nTMS mappings were feasible for all regions and patients without complications. In summary, nTMS seems to be the more promising non-invasive motor cortex mapping technique to approximate the gold standard DCS results.

Acute ischaemic stroke alters the brain's preference for distinct dynamic connectivity states.

Acute ischaemic stroke disturbs healthy brain organization, prompting subsequent plasticity and reorganization to compensate for the loss of specialized neural tissue and function. Static resting state functional MRI studies have already furthered our understanding of cerebral reorganization by estimating stroke-induced changes in network connectivity aggregated over the duration of several minutes. In this study, we used dynamic resting state functional MRI analyses to increase temporal resolution to seconds and explore transient configurations of motor network connectivity in acute stroke. To this end, we collected resting state functional MRI data of 31 patients with acute ischaemic stroke and 17 age-matched healthy control subjects. Stroke patients presented with moderate to severe hand motor deficits. By estimating dynamic functional connectivity within a sliding window framework, we identified three distinct connectivity configurations of motor-related networks. Motor networks were organized into three regional domains, i.e. a cortical, subcortical and cerebellar domain. The dynamic connectivity patterns of stroke patients diverged from those of healthy controls depending on the severity of the initial motor impairment. Moderately affected patients (n = 18) spent significantly more time in a weakly connected configuration that was characterized by low levels of connectivity, both locally as well as between distant regions. In contrast, severely affected patients (n = 13) showed a significant preference for transitions into a spatially segregated connectivity configuration. This configuration featured particularly high levels of local connectivity within the three regional domains as well as anti-correlated connectivity between distant networks across domains. A third connectivity configuration represented an intermediate connectivity pattern compared to the preceding two, and predominantly encompassed decreased interhemispheric connectivity between cortical motor networks independent of individual deficit severity. Alterations within this third configuration thus closely resembled previously reported ones originating from static resting state functional MRI studies post-stroke. In summary, acute ischaemic stroke not only prompted changes in connectivity between distinct networks, but it also caused characteristic changes in temporal properties of large-scale network interactions depending on the severity of the individual deficit. These findings offer new vistas on the dynamic neural mechanisms underlying acute neurological symptoms, cortical reorganization and treatment effects in stroke patients.

Selective attention to smoking cues in former smokers.

Repeated drug use modifies the emotional and cognitive processing of drug-associated cues. These changes are supposed to persist even after prolonged abstinence. Several studies demonstrated that smoking cues selectively attract the attention of smokers, but empirical evidence for such an attentional bias among successful quitters is inconclusive. Here, we investigated whether attentional biases persist after smoking cessation. Thirty-eight former smokers, 34 current smokers, and 29 non-smokers participated in a single experimental session. We used three measures of attentional bias for smoking stimuli: A visual probe task with short (500ms) and long (2000ms) picture stimulus durations, and a modified Stroop task with smoking-related and neutral words. Former smokers and current smokers, as compared to non-smokers, showed an attentional bias in visual orienting to smoking pictures in the 500ms condition of the visual probe task. The Stroop interference index of smoking words was negatively related to nicotine dependence in current smokers. Former smokers and mildly dependent smokers, as compared to non-smokers, showed increased interference by smoking words in the Stroop task. Neither current nor former smokers showed an attentional bias in maintained attention (2000ms visual probe task). In conclusion, even after prolonged abstinence smoking cues retain incentive salience in former smokers, who differed from non-smokers on two attentional bias indices. Attentional biases in former smokers operate mainly in early involuntary rather than in controlled processing, and may represent a vulnerability factor for relapse. Therefore, smoking cessation programs should strengthen self-control abilities to prevent relapses.

Interindividual differences in motor network connectivity and behavioral response to iTBS in stroke patients.

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 between supplemental motor area (SMA) and 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.

Individual prediction of chronic motor outcome in the acute post-stroke stage: Behavioral parameters versus functional imaging.

Several neurobiological factors have been found to correlate with functional recovery after brain lesions. However, predicting the individual potential of recovery remains difficult. Here we used multivariate support vector machine (SVM) classification to explore the prognostic value of functional magnetic resonance imaging (fMRI) to predict individual motor outcome at 4-6 months post-stroke. To this end, 21 first-ever stroke patients with hand motor deficits participated in an fMRI hand motor task in the first few days post-stroke. Motor impairment was quantified assessing grip force and the Action Research Arm Test. Linear SVM classifiers were trained to predict good versus poor motor outcome of unseen new patients. We found that fMRI activity acquired in the first week post-stroke correctly predicted the outcome for 86% of all patients. In contrast, the concurrent assessment of motor function provided 76% accuracy with low sensitivity (<60%). Furthermore, the outcome of patients with initially moderate impairment and high outcome variability could not be predicted based on motor tests. In contrast, fMRI provided 87.5% prediction accuracy in these patients. Classifications were driven by activity in ipsilesional motor areas and contralesional cerebellum. The accuracy of subacute fMRI data (two weeks post-stroke), age, time post-stroke, lesion volume, and location were at 50%-chance-level. In conclusion, multivariate decoding of fMRI data with SVM early after stroke enables a robust prediction of motor recovery. The potential for recovery is influenced by the initial dysfunction of the active motor system, particularly in those patients whose outcome cannot be predicted by behavioral tests.

Inter-individual variability in cortical excitability and motor network connectivity following multiple blocks of rTMS.

The responsiveness to non-invasive neuromodulation protocols shows high inter-individual variability, the reasons of which remain poorly understood. We here tested whether the response to intermittent theta-burst stimulation (iTBS) - an effective repetitive transcranial magnetic stimulation (rTMS) protocol for increasing cortical excitability - depends on network properties of the cortical motor system. We furthermore investigated whether the responsiveness to iTBS is dose-dependent. To this end, we used a sham-stimulation controlled, single-blinded within-subject design testing for the relationship between iTBS aftereffects and (i) motor-evoked potentials (MEPs) as well as (ii) resting-state functional connectivity (rsFC) in 16 healthy subjects. In each session, three blocks of iTBS were applied, separated by 15min. We found that non-responders (subjects not showing an MEP increase of ≥10% after one iTBS block) featured stronger rsFC between the stimulated primary motor cortex (M1) and premotor areas before stimulation compared to responders. However, only the group of responders showed increases in rsFC and MEPs, while most non-responders remained close to baseline levels after all three blocks of iTBS. Importantly, there was still a large amount of variability in both groups. Our data suggest that responsiveness to iTBS at the local level (i.e., M1 excitability) depends upon the pre-interventional network connectivity of the stimulated region. Of note, increasing iTBS dose did not turn non-responders into responders. The finding that higher levels of pre-interventional connectivity precluded a response to iTBS could reflect a ceiling effect underlying non-responsiveness to iTBS at the systems level.

Improved nTMS- and DTI-derived CST tractography through anatomical ROI seeding on anterior pontine level compared to internal capsule.

Imaging of the course of the corticospinal tract (CST) by diffusion tensor imaging (DTI) is useful for function-preserving tumour surgery. The integration of functional localizer data into tracking algorithms offers to establish a direct structure-function relationship in DTI data. However, alterations of MRI signals in and adjacent to brain tumours often lead to spurious tracking results. We here compared the impact of subcortical seed regions placed at different positions and the influences of the somatotopic location of the cortical seed and clinical co-factors on fibre tracking plausibility in brain tumour patients. The CST of 32 patients with intracranial tumours was investigated by means of deterministic DTI and neuronavigated transcranial magnetic stimulation (nTMS). The cortical seeds were defined by the nTMS hot spots of the primary motor area (M1) of the hand, the foot and the tongue representation. The CST originating from the contralesional M1 hand area was mapped as intra-individual reference. As subcortical region of interests (ROI), we used the posterior limb of the internal capsule (PLIC) and/or the anterior inferior pontine region (aiP). The plausibility of the fibre trajectories was assessed by a-priori defined anatomical criteria. The following potential co-factors were analysed: Karnofsky Performance Scale (KPS), resting motor threshold (RMT), T1-CE tumour volume, T2 oedema volume, presence of oedema within the PLIC, the fractional anisotropy threshold (FAT) to elicit a minimum amount of fibres and the minimal fibre length. The results showed a higher proportion of plausible fibre tracts for the aiP-ROI compared to the PLIC-ROI. Low FAT values and the presence of peritumoural oedema within the PLIC led to less plausible fibre tracking results. Most plausible results were obtained when the FAT ranged above a cut-off of 0.105. In addition, there was a strong effect of somatotopic location of the seed ROI; best plausibility was obtained for the contralateral hand CST (100%), followed by the ipsilesional hand CST (>95%), the ipsilesional foot (>85%) and tongue (>75%) CST. In summary, we found that the aiP-ROI yielded better tracking results compared to the IC-ROI when using deterministic CST tractography in brain tumour patients, especially when the M1 hand area was tracked. In case of FAT values lower than 0.10, the result of the respective CST tractography should be interpreted with caution with respect to spurious tracking results. Moreover, the presence of oedema within the internal capsule should be considered a negative predictor for plausible CST tracking.

Functional resting-state connectivity of the human motor network: differences between right- and left-handers.

Handedness is associated with differences in activation levels in various motor tasks performed with the dominant or non-dominant hand. Here we tested whether handedness is reflected in the functional architecture of the motor system even in the absence of an overt motor task. Using resting-state functional magnetic resonance imaging we investigated 18 right- and 18 left-handers. Whole-brain functional connectivity maps of the primary motor cortex (M1), supplementary motor area (SMA), dorsolateral premotor cortex (PMd), pre-SMA, inferior frontal junction and motor putamen were compared between right- and left-handers. We further used a multivariate linear support vector machine (SVM) classifier to reveal the specificity of brain regions for classifying handedness based on individual resting-state maps. Using left M1 as seed region, functional connectivity analysis revealed stronger interhemispheric functional connectivity between left M1 and right PMd in right-handers as compared to left-handers. This connectivity cluster contributed to the individual classification of right- and left-handers with 86.2% accuracy. Consistently, also seeding from right PMd yielded a similar handedness-dependent effect in left M1, albeit with lower classification accuracy (78.1%). Control analyses of the other resting-state networks including the speech and the visual network revealed no significant differences in functional connectivity related to handedness. In conclusion, our data revealed an intrinsically higher functional connectivity in right-handers. These results may help to explain that hand preference is more lateralized in right-handers than in left-handers. Furthermore, enhanced functional connectivity between left M1 and right PMd may serve as an individual marker of handedness.

Motor cortex excitability and connectivity in chronic stroke: a multimodal model of functional reorganization.

Cerebral ischemia triggers a cascade of cellular processes, which induce neuroprotection, inflammation, apoptosis and regeneration. At the neural network level, lesions concomitantly induce cerebral plasticity. Yet, many stroke survivors are left with a permanent motor deficit, and only little is known about the neurobiological factors that determine functional outcome after stroke. Transcranial magnetic stimulation (TMS) and magnetic resonance imaging (MRI) are non-invasive approaches that allow insights into the functional (re-) organization of the cortical motor system. We here combined neuronavigated TMS, MRI and analyses of connectivity to investigate to which degree recovery of hand function depends on corticospinal tract (CST) damage and biomarkers of cerebral plasticity like cortical excitability and motor network effective connectivity. As expected, individual motor performance of 12 stroke patients with persistent motor deficits was found to depend upon the degree of CST damage but also motor cortex excitability and interhemispheric connectivity. In addition, the data revealed a strong correlation between reduced ipsilesional motor cortex excitability and reduced interhemispheric inhibition in severely impaired patients. Interindividual differences in ipsilesional motor cortex excitability were stronger related to the motor deficit than abnormal interhemispheric connectivity or CST damage. Multivariate linear regression analysis combining the three factors accounted for more than 80 % of the variance in functional impairment. The inter-relation of cortical excitability and reduced interhemispheric inhibition provides direct multi-modal evidence for the disinhibition theory of the contralesional hemisphere following stroke. Finally, our data reveal a key mechanism (i.e., the excitability-related reduction in interhemispheric inhibition) accounting for the rehabilitative potential of novel therapeutic approaches which aim at modulating cortical excitability in stroke patients.

Handedness and effective connectivity of the motor system.

Handedness denotes the individual predisposition to consistently use the left or right hand for most types of skilled movements. A putative neurobiological mechanism for handedness consists in hemisphere-specific differences in network dynamics that govern unimanual movements. We, therefore, used functional magnetic resonance imaging and dynamic causal modeling to investigate effective connectivity between key motor areas during fist closures of the dominant or non-dominant hand performed by 18 right- and 18 left-handers. Handedness was assessed employing the Edinburgh-Handedness-Inventory (EHI). The network of interest consisted of key motor regions in both hemispheres including the primary motor cortex (M1), supplementary motor area (SMA), ventral premotor cortex (PMv), motor putamen (Put) and motor cerebellum (Cb). The connectivity analysis revealed that in right-handed subjects movements of the dominant hand were associated with significantly stronger coupling of contralateral (left, i.e., dominant) SMA with ipsilateral SMA, ipsilateral PMv, contralateral motor putamen and contralateral M1 compared to equivalent connections in left-handers. The degree of handedness as indexed by the individual EHI scores also correlated with coupling parameters of these connections. In contrast, we found no differences between right- and left-handers when testing for the effect of movement speed on effective connectivity. In conclusion, the data show that handedness is associated with differences in effective connectivity within the human motor network with a prominent role of SMA in right-handers. Left-handers featured less asymmetry in effective connectivity implying different hemispheric mechanisms underlying hand motor control compared to right-handers.

Dose-dependent effects of theta burst rTMS on cortical excitability and resting-state connectivity of the human motor system.

Theta burst stimulation (TBS), a specific protocol of repetitive transcranial magnetic stimulation (rTMS), induces changes in cortical excitability that last beyond stimulation. TBS-induced aftereffects, however, vary between subjects, and the mechanisms underlying these aftereffects to date remain poorly understood. Therefore, the purpose of this study was to investigate whether increasing the number of pulses of intermittent TBS (iTBS) (1) increases cortical excitability as measured by motor-evoked potentials (MEPs) and (2) alters functional connectivity measured using resting-state fMRI, in a dose-dependent manner. Sixteen healthy, human subjects received three serially applied iTBS blocks of 600 pulses over the primary motor cortex (M1 stimulation) and the parieto-occipital vertex (sham stimulation) to test for dose-dependent iTBS effects on cortical excitability and functional connectivity (four sessions in total). iTBS over M1 increased MEP amplitudes compared with sham stimulation after each stimulation block. Although the increase in MEP amplitudes did not differ between the first and second block of M1 stimulation, we observed a significant increase after three blocks (1800 pulses). Furthermore, iTBS enhanced resting-state functional connectivity between the stimulated M1 and premotor regions in both hemispheres. Functional connectivity between M1 and ipsilateral dorsal premotor cortex further increased dose-dependently after 1800 pulses of iTBS over M1. However, no correlation between changes in MEP amplitudes and functional connectivity was detected. In summary, our data show that increasing the number of iTBS stimulation blocks results in dose-dependent effects at the local level (cortical excitability) as well as at a systems level (functional connectivity) with a dose-dependent enhancement of dorsal premotor cortex-M1 connectivity.

Network connectivity and individual responses to brain stimulation in the human motor system.

The mechanisms driving cortical plasticity in response to brain stimulation are still incompletely understood. We here explored whether neural activity and connectivity in the motor system relate to the magnitude of cortical plasticity induced by repetitive transcranial magnetic stimulation (rTMS). Twelve right-handed volunteers underwent functional magnetic resonance imaging during rest and while performing a simple hand motor task. Resting-state functional connectivity, task-induced activation, and task-related effective connectivity were assessed for a network of key motor areas. We then investigated the effects of intermittent theta-burst stimulation (iTBS) on motor-evoked potentials (MEP) for up to 25 min after stimulation over left primary motor cortex (M1) or parieto-occipital vertex (for control). ITBS-induced increases in MEP amplitudes correlated negatively with movement-related fMRI activity in left M1. Control iTBS had no effect on M1 excitability. Subjects with better response to M1-iTBS featured stronger preinterventional effective connectivity between left premotor areas and left M1. In contrast, resting-state connectivity did not predict iTBS aftereffects. Plasticity-related changes in M1 following brain stimulation seem to depend not only on local factors but also on interconnected brain regions. Predominantly activity-dependent properties of the cortical motor system are indicative of excitability changes following induction of cortical plasticity with rTMS.

Network dynamics engaged in the modulation of motor behavior in healthy subjects.

Motor skills are mediated by a dynamic and finely regulated interplay of the primary motor cortex (M1) with various cortical and subcortical regions engaged in movement preparation and execution. To date, data elucidating the dynamics in the motor network that enable movements at different levels of behavioral performance remain scarce. We here used functional magnetic resonance imaging (fMRI) and dynamic causal modeling (DCM) to investigate effective connectivity of key motor areas at different movement frequencies performed by right-handed subjects (n=36) with the left or right hand. The network of interest consisted of motor regions in both hemispheres including M1, supplementary motor area (SMA), ventral premotor cortex (PMv), motor putamen, and motor cerebellum. The connectivity analysis showed that performing hand movements at higher frequencies was associated with a linear increase in neural coupling strength from premotor areas (SMA, PMv) contralateral to the moving hand and ipsilateral cerebellum towards contralateral, active M1. In addition, we found hemispheric differences in the amount by which the coupling of premotor areas and M1 was modulated, depending on which hand was moved. Other connections were not modulated by changes in motor performance. The results suggest that a stronger coupling, especially between contralateral premotor areas and M1, enables increased motor performance of simple unilateral hand movements.