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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Cerebral network disorders after stroke: evidence from imaging-based connectivity analyses of active and resting brain states in humans.

Stroke causes a sudden disruption of physiological brain function which leads to impairments of functional brain networks involved in voluntary movements. In some cases, the brain has the intrinsic capacity to reorganize itself, thereby compensating for the disruption of motor networks. In humans, such reorganization can be investigated in vivo using neuroimaging. Recent developments in connectivity analyses based on functional neuroimaging data have provided new insights into the network pathophysiology underlying neurological symptoms. Here we review recent neuroimaging studies using functional resting-state correlations, effective connectivity models or graph theoretical analyses to investigate changes in neural motor networks and recovery after stroke. The data demonstrate that network disturbances after stroke occur not only in the vicinity of the lesion but also between remote cortical areas in the affected and unaffected hemisphere. The reorganization of motor networks encompasses a restoration of interhemispheric functional coherence in the resting state, particularly between the primary motor cortices. Furthermore, reorganized neural networks feature strong excitatory interactions between fronto-parietal areas and primary motor cortex in the affected hemisphere, suggesting that greater top-down control over primary motor areas facilitates motor execution in the lesioned brain. In addition, there is evidence that motor recovery is accompanied by a more random network topology with reduced local information processing. In conclusion, Stroke induces changes in functional and effective connectivity within and across hemispheres which relate to motor impairments and recovery thereof. Connectivity analyses may hence provide new insights into the pathophysiology underlying neurological deficits and may be further used to develop novel, neurobiologically informed treatment strategies.

State-dependent differences between functional and effective connectivity of the human cortical motor system.

Neural processing is based on interactions between functionally specialized areas that can be described in terms of functional or effective connectivity. Functional connectivity is often assessed by task-free, resting-state functional magnetic resonance imaging (fMRI), whereas effective connectivity is usually estimated from task-based fMRI time-series. To investigate whether different connectivity approaches assess similar network topologies in the same subjects, we scanned 36 right-handed volunteers with resting-state fMRI followed by active-state fMRI involving a hand movement task. Time-series information was extracted from identical locations defined from individual activation maxima derived from the motor task. Dynamic causal modeling (DCM) was applied to the motor task time-series to estimate endogenous and context-dependent effective connectivity. In addition, functional connectivity was computed for both the rest and the motor task condition by means of inter-regional time-series correlations. At the group-level, we found strong interactions between the motor areas of interest in all three connectivity analyses. However, although the sample size warranted 90% power to detect correlations of medium effect size, resting-state functional connectivity was only weakly correlated with both task-based functional and task-based effective connectivity estimates for corresponding region-pairs. By contrast, task-based functional connectivity showed strong positive correlations with DCM effective connectivity parameters. In conclusion, resting-state and task-based connectivity reflect different components of functional integration that particularly depend on the functional state in which the subject is being scanned. Therefore, resting-state fMRI and DCM should be used as complementary measures when assessing functional brain networks.

Mapping the hand, foot and face representations in the primary motor cortex - retest reliability of neuronavigated TMS versus functional MRI.

INTRODUCTION: Functional magnetic resonance imaging (fMRI) is a frequently used non-invasive mapping technique for investigating the human motor system. Recently, neuronavigated transcranial magnetic stimulation (nTMS) has been established as an alternative approach. We here compared the test-retest reliability of both mapping techniques with regard to the cortical representations of the hand, leg, face and tongue areas. METHODS: Ten healthy subjects were examined three times (intervals: 3-5days/21-35days) with fMRI and nTMS. Motor-evoked potentials were recorded from the abductor pollicis brevis, plantaris, mentalis and the tongue muscles. The same muscles were activated in an fMRI motor task. Euclidean distances (ED) between hotspots and centers of gravity (CoG) were computed for the respective somatotopic representations. Furthermore, spatial reliability was tested by intersession overlap volumes (OV) and voxel-wise intraclass correlations (ICC). RESULTS: Feasibility of fMRI was 100% for all body parts and sessions. In contrast, nTMS was feasible in all sessions and subjects only for the hand area, while mappings of the foot (90%), face (70%) and tongue representations (40%) remained incomplete in several subjects due to technical constraints and co-stimulation artifacts. On average, the mean ED of the hotspots was better for fMRI (6.2±1.1mm) compared to nTMS (10.8±1.9mm) while stability of CoG was similar for both methods. Peak voxel reliability (ICC) was high for both methods (>0.8), and there was no influence of inter-session intervals. In contrast, the reliability of mapping the spatial extent of the hand, foot, lips and tongue representations was poor to moderate for both fMRI and nTMS (OVs and ICC<50%). Especially nTMS mappings of the face and tongue areas yielded poor reliability estimates. CONCLUSION: Both methods are highly reliable when mapping the core region of a given target muscle, especially for the hand representation area. In contrast, mapping the spatial extent of a cortical representation area was only little reliable for both nTMS and fMRI. In summary, fMRI was better suited when mapping motor representations of the head, while nTMS showed equal reliability for mapping the hand and foot representation areas. Hence, both methods may well complement each other.

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.

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.

Activation likelihood estimation meta-analysis of motor-related neural activity after stroke.

Over the past two decades, several functional neuroimaging experiments demonstrated changes in neural activity in stroke patients with motor deficits. Conclusions from single experiments are usually constrained by small sample sizes and high variability across studies. Here, we used coordinate-based activation likelihood estimation meta-analyses to provide a quantitative synthesis of the current literature on motor-related neural activity after stroke. Of over 1000 PubMed search results through January 2011, 36 studies reported standardized whole-brain group coordinates. Meta-analyses were performed on 54 experimental contrasts for movements of the paretic upper limb (472 patients, 452 activation foci) and on 20 experiments comparing activation between patients and healthy controls (177 patients, 113 activation foci). We computed voxelwise correlations between activation likelihood and motor impairment, time post-stroke, and task difficulty across samples. Patients showed higher activation likelihood in contralesional primary motor cortex (M1), bilateral ventral premotor cortex and supplementary motor area (SMA) relative to healthy subjects. Activity in contralesional areas was more likely found for active than for passive tasks. Better motor performance was associated with greater activation likelihood in ipsilesional M1, pre-SMA, contralesional premotor cortex and cerebellum. Over time post-stroke, activation likelihood in bilateral premotor areas and medial M1 hand knob decreased. This meta-analysis shows that increased activation in contralesional M1 and bilateral premotor areas is a highly consistent finding after stroke despite high inter-study variance resulting from different fMRI tasks and motor impairment levels. However, a good functional outcome relies on the recruitment of the original functional network rather than on contralesional activity.

Noradrenergic enhancement improves motor network connectivity in stroke patients.

OBJECTIVE: Both animal and human data suggest that noradrenergic stimulation may enhance motor performance after brain damage. We conducted a placebo-controlled, double-blind and crossover design study to investigate the effects of noradrenergic stimulation on the cortical motor system in hemiparetic stroke patients. METHODS: Stroke patients (n = 11) in the subacute or chronic stage with mild-to-moderate hand paresis received a single oral dose of 6 mg reboxetine (RBX), a selective noradrenaline reuptake inhibitor. We used functional magnetic resonance imaging and dynamic causal modeling to assess changes in neural activity and interregional effective connectivity while patients moved their paretic hand. RESULTS: RBX stimulation significantly increased maximum grip power and index finger-tapping frequency of the paretic hand. Enhanced motor performance was associated with a reduction of cortical "hyperactivity" toward physiological levels as observed in healthy control subjects, especially in the ipsilesional ventral premotor cortex (vPMC) and supplementary motor area (SMA), but also in the temporoparietal junction and prefrontal cortex. Connectivity analyses revealed that in stroke patients neural coupling with SMA or vPMC was significantly reduced compared with healthy controls. This "hypoconnectivity" was partially normalized when patients received RBX, especially for the coupling of ipsilesional SMA with primary motor cortex. INTERPRETATION: The data suggest that noradrenergic stimulation by RBX may help to modulate the pathologically altered motor network architecture in stroke patients, resulting in increased coupling of ipsilesional motor areas and thereby improved motor function.