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.

Interhemispheric Structural Connectivity Underlies Motor Recovery after Stroke

OBJECTIVE

Although ample evidence highlights that the ipsilesional corticospinal tract (CST) plays a crucial role in motor recovery after stroke, studies on cortico-cortical motor connections remain scarce and provide inconclusive results. Given their unique potential to serve as structural reserve enabling motor network reorganization, the question arises whether cortico-cortical connections may facilitate motor control depending on CST damage.

METHODS

Diffusion spectrum imaging (DSI) and a novel compartment-wise analysis approach were used to quantify structural connectivity between bilateral cortical core motor regions in chronic stroke patients. Basal and complex motor control were differentially assessed.

RESULTS

Both basal and complex motor performance were correlated with structural connectivity between bilateral premotor areas and ipsilesional primary motor cortex (M1) as well as interhemispheric M1 to M1 connectivity. Whereas complex motor skills depended on CST integrity, a strong association between M1 to M1 connectivity and basal motor control was observed independent of CST integrity especially in patients who underwent substantial motor recovery. Harnessing the informational wealth of cortico-cortical connectivity facilitated the explanation of both basal and complex motor control.

INTERPRETATION

We demonstrate for the first time that distinct aspects of cortical structural reserve enable basal and complex motor control after stroke. In particular, recovery of basal motor control may be supported via an alternative route through contralesional M1 and non-crossing fibers of the contralesional CST. Our findings help to explain previous conflicting interpretations regarding the functional role of the contralesional M1 and highlight the potential of cortico-cortical structural connectivity as a future biomarker for motor recovery post-stroke. ANN NEUROL 2023;94:785-797.

Transcranial Direct Current Stimulation Reverses Stroke-Induced Network Alterations in Mice

BACKGROUND

Beyond focal effects, stroke lesions impact the function of distributed networks. We here investigated (1) whether transcranial direct current stimulation (tDCS) alters the network changes induced by cerebral ischemia and (2) whether functional network parameters predict the therapeutic efficacy of tDCS in a mouse model of focal photothrombotic stroke.

METHODS

Starting 3 days after stroke, cathodal tDCS (charge density=39.6 kC/m²) was applied over 10 days in male C57Bl/6J mice under light anesthesia over the lesioned sensory-motor cortex. Functional connectivity (resting-state functional magnetic resonance imaging) was evaluated for up to 28-day poststroke, with global graph parameters of network integration computed.

RESULTS

Ischemia induced a subacute increase in connectivity accompanied by a significant reduction in characteristic path length, reversed by 10 days of tDCS. Early measures of functional network alterations and the network configuration at prestroke baseline predicted spontaneous and tDCS-augmented motor recovery.

DISCUSSION

Stroke induces characteristic network changes throughout the brain that can be detected by resting-state functional magnetic resonance imaging. These network changes were, at least in part, reversed by tDCS. Moreover, early markers of a network impairment and the network configuration before the insult improve the prediction of motor recovery.

The role of corticospinal and extrapyramidal pathways in motor impairment after stroke

Anisotropy of descending motor pathways has repeatedly been linked to the severity of motor impairment following stroke-related damage to the corticospinal tract. Despite promising findings consistently tying anisotropy of the ipsilesional corticospinal tract to motor outcome, anisotropy is not yet utilized as a biomarker for motor recovery in clinical practice as several methodological constraints hinder a conclusive understanding of degenerative processes in the ipsilesional corticospinal tract and compensatory roles of other descending motor pathways. These constraints include estimating anisotropy in voxels with multiple fibre directions, sampling biases and confounds due to ageing-related atrophy. The present study addressed these issues by combining diffusion spectrum imaging with a novel compartmentwise analysis approach differentiating voxels with one dominant fibre direction (one-directional voxels) from voxels with multiple fibre directions. Compartmentwise anisotropy for bihemispheric corticospinal and extrapyramidal tracts was compared between 25 chronic stroke patients, 22 healthy age-matched controls, and 24 healthy young controls and its associations with motor performance of the upper and lower limbs were assessed. Our results provide direct evidence for Wallerian degeneration along the entire length of the ipsilesional corticospinal tract reflected by decreased anisotropy in descending fibres compared with age-matched controls, while ageing-related atrophy was observed more ubiquitously across compartments. Anisotropy of descending ipsilesional corticospinal tract voxels showed highly robust correlations with various aspects of upper and lower limb motor impairment, highlighting the behavioural relevance of Wallerian degeneration. Moreover, anisotropy measures of two-directional voxels within bihemispheric rubrospinal and reticulospinal tracts were linked to lower limb deficits, while anisotropy of two-directional contralesional rubrospinal voxels explained gross motor performance of the affected hand. Of note, the relevant extrapyramidal structures contained fibres crossing the midline, fibres potentially mitigating output from brain stem nuclei, and fibres transferring signals between the extrapyramidal system and the cerebellum. Thus, specific parts of extrapyramidal pathways seem to compensate for impaired gross arm and leg movements incurred through stroke-related corticospinal tract lesions, while fine motor control of the paretic hand critically relies on ipsilesional corticospinal tract integrity. Importantly, our findings suggest that the extrapyramidal system may serve as a compensatory structural reserve independent of post-stroke reorganization of extrapyramidal tracts. In summary, compartment-specific anisotropy of ipsilesional corticospinal tract and extrapyramidal tracts explained distinct aspects of motor impairment, with both systems representing different pathophysiological mechanisms contributing to motor control post-stroke. Considering both systems in concert may help to develop diffusion imaging biomarkers for specific motor functions after stroke.

Recovered grasping performance after stroke depends on interhemispheric frontoparietal connectivity

Activity changes in the ipsi- and contralesional parietal cortex and abnormal interhemispheric connectivity between these regions are commonly observed after stroke, however, their significance for motor recovery remains poorly understood. We here assessed the contribution of ipsilesional and contralesional anterior intraparietal cortex (aIPS) for hand motor function in 18 recovered chronic stroke patients and 18 healthy control subjects using a multimodal assessment consisting of resting-state functional MRI, motor task functional MRI, online-repetitive transcranial magnetic stimulation (rTMS) interference, and 3D movement kinematics. Effects were compared against two control stimulation sites, i.e. contralesional M1 and a sham stimulation condition. We found that patients with good motor outcome compared to patients with more substantial residual deficits featured increased resting-state connectivity between ipsilesional aIPS and contralesional aIPS as well as between ipsilesional aIPS and dorsal premotor cortex. Moreover, interhemispheric connectivity between ipsilesional M1 and contralesional M1 as well as ipsilesional aIPS and contralesional M1 correlated with better motor performance across tasks. TMS interference at individual aIPS and M1 coordinates led to differential effects depending on the motor task that was tested, i.e. index finger-tapping, rapid pointing movements, or a reach-grasp-lift task. Interfering with contralesional aIPS deteriorated the accuracy of grasping, especially in patients featuring higher connectivity between ipsi- and contralesional aIPS. In contrast, interference with the contralesional M1 led to impaired grasping speed in patients featuring higher connectivity between bilateral M1. These findings suggest differential roles of contralesional M1 and aIPS for distinct aspects of recovered hand motor function, depending on the reorganization of interhemispheric connectivity.

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.

Cortical reorganization after motor stroke: A pilot study on differences between the upper and lower limbs

Stroke patients suffering from hemiparesis may show substantial recovery in the first months poststroke due to neural reorganization. While reorganization driving improvement of upper hand motor function has been frequently investigated, much less is known about the changes underlying recovery of lower limb function. We, therefore, investigated neural network dynamics giving rise to movements of both the hands and feet in 12 well-recovered left-hemispheric chronic stroke patients and 12 healthy participants using a functional magnetic resonance imaging sparse sampling design and dynamic causal modeling (DCM). We found that the level of neural activity underlying movements of the affected right hand and foot positively correlated with residual motor impairment, in both ipsilesional and contralesional premotor as well as left primary motor (M1) regions. Furthermore, M1 representations of the affected limb showed significantly stronger increase in BOLD activity compared to healthy controls and compared to the respective other limb. DCM revealed reduced endogenous connectivity of M1 of both limbs in patients compared to controls. However, when testing for the specific effect of movement on interregional connectivity, interhemispheric inhibition of the contralesional M1 during movements of the affected hand was not detected in patients whereas no differences in condition-dependent connectivity were found for foot movements compared to controls. In contrast, both groups featured positive interhemispheric M1 coupling, that is, facilitation of neural activity, mediating movements of the affected foot. These exploratory findings help to explain why functional recovery of the upper and lower limbs often develops differently after stroke, supporting limb-specific rehabilitative strategies.

Probing rapid network reorganization of motor and language functions via neuromodulation and neuroimaging

Motor and cognitive functions are organized in large-scale networks in the human brain that interact to enable flexible adaptation of information exchange to ever-changing environmental conditions. In this review, we discuss the unique potential of the consecutive combination of repetitive transcranial magnetic stimulation (rTMS) and functional neuroimaging to probe network organization and reorganization in the healthy and lesioned brain. First, we summarize findings highlighting the flexible (re-)distribution and short-term reorganization in motor and cognitive networks in the healthy brain. Plastic after-effects of rTMS result in large-scale changes on the network level affecting both local and remote activity within the stimulated network as well as interactions between the stimulated and distinct functional networks. While the number of combined rTMS-fMRI studies in patients with brain lesions remains scarce, preliminary evidence suggests that the lesioned brain flexibly (re-)distributes its computational capacities to functionally reorganize impaired brain functions, using a similar set of mechanisms to achieve adaptive network plasticity compared to short-term reorganization observed in the healthy brain after rTMS. In general, both short-term reorganization in the healthy brain and stroke-induced reorganization seem to rely on three general mechanisms of adaptive network plasticity that allow to maintain and recover function: i) interhemispheric changes, including increased contribution of homologous regions in the contralateral hemisphere and increased interhemispheric connectivity, ii) increased interactions between differentially specialized networks and iii) increased contributions of domain-general networks after disruption of more specific functions. These mechanisms may allow for computational flexibility of large-scale neural networks underlying motor and cognitive functions. Future studies should use complementary approaches to address the functional relevance of adaptive network plasticity and further delineate how these general mechanisms interact to enable network flexibility. Besides furthering our neurophysiological insights into brain network interactions, identifying approaches to support and enhance adaptive network plasticity may result in clinically relevant diagnostic and treatment approaches.

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.

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.

The differential roles of contralesional frontoparietal areas in cortical reorganization after stroke

BACKGROUND

Studies examining the contribution of contralesional brain regions to motor recovery after stroke have revealed conflicting results comprising both supporting and disturbing influences. Especially the relevance of contralesional brain regions beyond primary motor cortex (M1) has rarely been studied, particularly concerning the temporal dynamics post-stroke.

METHODS

We, therefore, used online transcranial magnetic stimulation (TMS) interference to longitudinally assess the role of contralesional (right) frontoparietal areas for recovery of hand motor function after left hemispheric stroke: contralesional M1, contralesional dorsal premotor cortex (dPMC), and contralesional anterior intraparietal sulcus (IPS). Fourteen stroke patients and sixteen age-matched healthy subjects performed motor tasks of varying complexity with their (paretic) right hand. Motor performance was quantified using three-dimensional kinematic data. All patients were assessed twice, (i) in the first week, and (ii) after more than three months post-stroke.

RESULTS

While we did not observe a significant effect of TMS interference on movement kinematics following the stimulation of contralesional M1 and dPMC in the first week post-stroke, we found improvements of motor performance upon interference with contralesional IPS across motor tasks early after stroke, an effect that persisted into the later phase. By contrast, for dPMC, TMS-induced deterioration of motor performance was only evident three months post-stroke, suggesting that a supportive role of contralesional premotor cortex might evolve with reorganization.

CONCLUSION

We here highlight time-sensitive and region-specific effects of contralesional frontoparietal areas after left hemisphere stroke, which may influence on neuromodulation regimes aiming at supporting recovery of motor function post-stroke.

Intermittent theta burst stimulation applied during early rehabilitation after stroke: study protocol for a randomised controlled trial

INTRODUCTION

Intermittent theta burst stimulation (iTBS) applied to primary motor cortex (M1) has been shown to modulate both the excitability and connectivity of the motor system. A recent proof-of-principle study, based on a small group of hospitalised patients with acute ischemic stroke, suggested that iTBS applied to the ipsilesional M1 combined with physical therapy early after stroke can amplify motor recovery with lasting after effects. A randomised controlled clinical trial using a double-blind design is warranted to justify the implementation of iTBS-assisted motor rehabilitation in neurorehabilitation from an acute ischaemic stroke.

METHODS/DESIGN

We investigate the effects of daily iTBS on early motor rehabilitation after stroke in an investigator-initiated, longitudinal randomised controlled trial. Patients (n=150) with hemiparesis receive either iTBS (600 pulses) applied to the ipsilesional motor cortex (M1) or a control stimulation (ie, coil placement over the parieto-occipital vertex in parallel to the interhemispheric fissure and with a tilt of 45°). On 8 consecutive workdays, a 45 min arm-centred motor training follows the intervention . The relative grip strength, defined as the grip force ratios of the affected and unaffected hands, serves as the primary outcome parameter. Secondary outcome parameters are measures of arm function (Action Research Arm Test, Fugl-Meyer Motor Scale), stroke severity (National Institutes of Health Stroke Scale), stroke-induced disability (modified Rankin Scale, Barthel Index), duration of inpatient rehabilitation, quality of life (EuroQol 5D), motor evoked potentials and the resting motor threshold of the ipsilesional M1.

ETHICS AND DISSEMINATION

The study was approved by the Ethics Commission of the Medical Faculty, University of Cologne, Germany (reference number 15-343). Data will be disseminated through peer-reviewed publications and presentations at conferences. Study title: Theta-Burst Stimulation in Early Rehabilitation after Stroke (acronym: TheSiReS). Study registration at German Registry for Clinical Trials (DRKS00008963) and at ClinicalTrials.gov (NCT02910024).

Modulation of I-wave generating pathways by theta-burst stimulation: a model of plasticity induction

KEY POINTS

Mechanisms underlying plasticity induction by repetitive transcranial magnetic stimulation protocols such as intermittent theta-burst stimulation (iTBS) remain poorly understood. Individual response to iTBS is associated with recruitment of late indirect wave (I-wave) generating pathways that can be probed by the onset latency of transcranial magnetic stimulation applied to primary motor cortex (M1) at different coil orientations. We found an association between late I-wave recruitment [reflected by anterior-posterior (AP)-lateromedial (LM) latency; i.e. the excess latency of motor-evoked potentials generated by transcranial magnetic stimulation with an AP orientation over the latency of motor-evoked potentials evoked by direct activation of corticospinal axons using LM stimulation] and changes in cortical excitability following iTBS, confirming previous studies. AP-LM latency significantly decreased following iTBS, and this decrease correlated with the iTBS-induced increase in cortical excitability across subjects. Plasticity in the motor network may in part derive from a modulation of excitability and the recruitment of late I-wave generating cortical pathways.

ABSTRACT

Plasticity-induction following theta burst transcranial stimulation (TBS) varies considerably across subjects, and the underlying neurophysiological mechanisms remain poorly understood, representing a challenge for scientific and clinical applications. In human motor cortex (M1), recruitment of indirect waves (I-waves) can be probed by the excess latency of motor-evoked potentials elicited by transcranial magnetic stimulation with an anterior-posterior (AP) orientation over the latency of motor-evoked potentials evoked by direct activation of corticospinal axons using lateromedial (LM) stimulation, referred to as the 'AP-LM latency' difference. Importantly, AP-LM latency has been shown to predict individual responses to TBS across subjects. We, therefore, hypothesized that the plastic changes in corticospinal excitability induced by TBS are the result, at least in part, of changes in excitability of these same I-wave generating pathways. In 20 healthy subjects, we investigated whether intermittent TBS (iTBS) modulates I-wave recruitment as reflected by changes in the AP-LM latency. As expected, we found that AP-LM latencies before iTBS were associated with iTBS-induced excitability changes. A novel finding was that iTBS reduced AP-LM latency, and that this reduction significantly correlated with changes in cortical excitability observed following iTBS: subjects with larger reductions in AP-LM latencies featured larger increases in cortical excitability following iTBS. Our findings suggest that plasticity-induction by iTBS may derive from the modulation of I-wave generating pathways projecting onto M1, accounting for the predictive potential of I-wave recruitment. The excitability of I-wave generating pathways may serve a critical role in modulating motor cortical excitability and hence represent a promising target for novel repetitive transcranial magnetic stimulation protocols.

Age affects the contribution of ipsilateral brain regions to movement kinematics

Healthy aging is accompanied by changes in brain activation patterns in the motor system. In older subjects, unilateral hand movements typically rely on increased recruitment of ipsilateral frontoparietal areas. While the two central concepts of aging‐related brain activity changes, “Hemispheric Asymmetry Reduction in Older Adults” (HAROLD), and “Posterior to Anterior Shift in Aging” (PASA), have initially been suggested in the context of cognitive tasks and were attributed to compensation, current knowledge regarding the functional significance of increased motor system activity remains scarce. We, therefore, used online interference transcranial magnetic stimulation in young and older subjects to investigate the role of key regions of the ipsilateral frontoparietal cortex, that is, (a) primary motor cortex (M1), (b) dorsal premotor cortex (dPMC), and (c) anterior intraparietal sulcus (IPS) in the control of hand movements of different motor demands. Our data suggest a change of the functional roles of ipsilateral brain areas in healthy age with a reduced relevance of ipsilateral M1 and a shift of importance toward dPMC for repetitive high‐frequency movements. These results support the notion that mechanisms conceptualized in the models of “PASA” and “HAROLD” also apply to the motor system.

Finding maximally disconnected subnetworks with shortest path tractography

Connectome-based lesion symptom mapping (CLSM) can be used to relate disruptions of brain network connectivity with clinical measures. We present a novel method that extends current CLSM approaches by introducing a fast reliable and accurate way for computing disconnectomes, i.e. identifying damaged or lesioned connections. We introduce a new algorithm that finds the maximally disconnected subgraph containing regions and region pairs with the greatest shared connectivity loss. After normalizing a stroke patient's segmented MRI lesion into template space, probability weighted structural connectivity matrices are constructed from shortest paths found in white matter voxel graphs of 210 subjects from the Human Connectome Project. Percent connectivity loss matrices are constructed by measuring the proportion of shortest-path probability weighted connections that are lost because of an intersection with the patient's lesion. Maximally disconnected subgraphs of the overall connectivity loss matrix are then derived using a computationally fast greedy algorithm that closely approximates the exact solution. We illustrate the approach in eleven stroke patients with hemiparesis by identifying expected disconnections of the corticospinal tract (CST) with cortical sensorimotor regions. Major disconnections are found in the thalamus, basal ganglia, and inferior parietal cortex. Moreover, the size of the maximally disconnected subgraph quantifies the extent of cortical disconnection and strongly correlates with multiple clinical measures. The methods provide a fast, reliable approach for both visualizing and quantifying the disconnected portion of a patient's structural connectome based on their routine clinical MRI, without reliance on concomitant diffusion weighted imaging. The method can be extended to large databases of stroke patients, multiple sclerosis or other diseases causing focal white matter injuries helping to better characterize clinically relevant white matter lesions and to identify biomarkers for the recovery potential of individual patients.

•

Significantly accelerated shortest path tractography approach for constructing connectomes and disconnectomes.

•

New algorithm extracts the subnetwork containing cortical connections and regions with maximal shared connectivity loss.

•

The size of the maximally disconnected subnetwork quantifies the extent of disconnection and correlates with stroke measures.

•

Fast and accurate approach for visualizing and analyzing the disconnected portion of a patient's structural connectome.

Failure to Affect Decision Criteria During Recognition Memory With Continuous Theta Burst Stimulation

A decision criterion establishes the minimum amount of memory evidence required for recognition. When a liberal criterion is set, items are recognized based on weak evidence whereas a conservative criterion requires greater memory strength for recognition. The decision criterion is a fundamental aspect of recognition memory but little is known about the underlying neural mechanisms of maintaining a criterion. We used continuous theta burst stimulation (cTBS) with the goal of inhibiting prefrontal cortex excitability while participants performed recognition tests. We hypothesized that inhibiting the right inferior frontal gyrus (rIFG), right middle frontal gyrus (rMFG), and right dorsolateral prefrontal cortex (rDLPFC) would cause participants to establish less conservative decision criteria without affecting recognition memory performance. Participants initially performed recognition memory tests while maintaining conservative decision criteria during fMRI scanning. Peak activity in the successful retrieval effect contrast (Hits > Correct Rejections) provided subject-specific cTBS target sites. During three separate sessions, participants completed the same recognition memory paradigm while maintaining conservative and liberal decision criteria both before and after cTBS. Across two experiments we failed to significantly alter decision criteria placement by applying cTBS to the rIFG, rMFG, and rDLPFC despite efforts to precisely target individualized brain areas. However, we unexpectedly improved discriminability following cTBS to the rDLPFC specifically when participants maintained a liberal criterion. Although this finding may guide future studies investigating the neural mechanisms underlying discriminability in recognition memory, cTBS proved ineffective at altering decision criteria.

Functional magnetic resonance imaging in glioma patients: from clinical applications to future perspectives

Functional magnetic resonance imaging (fMRI) allows the non-invasive assessment of human brain activity in vivo. In glioma patients, fMRI is frequently used to determine the individual functional anatomy of the motor and language network in a presurgical setting to optimize surgical procedures and prevent extensive damage to functionally eloquent areas. Novel developments based on resting-state fMRI may help to improve presurgical planning for patients which are unable to perform structured tasks and might extend presurgical mapping to include additional functional networks. Recent advances indicate a promising potential for future applications of fMRI in glioma patients which might help to identify neoplastic tissue or predict the long-term functional outcome of individual patients.

Network connectivity of motor control in the ageing brain

Older individuals typically display stronger regional brain activity than younger subjects during motor performance. However, knowledge regarding age-related changes of motor network interactions between brain regions remains scarce. We here investigated the impact of ageing on the interaction of cortical areas during movement selection and initiation using dynamic causal modelling (DCM). We found that age-related psychomotor slowing was accompanied by increases in both regional activity and effective connectivity, especially for ‘core’ motor coupling targeting primary motor cortex (M1). Interestingly, younger participants within the older group showed strongest connectivity targeting M1, which steadily decreased with advancing age. Conversely, prefrontal influences on the motor system increased with advancing age, and were inversely correlated with reduced parietal influences and core motor coupling. Interestingly, higher net coupling within the prefrontal-premotor-M1 axis predicted faster psychomotor speed in ageing. Hence, as opposed to a uniform age-related decline, our findings are compatible with the idea of different age-related compensatory mechanisms, with an important role of the prefrontal cortex compensating for reduced coupling within the core motor network.

•

Enhanced motor network activity and connectivity in ageing

•

Parietal-premotor and premotor-M1 coupling decreases with advancing age.

•

Prefrontal influences on the motor system increase with advancing age.

•

Prefrontal cortex compensates for age-related decline in other motor connections.

•

Prefrontal-premotor-M1 coupling predicts psychomotor speed in ageing.

Analytic tractography: A closed-form solution for estimating local white matter connectivity with diffusion MRI

White matter structures composed of myelinated axons in the living human brain are primarily studied by diffusion-weighted MRI (dMRI). These long-range projections are typically characterized in a two-step process: dMRI signal is used to estimate the orientation of axon segments within each voxel, then these local orientations are linked together to estimate the spatial extent of putative white matter bundles. Tractography, the process of tracing bundles across voxels, either requires computationally expensive (probabilistic) simulations to model uncertainty in fiber orientation or ignores it completely (deterministic). Furthermore, simulation necessarily generates a finite number of trajectories, introducing "simulation error" to trajectory estimates. Here we introduce a method to analytically (via a closed-form solution) take an orientation distribution function (ODF) from each voxel and calculate the probabilities that a trajectory projects from a voxel into each directly adjacent voxels. We validate our method by demonstrating experimentally that probabilistic simulations converge to our analytically computed transition probabilities at the voxel level as the number of simulated seeds increases. We then show that our method accurately calculates the ground-truth transition probabilities from a publicly available phantom dataset. As a demonstration, we incorporate our analytic method for voxel transition probabilities into the Voxel Graph framework, creating a quantitative framework for assessing white matter structure, which we call "analytic tractography". The long-range connectivity problem is reduced to finding paths in a graph whose adjacency structure reflects voxel-to-voxel analytic transition probabilities. We demonstrate that this approach performs comparably to the current most widely-used probabilistic and deterministic approaches at a fraction of the computational cost. We also demonstrate that analytic tractography works on multiple diffusion sampling schemes, reconstruction method or parameters used to define paths. Open source software compatible with popular dMRI reconstruction software is provided.

The differentiated networks related to essential tremor onset and its amplitude modulation after alcohol intake

The dysregulation of endogenous rhythms within brain networks have been implicated in a broad range of motor and non-motor pathologies. Essential tremor (ET), classically the purview of a single aberrant pacemaker, has recently become associated with network-level dysfunction across multiple brain regions. Specifically, it has been suggested that motor cortex constitutes an important node in a tremor-generating network involving the cerebellum. Yet the mechanisms by which these regions relate to tremor remain a matter of considerable debate. We sought to discriminate the contributions of cerebral and cerebellar dysregulation by combining high-density electroencephalography with subject-specific structural MRI. For that, we contrasted ET with voluntary (mimicked) tremor before and after ingestion of alcohol to regulate the tremorgenic networks. Our results demonstrate distinct loci of cortical tremor coherence, most pronounced over the sensorimotor cortices in healthy controls, but more frontal motor areas in ET-patients consistent with a heightened involvement of the supplementary motor area. We further demonstrate that the reduction in tremor amplitude associated with alcohol intake is reflected in altered cerebellar - but not cerebral - coupling with movement. Taken together, these findings implicate tremor emergence as principally associated with increases in activity within frontal motor regions, whereas modulation of the amplitude of established tremor relates to changes in cerebellar activity. These findings progress a mechanistic understanding of ET and implicate network-level vulnerabilities in the rhythmic nature of communication throughout the brain.

Time-dependent functional role of the contralesional motor cortex after stroke

After stroke, movements of the paretic hand rely on altered motor network dynamics typically including additional activation of the contralesional primary motor cortex (M1). The functional implications of contralesional M1 recruitment to date remain a matter of debate.

We here assessed the role of contralesional M1 in 12 patients recovering from a first-ever stroke using online transcranial magnetic stimulation (TMS): Short bursts of TMS were administered over contralesional M1 or a control site (occipital vertex) while patients performed different motor tasks with their stroke-affected hand.

In the early subacute phase (1–2 weeks post-stroke), we observed significant improvements in maximum finger tapping frequency when interfering with contralesional M1, while maximum grip strength and speeded movement initiation remained unaffected. After > 3 months of motor recovery, disruption of contralesional M1 activity did not interfere with performance in any of the three tasks, similar to what we observed in healthy controls.

In patients with mild to moderate motor deficits, contralesional M1 has a task- and time-specific negative influence on motor performance of the stroke-affected hand. Our results help to explain previous contradicting findings on the role of contralesional M1 in recovery of function.

•

Online TMS to contralesional M1 improves movement frequency in subacute but not chronic stroke.

•

No effects were observed for grip strength or speeded movement initiation.

•

Contralesional M1 has a task- and time-specific negative influence on motor performance.

Shaping Early Reorganization of Neural Networks Promotes Motor Function after Stroke

Neural plasticity is a major factor driving cortical reorganization after stroke. We here tested whether repetitively enhancing motor cortex plasticity by means of intermittent theta-burst stimulation (iTBS) prior to physiotherapy might promote recovery of function early after stroke. Functional magnetic resonance imaging (fMRI) was used to elucidate underlying neural mechanisms. Twenty-six hospitalized, first-ever stroke patients (time since stroke: 1–16 days) with hand motor deficits were enrolled in a sham-controlled design and pseudo-randomized into 2 groups. iTBS was administered prior to physiotherapy on 5 consecutive days either over ipsilesional primary motor cortex (M1-stimulation group) or parieto-occipital vertex (control-stimulation group). Hand motor function, cortical excitability, and resting-state fMRI were assessed 1 day prior to the first stimulation and 1 day after the last stimulation. Recovery of grip strength was significantly stronger in the M1-stimulation compared to the control-stimulation group. Higher levels of motor network connectivity were associated with better motor outcome. Consistently, control-stimulated patients featured a decrease in intra- and interhemispheric connectivity of the motor network, which was absent in the M1-stimulation group. Hence, adding iTBS to prime physiotherapy in recovering stroke patients seems to interfere with motor network degradation, possibly reflecting alleviation of post-stroke diaschisis.

The right temporoparietal junction in attention and social interaction: A transcranial magnetic stimulation study

The right temporoparietal junction (rTPJ) has been associated with the ability to reorient attention to unexpected stimuli and the capacity to understand others' mental states (theory of mind [ToM]/false belief). Using activation likelihood estimation meta-analysis we previously unraveled that the anterior rTPJ is involved in both, reorienting of attention and ToM, possibly indicating a more general role in attention shifting. Here, we used neuronavigated transcranial magnetic stimulation to directly probe the role of the rTPJ across attentional reorienting and false belief. Task performance in a visual cueing paradigm and false belief cartoon task was investigated after application of continuous theta burst stimulation (cTBS) over anterior rTPJ (versus vertex, for control). We found that attentional reorienting was significantly impaired after rTPJ cTBS compared with control. For the false belief task, error rates in trials demanding a shift in mental state significantly increased. Of note, a significant positive correlation indicated a close relation between the stimulation effect on attentional reorienting and false belief trials. Our findings extend previous neuroimaging evidence by indicating an essential overarching role of the anterior rTPJ for both cognitive functions, reorienting of attention and ToM. Hum Brain Mapp 37:796-807, 2016. © 2015 Wiley Periodicals, Inc.

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.

Dopaminergic modulation of motor network dynamics in Parkinson's disease

Using connectivity analyses based on functional MRI, Michely et al. investigate dopaminergic modulation of neural network dynamics involved in motor control in Parkinson’s disease. The findings provide insights into the pathophysiology underlying bradykinesia and deficits in executive function, and help to explain why dopaminergic treatments have a greater effect on the former.

Although characteristic motor symptoms of Parkinson’s disease such as bradykinesia typically improve under dopaminergic medication, deficits in higher motor control are less responsive. We here investigated the dopaminergic modulation of network dynamics underlying basic motor performance, i.e. finger tapping, and higher motor control, i.e. internally and externally cued movement preparation and selection. Twelve patients, assessed ON and OFF medication, and 12 age-matched healthy subjects underwent functional magnetic resonance imaging. Dynamic causal modelling was used to assess effective connectivity in a motor network comprising cortical and subcortical regions. In particular, we investigated whether impairments in basic and higher motor control, and the effects induced by dopaminergic treatment are due to connectivity changes in (i) the mesial premotor loop comprising the supplementary motor area; (ii) the lateral premotor loop comprising lateral premotor cortex; and (iii) cortico-subcortical interactions. At the behavioural level, we observed a marked slowing of movement preparation and selection when patients were internally as opposed to externally cued. Preserved performance during external cueing was associated with enhanced connectivity between prefrontal cortex and lateral premotor cortex OFF medication, compatible with a context-dependent compensatory role of the lateral premotor loop in the hypodopaminergic state. Dopaminergic medication significantly improved finger tapping speed in patients, which correlated with a drug-induced coupling increase of prefrontal cortex with the supplementary motor area, i.e. the mesial premotor loop. In addition, only in the finger tapping condition, patients ON medication showed enhanced excitatory influences exerted by cortical premotor regions and the thalamus upon the putamen. In conclusion, the amelioration of bradykinesia by dopaminergic medication seems to be driven by enhanced connectivity within the mesial premotor loop and cortico-striatal interactions. In contrast, medication did not improve internal motor control deficits concurrent to missing effects at the connectivity level. This differential effect of dopaminergic medication on the network dynamics underlying motor control provides new insights into the clinical finding that in Parkinson’s disease dopaminergic drugs especially impact on bradykinesia but less on executive functions.

Identifying Neuroimaging Markers of Motor Disability in Acute Stroke by Machine Learning Techniques

Conventional mass-univariate analyses have been previously used to test for group differences in neural signals. However, machine learning algorithms represent a multivariate decoding approach that may help to identify neuroimaging patterns associated with functional impairment in "individual" patients. We investigated whether fMRI allows classification of individual motor impairment after stroke using support vector machines (SVMs). Forty acute stroke patients and 20 control subjects underwent resting-state fMRI. Half of the patients showed significant impairment in hand motor function. Resting-state connectivity was computed by means of whole-brain correlations of seed time-courses in ipsilesional primary motor cortex (M1). Lesion location was identified using diffusion-weighted images. These features were used for linear SVM classification of unseen patients with respect to motor impairment. SVM results were compared with conventional mass-univariate analyses. Resting-state connectivity classified patients with hand motor deficits compared with controls and nonimpaired patients with 82.6-87.6% accuracy. Classification was driven by reduced interhemispheric M1 connectivity and enhanced connectivity between ipsilesional M1 and premotor areas. In contrast, lesion location provided only 50% sensitivity to classify impaired patients. Hence, resting-state fMRI reflects behavioral deficits more accurately than structural MRI. In conclusion, multivariate fMRI analyses offer the potential to serve as markers for endophenotypes of functional impairment.

What Makes the Muscle Twitch: Motor System Connectivity and TMS-Induced Activity

Transcranial magnetic stimulation (TMS) of the primary motor cortex (M1) evokes several volleys of corticospinal activity. While the earliest wave (D-wave) originates from axonal activation of cortico-spinal neurons (CSN), later waves (I-waves) result from activation of mono- and polysynaptic inputs to CSNs. Different coil orientations preferentially stimulate cortical elements evoking different outputs: latero-medial-induced current (LM) elicits D-waves and short-latency electromyographic responses (MEPs); posterior-anterior current (PA) evokes early I-waves. Anterior-posterior current (AP) is more variable and tends to recruit later I-waves, featuring longer onset latencies compared with PA-TMS. We tested whether the variability in response to AP-TMS was related to functional connectivity of the stimulated M1 in 20 right-handed healthy subjects who underwent functional magnetic resonance imaging while performing an isometric contraction task. The MEP-latency after AP-TMS (relative to LM-TMS) was strongly correlated with functional connectivity between the stimulated M1 and a network involving cortical premotor areas. This indicates that stronger premotor-M1 connectivity increases the probability that AP-TMS recruits shorter latency input to CSNs. In conclusion, our data strongly support the hypothesis that TMS of M1 activates distinct neuronal pathways depending on the orientation of the stimulation coil. Particularly, AP currents seem to recruit short latency cortico-cortical projections from premotor areas.