A widely used technique for coordinate-based meta-analyses of neuroimaging data is activation likelihood estimation (ALE). ALE assesses the overlap between foci based on modelling them as probability distributions centred at the respective coordinates. Here we present a revised ALE algorithm addressing drawbacks associated with former implementations:The first change pertains to the size of the probability distributions, which had to be specified by the used. To provide a more principled solution, we analysed fMRI data of 21 subjects, each normalised into MNI space using nine different approaches. This analysis provided quantitative estimates of between-subject and between-template variability for 16 functionally defined regions, which were then used to explicitly model the spatial uncertainty associated with each reported coordinate. Secondly, instead of testing for an above-chance clustering between foci, the revised algorithm assesses above-chance clustering between experiments. The spatial relationship between foci in a given experiment is now assumed to be fixed and ALE results are assessed against a nulldistribution of random spatial association between experiments. Critically, this modification entails a change from fixed-to random-effects inference in ALE analysis allowing generalisation of the results to the entire population of studies analysed.By comparative analysis of real and simulated data, we showed that the revised ALE-algorithm overcomes conceptual problems of former meta-analyses and increases the specificity of the ensuing results without loosing the sensitivity of the original approach. It may thus provide a methodologically improved tool for coordinate-based meta-analyses on functional imaging data.

Functional neuroimaging studies frequently demonstrated that stroke patients show bilateral activity in motor and premotor areas during movements of the paretic hand in contrast to a more lateralized activation observed in healthy subjects. Moreover, a few studies modeling functional or effective connectivity reported performance-related changes in the motor network after stroke. Here, we investigated the temporal evolution of intra- and interhemispheric (dys-) connectivity during motor recovery from the acute to the early chronic phase post-stroke. Twelve patients performed hand movements in an fMRI task in the acute (≤72 hours) and subacute stage (2 weeks) post-stroke. A subgroup of 10 patients participated in a third assessment in the early chronic stage (3-6 months). Twelve healthy subjects served as reference for brain connectivity. Changes in effective connectivity within a bilateral network comprising M1, premotor cortex (PMC), and supplementary motor area (SMA) were estimated by dynamic causal modeling. Motor performance was assessed by the Action Research Arm Test and maximum grip force. Results showed reduced positive coupling of ipsilesional SMA and PMC with ipsilesional M1 in the acute stage. Coupling parameters among these areas increased with recovery and predicted a better outcome. Likewise, negative influences from ipsilesional areas to contralesional M1 were attenuated in the acute stage. In the subacute stage, contralesional M1 exerted a positive influence on ipsilesional M1. Negative influences from ipsilesional areas on contralesional M1 subsequently normalized, but patients with poorer outcome in the chronic stage now showed enhanced negative coupling from contralesional upon ipsilesional M1. These findings show that the reinstatement of effective connectivity in the ipsilesional hemisphere is an important feature of motor recovery after stroke. The shift of an early, supportive role of contralesional M1 into enhanced inhibitory coupling might indicate maladaptive processes which could be a target of non-invasive brain stimulation techniques.

Data derived from transcranial magnetic stimulation (TMS) studies suggest that transcallosal inhibition mechanisms between the primary motor cortex of both hemispheres may contribute to the reduced motor performance of stroke patients. We here investigated the potential of modulating pathological interactions between cortical motor areas by means of repetitive TMS using functional magnetic resonance imaging (fMRI) and dynamic causal modeling (DCM). Eleven subacute stroke patients were scanned 1-3 months after symptom onset while performing whole hand fist closure movements. After a baseline scan, patients were stimulated with inhibitory 1-Hz rTMS applied over two different locations: (i) vertex (control stimulation) and (ii) primary motor cortex (M1) of the unaffected (contralesional) hemisphere. Changes in the endogenous and task-dependent effective connectivity were assessed by DCM of a bilateral network comprising M1, lateral premotor cortex, and the supplementary motor area (SMA). The results showed that rTMS applied over contralesional M1 significantly improved the motor performance of the paretic hand. The connectivity analysis revealed that the behavioral improvements were significantly correlated with a reduction of the negative influences originating from contralesional M1 during paretic hand movements. Concurrently, endogenous coupling between ipsilesional SMA and M1 was significantly enhanced only after rTMS applied over contralesional M1. Therefore, rTMS applied over contralesional M1 may be used to transiently remodel the disturbed functional network architecture of the motor system. The connectivity analyses suggest that both a reduction of pathological transcallosal influences (originating from contralesional M1) and a restitution of ipsilesional effective connectivity between SMA and M1 underlie improved motor performance.

Animal models of stroke demonstrated that white matter ischemia may cause both axonal damage and myelin degradation distant from the core lesion, thereby impacting on behavior and functional outcome after stroke. We here used parameters derived from diffusion magnetic resonance imaging (MRI) to investigate the effect of focal white matter ischemia on functional reorganization within the motor system. Patients (n = 18) suffering from hand motor deficits in the subacute or chronic stage after subcortical stroke and healthy controls (n = 12) were scanned with both diffusion MRI and functional MRI while performing a motor task with the left or right hand. A laterality index was employed on activated voxels to assess functional reorganization across hemispheres. Regression analyses revealed that diffusion MRI parameters of both the ipsilesional corticospinal tract (CST) and corpus callosum (CC) predicted increased activation of the unaffected hemisphere during movements of the stroke-affected hand. Changes in diffusion MRI parameters possibly reflecting axonal damage and/or destruction of myelin sheath correlated with a stronger bilateral recruitment of motor areas and poorer motor performance. Probabilistic fiber tracking analyses revealed that the region in the CC correlating with the fMRI laterality index and motor deficits connected to sensorimotor cortex, supplementary motor area, ventral premotor cortex, superior parietal lobule, and temporoparietal junction. The results suggest that degeneration of transcallosal fibers connecting higher order sensorimotor regions constitute a relevant factor influencing cortical reorganization and motor outcome after subcortical stroke.