Ling E. Wang

Coordinate‐based activation likelihood estimation meta‐analysis of neuroimaging data: A random‐effects approach based on empirical estimates of spatial uncertainty

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 modeling them as probability distributions centered at the respective coordinates. In this Human Brain Project/Neuroinformatics research, the authors 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, the authors analyzed fMRI data of 21 subjects, each normalized 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 null‐distribution of random spatial association between experiments. Critically, this modification entails a change from fixed‐ to random‐effects inference in ALE analysis allowing generalization of the results to the entire population of studies analyzed. By comparative analysis of real and simulated data, the authors 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. Hum Brain Mapp 2009.

Modulating cortical connectivity in stroke patients by rTMS assessed with fMRI and dynamic causal modeling

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.

Dynamic causal modeling of cortical activity from the acute to the chronic stage after stroke.

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.

Noradrenergic enhancement improves motor network connectivity in stroke patients

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.

Noradrenergic Modulation of Cortical Networks Engaged in Visuomotor Processing

Both animal and human data suggest that stimulation of the noradrenergic system may influence neuronal excitability in regions engaged in sensory processing and visuospatial attention. We tested the hypothesis that the neural mechanisms subserving motor performance in tasks relying on the visuomotor control of goal-directed hand movements might be modulated by noradrenergic influences. Healthy subjects were stimulated using the selective noradrenaline reuptake inhibitor reboxetine (RBX) in a placebo-controlled crossover design. Functional magnetic resonance imaging and dynamic causal modeling (DCM) were used to assess drug-related changes in blood oxygen level-dependent activity and interregional connectivity while subjects performed a joystick task requiring goal-directed movements. Improved task performance under RBX was associated with increased activity in right visual, intraparietal and superior frontal cortex (premotor/frontal eye field). DCM revealed that the neuronal coupling among these regions was significantly enhanced when subjects were stimulated with RBX. Concurrently, right intraparietal cortex and right superior frontal cortex exerted a stronger driving influence on visuomotor areas of the left hemisphere, including SMA and M1. These effects were independent from task difficulty. The data suggest that stimulating noradrenergic mechanisms may rearrange the functional network architecture within and across the hemispheres, for example, by synaptic gating, thereby optimizing motor behavior.

Convergence of human brain mapping tools: Neuronavigated TMS Parameters and fMRI activity in the hand motor area

Functional magnetic resonance imaging (fMRI) and transcranial magnetic stimulation (TMS) are well‐established tools for investigating the human motor system in‐vivo. We here studied the relationship between movement‐related fMRI signal changes in the primary motor cortex (M1) and electrophysiological properties of the hand motor area assessed with neuronavigated TMS in 17 healthy subjects. The voxel showing the highest task‐related BOLD response in the left hand motor area during right hand movements was identified for each individual subject. This fMRI peak voxel in M1 served as spatial target for coil positioning during neuronavigated TMS. We performed correlation analyses between TMS parameters, BOLD signal estimates and effective connectivity parameters of M1 assessed with dynamic causal modeling (DCM). The results showed a negative correlation between the movement‐related BOLD signal in left M1 and resting as well as active motor threshold (MT) obtained for left M1. The DCM analysis revealed that higher excitability of left M1 was associated with a stronger coupling between left supplementary motor area (SMA) and M1. Furthermore, BOLD activity in left M1 correlated with ipsilateral silent period (ISP), i.e. the stronger the task‐related BOLD response in left M1, the higher interhemispheric inhibition effects targeting right M1. DCM analyses revealed a positive correlation between the coupling of left SMA with left M1 and the duration of ISP. The data show that TMS parameters assessed for the hand area of M1 do not only reflect the intrinsic properties at the stimulation site but also interactions with remote areas in the human motor system. Hum Brain Mapp, 2011.