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.
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.
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.
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
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.
Introduction Coordinated hand movements derive from fine-tuned interactions of various motor regions. Transcranial magnetic stimulation (TMS) allows to test the role of cortical motor areas. ...Disturbing the activity of the primary motor cortex (M1) ipsilateral to the moving hand via ‘online’ TMS, i.e., applied during task execution, has been shown to alter the recruitment of hand muscles in grip-lift-tasks ( Davare et al., 2007 ). Then again, similar stimulation had no effect on the performance of simple reaction-time tasks ( Nardone et al., 2013 ). Conflicting data might result from differences in stimulation parameters (e.g., stimulation intensity) or from motor task specific effect of online-TMS interference. We, here, applied online TMS to M1 while subjects performed motor-tasks of different complexities with the ipsilateral hand to further our insights into the exact role of the ipsilateral M1 in hand movement. Material and methods 16 healthy, right-handed subjects performed three different motor tasks with the right index finger (simple reaction-time and maximum finger-tapping task) or the right hand (maximum grip strength over one second). TMS Pulses were applied as 10 Hz-trains time-locked to motor task execution. Performance was measured for four different conditions. Real-stimulation was applied at three different intensities: (i) 70%, (ii) 80%, or (iii) 90% of the resting motor threshold (RMT) to the right M1. Sham-stimulation was applied at 90% RMT over parieto-occipital vertex. The order of stimulation blocks was pseudo-randomized across subjects. Results Online TMS applied to the right M1 differentially affected motor task performance with the right (ipsilateral) hand. Maximum finger-tapping frequency and the integrated grip strength time course were significantly reduced by real compared to sham stimulation. Of note, we found a stimulation intensity dependent effect with higher stimulation intensities leading to stronger reduction in motor performance. In contrast, performance in the simple reaction-time task was not affected by online TMS. Discussion We found online TMS applied to M1 to impact on the motor function of the ipsilateral hand. Importantly, the ‘virtual lesion’ effect induced by online TMS strongly depended on the intensity at which pulses were applied and the given motor task. Our results suggest M1 to functionally contribute to the repetitive and timely precise recruitment of ipsilateral hand muscles. Finally, our experimental approach also offers the opportunity to study the altered role of the ipsilateral M1 in disease, e.g., during motor network reorganization following stroke.
Introduction Healthy elderly adults typically show greater regional activity in frontoparietal brain regions relative to young adults when performing motor control tasks ( Ward and Frackowiak, 2003; ...Vallesi et al., 2011 ). However, the functional role of enhanced activity within the motor network is still a matter of debate. One hypothesis is that higher levels of neural activity reflect a compensatory mechanism to account for age-related decline in neural networks. We, therefore, used a systems-level approach to investigate networks dynamics underlying motor control in young and elderly subjects. We hypothesized that advanced aging is associated with reduced connectivity in the basic motor network, which is compensated by stronger influence of non-primary motor areas like prefrontal cortex. Methods We scanned 12 young (age 22–33) and 12 elderly subjects (age 52–74) employing a computerized task involving both basic (finger tapping) and higher motor control processing (internally and externally cued movement selection and initiation). Dynamic Causal Modelling (DCM) for fMRI was used to assess effective connectivity in a bilateral frontoparietal network comprising dorsolateral prefrontal cortex, dorsal premotor cortex, intraparietal cortex and primary motor cortex. Results Elderly subjects showed a significant slowing in movement selection and initiation. This slowing was accompanied by increases in both regional brain activity and effective connectivity between frontoparietal brain regions in elderly compared to young subjects. However, within the group of elderly subjects, coupling strengths of premotor cortex with primary motor cortex and intraparietal cortex decreased with advancing age, whereas connectivity between prefrontal and premotor cortex increased as a function of age. Discussion Network interactions underlying visuomotor transformation (parietal-premotor) and motor execution (premotor-primary motor cortex) follow an U-curve relationship: Connectivity is generally elevated in old relative to young subjects, yet decreases with advanced aging. In contrast, prefrontal influences on premotor cortex increase with advanced aging. These findings are in line with the ”posterior to anterior shift theory” described for regional brain activity, thereby extending it to network interactions related to higher motor control ( Davis et al., 2008 ).
Introduction One of the key symptoms of Parkinson’s disease (PD) is the impairment of spontaneous movement also known as akinesia ( Berardelli et al., 2001 ). Correspondingly, patients performing ...motor tasks feature abnormal activation in regions such as posterior medial frontal cortex (pMFC) and putamen ( Herz et al., 2013 ). These areas play crucial roles in the internal timing of volitional movements in healthy individuals ( Hoffstaedter et al., 2013 ). Yet, little is known about these regions’ functional connectivity (FC) in PD and its relationship with akinesia. The present study investigated FC alterations of the ’motor initiation network’ in PD, using a seed-based resting-state (RS) analysis. Methods RS fMRI data of 60 patients diagnosed with idiopathic PD (mean age 61.6 ± 10.2; mean disease duration 6.5 ± 5.5 years) and 72 healthy volunteers (mean age 60.1 ± 8.8, matched for age, gender and within-scanner movement) was acquired at two sites. After spatial preprocessing (realignment, normalization, smoothing), temporal filtering was conducted including motion confound removal and band-pass filtering. Seeds in bilateral putamen and pMFC were derived from a meta-analysis on volitional movements ( Hoffstaedter et al., 2014 ). Two more seeds were selected in bilateral primary motor cortex (M1). For each seed, (i) whole-brain FC and (ii) its interaction with akinesia (UPDRS item 3.14) were assessed. RS networks for the aforementioned regions were first mapped in healthy controls only: Contrasting each region’s FC to the FC of all respective other seeds yielded maps of specific connectivity with either seed. These networks were then used to map whole-brain corrected changes of FC in PD. Results were cluster-level corrected for multiple comparisons ( p < 0.05). Results In healthy participants, RS analysis differentiated three networks, specifically (more than all other seeds) connected to bilateral putamen, bilateral M1, and pMFC. In PD, all seeds consistently featured decreased FC with regions in their most related network. That is, M1 mainly showed FC decrease within the M1-related network, pMFC lost FC with anterior insulae and left dorsolateral prefrontal cortex (DLPFC; pMFC-related network), and putamen lost FC with caudate nucleus, pallidum and thalamus (Putamen-related network). Additionally, putamen FC decreased extensively also in those regions more related to M1 and pMFC, including visual, superior parietal, primary somatosensory, M1, pMFC and DLPFC. Testing for each seed’s interaction with akinesia, pMFC showed a decreased FC with inferior parietal lobe (IPL) in the pMFC-related network. In turn, FC of the other seeds did not significantly relate to akinesia. Conclusions The present study examined RS FC changes of bilateral putamen, M1 and pMFC in PD. In patients, putamen FC suggests a marked cortico-striatal decoupling, in line with pathophysiological models of the disease ( Braak et al., 2004 ). In contrast, pMFC featured more selective FC decreases, predominantly in regions involved in motor control ( Hoffstaedter et al., 2013; Hoffstaedter et al., 2014 ). Notably, akinesia was exclusively related to pMFC-connectivity. With increasing impairment, pMFC decoupled from the right IPL. In sum, the present study demonstrates a disruption of cortico-striatal FC and specifies the role of pMFC - IPL connectivity for movement initiation in PD.
Diagnosis, monitoring of the efficiency of detoxification, and estimating the prognosis of acute poisonings are important tasks in emergency toxicology. Comprehensive screening and quantification of ...relevant substances by gas chromatography–mass spectrometry (GC–MS) or liquid chromatography–mass spectrometry (LC–MS) help in assessing the severity of most acute poisonings. Turnaround time for such analyses must be short enough to impact on clinical decisions. Therefore, a multi‐analyte LC–MS/MS approach with a 5‐minute gradient was developed and validated for 45 drugs and their active metabolites as a complement to an existing GC–MS approach using the same liquid–liquid extraction. The determination ranges were defined by quality control samples of low and high, representing concentrations from low therapeutic to highly toxic levels. To shorten the turnaround time, one‐point calibration was used. Validation showed low matrix effects and ionization effects of co‐eluting analytes thanks to APCI source as well as sufficient recoveries, precisions, and selectivities. For accuracy, 32 of the 45 compounds fulfilled the criteria for quantification in lower therapeutic and 41 in overdosed and toxic concentrations, considering limits of ±30% deviation. The reuse of the processed calibrator for a period of 30 days was possible for 32 compounds, showing sufficient stability at 8°C. In addition, analysis of authentic blood samples showed the applicability and yielded drug levels, which were comparable to those determined by fully validated therapeutic drug monitoring methods. In conclusion, the present approach in combination with the GC–MS approach should provide sufficient support for clinical assessment of the severity of poisonings with 68 compounds in an acceptable turnaround time.
In emergency toxicology, fast toxicological screening and blood levels of relevant drugs can support diagnosis of poisonings, monitoring efficiency of detoxification, and assessing prognosis. This study presents a validated LC‐MS/MS approach for quantification of 45 drugs and active metabolites with one‐point calibration. In conclusion, it should be sufficient to help in assessing the severity of corresponding poisonings in context of emergency toxicology.
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