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.
We used functional magnetic resonance imaging (fMRI) and cytoarchitectonic probability maps to investigate the responsiveness of individual areas in the human primary and secondary somatosensory ...cortices to hand, face, or trunk stimulation of either body-side. A Bayesian modeling approach to quantify the probability of ipsilateral activations revealed that areas OP 1, OP 4, and OP 3 of the SII cortex as well as the trunk and face representations within all SI subareas (areas 3b, 1, and 2) show robust bilateral responses to unilateral stimulation. Such bilateral response properties are in good agreement with the transcallosal projections demonstrated for these areas in nonhuman primates and other mammals. In contrast, the SI hand region showed a different pattern. Whereas ipsilateral areas 3b and 1 were deactivated by tactile hand stimulation, particularly on the left, there was strong evidence for ipsilateral processing of information from the right hand in area 2. These results demonstrate not only the behavioral importance of the hand representation, but also suggest that area 2 may have particularly evolved to form the cortical substrate of these specialized demands, in line with recent studies on cortical evolution hypothesizing that area 2 has developed with increasing manual abilities in anthropoid primates featuring opposable thumbs.
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.
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.
The secondary somatosensory cortex (SII) of nonhuman primates is located on the parietal operculum. In the monkey, electrophysiological and connectivity tracing studies as well as histological ...investigations provide converging evidence for 3 distinct cortical areas (SII, PV, and VS) within this region, each of which contains a complete somatotopic map. Although the equivalency of the parietal operculum as the location of SII between humans and nonhuman primates is undisputed, the internal organization of the human SII region is still largely unknown. Based on their topography, we have previously argued that the cytoarchitectonic areas OP 1, OP 4, and OP 3 may constitute the human homologues of areas SII, PV, and VS, respectively. To test this hypothesis, we here examined (using functional magnetic resonance imaging) the somatotopic organization of the human parietal operculum by applying tactile stimulation to the skin at 4 different locations on either side of the body (face, hands, trunk, and legs). The locations of the resulting activation foci were then compared with the cytoarchitectonic maps of this region. Data analysis revealed 2 somatotopic body representations on the lateral operculum in areas OP 1 and OP 4. The functional border between these 2 body maps was defined by a mirror reversal in the somatotopic arrangement and coincided with the cytoarchitectonically defined border between these 2 areas. This somatotopic arrangement closely matches that described for SII and PV in nonhuman primates. The data also suggested a third somatotopic map located deeper inside the Sylvian fissure in area OP 3. Based on the observed topographic arrangement and their functional response characteristics, we conclude that cytoarchitectonic areas OP1, OP 4, and OP 3 on the human parietal operculum constitute the human homologues of primate areas SII, PV, and VS, respectively.
Movements result from a complex interplay of multiple brain regions. These regions are assembled into distinct functional networks depending on the specific properties of the action. However, the ...nature and details of the dynamics of this complex assembly process are unknown. In this study, we sought to identify key markers of the neural processes underlying the preparation and execution of motor actions that always occur irrespective of differences in movement initiation, hence the specific neural processes and functional networks involved. To this end, EEG activity was continuously recorded from 18 right-handed healthy participants while they performed a simple motor task consisting of button presses with the left or right index finger. The movement was performed either in response to a visual cue or at a self-chosen, i.e., non-cued point in time. Despite these substantial differences in movement initiation, dynamic properties of the EEG signals common to both conditions could be identified using time–frequency and phase locking analysis of the EEG data. In both conditions, a significant phase locking effect was observed that started prior to the movement onset in the δ–θ frequency band (2–7Hz), and that was strongest at the electrodes nearest to the contralateral motor region (M1). This phase locking effect did not have a counterpart in the corresponding power spectra (i.e., amplitudes), or in the event-related potentials. Our finding suggests that phase locking in the δ–θ frequency band is a ubiquitous movement-related signal independent of how the actual movement has been initiated. We therefore suggest that phase-locked neural oscillations in the motor cortex are a prerequisite for the preparation and execution of motor actions.
•We found phase locking in the delta–theta frequency band in motor areas prior to movement execution.•Phase locking occurred irrespective of how the action was initiated.•Our results suggest that phase locking constitutes a prerequisite to trigger movement execution.
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.
Healthy aging is accompanied by a decrease in cognitive and motor capacities. In a network associated with movement initiation, we investigated age-related changes of functional connectivity (FC) as ...well as regional atrophy in a sample of 232 healthy subjects (age range 18–85 years). To this end, voxel-based morphometry and whole-brain resting-state FC were analyzed for the supplementary motor area (SMA), anterior midcingulate cortex (aMCC) and bilateral striatum (Str). To assess the specificity of age-related effects, bilateral primary sensorimotor cortex (S1/M1) closely associated with motor execution was used as control seeds. All regions showed strong reduction of gray matter volume with age. Corrected for this regional atrophy, the FC analysis revealed an age × seed interaction for each of the bilateral Str nodes against S1/M1 with consistent age-related decrease in FC with bilateral caudate nucleus and anterior putamen. Specific age-dependent FC decline of SMA was found in bilateral central insula and the adjacent frontal operculum. aMCC showed exclusive age-related decoupling from the anterior cingulate motor area. The present study demonstrates network as well as node-specific age-dependent FC decline of the SMA and aMCC to highly integrative cortical areas involved in cognitive motor control. FC decrease in addition to gray matter atrophy within the Str may provide a substrate for the declining motor control in elderly. Finally, age-related FC changes in both the network for movement initiation as well as the network for motor execution are not explained by regional atrophy in the healthy aging brain.
Background Event-related transcranial magnetic stimulation (TMS) allows to interfere with neural processing of cortical areas. While we have a rather good knowledge of the role of frontoparietal ...areas for motor performance of the contralateral hand, the contribution of ipsilateral areas is far less understood (Davare et al., 2007) . Neuroimaging studies found an increasing recruitment of ipsilateral motor regions in healthy elderly, implying a supportive influence during normative aging (Hutchinson et al., 2002; Riecker et al., 2006) . To test this hypothesis, we used online-TMS to investigate the role of ipsilateral primary motor cortex (M1), premotor cortex (dPMC), and the anterior intraparietal sulcus (aIPS) in motor tasks of different complexity in young and elderly subjects. Methods 30 healthy, right-handed subjects (15 young (27.8 y); 15 elderly (61.3 y)) conducted four motor tasks of different complexity: (i) simple reaction time task, (ii) maximum finger and (iii) hand tapping frequencies, and (iv) rapid pointing between two defined targets. Tapping and pointing tasks were recorded with kinematic motion analyzer system (Zebris). TMS pulses were applied as 10 Hz-trains, time-locked to task execution. Stimulation was applied at 90% intensity of the resting motor threshold (rMT) to ipsilateral M1, dPMC, and aIPS. Sham-stimulation at 90% of rMT to parieto-occipital vertex served as control condition. Results In the finger tapping task (ii) we found both a main effect of online-TMS and an interaction effect between group and stimulation site. While in elderly stimulation over dPMC led to a decrease in tapping intervall, performance in the young group was mainly affected by M1-stimulation. Furthermore, for the target pointing task (iv) we found a decrease of aiming accuracy in the elderly group upon TMS interference with aIPS and dPMC but the young stayed unaffected by stimulation over all sites. Finally, age correlated with a frequency reduction of hand tapping (iii) induced by aIPS-stimulation. Conclusion Our findings suggest that there are differential roles of investigated areas in motor performance in aging. The data further displays relevance of dPMC and aIPS in repetitive tapping and target pointing tasks in elderly. Both regions seem to be causally engaged in maintaining performance in elderly. This might indicate that an increasing recruitment of ipsilateral motor regions (Hutchinson et al., 2002; Riecker et al., 2006) seems to have a supportive influence on motor performance in elderly.
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