Limb immobilization and nonuse are well-known causes of corticomotor depression. While physical training can drive the recovery from nonuse-dependent corticomotor effects, it remains unclear if it is possible to gain access to motor cortex in alternative ways, such as through motor imagery (MI) or action observation (AO). Transcranial magnetic stimulation was used to study the excitability of the hand left motor cortex in normal subjects immediately before and after 10 h of right arm immobilization. During immobilization, subjects were requested either to imagine to act with their constrained limb or to observe hand actions performed by other individuals. A third group of control subjects watched a nature documentary presented on a computer screen. Hand corticomotor maps and recruitment curves reliably showed that AO, but not MI, prevented the corticomotor depression induced by immobilization. Our results demonstrate the existence of a visuomotor mechanism in humans that links AO and execution which is able to effect cortical plasticity in a beneficial way. This facilitation was not related to the action simulation, because it was not induced by explicit MI.
The activation of listener's motor system during speech processing was first demonstrated by the enhancement of electromyographic tongue potentials as evoked by single-pulse transcranial magnetic stimulation (TMS) over tongue motor cortex. This technique is, however, technically challenging and enables only a rather coarse measurement of this motor mirroring. Here, we applied TMS to listeners' tongue motor area in association with ultrasound tissue Doppler imaging to describe fine-grained tongue kinematic synergies evoked by passive listening to speech. Subjects listened to syllables requiring different patterns of dorso-ventral and antero-posterior movements (/ki/, /ko/, /ti/, /to/). Results show that passive listening to speech sounds evokes a pattern of motor synergies mirroring those occurring during speech production. Moreover, mirror motor synergies were more evident in those subjects showing good performances in discriminating speech in noise demonstrating a role of the speech-related mirror system in feed-forward processing the speaker's ongoing motor plan.
Conventional structural Magnetic Resonance (MR) techniques can accurately identify brain tumors but do not provide exhaustive information about the integrity of the surrounding/embedded white matter (WM). In this study, we used Diffusion-Weighted (DW) MRI tractography to explore tumor-induced alterations of WM architecture without any a priori knowledge about the fiber paths under consideration. We used deterministic multi-fiber tractography to analyze 16 cases of histologically classified brain tumors (meningioma, low-grade glioma, high-grade glioma) to evaluate the integrity of WM bundles in the tumoral region, in relation to the contralateral unaffected hemisphere. Our new tractographic approach yielded measures of WM involvement which were strongly correlated with the histopathological features of the tumor (r = 0.83, p = 0.0001). In particular, the number of affected fiber tracts were significantly (p = 0.0006) different among tumor types. Our method proposes a new application of diffusion tractography for the detection of tumor aggressiveness in those cases in which the lesion does not involve any major/known WM paths and when a priori information about the local fiber anatomy is lacking.
Recent data show a broad correspondence between human resting-state and task-related brain networks. We performed a functional magnetic resonance imaging (fMRI) study to compare, in the same subjects, the spatial independent component analysis (ICA) maps obtained at rest and during the observation of either reaching/grasping hand actions or matching static pictures. Two parietofrontal networks were identified by ICA from action observation task data. One network, specific to reaching/grasping observation, included portions of the anterior intraparietal cortex and of the dorsal and ventral lateral premotor cortices. A second network included more posterior portions of the parietal lobe, the dorsomedial frontal cortex, and more anterior and ventral parts, respectively, of the dorsal and ventral premotor cortices, extending toward Broca's area; this network was more generally related to the observation of hand action and static pictures. A good spatial correspondence was found between the 2 observation-related ICA maps and 2 ICA maps identified from resting-state data. The anatomical connectivity among the identified clusters was tested in the same volunteers, using persistent angular structure-MRI and deterministic tractography. These findings extend available knowledge of human parietofrontal circuits and further support the hypothesis of a persistent coherence within functionally relevant networks during rest.
At present, functional magnetic resonance imaging (fMRI) is one of the most useful methods of studying cognitive processes in the human brain in vivo, both for basic science and clinical goals. Although neuroscience studies often rely on group analysis, clinical applications must investigate single subjects (patients) only. Particularly for the latter, issues regarding the reliability of fMRI readings remain to be resolved. To determine the ability of intra-run variability (IRV) weighting to consistently detect active voxels, we first acquired fMRI data from a sample of healthy subjects, each of whom performed 4 runs (4 blocks each) of self-paced finger-tapping. Each subject's data was analyzed using single-run general linear model (GLM), and each block was then analyzed separately to calculate the IRV weighting. Results show that integrating IRV information into standard single-subject GLM activation maps significantly improved the reliability (p=0.007) of the single-subject fMRI data. This suggests that taking IRV into account can help identify the most constant and relevant neuronal activity at the single-subject level.
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