NeuroImage
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As yet, human cerebellar lesion studies have not taken advantage of direct magnetic resonance imaging (MRI) of the cerebellar nuclei in individual patients. In the present study, susceptibility weighted imaging (SWI) was used to visualize lesions of the dentate nuclei in patients with chronic focal lesions. Fifteen patients with cerebellar lesions either due to stroke or tumor surgery underwent SWI imaging using a 1.5T MRI scanner. ⋯ Subtraction analysis revealed that the more dorsal and rostral parts of the dentate nuclei were related to upper limb ataxia. Findings were in good accordance with the dentate hand area shown in recent fMRI studies. These data provide evidence that direct identification of dentate lesions together with the ROI-driven normalization technique allows for improved lesion-symptom mapping at the level of the cerebellar nuclei already at conventional 1.5T MRI field strength.
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Pain is known to comprise sensory, cognitive, and affective aspects. Despite numerous previous fMRI studies, however, it remains open which spatial distribution of activity is sufficient to encode whether a stimulus is perceived as painful or not. In this study, we analyzed fMRI data from a perceptual decision-making task in which participants were exposed to near-threshold laser pulses. ⋯ The most accurate prediction of pain perception from the stimulation period, however, was enabled by the combined activity in pain regions commonly referred to as the 'pain matrix'. Our results demonstrate that the neural representation of (near-threshold) pain is spatially distributed and can be best described at an intermediate spatial scale. In addition to its utility in establishing structure-function mappings, our approach affords trial-by-trial predictions and thus represents a step towards the goal of establishing an objective neuronal marker of pain perception.
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Spinal cord pathology can be functionally very important in neurological disease. Pathological studies have demonstrated the involvement of spinal cord grey matter (GM) and white matter (WM) in several diseases, although the clinical relevance of abnormalities detected histopathologically is difficult to assess without a reliable way to assess cord GM and WM in vivo. In this study, the feasibility of GM and WM segmentation was investigated in the upper cervical spinal cord of 10 healthy subjects, using high-resolution images acquired with a commercially available 3D gradient-echo pulse sequence at 3T. ⋯ The mean scan-rescan, intra- and inter-observer % coefficient of variation for measuring the TCA were 0.7%, 0.5% and 0.5% and for measuring the TGMA were 6.5%, 5.4% and 12.7%. The difference between WM-MTR and GM-MTR was found to be statistically significant (p=0.00006). This study has shown that GM and WM segmentation in the cervical cord is possible and the MR imaging protocol and analysis method presented here in healthy controls can be potentially extended to study the cervical cord in disease states, with the option to explore further quantitative measurements alongside MTR.
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Randomized Controlled Trial
Manipulating brain connectivity with δ⁹-tetrahydrocannabinol: a pharmacological resting state FMRI study.
Resting state-functional magnetic resonance imaging (RS-FMRI) is a neuroimaging technique that allows repeated assessments of functional connectivity in resting state. While task-related FMRI is limited to indirectly measured drug effects in areas affected by the task, resting state can show direct CNS effects across all brain networks. Hence, RS-FMRI could be an objective measure for compounds affecting the CNS. ⋯ Clear increases were found for feeling high, external perception, heart rate and cortisol, whereas prolactin decreased. This study shows that THC induces both increases and (to a lesser extent) decreases in functional brain connectivity, mainly in brain regions with high densities of CB(1)-receptors. Some of the involved regions could be functionally related to robust THC-induced CNS-effects that have been found in previous studies (Zuurman et al., 2008), such as postural stability, feeling high and altered time perception.
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We assessed the hypothesis that brain signal variability is a reflection of functional network reconfiguration during memory processing. In the present experiments, we use multiscale entropy to capture the variability of human electroencephalogram (EEG) while manipulating the knowledge representation associated with faces stored in memory. Across two experiments, we observed increased variability as a function of greater knowledge representation. ⋯ In Experiment 2, brain signal variability increased with learning after multiple experimental exposures to previously unfamiliar faces. The results demonstrate that variability increases with face familiarity; cognitive processes during the perception of familiar stimuli may engage a broader network of regions, which manifests as higher complexity/variability in spatial and temporal domains. In addition, effects of repetition suppression on brain signal variability were observed, and the pattern of results is consistent with a selectivity model of neural adaptation.