The dose-dependent toxicity of the main psychoactive component of cannabis in brain regions rich in cannabinoid CB1 receptors is well known in animal studies. However, research in humans does not show common findings across studies regarding the brain regions that are affected after long-term exposure to cannabis. In the present study, we investigate (using Voxel-based Morphometry) gray matter changes in a group of regular cannabis smokers in comparison with a group of occasional smokers matched by the years of cannabis use. We provide evidence that regular cannabis use is associated with gray matter volume reduction in the medial temporal cortex, temporal pole, parahippocampal gyrus, insula, and orbitofrontal cortex; these regions are rich in cannabinoid CB1 receptors and functionally associated with motivational, emotional, and affective processing. Furthermore, these changes correlate with the frequency of cannabis use in the 3 months before inclusion in the study. The age of onset of drug use also influences the magnitude of these changes. Significant gray matter volume reduction could result either from heavy consumption unrelated to the age of onset or instead from recreational cannabis use initiated at an adolescent age. In contrast, the larger gray matter volume detected in the cerebellum of regular smokers without any correlation with the monthly consumption of cannabis may be related to developmental (ontogenic) processes that occur in adolescence.

Isolated focal dystonias are a group of disorders with diverse symptomatology but unknown pathophysiology. Although recent neuroimaging studies demonstrated regional changes in brain connectivity, it remains unclear whether focal dystonia may be considered a disorder of abnormal networks. We examined topology as well as the global and local features of large-scale functional brain networks across different forms of isolated focal dystonia, including patients with task-specific (TSD) and nontask-specific (NTSD) dystonias. Compared with healthy participants, all patients showed altered network architecture characterized by abnormal expansion or shrinkage of neural communities, such as breakdown of basal ganglia-cerebellar community, loss of a pivotal region of information transfer (hub) in the premotor cortex, and pronounced connectivity reduction within the sensorimotor and frontoparietal regions. TSD were further characterized by significant connectivity changes in the primary sensorimotor and inferior parietal cortices and abnormal hub formation in insula and superior temporal cortex, whereas NTSD exhibited abnormal strength and number of regional connections. We suggest that isolated focal dystonias likely represent a disorder of large-scale functional networks, where abnormal regional interactions contribute to network-wide functional alterations and may underline the pathophysiology of isolated focal dystonia. Distinct symptomatology in TSD and NTSD may be linked to disorder-specific network aberrations.

The thalamic nuclei are involved in many neurodegenerative diseases and therefore, their identification is of key importance in numerous clinical treatments. Automated segmentation of thalamic subparts is currently achieved by exploring diffusion-weighted magnetic resonance imaging (DW-MRI), but in absence of such data, atlas-based segmentation can be used as an alternative. Currently, there is a limited number of available digital atlases of the thalamus. Moreover, all atlases are created using a few subjects only, thus are prone to errors due to the inter-subject variability of the thalamic morphology. In this work, we present a probabilistic atlas of anatomical subparts of the thalamus built upon a relatively large dataset where the individual thalamic parcellation was done by employing a recently proposed automatic diffusion-based clustering method. Our analyses, comparing the segmentation performance between the atlas-based and the clustering method, demonstrate the ability of the provided atlas to substitute the automated diffusion-based subdivision in the individual space when the DW-MRI is not available.

The thalamus is an essential relay station in the cortical–subcortical connections. It is characterized by a complex anatomical architecture composed of numerous small nuclei, which mediate the involvement of the thalamus in a wide range of neurological functions. We present a novel framework for segmenting the thalamic nuclei, which explores the orientation distribution functions (ODFs) from diffusion magnetic resonance images at 3 T. The differentiation of the complex intra-thalamic microstructure is improved by using the spherical harmonic (SH) representation of the ODFs, which provides full angular characterization of the diffusion process in each voxel. The clustering was performed using the k-means algorithm initialized in a data-driven manner. The method was tested on 35 healthy volunteers and our results show a robust, reproducible and accurate segmentation of the thalamus in seven nuclei groups. Six of them closely matched the anatomy and were labeled as anterior, ventral anterior, medio-dorsal, ventral latero-ventral, ventral latero-dorsal and pulvinar, while the seventh cluster included the centro-lateral and the latero-posterior nuclei. Results were evaluated both qualitatively, by comparing the segmented nuclei to the histological atlas of Morel, and quantitatively, by measuring the clusters’ extent and the clusters’ spatial distribution across subjects and hemispheres. We also showed the robustness of our approach across different sequences and scanners, as well as intra-subject reproducibility of the segmented clusters using additional two scan–rescan datasets. We also observed an overlap between the path of the main long-connection tracts passing through the thalamus and the spatial distribution of the nuclei identified with our clustering algorithm. Our approach, based on SH representations of the ODFs, outperforms the one based on angular differences between the principle diffusion directions, which is considered so far as state-of-the-art method. Our findings show an anatomically reliable segmentation of the main groups of thalamic nuclei that could be of potential use in many clinical applications.Electronic supplementary materialThe online version of this article (doi:10.1007/s00429-016-1336-4) contains supplementary material, which is available to authorized users.

Tremor, affecting a dystonic body part, is a frequent feature of adult-onset dystonia. However, our understanding of dystonic tremor pathophysiology remains ambiguous, as its interplay with the main co-occurring disorder, dystonia, is largely unknown. We used a combination of functional MRI, voxel-based morphometry and diffusion-weighted imaging to investigate similar and distinct patterns of brain functional and structural alterations in patients with dystonic tremor of voice (DTv) and isolated spasmodic dysphonia (SD). We found that, compared to controls, SD patients with and without DTv showed similarly increased activation in the sensorimotor cortex, inferior frontal (IFG) and superior temporal gyri, putamen and ventral thalamus, as well as deficient activation in the inferior parietal cortex and middle frontal gyrus (MFG). Common structural alterations were observed in the IFG and putamen, which were further coupled with functional abnormalities in both patient groups. Abnormal activation in left putamen was correlated with SD onset; SD/DTv onset was associated with right putaminal volumetric changes. DTv severity established a significant relationship with abnormal volume of the left IFG. Direct patient group comparisons showed that SD/DTv patients had additional abnormalities in MFG and cerebellar function and white matter integrity in the posterior limb of the internal capsule. Our findings suggest that dystonia and dystonic tremor, at least in the case of SD and SD/DTv, are heterogeneous disorders at different ends of the same pathophysiological spectrum, with each disorder carrying a characteristic neural signature, which may potentially help development of differential markers for these two conditions.

Time is a fundamental dimension of everyday experiences. We can unmistakably sense its passage and adjust our behavior accordingly. Despite its ubiquity, the neuronal mechanisms underlying the capacity to perceive time remains unclear. Here, in two experiments using ultrahigh-field 7-Tesla (7T) functional magnetic resonance imaging (fMRI), we show that in the medial premotor cortex (supplementary motor area [SMA]) of the human brain, neural units tuned to different durations are orderly mapped in contiguous portions of the cortical surface so as to form chronomaps. The response of each portion in a chronomap is enhanced by neighboring durations and suppressed by nonpreferred durations represented in distant portions of the map. These findings suggest duration-sensitive tuning as a possible neural mechanism underlying the recognition of time and demonstrate, for the first time, that the representation of an abstract feature such as time can be instantiated by a topographical arrangement of duration-sensitive neural populations.

Background Spasmodic dysphonia (SD), or laryngeal dystonia, is a task-specific isolated focal dystonia of unknown causes and pathophysiology. Although functional and structural abnormalities have been described in this disorder, the influence of its different clinical phenotypes and genotypes remains scant, making it difficult to explain SD pathophysiology and to identify potential biomarkers. Methods We used a combination of independent component analysis and linear discriminant analysis of resting-state functional MRI data to investigate brain organization in different SD phenotypes (abductor vs. adductor type) and putative genotypes (familial vs. sporadic cases) and to characterize neural markers for genotype/phenotype categorization. Results We found abnormal functional connectivity within sensorimotor and frontoparietal networks in SD patients compared to healthy individuals as well as phenotype- and genotype-distinct alterations of these networks, involving primary somatosensory, premotor and parietal cortices. The linear discriminant analysis achieved 71% accuracy classifying SD and healthy individuals using connectivity measures in the left inferior parietal and sensorimotor cortex. When categorizing between different forms of SD, the combination of measures from left inferior parietal, premotor and right sensorimotor cortices achieved 81% discriminatory power between familial and sporadic SD cases, whereas the combination of measures from the right superior parietal, primary somatosensory and premotor cortices led to 71% accuracy in the classification of adductor and abductor SD forms. Conclusions Our findings present the first effort to identify and categorize isolated focal dystonia based on its brain functional connectivity profile, which may have a potential impact on the future development of biomarkers for this rare disorder.

ObjectivesTo determine the directionality of regional interactions and influences of one region on another within the functionally abnormal sensorimotor network in isolated focal dystonia.MethodsA total of 40 patients with spasmodic dysphonia with and without dystonic tremor of voice and 35 healthy controls participated in the study. Independent component analysis (ICA) of resting-state fMRI was used to identify 4 abnormally coupled brain regions within the functional sensorimotor network in all patients compared to controls. Follow-up spectral dynamic causal modeling (DCM) estimated regional effective connectivity between patients and controls and between patients with spasmodic dysphonia with and without dystonic tremor of voice to expand the understanding of symptomatologic variability associated with this disorder.ResultsICA found abnormally reduced functional connectivity of the left inferior parietal cortex, putamen, and bilateral premotor cortex in all patients compared to controls, pointing to a largely overlapping pathophysiology of focal dystonia and dystonic tremor. DCM determined that the disruption of the sensorimotor network was both top-down, involving hyperexcitable parieto-putaminal influence, and interhemispheric, involving right-to-left hyperexcitable premotor coupling in all patients compared to controls. These regional alterations were associated with their abnormal self-inhibitory function when comparing patients with spasmodic dysphonia patients with and without dystonic tremor of voice.ConclusionsAbnormal hyperexcitability of premotor-parietal-putaminal circuitry may be explained by altered information transfer between these regions due to underlying deficient connectivity. Identification of brain regions involved in processing of sensorimotor information in preparation for movement execution suggests that complex network disruption is staged well before the dystonic behavior is produced by the primary motor cortex.