Compressed sensing with signal averaging for improved sensitivity and motion artifact reduction in fluorine-19 MRI.

Fluorine-19 (19 F) MRI of injected perfluorocarbon emulsions (PFCs) allows for the non-invasive quantification of inflammation and cell tracking, but suffers from a low signal-to-noise ratio and extended scan time. To address this limitation, we tested the hypotheses that a 19 F MRI pulse sequence that combines a specific undersampling regime with signal averaging has both increased sensitivity and robustness against motion artifacts compared with a non-averaged fully sampled pulse sequence, when both datasets are reconstructed with compressed sensing. As a proof of principle, numerical simulations and phantom experiments were performed on selected variable ranges to characterize the point spread function of undersampling patterns, as well as the vulnerability to noise of undersampling and reconstruction parameters with paired numbers of x signal averages and acceleration factor x (NAx-AFx). The numerical simulations demonstrated that a probability density function that uses 25% of the samples to fully sample the k-space central area allowed for an optimal balance between limited blurring and artifact incoherence. At all investigated noise levels, the Dice similarity coefficient (DSC) strongly depended on the regularization parameters and acceleration factor. In phantoms, the motion robustness of an NA8-AF8 undersampling pattern versus NA1-AF1 was evaluated with simulated and real motion patterns. Differences were assessed with the DSC, which was consistently higher for the NA8-AF8 compared with the NA1-AF1 strategy, for both simulated and real cyclic motion patterns (P < 0.001). Both strategies were validated in vivo in mice (n = 2) injected with perfluoropolyether. Here, the images displayed a sharper delineation of the liver with the NA8-AF8 strategy than with the NA1-AF1 strategy. In conclusion, we validated the hypotheses that in 19 F MRI the combination of undersampling and averaging improves both the sensitivity and the robustness against motion artifacts.

Partial-volume modeling reveals reduced gray matter in specific thalamic nuclei early in the time course of psychosis and chronic schizophrenia.

The structural complexity of the thalamus, due to its mixed composition of gray and white matter, make it challenging to disjoint and quantify each tissue contribution to the thalamic anatomy. This work promotes the use of partial-volume-based over probabilistic-based tissue segmentation approaches to better capture thalamic gray matter differences between patients at different stages of psychosis (early and chronic) and healthy controls. The study was performed on a cohort of 23 patients with schizophrenia, 41 with early psychosis and 69 age and sex-matched healthy subjects. Six tissue segmentation approaches were employed to obtain the gray matter concentration/probability images. The statistical tests were applied at three different anatomical scales: whole thalamus, thalamic subregions and voxel-wise. The results suggest that the partial volume model estimation of gray matter is more sensitive to detect atrophies within the thalamus of patients with psychosis. However all the methods detected gray matter deficit in the pulvinar, particularly in early stages of psychosis. This study demonstrates also that the gray matter decrease varies nonlinearly with age and between nuclei. While a gray matter loss was found in the pulvinar of patients in both stages of psychosis, reduced gray matter in the mediodorsal was only observed in early psychosis subjects. Finally, our analyses point to alterations in a sub-region comprising the lateral posterior and ventral posterior nuclei. The obtained results reinforce the hypothesis that thalamic gray matter assessment is more reliable when the tissues segmentation method takes into account the partial volume effect.

Improved susceptibility-weighted imaging for high contrast and resolution thalamic nuclei mapping at 7T.

PURPOSE: The thalamus is an important brain structure and neurosurgical target, but its constituting nuclei are challenging to image non-invasively. Recently, susceptibility-weighted imaging (SWI) at ultra-high field has shown promising capabilities for thalamic nuclei mapping. In this work, several methodological improvements were explored to enhance SWI quality and contrast, and specifically its ability for thalamic imaging. METHODS: High-resolution SWI was performed at 7T in healthy participants, and the following techniques were applied: (a) monitoring and retrospective correction of head motion and B0 perturbations using integrated MR navigators, (b) segmentation and removal of venous vessels on the SWI data using vessel enhancement filtering, and (c) contrast enhancement by tuning the parameters of the SWI phase-magnitude combination. The resulting improvements were evaluated with quantitative metrics of image quality, and by comparison to anatomo-histological thalamic atlases. RESULTS: Even with sub-millimeter motion and natural breathing, motion and field correction produced clear improvements in both magnitude and phase data quality (76% and 41%, respectively). The improvements were stronger in cases of larger motion/field deviations, mitigating the dependence of image quality on subject performance. Optimizing the SWI phase-magnitude combination yielded substantial improvements in image contrast, particularly in the thalamus, well beyond previously reported SWI results. The atlas comparisons provided compelling evidence of anatomical correspondence between SWI features and several thalamic nuclei, for example, the ventral intermediate nucleus. Vein detection performed favorably inside the thalamus, and vein removal further improved visualization. CONCLUSION: Altogether, the proposed developments substantially improve high-resolution SWI, particularly for thalamic nuclei imaging.

Right Brodmann area 18 predicts tremor arrest after Vim radiosurgery: a voxel-based morphometry study.

INTRODUCTION: Drug-resistant essential tremor (ET) can benefit from open standard stereotactic procedures, such as deep-brain stimulation or radiofrequency thalamotomy. Non-surgical candidates can be offered either high-focused ultrasound (HIFU) or radiosurgery (RS). All procedures aim to target the same thalamic site, the ventro-intermediate nucleus (e.g., Vim). The mechanisms by which tremor stops after Vim RS or HIFU remain unknown. We used voxel-based morphometry (VBM) on pretherapeutic neuroimaging data and assessed which anatomical site would best correlate with tremor arrest 1 year after Vim RS. METHODS: Fifty-two patients (30 male, 22 female; mean age 71.6 years, range 49-82) with right-sided ET benefited from left unilateral Vim RS in Marseille, France. Targeting was performed in a uniform manner, using 130 Gy and a single 4-mm collimator. Neurological (pretherapeutic and 1 year after) and neuroimaging (baseline) assessments were completed. Tremor score on the treated hand (TSTH) at 1 year after Vim RS was included in a statistical parametric mapping analysis of variance (ANOVA) model as a continuous variable with pretherapeutic neuroimaging data. Pretherapeutic gray matter density (GMD) was further correlated with TSTH improvement. No a priori hypothesis was used in the statistical model. RESULTS: The only statistically significant region was right Brodmann area (BA) 18 (visual association area V2, p = 0.05, cluster size Kc = 71). Higher baseline GMD correlated with better TSTH improvement at 1 year after Vim RS (Spearman's rank correlation coefficient = 0.002). CONCLUSIONS: Routine baseline structural neuroimaging predicts TSTH improvement 1 year after Vim RS. The relevant anatomical area is the right visual association cortex (BA 18, V2). The question whether visual areas should be included in the targeting remains open.

Clinical response to Vim's thalamic stereotactic radiosurgery for essential tremor is associated with distinctive functional connectivity patterns.

INTRODUCTION: Essential tremor (ET) is the most common movement disorder. Drug-resistant ET can benefit from standard surgical stereotactic procedures (deep brain stimulation, thalamotomy) or minimally invasive high-intensity focused ultrasound (HIFU) or stereotactic radiosurgical thalamotomy (SRS-T). Resting-state fMRI (rs-fMRI) is a non-invasive imaging method acquired in absence of a task. We examined whether rs-fMRI correlates with tremor score on the treated hand (TSTH) improvement 1 year after SRS-T. METHODS: We included 17 consecutive patients treated with left unilateral SRS-T in Marseille, France. Tremor score evaluation and rs-fMRI were acquired at baseline and 1 year after SRS-T. Resting-state data (34 scans) were analyzed without a priori hypothesis, in Lausanne, Switzerland. Based on degree of improvement in TSTH, to consider SRS-T at least as effective as medication, we separated two groups: 1, ≤ 50% (n = 6, 35.3%); 2, > 50% (n = 11, 64.7%). They did not differ statistically by age (p = 0.86), duration of symptoms (p = 0.41), or lesion volume at 1 year (p = 0.06). RESULTS: We report TSTH improvement correlated with interconnectivity strength between salience network with the left claustrum and putamen, as well as between bilateral motor cortices, frontal eye fields and left cerebellum lobule VI with right visual association area (the former also with lesion volume). Longitudinal changes showed additional associations in interconnectivity strength between right dorsal attention network with ventro-lateral prefrontal cortex and a reminiscent salience network with fusiform gyrus. CONCLUSIONS: Brain connectivity measured by resting-state fMRI relates to clinical response after SRS-T. Relevant networks are visual, motor, and attention. Interconnectivity between visual and motor areas is a novel finding, revealing implication in movement sensory guidance.

Assessing the clinical outcome of Vim radiosurgery with voxel-based morphometry: visual areas are linked with tremor arrest!

INTRODUCTION: Radiosurgery (RS) is an alternative to open standard stereotactic procedures (deep-brain stimulation or radiofrequency thalamotomy) for drug-resistant essential tremor (ET), aiming at the same target (ventro-intermediate nucleus, Vim). We investigated the Vim RS outcome using voxel-based morphometry by evaluating the interaction between clinical response and time. METHODS: Thirty-eight patients with right-sided ET benefited from left unilateral Vim RS. Targeting was performed using 130 Gy and a single 4-mm collimator. Neurological and neuroimaging assessment was completed at baseline and 1 year. Clinical responders were considered those with at least 50% improvement in tremor score on the treated hand (TSTH). RESULTS: Interaction between clinical response and time showed the left temporal pole and occipital cortex (Brodmann area 19, including V4, V5 and the parahippocampal place area) as statistically significant. A decrease in gray matter density (GMD) 1 year after Vim RS correlated with higher TSTH improvement (Spearman = 0.01) for both anatomical areas. Higher baseline GMD within the left temporal pole correlated with better TSTH improvement (Spearman = 0.004). CONCLUSIONS: Statistically significant structural changes in the relationship to clinical response after Vim RS are present in remote areas, advocating a distant neurobiological effect. The former regions are mainly involved in locomotor monitoring toward the local and distant environment, suggesting the recruiting requirement in targeting of the specific visuomotor networks.

Detecting stress caused by nitrogen deficit using deep learning techniques applied on plant electrophysiological data.

Plant electrophysiology carries a strong potential for assessing the health of a plant. Current literature for the classification of plant electrophysiology generally comprises classical methods based on signal features that portray a simplification of the raw data and introduce a high computational cost. The Deep Learning (DL) techniques automatically learn the classification targets from the input data, overcoming the need for precalculated features. However, they are scarcely explored for identifying plant stress on electrophysiological recordings. This study applies DL techniques to the raw electrophysiological data from 16 tomato plants growing in typical production conditions to detect the presence of stress caused by a nitrogen deficiency. The proposed approach predicts the stressed state with an accuracy of around 88%, which could be increased to over 96% using a combination of the obtained prediction confidences. It outperforms the current state-of-the-art with over 8% higher accuracy and a potential for a direct application in production conditions. Moreover, the proposed approach demonstrates the ability to detect the presence of stress at its early stage. Overall, the presented findings suggest new means to automatize and improve agricultural practices with the aim of sustainability.

A multi-scale probabilistic atlas of the human connectome.

The human brain is a complex system that can be efficiently represented as a network of structural connectivity. Many imaging studies would benefit from such network information, which is not always available. In this work, we present a whole-brain multi-scale structural connectome atlas. This tool has been derived from a cohort of 66 healthy subjects imaged with optimal technology in the setting of the Human Connectome Project. From these data we created, using extensively validated diffusion-data processing, tractography and gray-matter parcellation tools, a multi-scale probabilistic atlas of the human connectome. In addition, we provide user-friendly and accessible code to match this atlas to individual brain imaging data to extract connection-specific quantitative information. This can be used to associate individual imaging findings, such as focal white-matter lesions or regional alterations, to specific connections and brain circuits. Accordingly, network-level consequences of regional changes can be analyzed even in absence of diffusion and tractography data. This method is expected to broaden the accessibility and lower the yield for connectome research.

Electrophysiological assessment of plant status outside a Faraday cage using supervised machine learning.

Living organisms have evolved complex signaling networks to drive appropriate physiological processes in response to changing environmental conditions. Amongst them, electric signals are a universal method to rapidly transmit information. In animals, bioelectrical activity measurements in the heart or the brain provide information about health status. In plants, practical measurements of bioelectrical activity are in their infancy and transposition of technology used in human medicine could therefore, by analogy provide insight about the physiological status of plants. This paper reports on the development and testing of an innovative electrophysiological sensor that can be used in greenhouse production conditions, without a Faraday cage, enabling real-time electric signal measurements. The bioelectrical activity is modified in response to water stress conditions or to nycthemeral rhythm. Furthermore, the automatic classification of plant status using supervised machine learning allows detection of these physiological modifications. This sensor represents an efficient alternative agronomic tool at the service of producers for decision support or for taking preventive measures before initial visual symptoms of plant stress appear.

Comparison of MRI-based automated segmentation methods and functional neurosurgery targeting with direct visualization of the Ventro-intermediate thalamic nucleus at 7T.

The ventro-intermediate nucleus (Vim), as part of the motor thalamic nuclei, is a commonly used target in functional stereotactic neurosurgery for treatment of drug-resistant tremor. As it cannot be directly visualized on routinely used magnetic resonance imaging (MRI), its clinical targeting is performed using indirect methods. Recent literature suggests that the Vim can be directly visualized on susceptibility-weighted imaging (SWI) acquired at 7 T. Our work aims to assess the distinguishable Vim on 7 T SWI in both healthy-population and patients and, using it as a reference, to compare it with: (1) The clinical targeting, (2) The automated parcellation of thalamic subparts based on 3 T diffusion MRI (dMRI), and (3) The multi-atlas segmentation techniques. In 95.2% of the data, the manual outline was adjacent to the inferior lateral border of the dMRI-based motor-nuclei group, while in 77.8% of the involved cases, its ventral part enclosed the Guiot points. Moreover, the late MRI signature in the patients was always observed in the anterior part of the manual delineation and it overlapped with the multi-atlas outline. Overall, our study provides new insight on Vim discrimination through MRI and imply novel strategies for its automated segmentation, thereby opening new perspectives for standardizing the clinical targeting.

Normalization of aberrant pretherapeutic dynamic functional connectivity of extrastriate visual system in patients who underwent thalamotomy with stereotactic radiosurgery for essential tremor: a resting-state functional MRI study.

OBJECTIVE: The tremor circuitry has commonly been hypothesized to be driven by one or multiple pacemakers within the cerebello-thalamo-cortical pathway, including the cerebellum, contralateral motor thalamus, and primary motor cortex. However, previous studies, using multiple methodologies, have advocated that tremor could be influenced by changes within the right extrastriate cortex, at both the structural and functional level. The purpose of this work was to evaluate the role of the extrastriate cortex in tremor generation and further arrest after left unilateral stereotactic radiosurgery thalamotomy (SRS-T). METHODS: The authors considered 12 healthy controls (HCs, group 1); 15 patients with essential tremor (ET, right-sided, drug-resistant; group 2) before left unilateral SRS-T; and the same 15 patients (group 3) 1 year after the intervention, to account for delayed effects. Blood oxygenation level-dependent functional MRI during resting state was used to characterize the dynamic interactions of the right extrastriate cortex, comparing HC subjects against patients with ET before and 1 year after SRS-T. In particular, the authors applied coactivation pattern analysis to extract recurring whole-brain spatial patterns of brain activity over time. RESULTS: The authors found 3 different sets of coactivating regions within the right extrastriate cortex in HCs and patients with pretherapeutic ET, reminiscent of the "cerebello-visuo-motor," "thalamo-visuo-motor" (including the targeted thalamus), and "basal ganglia and extrastriate" networks. The occurrence of the first pattern was decreased in pretherapeutic ET compared to HCs, whereas the other two patterns showed increased occurrences. This suggests a misbalance between the more prominent cerebellar circuitry and the thalamo-visuo-motor and basal ganglia networks. Multiple regression analysis showed that pretherapeutic standard tremor scores negatively correlated with the increased occurrence of the thalamo-visuo-motor network, suggesting a compensatory pathophysiological trait. Clinical improvement after SRS-T was related to changes in occurrences of the basal ganglia and extrastriate cortex circuitry, which returned to HC values after the intervention, suggesting that the dynamics of the extrastriate cortex had a role in tremor generation and further arrest after the intervention. CONCLUSIONS: The data in this study point to a broader implication of the visual system in tremor generation, and not only through visual feedback, given its connections to the dorsal visual stream pathway and the cerebello-thalamo-cortical circuitry, with which its dynamic balance seems to be a crucial feature for reduced tremor. Furthermore, SRS-T seems to bring abnormal pretherapeutic connectivity of the extrastriate cortex to levels comparable to those of HC subjects.

In-vivo probabilistic atlas of human thalamic nuclei based on diffusion- weighted magnetic resonance imaging.

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.

Pretherapeutic resting-state fMRI profiles are associated with MR signature volumes after stereotactic radiosurgical thalamotomy for essential tremor.

OBJECTIVEEssential tremor (ET) is the most common movement disorder. Drug-resistant ET can benefit from standard stereotactic deep brain stimulation or radiofrequency thalamotomy or, alternatively, minimally invasive techniques, including stereotactic radiosurgery (SRS) and high-intensity focused ultrasound, at the level of the ventral intermediate nucleus (Vim). The aim of the present study was to evaluate potential correlations between pretherapeutic interconnectivity (IC), as depicted on resting-state functional MRI (rs-fMRI), and MR signature volume at 1 year after Vim SRS for tremor, to be able to potentially identify hypo- and hyperresponders based only on pretherapeutic neuroimaging data.METHODSSeventeen consecutive patients with ET were included, who benefitted from left unilateral SRS thalamotomy (SRS-T) between September 2014 and August 2015. Standard tremor assessment and rs-fMRI were acquired pretherapeutically and 1 year after SRS-T. A healthy control group was also included (n = 12). Group-level independent component analysis (ICA; only n = 17 for pretherapeutic rs-fMRI) was applied. The mean MR signature volume was 0.125 ml (median 0.063 ml, range 0.002-0.600 ml). The authors correlated baseline IC with 1-year MR signatures within all networks. A 2-sample t-test at the level of each component was first performed in two groups: group 1 (n = 8, volume < 0.063 ml) and group 2 (n = 9, volume ≥ 0.063 ml). These groups did not statistically differ by age, duration of symptoms, baseline ADL score, ADL point decrease at 1 year, time to tremor arrest, or baseline tremor score on the treated hand (TSTH; p > 0.05). An ANOVA was then performed on each component, using individual subject-level maps and continuous values of 1-year MR signatures, correlated with pretherapeutic IC.RESULTSUsing 2-sample t-tests, two networks were found to be statistically significant: network 3, including the brainstem, motor cerebellum, bilateral thalamus, and left supplementary motor area (SMA) (pFWE = 0.004, cluster size = 94), interconnected with the red nucleus (MNI -2, -22, -32); and network 9, including the brainstem, posterior insula, bilateral thalamus, and left SMA (pFWE = 0.002, cluster size = 106), interconnected with the left SMA (MNI 24, -28, 44). Higher pretherapeutic IC was associated with higher MR volumes, in a network including the anterior default-mode network and bilateral thalamus (ANOVA, pFWE = 0.004, cluster size = 73), interconnected with cerebellar lobule V (MNI -12, -70, -22). Moreover, in the same network, radiological hyporesponders presented with negative IC values.CONCLUSIONSThese findings have clinical implications for predicting MR signature volumes after SRS-T. Here, using pretherapeutic MRI and data processing without prior hypothesis, the authors showed that pretherapeutic network interconnectivity strength predicts 1-year MR signature volumes following SRS-T.

Pretherapeutic Motor Thalamus Resting-State Functional Connectivity with Visual Areas Predicts Tremor Arrest After Thalamotomy for Essential Tremor: Tracing the Cerebello-thalamo-visuo-motor Network.

BACKGROUND: Essential tremor (ET) is a common movement disorder. Resting-state functional magnetic resonance imaging is a noninvasive neuroimaging method acquired in absence of task. OBJECTIVE: Our study aimed to correlate pretherapeutic ventrolateral thalamus functional connectivity (FC) with clinical results 1 year after stereotactic radiosurgical thalamotomy (SRS-T) for drug-resistant ET. Data from 12 healthy control individuals were additionally included. METHODS: Resting state was acquired for 17 consecutive (right-handed) patients, before and 1 year after left unilateral SRS-T. Standard tremor scores were evaluated pretherapeutically and 1 year after SRS-T. Tremor network was investigated using region of interest, left ventrolateral ventral (VLV) cluster, obtained from pretherapeutic diffusion magnetic resonance imaging. Seed-based FC was obtained as correlations between the time courses of the VLV and that of every other voxel. The seed-connectivity maps were obtained pretherapeutically and correlated across all patients with clinical outcome 1 year after SRS-T. One-year magnetic resonance signature volume was always located inside VLV and did not correlate with reported seed-FC measures (P > 0.05). RESULTS: We report statistically significant correlations between pretherapeutic VLV FC with clinical outcome for 1) right visual association area (Brodmann area, BA19) predicting 1 year activities of daily living decrease (Punc = 0.02); 2) left fusiform gyrus (BA37) predicting 1 year head tremor score improvement (Punc = 0.04); and 3) posterior cingulate (left BA23, Puncor = 0.009), lateral temporal cortex (right BA21, Punc = 0.02) predicting time to tremor arrest. CONCLUSIONS: Our results suggest that pretherapeutic resting-state seed-FC of left VLV predicts tremor arrest after SRS-T for ET. Visual areas are identified as the main regions in this correlation.

Ventrolateral Motor Thalamus Abnormal Connectivity in Essential Tremor Before and After Thalamotomy: A Resting-State Functional Magnetic Resonance Imaging Study.

OBJECTIVE: To evaluate functional connectivity (FC) of the ventrolateral thalamus, a common target for drug-resistant essential tremor (ET), resting-state data were analyzed before and 1 year after stereotactic radiosurgical thalamotomy and compared against healthy controls (HCs). METHODS: In total, 17 consecutive patients with ET and 10 HCs were enrolled. Tremor network was investigated using the ventrolateral ventral (VLV) thalamic nucleus as the region of interest, extracted with automated segmentation from pretherapeutic diffusion magnetic resonance imaging. Temporal correlations of VLV at whole brain level were evaluated by comparing drug-naïve patients with ET with HCs, and longitudinally, 1 year after stereotactic radiosurgical thalamotomy. 1 year thalamotomy MR signature was always located inside VLV and did not correlate with any of FC measures (P > 0.05). This suggested presence of longitudinal changes in VLV FC independently of the MR signature volume. RESULTS: Pretherapeutic ET displayed altered VLV FC with left primary sensory-motor cortex, pedunculopontine nucleus, dorsal anterior cingulate, left visual association, and left superior parietal areas. Pretherapeutic negative FC with primary somatosensory cortex and pedunculopontine nucleus correlated with poorer baseline tremor scores (Spearman = 0.04 and 0.01). Longitudinal study displayed changes within right dorsal attention (frontal eye-fields and posterior parietal) and salience (anterior insula) networks, as well as areas involved in hand movement planning or language production. CONCLUSIONS: Our results demonstrated that patients with ET and HCs differ in their left VLV FC to primary somatosensory and supplementary motor, visual association, or brainstem areas (pedunculopontine nucleus). Longitudinal changes display reorganization of dorsal attention and salience networks after thalamotomy. Beside attentional gateway, they are also known for their major role in facilitating a rapid access to the motor system.

Pretherapeutic Functional Imaging Allows Prediction of Head Tremor Arrest After Thalamotomy for Essential Tremor: The Role of Altered Interconnectivity Between Thalamolimbic and Supplementary Motor Circuits.

OBJECTIVE: To correlate pretherapeutic resting-state functional magnetic resonance imaging (rs-fMRI) measures with pretherapeutic head tremor presence and/or further improvement 1 year after stereotactic radiosurgical thalamotomy (SRS-T) for essential tremor (ET). METHODS: We prospectively collected head tremor scores (range, 0-3) and rs-fMRI data for a cohort of 17 consecutive ET patients in pretherapeutic and 1 year after SRS-T states. We additionally acquired rs-fMRI data for a healthy control (HC) group (n = 12). Group-level independent component analysis (n = 17 for pretherapeutic rs-fMRI) was applied to decompose neuroimaging data into 20 large-scale brain networks using a standard approach. Through spatial regression, we projected 1 year after SRS-T and HC rs-fMRI time points, on the same 20 brain networks. RESULTS: Pretherapeutic interconnectivity (IC) strength between the network including bilateral thalamus and limbic system with left supplementary motor area predicted head tremor improvement at 1 year after SRS-T (family-wise corrected P < 0.001, cluster size Kc = 146). For the statistically significant cluster, IC strength was strongest in HCs (mean, 4.6; median, 3.8) compared with pre- (mean, 0.1; median, 0.2) or posttherapeutic (mean, -0.2; median, 0.09) states. CONCLUSIONS: Baseline measures of IC between bilateral thalamus and limbic system with left supplementary motor area may predict head tremor arrest after thalamotomy. However, procedures such as SRS-T, for this particular clinical feature, do not align patients to HCs in terms of functional brain connectivity. We postulate that supplementary motor area is modulating head tremor appearance, by abnormal connectivity with the thalamolimbic system.

Robust thalamic nuclei segmentation method based on local diffusion magnetic resonance properties.

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.