Robust Machine Learning-Based Correction on Automatic Segmentation of the Cerebellum and Brainstem.

Automated segmentation is a useful method for studying large brain structures such as the cerebellum and brainstem. However, automated segmentation may lead to inaccuracy and/or undesirable boundary. The goal of the present study was to investigate whether SegAdapter, a machine learning-based method, is useful for automatically correcting large segmentation errors and disagreement in anatomical definition. We further assessed the robustness of the method in handling size of training set, differences in head coil usage, and amount of brain atrophy. High resolution T1-weighted images were acquired from 30 healthy controls scanned with either an 8-channel or 32-channel head coil. Ten patients, who suffered from brain atrophy because of fragile X-associated tremor/ataxia syndrome, were scanned using the 32-channel head coil. The initial segmentations of the cerebellum and brainstem were generated automatically using Freesurfer. Subsequently, Freesurfer's segmentations were both manually corrected to serve as the gold standard and automatically corrected by SegAdapter. Using only 5 scans in the training set, spatial overlap with manual segmentation in Dice coefficient improved significantly from 0.956 (for Freesurfer segmentation) to 0.978 (for SegAdapter-corrected segmentation) for the cerebellum and from 0.821 to 0.954 for the brainstem. Reducing the training set size to 2 scans only decreased the Dice coefficient ≤0.002 for the cerebellum and ≤ 0.005 for the brainstem compared to the use of training set size of 5 scans in corrective learning. The method was also robust in handling differences between the training set and the test set in head coil usage and the amount of brain atrophy, which reduced spatial overlap only by <0.01. These results suggest that the combination of automated segmentation and corrective learning provides a valuable method for accurate and efficient segmentation of the cerebellum and brainstem, particularly in large-scale neuroimaging studies, and potentially for segmenting other neural regions as well

Dentate nucleus connectivity in adult patients with multiple sclerosis: functional changes at rest and correlation with clinical features

Background and objective: The dentate nucleus, which is the largest of the cerebellar nuclei, plays a critical role in movement and cognition. The aim of our study was to assess any changes in dentate functional connectivity (FC) in adult relapsing remitting multiple sclerosis (RR-MS) patients and to investigate possible clinical correlates. Materials and methods: In all, 54 patients and 24 healthy subjects (HS) underwent multimodal magnetic resonance imaging (MRI), including diffusion tensor imaging (DTI), three-dimensional-T1-weighted and resting state (RS) functional images; they also underwent a cognitive evaluation, that is, attention and information processing speed, by means of the Paced Auditory Serial Addition Test (PASAT). Patients were also scored according to Expanded Disability Status Scale (EDSS). RS-MRI data were analysed using FMRIB Software Library (FSL) tools, with the seed-based method to identify dentate FC. Results: When compared with HS, patients exhibited brain atrophy and widespread DTI abnormalities, as well as greater FC between the dentate nucleus and cortical areas, particularly in the frontal and parietal lobes. Within these areas, FC in patients correlated inversely with clinical impairment. Finally, FC correlated inversely with lesion load and microstructural brain damage. Conclusion: Our findings indicate that dentate FC at rest is altered in MS patients. Whether these functional changes are induced by the disease and play a compensatory role remains to be established

Dissociable neuroanatomical correlates of subsecond and suprasecond time perception

The ability to estimate durations varies across individuals. Although previous studies have reported that individual differences in perceptual skills and cognitive capacities are reflected in brain structures, it remains unknown whether timing abilities are also reflected in the brain anatomy. Here, we show that individual differences in the ability to estimate subsecond and suprasecond durations correlate with gray matter (GM) volume in different parts of cortical and subcortical areas. Better ability to discriminate subsecond durations was associated with a larger GM volume in the bilateral anterior cerebellum, whereas better performance in estimating the suprasecond range was associated with a smaller GM volume in the inferior parietal lobule. These results indicate that regional GM volume is predictive of an individual's timing abilities. These morphological results support the notion that subsecond durations are processed in the motor system, whereas suprasecond durations are processed in the parietal cortex by utilizing the capacity of attention and working memory to keep track of time

Development of a tool for automatic segmentation of the cerebellum in MR images of children

The human cerebellar cortex is a highly foliated structure that supports both motor and complex cognitive functions in humans. Magnetic Resonance Imaging (MRI) is commonly used to explore structural alterations in patients with psychiatric and neurological diseases. The ability to detect regional structural differences in cerebellar lobules may provide valuable insights into disease biology, progression and response to treatment, but has been hampered by the lack of appropriate tools for performing automated structural cerebellar segmentation and morphometry. In this thesis, time intensive manual tracings by an expert neuroanatomist of 16 cerebellar regions on high-resolution T1-weighted MR images of 18 children aged 9-13 years were used to generate the Cape Town Pediatric Cerebellar Atlas (CAPCA18) in the age-appropriate National Institute of Health Pediatric Database (NIHPD) asymmetric template space. An automated pipeline was developed to process the MR images and generate lobule-wise segmentations, as well as a measure of the uncertainty of the label assignments. Validation in an independent group of children with ages similar to those of the children used in the construction of the atlas, yielded spatial overlaps with manual segmentations greater than 70% in all lobules, except lobules VIIb and X. Average spatial overlap of the whole cerebellar cortex was 86%, compared to 78% using the alternative Spatially Unbiased Infra-tentorial Template (SUIT), which was developed using adult images

Predicting Fluid Intelligence of Children using T1-weighted MR Images and a StackNet

In this work, we utilize T1-weighted MR images and StackNet to predict fluid intelligence in adolescents. Our framework includes feature extraction, feature normalization, feature denoising, feature selection, training a StackNet, and predicting fluid intelligence. The extracted feature is the distribution of different brain tissues in different brain parcellation regions. The proposed StackNet consists of three layers and 11 models. Each layer uses the predictions from all previous layers including the input layer. The proposed StackNet is tested on a public benchmark Adolescent Brain Cognitive Development Neurocognitive Prediction Challenge 2019 and achieves a mean squared error of 82.42 on the combined training and validation set with 10-fold cross-validation. In addition, the proposed StackNet also achieves a mean squared error of 94.25 on the testing data. The source code is available on GitHub.Comment: 8 pages, 2 figures, 3 tables, Accepted by MICCAI ABCD-NP Challenge 2019; Added ND

Cerebellar Integrity in the Amyotrophic Lateral Sclerosis - Frontotemporal Dementia Continuum

Amyotrophic lateral sclerosis (ALS) and behavioural variant frontotemporal dementia (bvFTD) are multisystem neurodegenerative disorders that manifest overlapping cognitive, neuropsychiatric and motor features. The cerebellum has long been known to be crucial for intact motor function although emerging evidence over the past decade has attributed cognitive and neuropsychiatric processes to this structure. The current study set out i) to establish the integrity of cerebellar subregions in the amyotrophic lateral sclerosis-behavioural variant frontotemporal dementia spectrum (ALS-bvFTD) and ii) determine whether specific cerebellar atrophy regions are associated with cognitive, neuropsychiatric and motor symptoms in the patients. Seventy-eight patients diagnosed with ALS, ALS-bvFTD, behavioural variant frontotemporal dementia (bvFTD), most without C9ORF72 gene abnormalities, and healthy controls were investigated. Participants underwent cognitive, neuropsychiatric and functional evaluation as well as structural imaging using voxel-based morphometry (VBM) to examine the grey matter subregions of the cerebellar lobules, vermis and crus. VBM analyses revealed: i) significant grey matter atrophy in the cerebellum across the whole ALS-bvFTD continuum; ii) atrophy predominantly of the superior cerebellum and crus in bvFTD patients, atrophy of the inferior cerebellum and vermis in ALS patients, while ALS-bvFTD patients had both patterns of atrophy. Post-hoc covariance analyses revealed that cognitive and neuropsychiatric symptoms were particularly associated with atrophy of the crus and superior lobule, while motor symptoms were more associated with atrophy of the inferior lobules. Taken together, these findings indicate an important role of the cerebellum in the ALS-bvFTD disease spectrum, with all three clinical phenotypes demonstrating specific patterns of subregional atrophy that associated with different symptomology

Eye muscle proprioception is represented bilaterally in the sensorimotor cortex

The cortical representation of eye position is still uncertain. In the monkey a proprioceptive representation of the extraocular muscles (EOM) of an eye were recently found within the contralateral central sulcus. In humans, we have previously shown a change in the perceived position of the right eye after a virtual lesion with rTMS over the left somatosensory area. However, it is possible that the proprioceptive representation of the EOM extends to other brain sites, which were not examined in these previous studies. The aim of this fMRI study was to sample the whole brain to identify the proprioceptive representation for the left and the right eye separately. Data were acquired while passive eye movement was used to stimulate EOM proprioceptors in the absence of a motor command. We also controlled for the tactile stimulation of the eyelid by removing from the analysis voxels activated by eyelid touch alone. For either eye, the brain area commonly activated by passive and active eye movement was located bilaterally in the somatosensory area extending into the motor and premotor cytoarchitectonic areas. We suggest this is where EOM proprioception is processed. The bilateral representation for either eye contrasts with the contralateral representation of hand proprioception. We suggest that the proprioceptive representation of the two eyes next to each other in either somatosensory cortex and extending into the premotor cortex reflects the integrative nature of the eye position sense, which combines proprioceptive information across the two eyes with the efference copy of the oculomotor comman