Accuracy and precision of navigated transcranial magnetic stimulation

Objective. Transcranial magnetic stimulation (TMS) induces an electric field (E-field) in the cortex. To facilitate stimulation targeting, image-guided neuronavigation systems have been introduced. Such systems track the placement of the coil with respect to the head and visualize the estimated cortical stimulation location on an anatomical brain image in real time. The accuracy and precision of the neuronavigation is affected by multiple factors. Our aim was to analyze how different factors in TMS neuronavigation affect the accuracy and precision of the coil-head coregistration and the estimated E-field. Approach. By performing simulations, we estimated navigation errors due to distortions in magnetic resonance images (MRIs), head-to-MRI registration (landmark- and surface-based registrations), localization and movement of the head tracker, and localization of the coil tracker. We analyzed the effect of these errors on coil and head coregistration and on the induced E-field as determined with simplistic and realistic head models. Main results. Average total coregistration accuracies were in the range of 2.2-3.6 mm and 1 degrees; precision values were about half of the accuracy values. The coregistration errors were mainly due to head-to-MRI registration with average accuracies 1.5-1.9 mm/0.2-0.4 degrees and precisions 0.5-0.8 mm/0.1-0.2 degrees better with surface-based registration. The other major source of error was the movement of the head tracker with average accuracy of 1.5 mm and precision of 1.1 mm. When assessed within an E-field method, the average accuracies of the peak E-field location, orientation, and magnitude ranged between 1.5 and 5.0 mm, 0.9 and 4.8 degrees, and 4.4 and 8.5% across the E-field models studied. The largest errors were obtained with the landmark-based registration. When computing another accuracy measure with the most realistic E-field model as a reference, the accuracies tended to improve from about 10 mm/15 degrees/25% to about 2 mm/2 degrees/5% when increasing realism of the E-field model. Significance. The results of this comprehensive analysis help TMS operators to recognize the main sources of error in TMS navigation and that the coregistration errors and their effect in the E-field estimation depend on the methods applied. To ensure reliable TMS navigation, we recommend surface-based head-to-MRI registration and realistic models for E-field computations.Peer reviewe

Symmetry in Human Evolution, from Biology to Behaviours

Our knowledge of human evolution has made particular progress recently, due to the discovery of new fossils, the use of new methods and multidisciplinary approaches. Moreover, studies on the departure from symmetry, including variations in fluctuating or directional asymmetries, have contributed to the expansion of this knowledge. This Special Issue brings together articles that deal with symmetry and human evolution. The notion of symmetry is addressed, including whether to reconstruct deformed fossil specimens, study biological variations within hominins or compare them with extant primates, address the shape of the brain or seek possible relationships between biological and behavioural data

Unsupervised brain anomaly detection in MR images

Brain disorders are characterized by morphological deformations in shape and size of (sub)cortical structures in one or both hemispheres. These deformations cause deviations from the normal pattern of brain asymmetries, resulting in asymmetric lesions that directly affect the patient’s condition. Unsupervised methods aim to learn a model from unlabeled healthy images, so that an unseen image that breaks priors of this model, i.e., an outlier, is considered an anomaly. Consequently, they are generic in detecting any lesions, e.g., coming from multiple diseases, as long as these notably differ from healthy training images. This thesis addresses the development of solutions to leverage unsupervised machine learning for the detection/analysis of abnormal brain asymmetries related to anomalies in magnetic resonance (MR) images. First, we propose an automatic probabilistic-atlas-based approach for anomalous brain image segmentation. Second, we explore an automatic method for the detection of abnormal hippocampi from abnormal asymmetries based on deep generative networks and a one-class classifier. Third, we present a more generic framework to detect abnormal asymmetries in the entire brain hemispheres. Our approach extracts pairs of symmetric regions — called supervoxels — in both hemispheres of a test image under study. One-class classifiers then analyze the asymmetries present in each pair. Experimental results on 3D MR-T1 images from healthy subjects and patients with a variety of lesions show the effectiveness and robustness of the proposed unsupervised approaches for brain anomaly detection

Validation of plaster endocast morphology through 3D CT image analysis

A crucial component of research on brain evolution has been the comparison of fossil endocranial surfaces with modern human and primate endocrania. The latter have generally been obtained by creating endocasts out of rubber latex shells filled with plaster. The extent to which the method of production introduces errors in endocast replicas is unknown. We demonstrate a powerful method of comparing complex shapes in 3-dimensions (3D) that is broadly applicable to a wide range of paleoanthropological questions. Pairs of virtual endocasts (VEs) created from high-resolution CT scans of corresponding latex/plaster endocasts and their associated crania were rigidly registered (aligned) in 3D space for two Homo sapiens and two Pan troglodytes specimens. Distances between each cranial VE and its corresponding latex/plaster VE were then mapped on a voxel-by-voxel basis. The results show that between 79.7% and 91.0% of the voxels in the four latex/plaster VEs are within 2 mm of their corresponding cranial VEs surfaces. The average error is relatively small, and variation in the pattern of error across the surfaces appears to be generally random overall. However, inferior areas around the cranial base and the temporal poles were somewhat overestimated in both human and chimpanzee specimens, and the area overlaying Broca's area in humans was somewhat underestimated. This study gives an idea of the size of possible error inherent in latex/plaster endocasts, indicating the level of confidence we can have with studies relying on comparisons between them and, e.g., hominid fossil endocasts. Am J Phys Anthropol, 2007. © 2006 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/55857/1/20499_ftp.pd

Quantitative volumetric study of brain in chronic striatolenticular stroke

Perforating branches of the middle cerebral artery, namely the striato-lenticular arteries provide the majority of blood supply for the striatum and posterior limb of the internal capsules. Occlusions of these arteries cause a small stroke but have a devastating effect on patients’ functions. Previous studies showed that the anterior two thirds of the internal capsule is occupied by the prefrontal tracts with the posterior one third by connection to/from sensorimotor, temporal and posterior parietal cortices. In this study, we aimed to examine the long-term effect of infarction in the striato-capsular region on cerebral cortex thickness and also its association with stroke volume and different functional tests. We hypothesized that because of extensive connections of striatum and internal capsule with the cerebral cortex, infarction of this area results in an extensive cortical thickness degeneration which could in turn cause low fictional measurement scores. High resolution T1 weighted MRI was obtained from 21 patients with ischemic stroke in the striatum/posterior limb of the internal capsule region. Subjects were carefully selected from a pool of 140 stroke cases recruited for the Northstar Stroke Project. 63 healthy volunteers (30 male), matched for age and gender were also chosen to form the control group from the OASIS database. Patients and normal subjects were right handed except for 3 patients who have the stroke in the left side of the brain. Patients were defined as left-sided stroke and right-sided stroke depending on the side of the stroke in brain. MRI scans were done 6 months to 2 years after the stroke. To measure cortical thickness, we used Freesurfer software. Vertexwise group comparison was carried out using General Linear Models (GLM). With the Significance level set at 0.05. Population maps of stroke lesions showed that the majority of strokes were located in the striatum and posterior internal capsule. Cortical thickness reduction was greater in the ipsilateral hemisphere. Vertex-wise group comparison between leftsided stroke patients and controls group showed significant reduction in the cortical II thickness in the dorsal and medial prefrontal, premotor, posterior parietal, precuneus, and temporal cortex which survived after correction for multiple comparison using false discovery rate at Freesurfer. Similar comparison for rightsided stroke showed a similar pattern of cortical thinning, however the extent of cortical thinning was much less than in that of the left-sided stroke patients but the ROI analysis showed the main effect of side was significant (f (1, 19) =6.909, p=0.017), which showed that the left hemisphere stroke side group had a thicker cortex (mean=2.463, sd= 0.020) on average compare to the right hemisphere stroke side (mean=2.372, sd= 0.028). Primary motor cortex was surprisingly spared in both stroke groups. In addition, volume of the corpus callosum increased significantly in the stroke group. The differences between motor cortex (M1) thickness in left-hemispheric stroke patients versus controls (t=1.24, n=14, p>0.05) and right-hemispheric stroke patients versus controls (t=-0.511, n=7, p>0.05) were not significant. There was a negative correlation between the volume of the stroke lesions and the affected M1 thickness. There was no correlation between the stroke volume and functional tests in patients and also no correlation between the motor cortex thickness and functional tests in patients. Regarding normal subjects, comparison between two sides of the brain showed that the both hemispheres are symmetrical. In addition, correlation between age and cortical thickness showed a negative significant correlation (1-tailed, p<0.0007, manual correction for multiple comparisons) in M1, superior frontal, lingual cortex at both side of the brain and also negative significant correlation in superior temporal cortex and isthmus cingulated cortex on the left side of brain and supramarginal cortex on the right side of brain but there was no significant difference in cortical thickness between males and females. The finding from this study suggests that the size of the lesion can be a predictor of further M1 cortex reduction. The correlation of M1 thickness with stroke volume showed that secondary cortical degeneration may be mainly depends on the size of neuronal loss in strital-capsular stroke. From normal subject study it can be concluded that generally cortical thickness will decrease with ageing but gender does not have an effect on the cortical thickness. III Furthermore, the lack of behavioural correlation with M1 thickness and stroke volume and also the non significant M1 cortex reduction versus control group may suggest that the long-term functional disability after capsular-striatal stroke may not be entirely dependent on primary motor cortex and secondary motor cortex and primary somatosensory cortex could have an important role as well. These results may help to understand why relatively small subcortical infarcts often cause severe disability that is relatively resistant to recovery in the long term

Normative spatiotemporal fetal brain maturation with satisfactory development at 2 years

Maturation of the human fetal brain should follow precisely scheduled structural growth and folding of the cerebral cortex for optimal postnatal function1 . We present a normative digital atlas of fetal brain maturation based on a prospective international cohort of healthy pregnant women2 , selected using World Health Organization recommendations for growth standards3 . Their fetuses were accurately dated in the first trimester, with satisfactory growth and neurodevelopment from early pregnancy to 2 years of age4,5 . The atlas was produced using 1,059 optimal quality, three dimensional ultrasound brain volumes from 899 of the fetuses and an automated analysis pipeline6–8 . The atlas corresponds structurally to published magnetic resonance images9 , but with finer anatomical details in deep grey matter. The between study site variability represented less than 8.0% of the total variance of all brain measures, supporting pooling data from the eight study sites to produce patterns of normative maturation. We have thereby generated an average representation of each cerebral hemisphere between 14 and 31 weeks’ gestation with quantification of intracranial volume variability and growth patterns. Emergent asymmetries were detectable from as early as 14 weeks, with peak asymmetries in regions associated with language development and functional lateralization between 20 and 26 weeks’ gestation. These patterns were validated in 1,487 three-dimensional brain volumes from 1,295 different fetuses in the same cohort. We provide a unique spatiotemporal benchmark of fetal brain maturation from a large cohort with normative postnatal growth and neurodevelopment

The interindividual variability of multimodal brain connectivity maintains spatial heterogeneity and relates to tissue microstructure

Humans differ from each other in a wide range of biometrics, but to what extent brain connectivity varies between individuals remains largely unknown. By combining diffusion-weighted imaging (DWI) and magnetoencephalography (MEG), this study characterizes the inter-subject variability (ISV) of multimodal brain connectivity. Structural connectivity is characterized by higher ISV in association cortices including the core multiple-demand network and lower ISV in the sensorimotor cortex. MEG ISV exhibits frequency-dependent signatures, and the extent of MEG ISV is consistent with that of structural connectivity ISV in selective macroscopic cortical clusters. Across the cortex, the ISVs of structural connectivity and beta-band MEG functional connectivity are negatively associated with cortical myelin content indexed by the quantitative T1 relaxation rate measured by high-resolution 7 T MRI. Furthermore, MEG ISV from alpha to gamma bands relates to the hindrance and restriction of the white-matter tissue estimated by DWI microstructural models. Our findings depict the inter-relationship between the ISV of brain connectivity from multiple modalities, and highlight the role of tissue microstructure underpinning the ISV

Quantification of cortical folding using MR image data

The cerebral cortex is a thin layer of tissue lining the brain where neural circuits perform important high level functions including sensory perception, motor control and language processing. In the third trimester the fetal cortex folds rapidly from a smooth sheet into a highly convoluted arrangement of gyri and sulci. Premature birth is a high risk factor for poor neurodevelopmental outcome and has been associated with abnormal cortical development, however the nature of the disruption to developmental processes is not fully understood. Recent developments in magnetic resonance imaging have allowed the acquisition of high quality brain images of preterms and also fetuses in-utero. The aim of this thesis is to develop techniques which quantify folding from these images in order to better understand cortical development in these two populations. A framework is presented that quantifies global and regional folding using curvature-based measures. This methodology was applied to fetuses over a wide gestational age range (21.7 to 38.9 weeks) for a large number of subjects (N = 80) extending our understanding of how the cortex folds through this critical developmental period. The changing relationship between the folding measures and gestational age was modelled with a Gompertz function which allowed an accurate prediction of physiological age. A spectral-based method is outlined for constructing a spatio-temporal surface atlas (a sequence of mean cortical surface meshes for weekly intervals). A key advantage of this method is the ability to do group-wise atlasing without bias to the anatomy of an initial reference subject. Mean surface templates were constructed for both fetuses and preterms allowing a preliminary comparison of mean cortical shape over the postmenstrual age range 28-36 weeks. Displacement patterns were revealed which intensified with increasing prematurity, however more work is needed to evaluate the reliability of these findings.Open Acces