OBJECTIVE: This review aims to rediscuss the leading theories concerning the role of basal ganglia and the thalamus in the genesis of aphasic symptoms in the absence of gross anatomical lesions in cortical language areas as assessed by conventional neuroimaging studies.
RESULTS: New concepts in language processing and modern neuroimaging techniques have enabled some progress in resolving the impasse between the current dominant theories: (a) direct and specific linguistic processing and (b) subcortical structures as processing relays in domain-general functions. Of particular interest are studies of connectivity based on functional magnetic resonance imaging (MRI) and tractography that highlight the impact of white matter pathway lesions on aphasia development and recovery. Connectivity studies have put into evidence the central role of the arcuate fasciculus (AF), inferior frontal occipital fasciculus (IFOF), and uncinate fasciculus (UF) in the genesis of aphasia. Regarding the thalamus, its involvement in lexical-semantic processing through modulation of the frontal cortex is becoming increasingly apparent.

OBJECTIVE: Sacral chordomas are slow growing but locally aggressive tumours with a high rate of local recurrence if not completely removed. Surgical resection with negative margins represents the most important survival predictor but it can be challenging to accomplish. Thanks to improvements in intraoperative imaging and surgical techniques, en bloc resection through a partial sacral resection with wide surgical margins has become feasible but it comes with a significant morbidity rate. In this technical note we detail the virtual reality-assisted surgical planning used during resection.
METHODS: A 70-year-old patient underwent en bloc resection of the tumor by an antero-posterior two-stage surgery approach. Pre-operatively, based on MR- and CT-imaging, virtual objects were designed, representing the tumour, the surrounding bone and the neurovascular structures. This 3D-model was used to plan the well delimited partial sacral resection and the posterior surgical approach. Intraoperatively the instruments were registered, allowing for a real-time visualization of the tumor, of the neurovascular structures, and for an optimal margin control resection.
RESULTS: Postoperatively the patient was intact in the lower extremities, without any deficit up to S1 roots. An intentional middle-low sacral amputation of S2-S5 roots was necessary to have a wide resection with free margins. At follow-up, the patient did not present any lower extremities motor deficit with an improvement of sensory function on S1 dermatome.
CONCLUSIONS: Three-dimensional virtual reality-assisted surgical planning for neuronavigated sacrectomy in chordoma is useful, feasible and safe. This technology can increase surgeon\'s chances to perform a larger margin-free resection decreasing the risk of neurovascular damage.

This pilot study aimed to investigate the interest of high angular resolution diffusion imaging (HARDI) and tractography of the spinal cord (SC) in the management of patients with intramedullary tumors by providing predictive elements for tumor resection. Eight patients were included in a prospective study. HARDI images of the SC were acquired using a 3T MRI scanner with a reduced field of view. Opposed phase-encoding directions allowed distortion corrections. SC fiber tracking was performed using a deterministic approach, with extraction of tensor metrics. Then, regions of interest were drawn to track the spinal pathways of interest. HARDI and tractography added value by providing characteristics about the microstructural organization of the spinal white fibers. In patients with SC tumors, tensor metrics demonstrated significant changes in microstructural architecture, axonal density, and myelinated fibers (all, p < 0.0001) of the spinal white matter. Tractography aided in the differentiation of tumor histological types (SC-invaded vs. pushed back by the tumor), and differentiation of the spinal tracts enabled the determination of precise anatomical relationships between the tumor and the SC, defining the tumor resectability. This study underlines the value of using HARDI and tractography in patients with intramedullary tumors, to show alterations in SC microarchitecture and to differentiate spinal tracts to establish predictive factors for tumor resectability.

Parcellation of human cerebellar pathways is essential for advancing our understanding of the human brain. Existing diffusion magnetic resonance imaging tractography parcellation methods have been successful in defining major cerebellar fibre tracts, while relying solely on fibre tract structure. However, each fibre tract may relay information related to multiple cognitive and motor functions of the cerebellum. Hence, it may be beneficial for parcellation to consider the potential importance of the fibre tracts for individual motor and cognitive functional performance measures. In this work, we propose a multimodal data-driven method for cerebellar pathway parcellation, which incorporates both measures of microstructure and connectivity, and measures of individual functional performance. Our method involves first training a multitask deep network to predict various cognitive and motor measures from a set of fibre tract structural features. The importance of each structural feature for predicting each functional measure is then computed, resulting in a set of structure-function saliency values that are clustered to parcellate cerebellar pathways. We refer to our method as Deep Multimodal Saliency Parcellation (DeepMSP), as it computes the saliency of structural measures for predicting cognitive and motor functional performance, with these saliencies being applied to the task of parcellation. Applying DeepMSP to a large-scale dataset from the Human Connectome Project Young Adult study (n = 1065), we found that it was feasible to identify multiple cerebellar pathway parcels with unique structure-function saliency patterns that were stable across training folds. We thoroughly experimented with all stages of the DeepMSP pipeline, including network selection, structure-function saliency representation, clustering algorithm, and cluster count. We found that a 1D convolutional neural network architecture and a transformer network architecture both performed comparably for the multitask prediction of endurance, strength, reading decoding, and vocabulary comprehension, with both architectures outperforming a fully connected network architecture. Quantitative experiments demonstrated that a proposed low-dimensional saliency representation with an explicit measure of motor versus cognitive category bias achieved the best parcellation results, while a parcel count of four was most successful according to standard cluster quality metrics. Our results suggested that motor and cognitive saliencies are distributed across the cerebellar white matter pathways. Inspection of the final k = 4 parcellation revealed that the highest-saliency parcel was most salient for the prediction of both motor and cognitive performance scores and included parts of the middle and superior cerebellar peduncles. Our proposed saliency-based parcellation framework, DeepMSP, enables multimodal, data-driven tractography parcellation. Through utilising both structural features and functional performance measures, this parcellation strategy may have the potential to enhance the study of structure-function relationships of the cerebellar pathways.

Neurobiological models of receptive language have focused on the left-hemisphere perisylvian cortex with the assumption that the cerebellum supports peri-linguistic cognitive processes such as verbal working memory. The goal of this study was to identify language-sensitive regions of the cerebellum then map the structural connectivity profile of these regions. Functional imaging data and diffusion-weighted imaging data from the Human Connectome Project (HCP) were analyzed. We found that (a) working memory, motor activity, and language comprehension activated partially overlapping but mostly unique subregions of the cerebellum; (b) the linguistic portion of the cerebello-thalamo-cortical circuit was more extensive than the linguistic portion of the cortico-ponto-cerebellar tract; (c) there was a frontal-lobe bias in the connectivity from the cerebellum to the cerebrum; (d) there was some degree of specificity; and (e) for some cerebellar tracts, individual differences in picture identification ability covaried with fractional anisotropy metrics. These findings yield insights into the structural connectivity of the cerebellum as relates to the uniquely human process of language comprehension.

Children with developmental language disorder (DLD) struggle to learn their native language for no apparent reason. While research on the neurobiological underpinnings of the disorder has focused on the role of corticostriatal systems, little is known about the role of the cerebellum in DLD. Corticocerebellar circuits might be involved in the disorder as they contribute to complex sensorimotor skill learning, including the acquisition of spoken language. Here, we used diffusion-weighted imaging data from 77 typically developing and 54 children with DLD and performed probabilistic tractography to identify the cerebellum\'s white matter tracts: the inferior, middle, and superior cerebellar peduncles. Children with DLD showed lower fractional anisotropy (FA) in the inferior cerebellar peduncles (ICP), fiber tracts that carry motor and sensory input via the inferior olive to the cerebellum. Lower FA in DLD was driven by lower axial diffusivity. Probing this further with more sophisticated modeling of diffusion data, we found higher orientation dispersion but no difference in neurite density in the ICP of children with DLD. Reduced FA is therefore unlikely to be reflecting microstructural differences in myelination, rather the organization of axons in these pathways is disrupted. ICP microstructure was not associated with language or motor coordination performance in our sample. We also found no differences in the middle and superior peduncles, the main pathways connecting the cerebellum with the cortex. To conclude, it is not corticocerebellar but atypical olivocerebellar white matter connections that characterize DLD and suggest the involvement of the olivocerebellar system in speech and language acquisition and development.

BACKGROUND: Diffusion tensor imaging (DTI) can characterize eloquent white matter tracts affected by brain arteriovenous malformations (AVMs). However, DTI interpretation can be difficult in ruptured cases due to the presence of blood products. The authors present the case of a ruptured pediatric AVM in the corticospinal tract (CST) and discuss how DTI at different time points informed the treatment.
METHODS: A 9-year-old female presented with a sudden headache and left hemiparesis. She was found to have a Spetzler-Martin grade III, Supplementary grade I AVM in the right caudate and centrum semiovale, with obliteration and corresponding reduced fractional anisotropy (FA), fiber density (FD), and tract count (TC) of the adjacent CST on DTI. The patient remained stable and was scheduled for elective resection following a 6-week period to facilitate hematoma resorption. After 6 weeks, repeat DTI showed part of the nidus within intact CST fibers with concordant improvement in FA, FD, and TC. Considering the nidus location, CST integrity, and motor function recovery, surgery was deferred in favor of stereotactic radiosurgery.
CONCLUSIONS: In ruptured AVMs, DTI may initially create an incomplete picture and false assumptions about white matter tract integrity. DTI should be repeated if delayed treatment is appropriate to ensure informed decision-making and prevent avoidable permanent neurological deficits. https://thejns.org/doi/10.3171/CASE24225.

UNASSIGNED: Operculo-insular epilepsy (OIE) is a rare condition amenable to surgery in well-selected cases. Despite the high rate of neurological complications associated with OIE surgery, most postoperative deficits recover fully and rapidly. We provide insights into this peculiar pattern of functional recovery by investigating the longitudinal reorganization of structural networks after surgery for OIE in 10 patients.
UNASSIGNED: Structural T1 and diffusion-weighted MRIs were performed before surgery (t0) and at 6 months (t1) and 12 months (t2) postoperatively. These images were processed with an original, comprehensive structural connectivity pipeline. Using our method, we performed comparisons between the t0 and t1 timepoints and between the t1 and t2 timepoints to characterize the progressive structural remodeling.
UNASSIGNED: We found a widespread pattern of postoperative changes primarily in the surgical hemisphere, most of which consisted of reductions in connectivity strength (CS) and regional graph theoretic measures (rGTM) that reflect local connectivity. We also observed increases in CS and rGTMs predominantly in regions located near the resection cavity and in the contralateral healthy hemisphere. Finally, most structural changes arose in the first six months following surgery (i.e., between t0 and t1).
UNASSIGNED: To our knowledge, this study provides the first description of postoperative structural connectivity changes following surgery for OIE. The ipsilateral reductions in connectivity unveiled by our analysis may result from the reversal of seizure-related structural alterations following postoperative seizure control. Moreover, the strengthening of connections in peri-resection areas and in the contralateral hemisphere may be compatible with compensatory structural plasticity, a process that could contribute to the recovery of functions seen following operculo-insular resections for focal epilepsy.

Streamline tractography locally traces peak directions extracted from fiber orientation distribution (FOD) functions, lacking global information about the trend of the whole fiber bundle. Therefore, it is prone to producing erroneous tracks while missing true positive connections. In this work, we propose a new bundle-specific tractography (BST) method based on a bundle-specific tractogram distribution (BTD) function, which directly reconstructs the fiber trajectory from the start region to the termination region by incorporating the global information in the fiber bundle mask. A unified framework for any higher-order streamline differential equation is presented to describe the fiber bundles with disjoint streamlines defined based on the diffusion vectorial field. At the global level, the tractography process is simplified as the estimation of BTD coefficients by minimizing the energy optimization model, and is used to characterize the relations between BTD and diffusion tensor vector under the prior guidance by introducing the tractogram bundle information to provide anatomic priors. Experiments are performed on simulated Hough, Sine, Circle data, ISMRM 2015 Tractography Challenge data, FiberCup data, and in vivo data from the Human Connectome Project (HCP) for qualitative and quantitative evaluation. Results demonstrate that our approach reconstructs complex fiber geometry more accurately. BTD reduces the error deviation and accumulation at the local level and shows better results in reconstructing long-range, twisting, and large fanning tracts.

Van den Hoven et al. contested my interpretation of Wernicke regarding the role of the arcuate fasciculus (AF) in word production. Here, I clarify and defend my interpretation. They also questioned the assumption of AF subtracts in my modern account, stating that subtracts are difficult to distinguish anatomically due to overlapping terminations. Here, I make clear that overlap in terminations was actually part of my account, in which differentially damaged subtracts explained patients\' differential naming and repetition performance as well as types of repetition performance.