Comprehensive in vivo Mapping of the Human Basal Ganglia and Thalamic Connectome in Individuals Using 7T MRI

Basal ganglia circuits are affected in neurological disorders such as Parkinson's disease (PD), essential tremor, dystonia and Tourette syndrome. Understanding the structural and functional connectivity of these circuits is critical for elucidating the mechanisms of the movement and neuropsychiatric disorders, and is vital for developing new therapeutic strategies such as deep brain stimulation (DBS). Knowledge about the connectivity of the human basal ganglia and thalamus has rapidly evolved over recent years through non-invasive imaging techniques, but has remained incomplete because of insufficient resolution and sensitivity of these techniques. Here, we present an imaging and computational protocol designed to generate a comprehensive in vivo and subject-specific, three-dimensional model of the structure and connections of the human basal ganglia. High-resolution structural and functional magnetic resonance images were acquired with a 7-Tesla magnet. Capitalizing on the enhanced signal-to-noise ratio (SNR) and enriched contrast obtained at high-field MRI, detailed structural and connectivity representations of the human basal ganglia and thalamus were achieved. This unique combination of multiple imaging modalities enabled the in-vivo visualization of the individual human basal ganglia and thalamic nuclei, the reconstruction of seven white-matter pathways and their connectivity probability that, to date, have only been reported in animal studies, histologically, or group-averaged MRI population studies. Also described are subject-specific parcellations of the basal ganglia and thalamus into sub-territories based on their distinct connectivity patterns. These anatomical connectivity findings are supported by functional connectivity data derived from resting-state functional MRI (R-fMRI). This work demonstrates new capabilities for studying basal ganglia circuitry, and opens new avenues of investigation into the movement and neuropsychiatric disorders, in individual human subjects

The Organization of Corticostriatal Connectivity in the Human Brain

Neurological and psychiatric disorders reveal that the basal ganglia subserve diverse functional domains, including movement, reward, and cognitive disorders (e.g., Parkinson's disease, addiction, schizophrenia). Monkey anatomical studies show that the striatum, the input structure of the basal ganglia, receives projections from nearly the entire cerebral cortex with a broad topography of motor, limbic, and association zones. However, until recently, non-invasive methods have not been available to conduct the complete mapping of the cortex to the striatum in humans. The development of functional connectivity magnetic resonance imaging (fcMRI) now allows the identification of functional connections in humans. The present dissertation reports two studies that first create a complete map of corticostriatal connectivity and then more closely examine striatal connectivity with association networks underlying cognition

Cerebellar atrophy in Parkinson's disease and its implication for network connectivity.

Pathophysiological and atrophic changes in the cerebellum are documented in Parkinson's disease. Without compensatory activity, such abnormalities could potentially have more widespread effects on both motor and non-motor symptoms. We examined how atrophic change in the cerebellum impacts functional connectivity patterns within the cerebellum and between cerebellar-cortical networks in 42 patients with Parkinson's disease and 29 control subjects. Voxel-based morphometry confirmed grey matter loss across the motor and cognitive cerebellar territories in the patient cohort. The extent of cerebellar atrophy correlated with decreased resting-state connectivity between the cerebellum and large-scale cortical networks, including the sensorimotor, dorsal attention and default networks, but with increased connectivity between the cerebellum and frontoparietal networks. The severity of patients' motor impairment was predicted by a combination of cerebellar atrophy and decreased cerebellar-sensorimotor connectivity. These findings demonstrate that cerebellar atrophy is related to both increases and decreases in cerebellar-cortical connectivity in Parkinson's disease, identifying potential cerebellar driven functional changes associated with sensorimotor deficits. A post hoc analysis exploring the effect of atrophy in the subthalamic nucleus, a cerebellar input source, confirmed that a significant negative relationship between grey matter volume and intrinsic cerebellar connectivity seen in controls was absent in the patients. This suggests that the modulatory relationship of the subthalamic nucleus on intracerebellar connectivity is lost in Parkinson's disease, which may contribute to pathological activation within the cerebellum. The results confirm significant changes in cerebellar network activity in Parkinson's disease and reveal that such changes occur in association with atrophy of the cerebellum

Multi-neuroimaging model of identifying neuroplasticity under motor cognitive learning condition: MRI based study.

Motor learning is a fundamental ability and one of the most robust models to study neural plasticity. The majority of human motor learning imaging studies focused on either short-term or long-term learning using one single imaging modality. These studies were thus not able to systematically investigate the dynamic process of motor learning from a multimodal perspective. The current project combined both short-term and long-term motor learning to comprehensively characterize neural plasticity at multiple phenotypic levels of the brain: functional activation, functional connectivity, grey matter volume, and glutamate concentration. To this end, this project involved a cross-sectional and a longitudinal study with multimodal brain imaging techniques (task fMRI, resting-state fMRI, gray matter structural fMRI, pharmacological fMRI, and MRS). Short-term motor learning was significantly correlated with brain network features related to network efficiency. It was also associated with a highly reliable cerebellum-centered network which was significantly modulated by the NMDA antagonist ketamine. Long-term motor learning was associated with increased activation in premotor / SMA and parietal regions and with increased gray matter volume of the SMA and the hippocampus. In addition, long-term motor learning was accompanied by a decrease in the functional connectivity of a network centered on the sensorimotor cortex which was related to handknob glutamate concentration levels and which involved regions that were highlighted by our activation and structural analyses. Taken together, this thesis contributes important evidence to the neurofunctional and neurostructural underpinnings of motor learning and points to the critical roles of the cerebellum, the hippocampus and the relevance of glutamate for motor learning in humans

Anatomical and Functional Organization of Domain-General Brain Regions

How does complex brain activity organize thought and behaviour? Theoretical proposals have long emphasized that intelligent behaviour must be supported by a flexible control system. Numerous brain imaging studies identified a domain-general or “multiple-demand” (MD) brain system co-activated accompanying many tasks and is hypothesised to play a central role in cognitive control. However, the limited spatial localization provided by traditional imaging methods precluded a consensus regarding its anatomy and physiology. To address these limitations, the experiments in chapters 2 and 3 capitalize on novel multi-modal magnetic resonance imaging (MRI) methods developed by the Human Connectome Project. Chapter 2 delineated nine cortical MD patches per hemisphere and subdivided them into 10 regions forming a core of most strongly activated and functionally interconnected regions, surrounded by a penumbra of 17 additional regions. MD activations were also identified in specific subcortical and cerebellar regions. Chapter 3 investigated the relation between the newly defined MD regions and previously identified sensory-biased cortical regions. Contrasting auditory and visual low working memory demands revealed the strongest sensory-biases are localized just outside of MD regions. And additional working memory demands revealed MD activations showed no sensory biases. Chapter 4 used human electrophysiological recordings from the lateral frontal cortex to functionally map cognitive control regions during awake neurosurgeries. By contrasting a hard vs easy cognitive demand, spectral analysis revealed localized power increases in the gamma range (>30 Hz) that overlap with a canonical mask of the fronto-parietal control network. These findings contrast with spatially non-specific power decreases in the beta range (12-30 Hz). Thus, using similar task difficulty manipulations, electrophysiology and MRI functional signals converged on localizing lateral frontal regions related to cognitive control and support their clinical potential for intraoperative mapping of cognitive control. All together, the distributed anatomical organization, mosaic functional preferences, and strong functional interconnectivity of MD regions, suggest a skeleton for integrating and organizing the diverse components of cognitive operations. The precise anatomical delineation of MD regions provides the groundwork for refined analyses of their functions

Brain dysconnectome: a potential biomarker for functional outcome after mechanical thrombectomy

Mechanical thrombectomy (MT) is a safe and effective procedure that has improved the prognosis of patients with large vessel obstruction (LVO) stroke. Even though we select patients based on various clinical and imaging criteria, more than half of those undergoing this procedure remain with severe disability. Several factors, both pre-treatment (pre-stroke mRS, NIHSS, event-recanalization time, ASPECTS, core/ penumbra volumes) and post-treatment (TICI, NIHSS, final infarct volume, complications) have been identified as predictors of outcome. Among these factors, the volume of the lesion and the size of the hypo-perfused region of the brain are used to make individual decisions about treatment. In retrospective studies, the volume of the lesion weakly correlates with clinical outcomes, while lesion location is more predictive. In addition measures of large-scale (brain networks) disruption have been developed based on the concept of structural and functional disconnection, i.e., the ensemble of structural and functional connections that are directly or indirectly damaged by the focal injury. These disconnection measures have been shown to be strongly predictive of acute impairment and recovery of function. Here we plan to measure in a group of patients with LVO who underwent MT the relationship between outcome (3 month-mRS) and the location of the lesion or its effect on structural and functional networks. To examine whether the outcome is more related to the vascular distribution stroke or their effects on structural-functional brain networks, we mapped the lesions onto a vascular atlas, a gray matter functional regions’ atlas, or a white matter structural connections’ atlas. Then using multi-variate statistical models, we tested which atlas was more predictive of clinical outcome. The same analysis was then applied to structural and functional disconnection patterns. A total of n=66 patients underwent MT at the Neurology Unit of Padua hospital from January 2019 to June 2022. They were examined with the mRS and the NIHSS at admission and discharge. The mRS was also administered at three months post-stroke for measuring clinical outcomes. The location and volume of the lesions were measured from CT, and FLAIR MRI scans performed after MT and manually segmented using the software ITK-SNAP. We computed voxel-wise maps of structural and functional disconnections that were significantly related to functional outcomes. We also investigated the relationship between lesion location computed on three different atlases (vascular, functional grey matter, and structural white matter atlas) and 3-month mRS. The mean pre-event mRS was 0.5±0.9, post-MT mRS was 3.1±1.9, at three-month mRS was 2.5±2.1. A voxel-wise analysis of the functional disconnection showed a significant involvement of the sensory-motor network (SMN) (R2= 0.340), the visual network (VIS)(R2= 0.379), and the dorsal attention network (DAN)(R2=0.318). The voxel-wise structural disconnection analysis localized sensorimotor pathways and long-range association pathways. The prediction of lesion topography on clinical outcome was more robust for the functional atlas (R2=0.382), followed by the structural atlas (R2=0.338), while the vascular atlas provided the lowest prediction (R2=0.146). Structural disconnection performed better than functional disconnection in predicting outcomes (respectively R2=0.339 and R2=0.205). Stroke lesion topography is a strong prognostic factor of outcome at three months when computed on an atlas of functional and structural networks, as compared to a vascular-based atlas. These findings indicate that pre-treatment evaluations for MT shall take into consideration the network structure of the brain and less its vascular supply. Structural disconnection measures are of high prognostic value. Future studies will define the prognostic value of a network-based atlas in a pre-treatment setting.Mechanical thrombectomy (MT) is a safe and effective procedure that has improved the prognosis of patients with large vessel obstruction (LVO) stroke. Even though we select patients based on various clinical and imaging criteria, more than half of those undergoing this procedure remain with severe disability. Several factors, both pre-treatment (pre-stroke mRS, NIHSS, event-recanalization time, ASPECTS, core/ penumbra volumes) and post-treatment (TICI, NIHSS, final infarct volume, complications) have been identified as predictors of outcome. Among these factors, the volume of the lesion and the size of the hypo-perfused region of the brain are used to make individual decisions about treatment. In retrospective studies, the volume of the lesion weakly correlates with clinical outcomes, while lesion location is more predictive. In addition measures of large-scale (brain networks) disruption have been developed based on the concept of structural and functional disconnection, i.e., the ensemble of structural and functional connections that are directly or indirectly damaged by the focal injury. These disconnection measures have been shown to be strongly predictive of acute impairment and recovery of function. Here we plan to measure in a group of patients with LVO who underwent MT the relationship between outcome (3 month-mRS) and the location of the lesion or its effect on structural and functional networks. To examine whether the outcome is more related to the vascular distribution stroke or their effects on structural-functional brain networks, we mapped the lesions onto a vascular atlas, a gray matter functional regions’ atlas, or a white matter structural connections’ atlas. Then using multi-variate statistical models, we tested which atlas was more predictive of clinical outcome. The same analysis was then applied to structural and functional disconnection patterns. A total of n=66 patients underwent MT at the Neurology Unit of Padua hospital from January 2019 to June 2022. They were examined with the mRS and the NIHSS at admission and discharge. The mRS was also administered at three months post-stroke for measuring clinical outcomes. The location and volume of the lesions were measured from CT, and FLAIR MRI scans performed after MT and manually segmented using the software ITK-SNAP. We computed voxel-wise maps of structural and functional disconnections that were significantly related to functional outcomes. We also investigated the relationship between lesion location computed on three different atlases (vascular, functional grey matter, and structural white matter atlas) and 3-month mRS. The mean pre-event mRS was 0.5±0.9, post-MT mRS was 3.1±1.9, at three-month mRS was 2.5±2.1. A voxel-wise analysis of the functional disconnection showed a significant involvement of the sensory-motor network (SMN) (R2= 0.340), the visual network (VIS)(R2= 0.379), and the dorsal attention network (DAN)(R2=0.318). The voxel-wise structural disconnection analysis localized sensorimotor pathways and long-range association pathways. The prediction of lesion topography on clinical outcome was more robust for the functional atlas (R2=0.382), followed by the structural atlas (R2=0.338), while the vascular atlas provided the lowest prediction (R2=0.146). Structural disconnection performed better than functional disconnection in predicting outcomes (respectively R2=0.339 and R2=0.205). Stroke lesion topography is a strong prognostic factor of outcome at three months when computed on an atlas of functional and structural networks, as compared to a vascular-based atlas. These findings indicate that pre-treatment evaluations for MT shall take into consideration the network structure of the brain and less its vascular supply. Structural disconnection measures are of high prognostic value. Future studies will define the prognostic value of a network-based atlas in a pre-treatment setting

The Overlapping Community Structure of Structural Brain Network in Young Healthy Individuals

Community structure is a universal and significant feature of many complex networks in biology, society, and economics. Community structure has also been revealed in human brain structural and functional networks in previous studies. However, communities overlap and share many edges and nodes. Uncovering the overlapping community structure of complex networks remains largely unknown in human brain networks. Here, using regional gray matter volume, we investigated the structural brain network among 90 brain regions (according to a predefined anatomical atlas) in 462 young, healthy individuals. Overlapped nodes between communities were defined by assuming that nodes (brain regions) can belong to more than one community. We demonstrated that 90 brain regions were organized into 5 overlapping communities associated with several well-known brain systems, such as the auditory/language, visuospatial, emotion, decision-making, social, control of action, memory/learning, and visual systems. The overlapped nodes were mostly involved in an inferior-posterior pattern and were primarily related to auditory and visual perception. The overlapped nodes were mainly attributed to brain regions with higher node degrees and nodal efficiency and played a pivotal role in the flow of informa- tion through the structural brain network. Our results revealed fuzzy boundaries between communities by identifying overlapped nodes and provided new insights into the understanding of the relationship between the structure and function of the human brain. This study provides the first report of the overlapping community structure of the structural network of the human brain

Functional Alterations in Cerebellar Functional Connectivity in Anxiety Disorders

Adolescents with anxiety disorders exhibit excessive emotional and somatic arousal. Neuroimaging studies have shown abnormal cerebral cortical activation and connectivity in this patient population. The specific role of cerebellar output circuitry, specifically the dentate nuclei (DN), in adolescent anxiety disorders remains largely unexplored. Resting-state functional connectivity analyses have parcellated the DN, the major output nuclei of the cerebellum, into three functional territories (FTs) that include default-mode, salience-motor, and visual networks. The objective of this study was to understand whether FTs of the DN are implicated in adolescent anxiety disorders. Forty-one adolescents (mean age 15.19 ± 0.82, 26 females) with one or more anxiety disorders and 55 age- and gender-matched healthy controls completed resting-state fMRI scans and a self-report survey on anxiety symptoms. Seed-to-voxel functional connectivity analyses were performed using the FTs from DN parcellation. Brain connectivity metrics were then correlated with State-Trait Anxiety Inventory (STAI) measures within each group. Adolescents with an anxiety disorder showed significant hyperconnectivity between salience-motor DN FT and cerebral cortical salience-motor regions compared to controls. Salience-motor FT connectivity with cerebral cortical sensorimotor regions was significantly correlated with STAI-trait scores in HC (R2 = 0.41). Here, we report DN functional connectivity differences in adolescents diagnosed with anxiety, as well as in HC with variable degrees of anxiety traits. These observations highlight the relevance of DN as a potential clinical and sub-clinical marker of anxiety