Establishing connectivity through microdissections of midbrain stimulation-related neural circuits.

Comprehensive understanding of the neural circuits involving the ventral tegmental area is essential for elucidating the anatomo-functional mechanisms governing human behaviour as well as the therapeutic and adverse effects of deep brain stimulation for neuropsychiatric diseases. While the ventral tegmental area has been successfully targeted with deep brain stimulation for different neuropsychiatric diseases, the axonal connectivity of the region has not been fully understood. Here using fiber micro-dissections in human cadaveric hemispheres, population-based high-definition fiber tractography, and previously reported deep brain stimulation hotspots, we find that the ventral tegmental area participates in an intricate network involving the serotonergic pontine nuclei, basal ganglia, limbic system, basal forebrain, and prefrontal cortex, which is implicated in the treatment of obsessive-compulsive disorder, major depressive disorder, Alzheimer's disease, cluster headaches, and aggressive behaviors.

Diffusion and functional MRI in surgical neuromodulation.

Surgical neuromodulation has witnessed significant progress in recent decades. Notably, deep brain stimulation (DBS), delivered precisely within therapeutic targets, has revolutionized the treatment of medication-refractory movement disorders and is now expanding for refractory psychiatric disorders, refractory epilepsy, and post-stroke motor recovery. In parallel, the advent of incisionless treatment with focused ultrasound ablation (FUSA) can offer patients life-changing symptomatic relief. Recent research has underscored the potential to further optimize DBS and FUSA outcomes by conceptualizing the therapeutic targets as critical nodes embedded within specific brain networks instead of strictly anatomical structures. This paradigm shift was facilitated by integrating two imaging modalities used regularly in brain connectomics research: diffusion MRI (dMRI) and functional MRI (fMRI). These advanced imaging techniques have helped optimize the targeting and programming techniques of surgical neuromodulation, all while holding immense promise for investigations into treating other neurological and psychiatric conditions. This review aims to provide a fundamental background of advanced imaging for clinicians and scientists, exploring the synergy between current and future approaches to neuromodulation as they relate to dMRI and fMRI capabilities. Focused research in this area is required to optimize existing, functional neurosurgical treatments while serving to build an investigative infrastructure to unlock novel targets to alleviate the burden of other neurological and psychiatric disorders.

Probabilistic coverage of the frontal aslant tract in young adults: Insights into individual variability, lateralization, and language functions.

The frontal aslant tract (FAT) is a crucial neural pathway of language and speech, but little is known about its connectivity and segmentation differences across populations. In this study, we investigate the probabilistic coverage of the FAT in a large sample of 1065 young adults. Our primary goal was to reveal individual variability and lateralization of FAT and its structure-function correlations in language processing. The study utilized diffusion MRI data from 1065 subjects obtained from the Human Connectome Project. Automated tractography using DSI Studio software was employed to map white matter bundles, and the results were examined to study the population variation of the FAT. Additionally, anatomical dissections were performed to validate the fiber tracking results. The tract-to-region connectome, based on Human Connectome Project-MMP parcellations, was utilized to provide population probability of the tract-to-region connections. Our results showed that the left anterior FAT exhibited the most substantial individual differences, particularly in the superior and middle frontal gyrus, with greater variability in the superior than the inferior region. Furthermore, we found left lateralization in FAT, with a greater difference in coverage in the inferior and posterior portions. Additionally, our analysis revealed a significant positive correlation between the left FAT inferior coverage area and the performance on the oral reading recognition (p = .016) and picture vocabulary (p = .0026) tests. In comparison, fractional anisotropy of the right FAT exhibited marginal significance in its correlation (p = .056) with Picture Vocabulary Test. Our findings, combined with the connectivity patterns of the FAT, allowed us to segment its structure into anterior and posterior segments. We found significant variability in FAT coverage among individuals, with left lateralization observed in both macroscopic shape measures and microscopic diffusion metrics. Our findings also suggested a potential link between the size of the left FAT's inferior coverage area and language function tests. These results enhance our understanding of the FAT's role in brain connectivity and its potential implications for language and executive functions.

The anatomy of the four streams of the prefrontal cortex. Preliminary evidence from a population based high definition tractography study.

The model of the four streams of the prefrontal cortex proposes 4 streams of information: motor through Brodmann area (BA) 8, emotion through BA 9, memory through BA 10, and emotional-related sensory through BA 11. Although there is a surge of functional data supporting these 4 streams within the PFC, the structural connectivity underlying these neural networks has not been fully clarified. Here we perform population-based high-definition tractography using an averaged template generated from data of 1,065 human healthy subjects acquired from the Human Connectome Project to further elucidate the structural organization of these regions. We report the structural connectivity of BA 8 with BA 6, BA 9 with the insula, BA 10 with the hippocampus, BA 11 with the temporal pole, and BA 11 with the amygdala. The 4 streams of the prefrontal cortex are subserved by a structural neural network encompassing fibers of the anterior part of the superior longitudinal fasciculus-I and II, corona radiata, cingulum, frontal aslant tract, and uncinate fasciculus. The identified neural network of the four streams of the PFC will allow the comprehensive analysis of these networks in normal and pathological brain function.

POTENTIATION OF CORTICO-SPINAL OUTPUT VIA TARGETED ELECTRICAL STIMULATION OF THE MOTOR THALAMUS.

Cerebral white matter lesions prevent cortico-spinal descending inputs from effectively activating spinal motoneurons, leading to loss of motor control. However, in most cases, the damage to cortico-spinal axons is incomplete offering a potential target for new therapies aimed at improving volitional muscle activation. Here we hypothesized that, by engaging direct excitatory connections to cortico-spinal motoneurons, stimulation of the motor thalamus could facilitate activation of surviving cortico-spinal fibers thereby potentiating motor output. To test this hypothesis, we identified optimal thalamic targets and stimulation parameters that enhanced upper-limb motor evoked potentials and grip forces in anesthetized monkeys. This potentiation persisted after white matter lesions. We replicated these results in humans during intra-operative testing. We then designed a stimulation protocol that immediately improved voluntary grip force control in a patient with a chronic white matter lesion. Our results show that electrical stimulation targeting surviving neural pathways can improve motor control after white matter lesions.

Differential tractography as a dynamic imaging biomarker: A methodological pilot study for Huntington's disease.

Huntington's disease (HD) is a neurodegenerative disorder characterized by motor, psychiatric, and cognitive symptoms. Due to its diverse manifestations, the scientific community has long recognized the need for sensitive, objective, individualized, and dynamic disease assessment tools. We examined the feasibility of Differential Tractography as a biomarker to evaluate correlation of symptom severity and of HD progression at the individual level. Differential tractography is a novel tractography modality that maps pathways with axonal injury characterized by a decrease of anisotropic diffusion pattern. We recruited sixteen patients scanned at 0-, 6-, and 12-month intervals by diffusion MRI scans for differential tractography assessment and correlated its volumetric findings with the Unified Huntington's Disease Rating Scale (UHDRS). Deterministic fiber tracking algorithm was applied. Longitudinal data was modeled using the generalized estimating equation (GEE) model and correlated with UHDRS scores, in addition to Spearman correlation for cross-sectional data. Our results show that volumes of affected pathways revealed by differential tractography significantly correlated with UHDRS scores in longitudinal data (p-value < 0.001), and chronological changes in differential tractography also correlated with the changes in UHDRS (p-value < 0.001). This technique opens new clinical avenues as a clinical translational tool to evaluate presymptomatic and symptomatic gene positive individuals. Our results provide support that differential tractography has the potential to be used as a dynamic imaging biomarker to assess at the individual level in a non-invasive manner, disease progression in HD. Critically important, differential tractography proves to be a quantitative tool for following degeneration in presymptomatic patients, with potential applications in clinical trials.

Applying Deep Learning to Accelerated Clinical Brain Magnetic Resonance Imaging for Multiple Sclerosis.

Background: Magnetic resonance (MR) scans are routine clinical procedures for monitoring people with multiple sclerosis (PwMS). Patient discomfort, timely scheduling, and financial burden motivate the need to accelerate MR scan time. We examined the clinical application of a deep learning (DL) model in restoring the image quality of accelerated routine clinical brain MR scans for PwMS. Methods: We acquired fast 3D T1w BRAVO and fast 3D T2w FLAIR MRI sequences (half the phase encodes and half the number of slices) in parallel to conventional parameters. Using a subset of the scans, we trained a DL model to generate images from fast scans with quality similar to the conventional scans and then applied the model to the remaining scans. We calculated clinically relevant T1w volumetrics (normalized whole brain, thalamic, gray matter, and white matter volume) for all scans and T2 lesion volume in a sub-analysis. We performed paired t-tests comparing conventional, fast, and fast with DL for these volumetrics, and fit repeated measures mixed-effects models to test for differences in correlations between volumetrics and clinically relevant patient-reported outcomes (PRO). Results: We found statistically significant but small differences between conventional and fast scans with DL for all T1w volumetrics. There was no difference in the extent to which the key T1w volumetrics correlated with clinically relevant PROs of MS symptom burden and neurological disability. Conclusion: A deep learning model that improves the image quality of the accelerated routine clinical brain MR scans has the potential to inform clinically relevant outcomes in MS.

Redundancy circuits of the commissural pathways in human and rhesus macaque brains.

It has been hypothesized that the human brain has less redundancy than animals, but the structural evidence has not been identified to confirm this claim. Here, we report three redundancy circuits of the commissural pathways in primate brains, namely the orbitofrontal, temporal, and occipital redundancy circuits of the anterior commissure and corpus callosum. Each redundancy circuit has two distinctly separated routes connecting a common pair of cortical regions. We mapped their trajectories in human and rhesus macaque brains using individual and population-averaged tractography. The dissection results confirmed the existence of these redundancy circuits connecting the orbitofrontal lobe, amygdala, and visual cortex. The volume analysis showed a significant reduction in the orbitofrontal and occipital redundancy circuits of the human brain, whereas the temporal redundancy circuit had a substantial organizational difference between the human and rhesus macaque. Our results support the hypothesis that the human brain has less redundancy in the commissural pathways than that of the rhesus macaque brain. Further studies are needed to explore its neuropathological implications.

Differential tractography as a track-based biomarker for neuronal injury.

Diffusion MRI tractography has been used to map the axonal structure of the human brain, but its ability to detect neuronal injury is yet to be explored. Here we report differential tractography, a new type of tractography that utilizes repeat MRI scans and a novel tracking strategy to map the exact segment of fiber pathways with a neuronal injury. We examined differential tractography on multiple sclerosis, Huntington's disease, amyotrophic lateral sclerosis, and epileptic patients. The results showed that the affected pathways shown by differential tractography matched well with the unique clinical symptoms of the patients, and the false discovery rate of the findings could be estimated using a sham setting to provide a reliability measurement. This novel approach enables a quantitative and objective method to monitor neuronal injury in individuals, allowing for diagnostic and prognostic evaluation of brain diseases.