Functional Segmentation of the Anterior Limb of the Internal Capsule: Linking White Matter Abnormalities to Specific Connections.

The anterior limb of the internal capsule (ALIC) carries thalamic and brainstem fibers from prefrontal cortical regions that are associated with different aspects of emotion, motivation, cognition processing, and decision-making. This large fiber bundle is abnormal in several psychiatric illnesses and a major target for deep brain stimulation. Yet, we have very little information about where specific prefrontal fibers travel within the bundle. Using a combination of tracing studies and diffusion MRI in male nonhuman primates, as well as diffusion MRI in male and female human subjects, we segmented the human ALIC into five regions based on the positions of axons from different cortical regions within the capsule. Fractional anisotropy (FA) abnormalities in patients with bipolar disorder were detected when FA was averaged in the ALIC segment that carries ventrolateral prefrontal cortical connections. Together, the results set the stage for linking abnormalities within the ALIC to specific connections and demonstrate the utility of applying connectivity profiles of large white matter bundles based on animal anatomic studies to human connections and associating disease abnormalities in those pathways with specific connections. The ability to functionally segment large white matter bundles into their components begins a new era of refining how we think about white matter organization and use that information in understanding abnormalities.SIGNIFICANCE STATEMENT The anterior limb of the internal capsule (ALIC) connects prefrontal cortex with the thalamus and brainstem and is abnormal in psychiatric illnesses. However, we know little about the location of specific prefrontal fibers within the bundle. Using a combination of animal tracing studies and diffusion MRI in animals and human subjects, we segmented the human ALIC into five regions based on the positions of axons from different cortical regions. We then demonstrated that differences in FA values between bipolar disorder patients and healthy control subjects were specific to a given segment. Together, the results set the stage for linking abnormalities within the ALIC to specific connections and for refining how we think about white matter organization in general.

Organization of the Anterior Limb of the Internal Capsule in the Rat.

Dysfunction of the orbitofrontal (OFC) and anterior cingulate (ACC) cortices has been linked with several psychiatric disorders, including obsessive-compulsive disorder, major depressive disorder, posttraumatic stress disorder, and addiction. These conditions are also associated with abnormalities in the anterior limb of the internal capsule, the white matter (WM) bundle carrying ascending and descending fibers from the OFC and ACC. Furthermore, deep-brain stimulation (DBS) for psychiatric disorders targets these fibers. Experiments in rats provide essential information on the mechanisms of normal and abnormal brain anatomy, including WM composition and perturbations. However, whereas descending prefrontal cortex (PFC) fibers in primates form a well defined and topographic anterior limb of the internal capsule, the specific locations and organization of these fibers in rats is unknown. We address this gap by analyzing descending fibers from injections of an anterograde tracer in the rat ACC and OFC. Our results show that the descending PFC fibers in the rat form WM fascicles embedded within the striatum. These bundles are arranged topographically and contain projections, not only to the striatum, but also to the thalamus and brainstem. They can therefore be viewed as the rat homolog of the primate anterior limb of the internal capsule. Furthermore, mapping these projections allows us to identify the fibers likely to be affected by experimental manipulations of the striatum and the anterior limb of the internal capsule. These results are therefore essential for translating abnormalities of human WM and effects of DBS to rodent models.SIGNIFICANCE STATEMENT Psychiatric diseases are linked to abnormalities in specific white matter (WM) pathways, and the efficacy of deep-brain stimulation relies upon activation of WM. Experiments in rodents are necessary for studying the mechanisms of brain function. However, the translation of results between primates and rodents is hindered by the fact that the organization of descending WM in rodents is poorly understood. This is especially relevant for the prefrontal cortex, abnormal connectivity of which is central to psychiatric disorders. We address this gap by studying the organization of descending rodent prefrontal pathways. These fibers course through a subcortical structure, the striatum, and share important organization principles with primate WM. These results allow us to model primate WM effectively in the rodent.

Human and monkey ventral prefrontal fibers use the same organizational principles to reach their targets: tracing versus tractography.

This article is a comparative study of white matter projections from ventral prefrontal cortex (vPFC) between human and macaque brains. We test whether the organizational rules that vPFC connections follow in macaques are preserved in humans. These rules concern the trajectories of some of the white matter projections from vPFC and how the position of regions in the vPFC dictate the trajectories of their projections in the white matter. To address this question, we present a novel approach that combines direct tracer measurements of entire white matter trajectories in macaque monkeys with diffusion MRI tractography of both macaques and humans. The approach allows us to provide explicit validation of diffusion tractography and transfer tractography strategies across species to test the extent to which inferences from macaques can be applied to human neuroanatomy. Apart from one exception, we found a remarkable overlap between the two techniques in the macaque. Furthermore, the organizational principles followed by vPFC tracts in macaques are preserved in humans.

Self-supervised segmentation and characterization of fiber bundles in anatomic tracing data.

Anatomic tracing is the gold standard tool for delineating brain connections and for validating more recently developed imaging approaches such as diffusion MRI tractography. A key step in the analysis of data from tracer experiments is the careful, manual charting of fiber trajectories on histological sections. This is a very time-consuming process, which limits the amount of annotated tracer data that are available for validation studies. Thus, there is a need to accelerate this process by developing a method for computer-assisted segmentation. Such a method must be robust to the common artifacts in tracer data, including variations in the intensity of stained axons and background, as well as spatial distortions introduced by sectioning and mounting the tissue. The method should also achieve satisfactory performance using limited manually charted data for training. Here we propose the first deeplearning method, with a self-supervised loss function, for segmentation of fiber bundles on histological sections from macaque brains that have received tracer injections. We address the limited availability of manual labels with a semi-supervised training technique that takes advantage of unlabeled data to improve performance. We also introduce anatomic and across-section continuity constraints to improve accuracy. We show that our method can be trained on manually charted sections from a single case and segment unseen sections from different cases, with a true positive rate of ~0.80. We further demonstrate the utility of our method by quantifying the density of fiber bundles as they travel through different white-matter pathways. We show that fiber bundles originating in the same injection site have different levels of density when they travel through different pathways, a finding that can have implications for microstructure-informed tractography methods. The code for our method is available at https://github.com/v-sundaresan/fiberbundle_seg_tracing.

Rules ventral prefrontal cortical axons use to reach their targets: implications for diffusion tensor imaging tractography and deep brain stimulation for psychiatric illness.

The ventral prefrontal cortex (vPFC) is involved in reinforcement-based learning and is associated with depression, obsessive-compulsive disorder, and addiction. Neuroimaging is increasingly used to develop models of vPFC connections, to examine white matter (WM) integrity, and to target surgical interventions, including deep brain stimulation. We used primate (Macaca nemestrina/Macaca fascicularis) tracing studies and 3D reconstructions of WM tracts to delineate the rules vPFC projections follow to reach their targets. vPFC efferent axons travel through the uncinate fasciculus, connecting different vPFC regions and linking different functional regions. The uncinate fasciculus also is a conduit for vPFC fibers to reach other cortical bundles. Fibers in the internal capsule are organized according to destination. Thalamic fibers from each vPFC region travel dorsal to their brainstem fibers. The results show regional differences in the trajectories of fibers from different vPFC areas. Overall, the medial/lateral vPFC position dictates the route that fibers take to enter major WM tracts, as well as the position within specific tracts: axons from medial vPFC regions travel ventral to those from more lateral areas. This arrangement, coupled with dorsal/ventral organization of thalamic/brainstem fibers through the internal capsule, results in a complex mingling of thalamic and brainstem axons from different vPFC areas. Together, these data provide the foundation for dividing vPFC WM bundles into functional components and for predicting what is likely to be carried at different points through each bundle. These results also help determine the specific connections that are likely to be captured at different neurosurgical targets.

Anatomical and functional connectivity support the existence of a salience network node within the caudal ventrolateral prefrontal cortex.

Three large-scale networks are considered essential to cognitive flexibility: the ventral and dorsal attention (VANet and DANet) and salience (SNet) networks. The ventrolateral prefrontal cortex (vlPFC) is a known component of the VANet and DANet, but there is a gap in the current knowledge regarding its involvement in the SNet. Herein, we used a translational and multimodal approach to demonstrate the existence of a SNet node within the vlPFC. First, we used tract-tracing methods in non-human primates (NHP) to quantify the anatomical connectivity strength between different vlPFC areas and the frontal and insular cortices. The strongest connections were with the dorsal anterior cingulate cortex (dACC) and anterior insula (AI) - the main cortical SNet nodes. These inputs converged in the caudal area 47/12, an area that has strong projections to subcortical structures associated with the SNet. Second, we used resting-state functional MRI (rsfMRI) in NHP data to validate this SNet node. Third, we used rsfMRI in the human to identify a homologous caudal 47/12 region that also showed strong connections with the SNet cortical nodes. Taken together, these data confirm a SNet node in the vlPFC, demonstrating that the vlPFC contains nodes for all three cognitive networks: VANet, DANet, and SNet. Thus, the vlPFC is in a position to switch between these three networks, pointing to its key role as an attentional hub. Its additional connections to the orbitofrontal, dorsolateral, and premotor cortices, place the vlPFC at the center for switching behaviors based on environmental stimuli, computing value, and cognitive control.

A connectional hub in the rostral anterior cingulate cortex links areas of emotion and cognitive control.

We investigated afferent inputs from all areas in the frontal cortex (FC) to different subregions in the rostral anterior cingulate cortex (rACC). Using retrograde tracing in macaque monkeys, we quantified projection strength by counting retrogradely labeled cells in each FC area. The projection from different FC regions varied across injection sites in strength, following different spatial patterns. Importantly, a site at the rostral end of the cingulate sulcus stood out as having strong inputs from many areas in diverse FC regions. Moreover, it was at the integrative conjunction of three projection trends across sites. This site marks a connectional hub inside the rACC that integrates FC inputs across functional modalities. Tractography with monkey diffusion magnetic resonance imaging (dMRI) located a similar hub region comparable to the tracing result. Applying the same tractography method to human dMRI data, we demonstrated that a similar hub can be located in the human rACC.