Connectivity-based parcellation of the anterior limb of the internal capsule.
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ABSTRACT:
SUBMITTER: Nanda P
PROVIDER: S-EPMC6206867 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:A number of studies have shown an association between diabetes and depression. However, the underlying mechanisms are still unclear. Previous findings indicate a role for the prefrontal cortex and subcortical gray matter regions in type 2 diabetes and major depressive disorder (MDD). The purpose of this study was to examine the white matter integrity in the fibers that are part of the anterior limb of internal capsule (ALIC) in MDD and diabetic subjects using diffusion tensor imaging tractography. We studied 4 groups of subjects including 1) 42 healthy controls (HC), 2) 28 MDD subjects (MD), 3) 24 patients diagnosed with type 2 diabetes without depression (DC), and 4) 22 patients diagnosed with diabetes and depression (DD). Results revealed significantly decreased fractional anisotropy (FA; P=.021) and a trend towards significant increase in radial diffusivity (RD; P=.078) of the right ALIC in depressed subjects (MD+DD) compared to non-depressed subjects (HC+DC). While there were no significant diabetes effects or interactions between depression and diabetes, subjects with high depression ratings and high hemoglobin A1c levels had the lowest mean FA values in the right ALIC. In addition, we found a significant negative correlation between FA of the left ALIC with hemoglobin A1c in diabetic subjects (DC+DD; P=.016). Our study demonstrated novel findings of white matter abnormalities of the ALIC in depression and diabetes. These findings have implications for clinical manifestations of depression and diabetes as well as their pathophysiology.
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Project description:The orbital and medial prefrontal cortex (OMPFC) has been implicated in decision-making, reward and emotion processing, and psychopathology, such as depression and obsessive-compulsive disorder. Human and monkey anatomical studies indicate the presence of various cortical subdivisions and suggest that these are organized in two extended networks, a medial and an orbital one. Attempts have been made to replicate these neuroanatomical findings in vivo using MRI techniques for imaging connectivity. These revealed several consistencies, but also many inconsistencies between reported results. Here, we use fMRI resting-state functional connectivity (FC) and data-driven modularity optimization to parcellate the OMPFC to investigate replicability of in vivo parcellation more systematically. By collecting two resting-state data sets per participant, we were able to quantify the reliability of the observed modules and their boundaries. Results show that there was significantly more than chance overlap in modules and their boundaries at the level of individual data sets. Moreover, some of these consistent boundaries significantly co-localized across participants. Hierarchical clustering showed that the whole-brain FC profiles of the OMPFC subregions separate them in two networks, a medial and orbital one, which overlap with the organization proposed by Barbas and Pandya (J Comp Neurol 286:353-375, 1989) and Ongür and Price (Cereb Cortex 10:206-219, 2000). We conclude that in vivo resting-state FC can delineate reliable and neuroanatomically plausible subdivisions that agree with established cytoarchitectonic trends and connectivity patterns, while other subdivisions do not show the same consistency across data sets and studies.
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Project description:Human brain can be divided into multiple brain regions based on anatomical and functional properties. Recent studies showed that resting-state connectivity can be utilized for parcellating brain regions and identifying their distinctive roles. In this study, we aimed to parcellate the primary and secondary visual cortices (V1 and V2) into several subregions based on functional connectivity and to examine the functional characteristics of each subregion. We used resting-state data from a research database and also acquired resting-state data with retinotopy results from a local site. The long-range connectivity profile and three different algorithms (i.e., K-means, Gaussian mixture model distribution, and Ward's clustering algorithms) were adopted for the parcellation. We compared the parcellation results within V1 and V2 with the eccentric map in retinotopy. We found that the boundaries between subregions within V1 and V2 were located in the parafovea, indicating that the anterior and posterior subregions within V1 and V2 corresponded to peripheral and central visual field representations, respectively. Next, we computed correlations between each subregion within V1 and V2 and intermediate and high-order regions in ventral and dorsal visual pathways. We found that the anterior subregions of V1 and V2 were strongly associated with regions in the dorsal stream (V3A and inferior parietal gyrus), whereas the posterior subregions of V1 and V2 were highly related to regions in the ventral stream (V4v and inferior temporal gyrus). Our findings suggest that the anterior and posterior subregions of V1 and V2, parcellated based on functional connectivity, may have distinct functional properties.
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Project description:BackgroundMajor depression (MD) and obsessive-compulsive disorder (OCD) are psychiatric diseases with a huge impact on individual well-being. Despite optimal treatment regiments a subgroup of patients remains treatment resistant and stereotactic surgery (stereotactic lesion surgery, SLS or Deep Brain Stimulation, DBS) might be an option. Recent research has described four networks related to MD and OCD (affect, reward, cognitive control, default network) but only on a cortical and the adjacent sub-cortical level. Despite the enormous impact of comparative neuroanatomy, animal science and stereotactic approaches a holistic theory of subcortical and cortical network interactions is elusive. Because of the dominant hierarchical rank of the neocortex, corticofugal approaches have been used to identify connections in subcortical anatomy without anatomical priors and in part confusing results. We here propose a different corticopetal approach by identifying subcortical networks and search for neocortical convergences thereby following the principle of phylogenetic and ontogenetic network development.Material and methodsThis work used a diffusion tensor imaging data from a normative cohort (Human Connectome Project, HCP; n = 200) to describe eight subcortical fiber projection pathways (PPs) from subthalamic nucleus (STN), substantia nigra (SNR), red nucleus (RN), ventral tegmental area (VTA), ventrolateral thalamus (VLT) and mediodorsal thalamus (MDT) in a normative space (MNI). Subcortical and cortical convergences were described including an assignment of the specific pathways to MD/OCD-related networks. Volumes of activated tissue for different stereotactic stimulation sites and procedures were simulated to understand the role of the distinct networks, with respect to symptoms and treatment of OCD and MD.ResultsThe detailed course of eight subcortical PPs (stnPP, snrPP, rnPP, vlATR, vlATRc, mdATR, mdATRc, vtaPP/slMFB) were described together with their subcortical and cortical convergences. The anterior limb of the internal capsule can be subdivided with respect to network occurrences in ventral-dorsal and medio-lateral gradients. Simulation of stereotactic procedures for OCD and MD showed dominant involvement of mdATR/mdATRc (affect network) and vtaPP/slMFB (reward network).DiscussionCorticofugal search strategies for the evaluation of stereotactic approaches without anatomical priors often lead to confusing results which do not allow for a clear assignment of a procedure to an involved network. According to our simulation of stereotactic procedures in the treatment of OCD and MD, most of the target regions directly involve the reward (and affect) networks, while side-effects can in part be explained with a co-modulation of the control network.ConclusionThe here proposed corticopetal approach of a hierarchical description of 8 subcortical PPs with subcortical and cortical convergences represents a new systematics of networks found in all different evolutionary and distinct parts of the human brain.
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Project description:The frontal pole corresponds to Brodmann area (BA) 10, the largest single architectonic area in the human frontal lobe. Generally, BA10 is thought to contain two or three subregions that subserve broad functions such as multitasking, social cognition, attention, and episodic memory. However, there is a substantial debate about the functional and structural heterogeneity of this large frontal region. Previous connectivity-based parcellation studies have identified two or three subregions in the human frontal pole. Here, we used diffusion tensor imaging to assess structural connectivity of BA10 in 35 healthy subjects and delineated subregions based on this connectivity. This allowed us to determine the correspondence of structurally based subregions with the scheme previously defined functionally. Three subregions could be defined in each subject. However, these three subregions were not spatially consistent between subjects. Therefore, we accepted a solution with two subregions that encompassed the lateral and medial frontal pole. We then examined resting-state functional connectivity of the two subregions and found significant differences between their connectivities. The medial cluster was connected to nodes of the default-mode network, which is implicated in internally focused, self-related thought, and social cognition. The lateral cluster was connected to nodes of the executive control network, associated with directed attention and working memory. These findings support the concept that there are two major anatomical subregions of the frontal pole related to differences in functional connectivity.
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Project description:Regional connectivity-based parcellation (rCBP) is a widely used procedure for investigating the structural and functional differentiation within a region of interest (ROI) based on its long-range connectivity. No standardized software or guidelines currently exist for applying rCBP, making the method only accessible to those who develop their own tools. As such, there exists a discrepancy between the laboratories applying the procedure each with their own software solutions, making it difficult to compare and interpret the results. Here, we outline an rCBP procedure accompanied by an open source software package called CBPtools. CBPtools is a Python (version 3.5+) package that allows users to run an extensively evaluated rCBP analysis workflow on a given ROI. It currently supports two modalities: resting-state functional connectivity and structural connectivity based on diffusion-weighted imaging, along with support for custom connectivity matrices. Analysis parameters are customizable and the workflow can be scaled to a large number of subjects using a parallel processing environment. Parcellation results with corresponding validity metrics are provided as textual and graphical output. Thus, CBPtools provides a simple plug-and-play, yet customizable way to conduct rCBP analyses. By providing an open-source software we hope to promote reproducible and comparable rCBP analyses and, importantly, make the rCBP procedure readily available. Here, we demonstrate the utility of CBPtools using a voluminous data set on an average compute-cluster infrastructure by performing rCBP on three ROIs prominently featured in parcellation literature.
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Project description:Regional differences in large-scale connectivity have been proposed to underlie functional specialization along the anterior-posterior axis of the medial temporal lobe (MTL), including the hippocampus (HC) and the parahippocampal gyrus (PHG). However, it is unknown whether functional connectivity (FC) can be used reliably to parcellate the human MTL. The current study aimed to differentiate subregions of the HC and the PHG based on patterns of whole-brain intrinsic FC. FC maps were calculated for each slice along the longitudinal axis of the PHG and the HC. A hierarchical clustering algorithm was then applied to these data in order to group slices according to the similarity of their connectivity patterns. Surprisingly, three discrete clusters were identified in the PHG. Two clusters corresponded to the parahippocampal cortex (PHC) and the perirhinal cortex (PRC), and these regions showed preferential connectivity with previously described posterior-medial and anterior-temporal networks, respectively. The third cluster corresponded to an anterior PRC region previously described as area 36d, and this region exhibited preferential connectivity with auditory cortical areas and with a network involved in visceral processing. The three PHG clusters showed different profiles of activation during a memory-encoding task, demonstrating that the FC-based parcellation identified functionally dissociable sub-regions of the PHG. In the hippocampus, no sub-regions were identified via the parcellation procedure. These results indicate that connectivity-based methods can be used to parcellate functional regions within the MTL, and they suggest that studies of memory and high-level cognition need to differentiate between PHC, posterior PRC, and anterior PRC.
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Project description:Non-human primate models are widely used in studying the brain mechanism underlying brain development, cognitive functions, and psychiatric disorders. Neuroimaging techniques, such as magnetic resonance imaging, play an important role in the examinations of brain structure and functions. As an indispensable tool for brain imaging data analysis, brain atlases have been extensively investigated, and a variety of versions constructed. These atlases diverge in the criteria based on which they are plotted. The criteria range from cytoarchitectonic features, neurotransmitter receptor distributions, myelination fingerprints, and transcriptomic patterns to structural and functional connectomic profiles. Among them, brainnetome atlas is tightly related to brain connectome information and built by parcellating the brain on the basis of the anatomical connectivity profiles derived from structural neuroimaging data. The pipeline for building the brainnetome atlas has been published as a toolbox named ATPP (A Pipeline for Automatic Tractography-Based Brain Parcellation). In this paper, we present a variation of ATPP, which is dedicated to monkey brain parcellation, to address the significant differences in the process between the two species. The new toolbox, MonkeyCBP, has major alterations in three aspects: brain extraction, image registration, and validity indices. By parcellating two different brain regions (posterior cingulate cortex) and (frontal pole) of the rhesus monkey, we demonstrate the efficacy of these alterations. The toolbox has been made public (https://github.com/bheAI/MonkeyCBP_CLI, https://github.com/bheAI/MonkeyCBP_GUI). It is expected that the toolbox can benefit the non-human primate neuroimaging community with high-throughput computation and low labor involvement.
| S-EPMC7198896 | biostudies-literature
Project description:IntroductionHuman cingulate cortex (CC) has been implicated in many functions, which is highly suggestive of the existence of functional subregions.MethodsIn this study, we used resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI) to parcellate the human cingulate cortex (CC) based on resting-state functional connectivity (rsFC) patterns and anatomical connectivity (AC) patterns, to analyze the rsFC patterns and the AC patterns of different subregions, and to recognize whether the parcellation results obtained by the two different methods were consistent.ResultsThe CC was divided into six functional subregions, including the anterior cingulate cortex, dorsal anterior midcingulate cortex, ventral anterior midcingulate cortex, posterior midcingulate cortex, dorsal posterior cingulate cortex, and ventral posterior cingulate cortex. The CC was also divided into ten anatomical subregions, termed Subregion 1 (S1) to Subregion 10 (S10). Each subregion showed specific connectivity patterns, although the functional subregions and the anatomical subregions were internally consistent.ConclusionsUsing different model MRI images, we established a parcellation scheme, which is internally consistent for the human CC, which may provide an in vivo guide for subregion-level studies and improve our understanding of this brain area at subregional levels.
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Project description:BackgroundChronic neuropathic pain in thalamic pain syndrome remains intractable. Its poor response is ascribed to destruction of the integrated neuromatrix in experience of pain. Deep brain stimulation is a promising technique to modulate activity of implicated structures. However, traditional approaches targeting sensori-motor substrates have failed to affect disability. The offending lesion in thalamic pain syndrome that almost invariably destroys sensory pain pathways may render these classical approaches ineffective. Instead, we hypothesize that targeting structures representing emotion and affective behavior-ventral striatum/anterior limb of the internal capsule, may alleviate disability.Methods/designWe present the design of our phase I randomized, double-blinded, sham-controlled, crossover trial that examines safety, feasibility and efficacy of our proposed approach. In our ongoing trial, we intend to enroll ten patients with thalamic pain syndrome. Following implantation, patients are randomized to receive active deep brain stimulation to the ventral striatum/anterior limb of the internal capsule or sham for 3 months, after which they are crossed over. The primary endpoint is Pain Disability Index. Other outcomes include visual analog scale, depression and anxiety inventories, quality of life, and functional neuroimaging.DiscussionDesigning trials of deep brain stimulation for pain is challenging owing to the ethical-scientific dilemma of introducing a control arm, complicated blinding, heterogeneous etiologies, patient expectations, and inadequate assessment of disability. The quality of evidence in the field is classified as level III (poor) because it mainly includes a multitude of uncontrolled case series reporting variable outcomes, with little regard for the placebo effect related to implantation. Without valid data on efficacy, use of deep brain stimulation for pain remains "off label". We present our trial design to discuss feasibility of conducting sham-controlled phase I studies that may represent significant refinement for the field. Double-blinding would reduce influence of patient expectations and therapeutic confusion amongst investigators. With a cross-over approach, the dilemma regarding including a control group can be mitigated. Use of homogeneous etiology, measurement of disability, depression and quality of life, besides pain perception, all represent strategies to evaluate efficacy rigorously. Functional imaging would serve to define mechanisms underlying observed effects and may help optimize future targeting.Trial registrationClinicaltrials.gov NCT01072656.
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