Publications

Journal Article
Suzanne N Haber, Anastasia Yendiki, and Saad Jbabdi. 2021. “Four Deep Brain Stimulation Targets for Obsessive-Compulsive Disorder: Are They Different?” Biol Psychiatry, 90, 10, Pp. 667-677.Abstract
Deep brain stimulation is a promising therapeutic approach for patients with treatment-resistant obsessive-compulsive disorder, a condition linked to abnormalities in corticobasal ganglia networks. Effective targets are placed in one of four subcortical areas with the goal of capturing prefrontal, anterior cingulate, and basal ganglia connections linked to the limbic system. These include the anterior limb of the internal capsule, the ventral striatum, the subthalamic nucleus, and a midbrain target. The goal of this review is to examine these 4 targets with respect to the similarities and differences of their connections. Following a review of the connections for each target based on anatomic studies in nonhuman primates, we examine the accuracy of diffusion magnetic resonance imaging tractography to replicate those connections in nonhuman primates, before evaluating the connections in the human brain based on diffusion magnetic resonance imaging tractography. Results demonstrate that the four targets generally involve similar connections, all of which are part of the internal capsule. Nonetheless, some connections are unique to each site. Delineating the similarities and differences across targets is a critical step for evaluating and comparing the effectiveness of each and how circuits contribute to the therapeutic outcome. It also underscores the importance that the terminology used for each target accurately reflects its position and its anatomic connections, so as to enable comparisons across clinical studies and for basic scientists to probe mechanisms underlying deep brain stimulation.
Susie Y Huang, Thomas Witzel, Boris Keil, Alina Scholz, Mathias Davids, Peter Dietz, Elmar Rummert, Rebecca Ramb, John E Kirsch, Anastasia Yendiki, Qiuyun Fan, Qiyuan Tian, Gabriel Ramos-Llordén, Hong-Hsi Lee, Aapo Nummenmaa, Berkin Bilgic, Kawin Setsompop, Fuyixue Wang, Alexandru V Avram, Michal Komlosh, Dan Benjamini, Kulam Najmudeen Magdoom, Sudhir Pathak, Walter Schneider, Dmitry S Novikov, Els Fieremans, Slimane Tounekti, Choukri Mekkaoui, Jean Augustinack, Daniel Berger, Alexander Shapson-Coe, Jeff LICHTMAN, Peter J Basser, Lawrence L Wald, and Bruce R Rosen. 2021. “Connectome 2.0: Developing the next-generation ultra-high gradient strength human MRI scanner for bridging studies of the micro-, meso- and macro-connectome.” Neuroimage, 243, Pp. 118530.Abstract
The first phase of the Human Connectome Project pioneered advances in MRI technology for mapping the macroscopic structural connections of the living human brain through the engineering of a whole-body human MRI scanner equipped with maximum gradient strength of 300 mT/m, the highest ever achieved for human imaging. While this instrument has made important contributions to the understanding of macroscale connectional topology, it has also demonstrated the potential of dedicated high-gradient performance scanners to provide unparalleled in vivo assessment of neural tissue microstructure. Building on the initial groundwork laid by the original Connectome scanner, we have now embarked on an international, multi-site effort to build the next-generation human 3T Connectome scanner (Connectome 2.0) optimized for the study of neural tissue microstructure and connectional anatomy across multiple length scales. In order to maximize the resolution of this in vivo microscope for studies of the living human brain, we will push the diffusion resolution limit to unprecedented levels by (1) nearly doubling the current maximum gradient strength from 300 mT/m to 500 mT/m and tripling the maximum slew rate from 200 T/m/s to 600 T/m/s through the design of a one-of-a-kind head gradient coil optimized to minimize peripheral nerve stimulation; (2) developing high-sensitivity multi-channel radiofrequency receive coils for in vivo and ex vivo human brain imaging; (3) incorporating dynamic field monitoring to minimize image distortions and artifacts; (4) developing new pulse sequences to integrate the strongest diffusion encoding and highest spatial resolution ever achieved in the living human brain; and (5) calibrating the measurements obtained from this next-generation instrument through systematic validation of diffusion microstructural metrics in high-fidelity phantoms and ex vivo brain tissue at progressively finer scales with accompanying diffusion simulations in histology-based micro-geometries. We envision creating the ultimate diffusion MRI instrument capable of capturing the complex multi-scale organization of the living human brain - from the microscopic scale needed to probe cellular geometry, heterogeneity and plasticity, to the mesoscopic scale for quantifying the distinctions in cortical structure and connectivity that define cyto- and myeloarchitectonic boundaries, to improvements in estimates of macroscopic connectivity.
Giorgia Grisot, Suzanne N Haber, and Anastasia Yendiki. 2021. “Diffusion MRI and anatomic tracing in the same brain reveal common failure modes of tractography.” Neuroimage, 239, Pp. 118300.Abstract
Anatomic tracing is recognized as a critical source of knowledge on brain circuitry that can be used to assess the accuracy of diffusion MRI (dMRI) tractography. However, most prior studies that have performed such assessments have used dMRI and tracer data from different brains and/or have been limited in the scope of dMRI analysis methods allowed by the data. In this work, we perform a quantitative, voxel-wise comparison of dMRI tractography and anatomic tracing data in the same macaque brain. An ex vivo dMRI acquisition with high angular resolution and high maximum b-value allows us to compare a range of q-space sampling, orientation reconstruction, and tractography strategies. The availability of tracing in the same brain allows us to localize the sources of tractography errors and to identify axonal configurations that lead to such errors consistently, across dMRI acquisition and analysis strategies. We find that these common failure modes involve geometries such as branching or turning, which cannot be modeled well by crossing fibers. We also find that the default thresholds that are commonly used in tractography correspond to rather conservative, low-sensitivity operating points. While deterministic tractography tends to have higher sensitivity than probabilistic tractography in that very conservative threshold regime, the latter outperforms the former as the threshold is relaxed to avoid missing true anatomical connections. On the other hand, the q-space sampling scheme and maximum b-value have less of an impact on accuracy. Finally, using scans from a set of additional macaque brains, we show that there is enough inter-individual variability to warrant caution when dMRI and tracer data come from different animals, as is often the case in the tractography validation literature. Taken together, our results provide insights on the limitations of current tractography methods and on the critical role that anatomic tracing can play in identifying potential avenues for improvement.
Alina Scholz, Robin Etzel, Markus W May, Mirsad Mahmutovic, Qiyuan Tian, Gabriel Ramos-Llordén, Chiara Maffei, Berkin Bilgiç, Thomas Witzel, Jason P Stockmann, Choukri Mekkaoui, Lawrence L Wald, Susie Yi Huang, Anastasia Yendiki, and Boris Keil. 2021. “A 48-channel receive array coil for mesoscopic diffusion-weighted MRI of ex vivo human brain on the 3 T connectome scanner.” Neuroimage, 238, Pp. 118256.Abstract
In vivo diffusion-weighted magnetic resonance imaging is limited in signal-to-noise-ratio (SNR) and acquisition time, which constrains spatial resolution to the macroscale regime. Ex vivo imaging, which allows for arbitrarily long scan times, is critical for exploring human brain structure in the mesoscale regime without loss of SNR. Standard head array coils designed for patients are sub-optimal for imaging ex vivo whole brain specimens. The goal of this work was to design and construct a 48-channel ex vivo whole brain array coil for high-resolution and high b-value diffusion-weighted imaging on a 3T Connectome scanner. The coil was validated with bench measurements and characterized by imaging metrics on an agar brain phantom and an ex vivo human brain sample. The two-segment coil former was constructed for a close fit to a whole human brain, with small receive elements distributed over the entire brain. Imaging tests including SNR and G-factor maps were compared to a 64-channel head coil designed for in vivo use. There was a 2.9-fold increase in SNR in the peripheral cortex and a 1.3-fold gain in the center when compared to the 64-channel head coil. The 48-channel ex vivo whole brain coil also decreases noise amplification in highly parallel imaging, allowing acceleration factors of approximately one unit higher for a given noise amplification level. The acquired diffusion-weighted images in a whole ex vivo brain specimen demonstrate the applicability and advantage of the developed coil for high-resolution and high b-value diffusion-weighted ex vivo brain MRI studies.
Aina Frau-Pascual, Jean Augustinack, Divya Varadarajan, Anastasia Yendiki, David H Salat, Bruce Fischl, and Iman Aganj. 2021. “Conductance-Based Structural Brain Connectivity in Aging and Dementia.” Brain Connect, 11, 7, Pp. 566-583.Abstract
Background: Structural brain connectivity has been shown to be sensitive to the changes that the brain undergoes during Alzheimer's disease (AD) progression. Methods: In this work, we used our recently proposed structural connectivity quantification measure derived from diffusion magnetic resonance imaging, which accounts for both direct and indirect pathways, to quantify brain connectivity in dementia. We analyzed data from the second phase of Alzheimer's Disease Neuroimaging Initiative and third release in the Open Access Series of Imaging Studies data sets to derive relevant information for the study of the changes that the brain undergoes in AD. We also compared these data sets to the Human Connectome Project data set, as a reference, and eventually validated externally on two cohorts of the European DTI Study in Dementia database. Results: Our analysis shows expected trends of mean conductance with respect to age and cognitive scores, significant age prediction values in aging data, and regional effects centered among subcortical regions, and cingulate and temporal cortices. Discussion: Results indicate that the conductance measure has prediction potential, especially for age, that age and cognitive scores largely overlap, and that this measure could be used to study effects such as anticorrelation in structural connections. Impact statement This work presents a methodology and a set of analyses that open new possibilities in the study of healthy and pathological aging. The methodology used here is sensitive to direct and indirect pathways in deriving brain connectivity measures from diffusion-weighted magnetic resonance imaging, and therefore provides information that many state-of-the-art methods do not account for. As a result, this technique may provide the research community with ways to detect subtle effects of healthy aging and Alzheimer's disease.
Maria Gabriela Figueiro Longo, Can Ozan Tan, Suk-Tak Chan, Jonathan Welt, Arman Avesta, Eva Ratai, Nathaniel David Mercaldo, Anastasia Yendiki, Jacqueline Namati, Isabel Chico-Calero, Blair A Parry, Lynn Drake, Rox Anderson, Terry Rauch, Ramon Diaz-Arrastia, Michael Lev, Jarone Lee, Michael Hamblin, Benjamin Vakoc, and Rajiv Gupta. 2020. “Effect of Transcranial Low-Level Light Therapy vs Sham Therapy Among Patients With Moderate Traumatic Brain Injury: A Randomized Clinical Trial.” JAMA Netw Open, 3, 9, Pp. e2017337.Abstract
Importance: Preclinical studies have shown that transcranial near-infrared low-level light therapy (LLLT) administered after traumatic brain injury (TBI) confers a neuroprotective response. Objectives: To assess the feasibility and safety of LLLT administered acutely after a moderate TBI and the neuroreactivity to LLLT through quantitative magnetic resonance imaging metrics and neurocognitive assessment. Design, Setting, and Participants: A randomized, single-center, prospective, double-blind, placebo-controlled parallel-group trial was conducted from November 27, 2015, through July 11, 2019. Participants included 68 men and women with acute, nonpenetrating, moderate TBI who were randomized to LLLT or sham treatment. Analysis of the response-evaluable population was conducted. Interventions: Transcranial LLLT was administered using a custom-built helmet starting within 72 hours after the trauma. Magnetic resonance imaging was performed in the acute (within 72 hours), early subacute (2-3 weeks), and late subacute (approximately 3 months) stages of recovery. Clinical assessments were performed concomitantly and at 6 months via the Rivermead Post-Concussion Questionnaire (RPQ), a 16-item questionnaire with each item assessed on a 5-point scale ranging from 0 (no problem) to 4 (severe problem). Main Outcomes and Measures: The number of participants to successfully and safely complete LLLT without any adverse events within the first 7 days after the therapy was the primary outcome measure. Secondary outcomes were the differential effect of LLLT on MR brain diffusion parameters and RPQ scores compared with the sham group. Results: Of the 68 patients who were randomized (33 to LLLT and 35 to sham therapy), 28 completed at least 1 LLLT session. No adverse events referable to LLLT were reported. Forty-three patients (22 men [51.2%]; mean [SD] age, 50.49 [17.44] years]) completed the study with at least 1 magnetic resonance imaging scan: 19 individuals in the LLLT group and 24 in the sham treatment group. Radial diffusivity (RD), mean diffusivity (MD), and fractional anisotropy (FA) showed significant time and treatment interaction at 3-month time point (RD: 0.013; 95% CI, 0.006 to 0.019; P < .001; MD: 0.008; 95% CI, 0.001 to 0.015; P = .03; FA: -0.018; 95% CI, -0.026 to -0.010; P < .001).The LLLT group had lower RPQ scores, but this effect did not reach statistical significance (time effect P = .39, treatment effect P = .61, and time × treatment effect P = .91). Conclusions and Relevance: In this randomized clinical trial, LLLT was feasible in all patients and did not exhibit any adverse events. Light therapy altered multiple diffusion tensor parameters in a statistically significant manner in the late subacute stage. This study provides the first human evidence to date that light therapy engages neural substrates that play a role in the pathophysiologic factors of moderate TBI and also suggests diffusion imaging as the biomarker of therapeutic response. Trial Registration: ClinicalTrials.gov Identifier: NCT02233413.
NA Hubbard, V Siless, IR Frosch, M Goncalves, N Lo, J Wang, CCC Bauer, K Conroy, E Cosby, A Hay, R Jones, M Pinaire, F Vaz De Souza, G Vergara, S Ghosh, A Henin, DR Hirshfeld-Becker, SG Hofmann, IM Rosso, RP Auerbach, DA Pizzagalli, A Yendiki, JDE Gabrieli, and S Whitfield-Gabrieli. 2020. “Brain function and clinical characterization in the Boston adolescent neuroimaging of depression and anxiety study.” Neuroimage Clin, 27, Pp. 102240.Abstract
We present a Human Connectome Project study tailored toward adolescent anxiety and depression. This study is one of the first studies of the Connectomes Related to Human Diseases initiative and is collecting structural, functional, and diffusion-weighted brain imaging data from up to 225 adolescents (ages 14-17 years), 150 of whom are expected to have a current diagnosis of an anxiety and/or depressive disorder. Comprehensive clinical and neuropsychological evaluations and longitudinal clinical data are also being collected. This article provides an overview of task functional magnetic resonance imaging (fMRI) protocols and preliminary findings (N = 140), as well as clinical and neuropsychological characterization of adolescents. Data collection is ongoing for an additional 85 adolescents, most of whom are expected to have a diagnosis of an anxiety and/or depressive disorder. Data from the first 140 adolescents are projected for public release through the National Institutes of Health Data Archive (NDA) with the timing of this manuscript. All other data will be made publicly-available through the NDA at regularly scheduled intervals. This article is intended to serve as an introduction to this project as well as a reference for those seeking to clinical, neurocognitive, and task fMRI data from this public resource.
Viviana Siless, Nicholas A Hubbard, Robert Jones, Jonathan Wang, Nicole Lo, Clemens CC Bauer, Mathias Goncalves, Isabelle Frosch, Daniel Norton, Genesis Vergara, Kristina Conroy, Flavia Vaz De Souza, Isabelle M Rosso, Aleena Hay Wickham, Elizabeth Ann Cosby, Megan Pinaire, Dina Hirshfeld-Becker, Diego A Pizzagalli, Aude Henin, Stefan G Hofmann, Randy P Auerbach, Satrajit Ghosh, John Gabrieli, Susan Whitfield-Gabrieli, and Anastasia Yendiki. 2020. “Image acquisition and quality assurance in the Boston Adolescent Neuroimaging of Depression and Anxiety study.” Neuroimage Clin, 26, Pp. 102242.Abstract
The Connectomes Related to Human Diseases (CRHD) initiative was developed with the Human Connectome Project (HCP) to provide high-resolution, open-access, multi-modal MRI data to better understand the neural correlates of human disease. Here, we present an introduction to a CRHD project, the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA) study, which is collecting multimodal neuroimaging, clinical, and neuropsychological data from 225 adolescents (ages 14-17), 150 of whom are expected to have a diagnosis of depression and/or anxiety. Our transdiagnostic recruitment approach samples the full spectrum of depressed/anxious symptoms and their comorbidity, consistent with NIMH Research Domain Criteria (RDoC). We focused on an age range that is critical for brain development and for the onset of mental illness. This project sought to harmonize imaging sequences, hardware, and functional tasks with other HCP studies, although some changes were made to canonical HCP methods to accommodate our study population and questions. We present a thorough overview of our imaging sequences, hardware, and scanning protocol. We detail similarities and differences between this study and other HCP studies. We evaluate structural-, diffusion-, and functional-image-quality measures that may be influenced by clinical factors (e.g., disorder, symptomatology). Signal-to-noise and motion estimates from the first 140 adolescents suggest minimal influence of clinical factors on image quality. We anticipate enrollment of an additional 85 participants, most of whom are expected to have a diagnosis of anxiety and/or depression. Clinical and neuropsychological data from the first 140 participants are currently freely available through the National Institute of Mental Health Data Archive (NDA).
Zhiqiang Sha, Amelia Versace, Kale E Edmiston, Jay Fournier, Simona Graur, Tsafrir Greenberg, João Paulo Lima Santos, Henry W Chase, Richelle S Stiffler, Lisa Bonar, Robert Hudak, Anastasia Yendiki, Benjamin D Greenberg, Steven Rasmussen, Hesheng Liu, Gregory Quirk, Suzanne Haber, and Mary L Phillips. 2020. “Functional disruption in prefrontal-striatal network in obsessive-compulsive disorder.” Psychiatry Res Neuroimaging, 300, Pp. 111081.Abstract
Obsessive-compulsive disorder (OCD) is characterized by intrusive thoughts and repetitive, compulsive behaviors. While a cortico-striatal-limbic network has been implicated in the pathophysiology of OCD, the neural correlates of this network in OCD are not well understood. In this study, we examined resting state functional connectivity among regions within the cortico-striatal-limbic OCD neural network, including the rostral anterior cingulate cortex, dorsolateral prefrontal cortex, ventrolateral prefrontal cortex, orbitofrontal cortex, ventromedial prefrontal cortex, amygdala, thalamus and caudate, in 44 OCD and 43 healthy participants. We then examined relationships between OCD neural network connectivity and OCD symptom severity in OCD participants. OCD relative to healthy participants showed significantly greater connectivity between the left caudate and bilateral dorsolateral prefrontal cortex. We also found a positive correlation between left caudate-bilateral dorsolateral prefrontal cortex connectivity and depression scores in OCD participants, such that greater positive connectivity was associated with more severe symptoms. This study makes a significant contribution to our understanding of functional networks and their relationship with depression in OCD.
Robert Jones, Giorgia Grisot, Jean Augustinack, Caroline Magnain, David A Boas, Bruce Fischl, Hui Wang, and Anastasia Yendiki. 2020. “Insight into the fundamental trade-offs of diffusion MRI from polarization-sensitive optical coherence tomography in ex vivo human brain.” Neuroimage, 214, Pp. 116704.Abstract
In the first study comparing high angular resolution diffusion MRI (dMRI) in the human brain to axonal orientation measurements from polarization-sensitive optical coherence tomography (PSOCT), we compare the accuracy of orientation estimates from various dMRI sampling schemes and reconstruction methods. We find that, if the reconstruction approach is chosen carefully, single-shell dMRI data can yield the same accuracy as multi-shell data, and only moderately lower accuracy than a full Cartesian-grid sampling scheme. Our results suggest that current dMRI reconstruction approaches do not benefit substantially from ultra-high b-values or from very large numbers of diffusion-encoding directions. We also show that accuracy remains stable across dMRI voxel sizes of 1 ​mm or smaller but degrades at 2 ​mm, particularly in areas of complex white-matter architecture. We also show that, as the spatial resolution is reduced, axonal configurations in a dMRI voxel can no longer be modeled as a small set of distinct axon populations, violating an assumption that is sometimes made by dMRI reconstruction techniques. Our findings have implications for in vivo studies and illustrate the value of PSOCT as a source of ground-truth measurements of white-matter organization that does not suffer from the distortions typical of histological techniques.
Viviana Siless, Juliet Y Davidow, Jared Nielsen, Qiuyun Fan, Trey Hedden, Marisa Hollinshead, Elizabeth Beam, Constanza M Vidal Bustamante, Megan C Garrad, Rosario Santillana, Emily E Smith, Aya Hamadeh, Jenna Snyder, Michelle K Drews, Koene RA Van Dijk, Margaret Sheridan, Leah H Somerville, and Anastasia Yendiki. 2020. “Registration-free analysis of diffusion MRI tractography data across subjects through the human lifespan.” Neuroimage, 214, Pp. 116703.Abstract
Diffusion MRI tractography produces massive sets of streamlines that need to be clustered into anatomically meaningful white-matter bundles. Conventional clustering techniques group streamlines based on their proximity in Euclidean space. We have developed AnatomiCuts, an unsupervised method for clustering tractography streamlines based on their neighboring anatomical structures, rather than their coordinates in Euclidean space. In this work, we show that the anatomical similarity metric used in AnatomiCuts can be extended to find corresponding clusters across subjects and across hemispheres, without inter-subject or inter-hemispheric registration. Our proposed approach enables group-wise tract cluster analysis, as well as studies of hemispheric asymmetry. We evaluate our approach on data from the pilot MGH-Harvard-USC Lifespan Human Connectome project, showing improved correspondence in tract clusters across 184 subjects aged 8-90. Our method shows up to 38% improvement in the overlap of corresponding clusters when comparing subjects with large age differences. The techniques presented here do not require registration to a template and can thus be applied to populations with large inter-subject variability, e.g., due to brain development, aging, or neurological disorders.
Suzanne N Haber, Wei Tang, Eun Young Choi, Anastasia Yendiki, Hesheng Liu, Saad Jbabdi, Amelia Versace, and Mary Phillips. 2020. “Circuits, Networks, and Neuropsychiatric Disease: Transitioning From Anatomy to Imaging.” Biol Psychiatry, 87, 4, Pp. 318-327.Abstract
Since the development of cellular and myelin stains, anatomy has formed the foundation for understanding circuitry in the human brain. However, recent functional and structural studies using magnetic resonance imaging have taken the lead in this endeavor. These innovative and noninvasive approaches have the advantage of studying connectivity patterns under different conditions directly in the human brain. They demonstrate dynamic and structural changes within and across networks linked to normal function and to a wide range of psychiatric illnesses. However, these indirect methods are unable to link networks to the hardwiring that underlies them. In contrast, anatomic invasive experimental studies can. Following a brief review of prefrontal cortical, anterior cingulate, and striatal connections and the different methodologies used, this article discusses how data from anatomic studies can help inform how hardwired connections are linked to the functional and structural networks identified in imaging studies.
Zhiqiang Sha, Kale E Edmiston, Amelia Versace, Jay C Fournier, Simona Graur, Tsafrir Greenberg, João Paulo Lima Santos, Henry W Chase, Richelle S Stiffler, Lisa Bonar, Robert Hudak, Anastasia Yendiki, Benjamin D Greenberg, Steven Rasmussen, Hesheng Liu, Gregory Quirk, Suzanne Haber, and Mary L Phillips. 2020. “Functional Disruption of Cerebello-thalamo-cortical Networks in Obsessive-Compulsive Disorder.” Biol Psychiatry Cogn Neurosci Neuroimaging, 5, 4, Pp. 438-447.Abstract
BACKGROUND: Obsessive-compulsive disorder (OCD) is characterized by intrusive thoughts and repetitive, compulsive behaviors. Neuroimaging studies have implicated altered connectivity among the functional networks of the cerebral cortex in the pathophysiology of OCD. However, there has been no comprehensive investigation of the cross-talk between the cerebellum and functional networks in the cerebral cortex. METHODS: This functional neuroimaging study was completed by 44 adult participants with OCD and 43 healthy control participants. We performed large-scale data-driven brain network analysis to identify functional connectivity patterns using resting-state functional magnetic resonance imaging data. RESULTS: Participants with OCD showed lower functional connectivity within the somatomotor network and greater functional connectivity among the somatomotor network, cerebellum, and subcortical network (e.g., thalamus and pallidum; all p < .005). Network-based statistics analyses demonstrated one component comprising connectivity within the somatomotor network that showed lower connectivity and a second component comprising connectivity among the somatomotor network, and motor regions in particular, and the cerebellum that showed greater connectivity in participants with OCD relative to healthy control participants. In participants with OCD, abnormal connectivity across both network-based statistics-derived components positively correlated with OCD symptom severity (p = .006). CONCLUSIONS: To our knowledge, this study is the first comprehensive investigation of large-scale network alteration across the cerebral cortex, subcortical regions, and cerebellum in OCD. Our findings highlight a critical role of the cerebellum in the pathophysiology of OCD.
Lilla Zöllei, Camilo Jaimes, Elie Saliba, Ellen P Grant, and Anastasia Yendiki. 2019. “TRActs constrained by UnderLying INfant anatomy (TRACULInA): An automated probabilistic tractography tool with anatomical priors for use in the newborn brain.” Neuroimage, 199, Pp. 1-17.Abstract
The ongoing myelination of white-matter fiber bundles plays a significant role in brain development. However, reliable and consistent identification of these bundles from infant brain MRIs is often challenging due to inherently low diffusion anisotropy, as well as motion and other artifacts. In this paper we introduce a new tool for automated probabilistic tractography specifically designed for newborn infants. Our tool incorporates prior information about the anatomical neighborhood of white-matter pathways from a training data set. In our experiments, we evaluate this tool on data from both full-term and prematurely born infants and demonstrate that it can reconstruct known white-matter tracts in both groups robustly, even in the presence of differences between the training set and study subjects. Additionally, we evaluate it on a publicly available large data set of healthy term infants (UNC Early Brain Development Program). This paves the way for performing a host of sophisticated analyses in newborns that we have previously implemented for the adult brain, such as pointwise analysis along tracts and longitudinal analysis, in both health and disease.
Wei Tang, Saad Jbabdi, Ziyi Zhu, Michiel Cottaar, Giorgia Grisot, Julia F Lehman, Anastasia Yendiki, and Suzanne N Haber. 2019. “A connectional hub in the rostral anterior cingulate cortex links areas of emotion and cognitive control.” Elife, 8.Abstract
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.
A Versace, S Graur, T Greenberg, JP Lima Santos, HW Chase, L Bonar, RS Stiffler, R Hudak, Tae Kim, A Yendiki, B Greenberg, S Rasmussen, H Liu, S Haber, and ML Phillips. 2019. “Reduced focal fiber collinearity in the cingulum bundle in adults with obsessive-compulsive disorder.” Neuropsychopharmacology, 44, 7, Pp. 1182-1188.Abstract
Obsessive-compulsive disorder (OCD) is a disabling condition, often associated with a chronic course. Given its role in attentional control, decision-making, and emotional regulation, the anterior cingulate cortex is considered to have a key role in the pathophysiology of the disorder. Notably, the cingulum bundle, being the major white matter tract connecting to this region, has been historically a target for the surgical treatment of intractable OCD. In this study, we aimed to identify the extent to which focal-more than diffuse-abnormalities in fiber collinearity of the cingulum bundle could distinguish 48 adults with OCD (mean age [SD] = 23.3 [4.5] years; F/M = 30/18) from 45 age- and sex-matched healthy control adults (CONT; mean age [SD] = 23.2 [3.8] years; F/M = 28/17) and further examine if these abnormalities correlated with symptom severity. Use of tract-profiles rather than a conventional diffusion imaging approach allowed us to characterize white matter microstructural properties along (100 segments), as opposed to averaging these measures across, the entire tract. To account for these 100 different segments of the cingulum bundle, a repeated measures analysis of variance revealed a main effect of group (OCD < CONT; F = 5.3; P = 0.024) upon fractional anisotropy (FA, a measure of fiber collinearity and/or white matter integrity), in the cingulum bundle, bilaterally. Further analyses revealed that these abnormalities were focal (middle portion) within the left and right cingulum bundle, although did not correlate with symptom severity in OCD. Findings indicate that focal abnormalities in connectivity between the anterior cingulate cortex and other prefrontal cortical regions may represent neural mechanisms of OCD.
Aina Frau-Pascual, Morgan Fogarty, Bruce Fischl, Anastasia Yendiki, and Iman Aganj. 2019. “Quantification of structural brain connectivity via a conductance model.” Neuroimage, 189, Pp. 485-496.Abstract
Connectomics has proved promising in quantifying and understanding the effects of development, aging and an array of diseases on the brain. In this work, we propose a new structural connectivity measure from diffusion MRI that allows us to incorporate direct brain connections, as well as indirect ones that would not be otherwise accounted for by standard techniques and that may be key for the better understanding of function from structure. From our experiments on the Human Connectome Project dataset, we find that our measure of structural connectivity better correlates with functional connectivity than streamline tractography does, meaning that it provides new structural information related to function. Through additional experiments on the ADNI-2 dataset, we demonstrate the ability of this new measure to better discriminate different stages of Alzheimer's disease. Our findings suggest that this measure is useful in the study of the normal brain structure, and for quantifying the effects of disease on the brain structure.
Lars M Rimol, Violeta L Botellero, Knut J Bjuland, Gro CC Løhaugen, Stian Lydersen, Kari Anne I Evensen, Ann-Mari Brubakk, Live Eikenes, Marit S Indredavik, Marit Martinussen, Anastasia Yendiki, Asta K Håberg, and Jon Skranes. 2019. “Reduced white matter fractional anisotropy mediates cortical thickening in adults born preterm with very low birthweight.” Neuroimage, 188, Pp. 217-227.Abstract
Development of the cerebral cortex may be affected by aberrant white matter development. Preterm birth with very low birth weight (VLBW) has been associated with reduced fractional anisotropy of white matter and changes in cortical thickness and surface area. We use a new methodological approach to combine white and gray matter data and test the hypothesis that white matter injury is primary, and acts as a mediating factor for concomitant gray matter aberrations, in the developing VLBW brain. T1 and dMRI data were obtained from 47 young adults born preterm with VLBW and 73 term-born peers (mean age = 26). Cortical thickness was measured across the cortical mantle and compared between the groups, using the FreeSurfer software suite. White matter pathways were reconstructed with the TRACULA software and projected to their cortical end regions, where cortical thickness was averaged. In the VLBW group, cortical thickness was increased in anteromedial frontal, orbitofrontal, and occipital regions, and fractional anisotropy (FA) was reduced in frontal lobe pathways, indicating compromised white matter integrity. Statistical mediation analyses demonstrated that increased cortical thickness in the frontal regions was mediated by reduced FA in the corpus callosum forceps minor, consistent with the notion that white matter injury can disrupt frontal lobe cortical development. Combining statistical mediation analysis with pathway projection onto the cortical surface offers a powerful novel tool to investigate how cortical regions are differentially affected by white matter injury.
Brian L Edlow, Dirk C Keene, Daniel P Perl, Diego Iacono, Rebecca D Folkerth, William Stewart, Christine L MacDonald, Jean Augustinack, Ramon Diaz-Arrastia, Camilo Estrada, Elissa Flannery, Wayne A Gordon, Thomas J Grabowski, Kelly Hansen, Jeanne Hoffman, Christopher Kroenke, Eric B Larson, Patricia Lee, Azma Mareyam, Jennifer A McNab, Jeanne McPhee, Allison L Moreau, Anne Renz, KatieRose Richmire, Allison Stevens, Cheuk Y Tang, Lee S Tirrell, Emily H Trittschuh, Andre van der Kouwe, Ani Varjabedian, Lawrence L Wald, Ona Wu, Anastasia Yendiki, Liza Young, Lilla Zöllei, Bruce Fischl, Paul K Crane, and Kristen Dams-O'Connor. 2018. “Multimodal Characterization of the Late Effects of Traumatic Brain Injury: A Methodological Overview of the Late Effects of Traumatic Brain Injury Project.” J Neurotrauma, 35, 14, Pp. 1604-1619.Abstract
Epidemiological studies suggest that a single moderate-to-severe traumatic brain injury (TBI) is associated with an increased risk of neurodegenerative disease, including Alzheimer's disease (AD) and Parkinson's disease (PD). Histopathological studies describe complex neurodegenerative pathologies in individuals exposed to single moderate-to-severe TBI or repetitive mild TBI, including chronic traumatic encephalopathy (CTE). However, the clinicopathological links between TBI and post-traumatic neurodegenerative diseases such as AD, PD, and CTE remain poorly understood. Here, we describe the methodology of the Late Effects of TBI (LETBI) study, whose goals are to characterize chronic post-traumatic neuropathology and to identify in vivo biomarkers of post-traumatic neurodegeneration. LETBI participants undergo extensive clinical evaluation using National Institutes of Health TBI Common Data Elements, proteomic and genomic analysis, structural and functional magnetic resonance imaging (MRI), and prospective consent for brain donation. Selected brain specimens undergo ultra-high resolution ex vivo MRI and histopathological evaluation including whole-mount analysis. Co-registration of ex vivo and in vivo MRI data enables identification of ex vivo lesions that were present during life. In vivo signatures of postmortem pathology are then correlated with cognitive and behavioral data to characterize the clinical phenotype(s) associated with pathological brain lesions. We illustrate the study methods and demonstrate proof of concept for this approach by reporting results from the first LETBI participant, who despite the presence of multiple in vivo and ex vivo pathoanatomic lesions had normal cognition and was functionally independent until her mid-80s. The LETBI project represents a multidisciplinary effort to characterize post-traumatic neuropathology and identify in vivo signatures of postmortem pathology in a prospective study.
Rachel R Romeo, Joshua Segaran, Julia A Leonard, Sydney T Robinson, Martin R West, Allyson P Mackey, Anastasia Yendiki, Meredith L Rowe, and John DE Gabrieli. 2018. “Language Exposure Relates to Structural Neural Connectivity in Childhood.” J Neurosci, 38, 36, Pp. 7870-7877.Abstract
Neuroscience research has elucidated broad relationships between socioeconomic status (SES) and young children's brain structure, but there is little mechanistic knowledge about specific environmental factors that are associated with specific variation in brain structure. One environmental factor, early language exposure, predicts children's linguistic and cognitive skills and later academic achievement, but how language exposure relates to neuroanatomy is unknown. By measuring the real-world language exposure of young children (ages 4-6 years, 27 male/13 female), we confirmed the preregistered hypothesis that greater adult-child conversational experience, independent of SES and the sheer amount of adult speech, is related to stronger, more coherent white matter connectivity in the left arcuate and superior longitudinal fasciculi on average, and specifically near their anterior termination at Broca's area in left inferior frontal cortex. Fractional anisotropy of significant tract subregions mediated the relationship between conversational turns and children's language skills and indicated a neuroanatomical mechanism underlying the SES "language gap." whole-brain analyses revealed that language exposure was not related to any other white matter tracts, indicating the specificity of this relationship. Results suggest that the development of dorsal language tracts is environmentally influenced, specifically by early, dialogic interaction. Furthermore, these findings raise the possibility that early intervention programs aiming to ameliorate disadvantages in development due to family SES may focus on increasing children's conversational exposure to capitalize on the early neural plasticity underlying cognitive development. Over the last decade, cognitive neuroscience has highlighted the detrimental impact of disadvantaged backgrounds on young children's brain structure. However, to intervene effectively, we must know which proximal aspects of the environmental aspects are most strongly related to neural development. The present study finds that young children's real-world language exposure, and specifically the amount of adult-child conversation, correlates with the strength of connectivity in the left hemisphere white matter pathway connecting two canonical language regions, independent of socioeconomic status and the sheer volume of adult speech. These findings suggest that early intervention programs aiming to close the achievement gap may focus on increasing children's conversational exposure to capitalize on the early neural plasticity underlying cognitive development.

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