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Dive into the research topics where Anastasia Yendiki is active.

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Featured researches published by Anastasia Yendiki.


NeuroImage | 2014

Spurious group differences due to head motion in a diffusion MRI study

Anastasia Yendiki; Kami Koldewyn; Sita Kakunoori; Nancy Kanwisher; Bruce Fischl

Diffusion-weighted MRI (DW-MRI) has become a popular imaging modality for probing the microstructural properties of white matter and comparing them between populations in vivo. However, the contrast in DW-MRI arises from the microscopic random motion of water molecules in brain tissues, which makes it particularly sensitive to macroscopic head motion. Although this has been known since the introduction of DW-MRI, most studies that use this modality for group comparisons do not report measures of head motion for each group and rely on registration-based correction methods that cannot eliminate the full effects of head motion on the DW-MRI contrast. In this work we use data from children with autism and typically developing children to investigate the effects of head motion on differences in anisotropy and diffusivity measures between groups. We show that group differences in head motion can induce group differences in DW-MRI measures, and that this is the case even when comparing groups that include control subjects only, where no anisotropy or diffusivity differences are expected. We also show that such effects can be more prominent in some white-matter pathways than others, and that they can be ameliorated by including motion as a nuisance regressor in the analyses. Our results demonstrate the importance of taking head motion into account in any population study where one group might exhibit more head motion than the other.


The Journal of Neuroscience | 2013

Tracking the Roots of Reading Ability: White Matter Volume and Integrity Correlate with Phonological Awareness in Prereading and Early-Reading Kindergarten Children

Zeynep M. Saygin; Elizabeth S. Norton; David E. Osher; Sara D. Beach; Abigail Cyr; Ola Ozernov-Palchik; Anastasia Yendiki; Bruce Fischl; Nadine Gaab; John D. E. Gabrieli

Developmental dyslexia, an unexplained difficulty in learning to read, has been associated with alterations in white matter organization as measured by diffusion-weighted imaging. It is unknown, however, whether these differences in structural connectivity are related to the cause of dyslexia or if they are consequences of reading difficulty (e.g., less reading experience or compensatory brain organization). Here, in 40 kindergartners who had received little or no reading instruction, we examined the relation between behavioral predictors of dyslexia and white matter organization in left arcuate fasciculus, inferior longitudinal fasciculus, and the parietal portion of the superior longitudinal fasciculus using probabilistic tractography. Higher composite phonological awareness scores were significantly and positively correlated with the volume of the arcuate fasciculus, but not with other tracts. Two other behavioral predictors of dyslexia, rapid naming and letter knowledge, did not correlate with volumes or diffusion values in these tracts. The volume and fractional anisotropy of the left arcuate showed a particularly strong positive correlation with a phoneme blending test. Whole-brain regressions of behavioral scores with diffusion measures confirmed the unique relation between phonological awareness and the left arcuate. These findings indicate that the left arcuate fasciculus, which connects anterior and posterior language regions of the human brain and which has been previously associated with reading ability in older individuals, is already smaller and has less integrity in kindergartners who are at risk for dyslexia because of poor phonological awareness. These findings suggest a structural basis of behavioral risk for dyslexia that predates reading instruction.


Schizophrenia Bulletin | 2012

Associations of Cortical Thickness and Cognition in Patients With Schizophrenia and Healthy Controls

Stefan Ehrlich; Stefan Brauns; Anastasia Yendiki; Beng-Choon Ho; Vince D. Calhoun; S. Charles Schulz; Randy L. Gollub; Scott R. Sponheim

Previous studies have found varying relationships between cognitive functioning and brain volumes in patients with schizophrenia. However, cortical thickness may more closely reflect cytoarchitectural characteristics than gray matter density or volume estimates. Here, we aimed to compare associations between regional variation in cortical thickness and executive functions, memory, as well as verbal and spatial processing in patients with schizophrenia and healthy controls (HCs). We obtained magnetic resonance imaging and neuropsychological data for 131 patients and 138 matched controls. Automated cortical pattern matching methods allowed testing for associations with cortical thickness estimated as the shortest distance between the gray/white matter border and the pial surface at thousands of points across the entire cortical surface. Two independent measures of working memory showed robust associations with cortical thickness in lateral prefrontal cortex in HCs, whereas patients exhibited associations between working memory and cortical thickness in the right middle and superior temporal lobe. This study provides additional evidence for a disrupted structure-function relationship in schizophrenia. In line with the prefrontal inefficiency hypothesis, schizophrenia patients may engage a larger compensatory network of brain regions other than frontal cortex to recall and manipulate verbal material in working memory.


NeuroImage | 2009

The COMT Val108/158Met Polymorphism and Medial Temporal Lobe Volumetry in Patients with Schizophrenia and Healthy Adults

Stefan Ehrlich; Eric M. Morrow; Joshua L. Roffman; Stuart Wallace; Melissa Naylor; H. Jeremy Bockholt; Antonia Lundquist; Anastasia Yendiki; Beng-Choon Ho; Tonya White; Dara S. Manoach; Vincent P. Clark; Vince D. Calhoun; Randy L. Gollub; Daphne J. Holt

Abnormalities of the medial temporal lobe have been consistently demonstrated in schizophrenia. A common functional polymorphism, Val108/158Met, in the putative schizophrenia susceptibility gene, catechol-O-methyltransferase (COMT), has been shown to influence medial temporal lobe function. However, the effects of this polymorphism on volumes of medial temporal lobe structures, particularly in patients with schizophrenia, are less clear. Here we measured the effects of COMT Val108/158Met genotype on the volume of two regions within the medial temporal lobe, the amygdala and hippocampus, in patients with schizophrenia and healthy control subjects. We obtained MRI and genotype data for 98 schizophrenic patients and 114 matched controls. An automated atlas-based segmentation algorithm was used to generate volumetric measures of the amygdala and hippocampus. Regression analyses included COMT met allele load as an additive effect, and also controlled for age, intracranial volume, gender and acquisition site. Across patients and controls, each copy of the COMT met allele was associated on average with a 2.6% increase in right amygdala volume, a 3.8% increase in left amygdala volume and a 2.2% increase in right hippocampus volume. There were no effects of COMT genotype on volumes of the whole brain and prefrontal regions. Thus, the COMT Val108/158Met polymorphism was shown to influence medial temporal lobe volumes in a linear-additive manner, mirroring its effect on dopamine catabolism. Taken together with previous work, our data support a model in which lower COMT activity, and a resulting elevation in extracellular dopamine levels, stimulates growth of medial temporal lobe structures.


Proceedings of the National Academy of Sciences of the United States of America | 2014

Differences in the right inferior longitudinal fasciculus but no general disruption of white matter tracts in children with autism spectrum disorder

Kami Koldewyn; Anastasia Yendiki; Sarah Weigelt; Hyowon Gweon; Joshua B. Julian; Hilary Richardson; Caitlin Malloy; Rebecca Saxe; Bruce Fischl; Nancy Kanwisher

Significance One of the most accepted brain “signatures” of autism spectrum disorder (ASD) is a reduction in the integrity of long-range white-matter fiber tracts. Here, we assessed known white matter tracts in children with ASD by using diffusion-weighted imaging. In contrast to most prior studies, we carefully matched for head motion between groups. When data quality was matched, there was no evidence of widespread changes in white-matter tracts in the ASD group. Instead, differences were present in only one tract, the right inferior longitudinal fasciculus. These data challenge the idea that widespread changes in white-matter integrity are a signature of ASD and highlight the importance of matching for data quality in future diffusion studies of ASD and other clinical disorders. One of the most widely cited features of the neural phenotype of autism is reduced “integrity” of long-range white matter tracts, a claim based primarily on diffusion imaging studies. However, many prior studies have small sample sizes and/or fail to address differences in data quality between those with autism spectrum disorder (ASD) and typical participants, and there is little consensus on which tracts are affected. To overcome these problems, we scanned a large sample of children with autism (n = 52) and typically developing children (n = 73). Data quality was variable, and worse in the ASD group, with some scans unusable because of head motion artifacts. When we follow standard data analysis practices (i.e., without matching head motion between groups), we replicate the finding of lower fractional anisotropy (FA) in multiple white matter tracts. However, when we carefully match data quality between groups, all these effects disappear except in one tract, the right inferior longitudinal fasciculus (ILF). Additional analyses showed the expected developmental increases in the FA of fiber tracts within ASD and typical groups individually, demonstrating that we had sufficient statistical power to detect known group differences. Our data challenge the widely claimed general disruption of white matter tracts in autism, instead implicating only one tract, the right ILF, in the ASD phenotype.


Schizophrenia Bulletin | 2013

Cumulative Genetic Risk and Prefrontal Activity in Patients With Schizophrenia

Esther Walton; Jessica A. Turner; Randy L. Gollub; Dara S. Manoach; Anastasia Yendiki; Beng-Choon Ho; Scott R. Sponheim; Vince D. Calhoun; Stefan Ehrlich

The lack of consistency of genetic associations in highly heritable mental illnesses, such as schizophrenia, remains a challenge in molecular psychiatry. Because clinical phenotypes for psychiatric disorders are often ill defined, considerable effort has been made to relate genetic polymorphisms to underlying physiological aspects of schizophrenia (so called intermediate phenotypes), that may be more reliable. Given the polygenic etiology of schizophrenia, the aim of this work was to form a measure of cumulative genetic risk and study its effect on neural activity during working memory (WM) using functional magnetic resonance imaging. Neural activity during the Sternberg Item Recognition Paradigm was measured in 79 schizophrenia patients and 99 healthy controls. Participants were genotyped, and a genetic risk score (GRS), which combined the additive effects of 41 single-nucleotide polymorphisms (SNPs) from 34 risk genes for schizophrenia, was calculated. These risk SNPs were chosen according to the continuously updated meta-analysis of genetic studies on schizophrenia available at www.schizophreniaresearchforum.org. We found a positive relationship between GRS and left dorsolateral prefrontal cortex inefficiency during WM processing. GRS was not correlated with age, performance, intelligence, or medication effects and did not differ between acquisition sites, gender, or diagnostic groups. Our study suggests that cumulative genetic risk, combining the impact of many genes with small effects, is associated with a known brain-based intermediate phenotype for schizophrenia. The GRS approach could provide an advantage over studying single genes in studies focusing on the genetic basis of polygenic conditions such as neuropsychiatric disorders.


Magnetic Resonance in Medicine | 2012

Accelerated diffusion spectrum imaging with compressed sensing using adaptive dictionaries

Berkin Bilgic; Kawin Setsompop; Julien Cohen-Adad; Anastasia Yendiki; Lawrence L. Wald; Elfar Adalsteinsson

Diffusion spectrum imaging offers detailed information on complex distributions of intravoxel fiber orientations at the expense of extremely long imaging times (∼1 h). Recent work by Menzel et al. demonstrated successful recovery of diffusion probability density functions from sub‐Nyquist sampled q‐space by imposing sparsity constraints on the probability density functions under wavelet and total variation transforms. As the performance of compressed sensing reconstruction depends strongly on the level of sparsity in the selected transform space, a dictionary specifically tailored for diffusion probability density functions can yield higher fidelity results. To our knowledge, this work is the first application of adaptive dictionaries in diffusion spectrum imaging, whereby we reduce the scan time of whole brain diffusion spectrum imaging acquisition from 50 to 17 min while retaining high image quality. In vivo experiments were conducted with the 3T Connectome MRI. The root‐mean‐square error of the reconstructed “missing” diffusion images were calculated by comparing them to a gold standard dataset (obtained from acquiring 10 averages of diffusion images in these missing directions). The root‐mean‐square error from the proposed reconstruction method is up to two times lower than that of Menzel et al.s method and is actually comparable to that of the fully‐sampled 50 minute scan. Comparison of tractography solutions in 18 major white‐matter pathways also indicated good agreement between the fully‐sampled and 3‐fold accelerated reconstructions. Further, we demonstrate that a dictionary trained using probability density functions from a single slice of a particular subject generalizes well to other slices from the same subject, as well as to slices from other subjects. Magn Reson Med, 2012.


NeuroImage | 2011

DISC1 is associated with cortical thickness and neural efficiency

Stefan Brauns; Randy L. Gollub; Joshua L. Roffman; Anastasia Yendiki; Beng-Choon Ho; Thomas H. Wassink; Andreas Heinz; Stefan Ehrlich

BACKGROUND Disrupted in schizophrenia 1 (DISC1) is known to play a major role during brain development and is a candidate gene for schizophrenia. Cortical thickness is highly heritable and several MRI studies have shown widespread reductions of cortical thickness in patients with schizophrenia. Here, we investigated the effects of variation in DISC1 on cortical thickness. In a subsequent analysis we tested whether the identified DISC1 risk variant is also associated with neural activity during working memory functioning. METHODS We acquired structural MRI (sMRI), functional MRI (fMRI) and genotype data from 96 healthy volunteers. Separate cortical statistical maps for five single nucleotide polymorphisms (SNP) of DISC1 were generated to detect differences of cortical thickness in genotype groups across the entire cortical surface. Working-memory related load-dependent activation was measured during the Sternberg Item Recognition Paradigm and analyzed using a region-of-interest approach. RESULTS Phe allele carriers of the DISC1 SNP Leu607Phe had significantly reduced cortical thickness in the left supramarginal gyrus compared to Leu/Leu homozygotes. Neural activity in the left dorsolateral prefrontal cortex (DLPFC) during working memory task was increased in Phe allele carriers, whereas working memory performance did not differ between genotype groups. CONCLUSIONS This study provides convergent evidence for the effect of DISC1 risk variants on two independent brain-based intermediate phenotypes of schizophrenia. The same risk variant was associated with cortical thickness reductions and signs of neural inefficiency during a working memory task. Our findings provide further evidence for a neurodevelopmental model of schizophrenia.


Schizophrenia Research | 2010

Gray matter volume reduction in rostral middle frontal gyrus in patients with chronic schizophrenia

Zora Kikinis; James H. Fallon; Margaret A. Niznikiewicz; Paul G. Nestor; C. Davidson; L.H. Bobrow; Paula E. Pelavin; Bruce Fischl; Anastasia Yendiki; Robert W. McCarley; Ron Kikinis; Marek Kubicki; Martha Elizabeth Shenton

The dorsolateral prefrontal cortex (DLPFC) is a brain region that has figured prominently in studies of schizophrenia and working memory, yet the exact neuroanatomical localization of this brain region remains to be defined. DLPFC primarily involves the superior frontal gyrus and middle frontal gyrus (MFG). The latter, however is not a single neuroanatomical entity but instead is comprised of rostral (anterior, middle, and posterior) and caudal regions. In this study we used structural MRI to develop a method for parcellating MFG into its component parts. We focused on this region of DLPFC because it includes BA46, a region involved in working memory. We evaluated volume differences in MFG in 20 patients with chronic schizophrenia and 20 healthy controls. Mid-rostral MFG (MR-MFG) was delineated within the rostral MFG using anterior and posterior neuroanatomical landmarks derived from cytoarchitectonic definitions of BA46. Gray matter volumes of MR-MFG were then compared between groups, and a significant reduction in gray matter volume was observed (p<0.008), but not in other areas of MFG (i.e., anterior or posterior rostral MFG, or caudal regions of MFG). Our results demonstrate that volumetric alterations in MFG gray matter are localized exclusively to MR-MFG. 3D reconstructions of the cortical surface made it possible to follow MFG into its anterior part, where other approaches have failed. This method of parcellation offers a more precise way of measuring MR-MFG that will likely be important in further documentation of DLPFC anomalies in schizophrenia.


Physics in Medicine and Biology | 2004

A comparison of rotation- and blob-based system models for 3D SPECT with depth-dependent detector response

Anastasia Yendiki; Jeffrey A. Fessler

We compare two different implementations of a 3D SPECT system model for iterative reconstruction, both of which compensate for non-uniform photon attenuation and depth-dependent system response. One implementation performs fast rotation of images represented using a basis of rectangular voxels, whereas the other represents images using a basis of rotationally symmetric volume elements. In our simulations the blob-based approach was found to slightly outperform the rotation-based one in terms of the bias-variance tradeoff in the reconstructed images. Their difference can be significant, however, in terms of computational load. The rotation-based method is faster for many typical SPECT reconstruction problems, but the blob-based one can be better-suited to cases where the reconstruction algorithm needs to process one volume element at a time.

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Stefan Ehrlich

Dresden University of Technology

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