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Dive into the research topics where Allison Stevens is active.

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Featured researches published by Allison Stevens.


Nature | 2014

Transcriptional landscape of the prenatal human brain

Jeremy A. Miller; Song Lin Ding; Susan M. Sunkin; Kimberly A. Smith; Lydia Ng; Aaron Szafer; Amanda Ebbert; Zackery L. Riley; Joshua J. Royall; Kaylynn Aiona; James M. Arnold; Crissa Bennet; Darren Bertagnolli; Krissy Brouner; Stephanie Butler; Shiella Caldejon; Anita Carey; Christine Cuhaciyan; Rachel A. Dalley; Nick Dee; Tim Dolbeare; Benjamin Facer; David Feng; Tim P. Fliss; Garrett Gee; Jeff Goldy; Lindsey Gourley; Benjamin W. Gregor; Guangyu Gu; Robert Howard

The anatomical and functional architecture of the human brain is mainly determined by prenatal transcriptional processes. We describe an anatomically comprehensive atlas of the mid-gestational human brain, including de novo reference atlases, in situ hybridization, ultra-high-resolution magnetic resonance imaging (MRI) and microarray analysis on highly discrete laser-microdissected brain regions. In developing cerebral cortex, transcriptional differences are found between different proliferative and post-mitotic layers, wherein laminar signatures reflect cellular composition and developmental processes. Cytoarchitectural differences between human and mouse have molecular correlates, including species differences in gene expression in subplate, although surprisingly we find minimal differences between the inner and outer subventricular zones even though the outer zone is expanded in humans. Both germinal and post-mitotic cortical layers exhibit fronto-temporal gradients, with particular enrichment in the frontal lobe. Finally, many neurodevelopmental disorder and human-evolution-related genes show patterned expression, potentially underlying unique features of human cortical formation. These data provide a rich, freely-accessible resource for understanding human brain development.


NeuroImage | 2010

Genetic and environmental influences on the size of specific brain regions in midlife: The VETSA MRI study

William S. Kremen; Elizabeth Prom-Wormley; Matthew S. Panizzon; Lisa T. Eyler; Bruce Fischl; Michael C. Neale; Carol E. Franz; Michael J. Lyons; Jennifer Pacheco; Michele E. Perry; Allison Stevens; J. Eric Schmitt; Michael D. Grant; Larry J. Seidman; Heidi W. Thermenos; Ming T. Tsuang; Seth A. Eisen; Anders M. Dale; Christine Fennema-Notestine

The impact of genetic and environmental factors on human brain structure is of great importance for understanding normative cognitive and brain aging as well as neuropsychiatric disorders. However, most studies of genetic and environmental influences on human brain structure have either focused on global measures or have had samples that were too small for reliable estimates. Using the classical twin design, we assessed genetic, shared environmental, and individual-specific environmental influences on individual differences in the size of 96 brain regions of interest (ROIs). Participants were 474 middle-aged male twins (202 pairs; 70 unpaired) in the Vietnam Era Twin Study of Aging (VETSA). They were 51-59 years old, and were similar to U.S. men in their age range in terms of sociodemographic and health characteristics. We measured thickness of cortical ROIs and volume of other ROIs. On average, genetic influences accounted for approximately 70% of the variance in the volume of global, subcortical, and ventricular ROIs and approximately 45% of the variance in the thickness of cortical ROIs. There was greater variability in the heritability of cortical ROIs (0.00-0.75) as compared with subcortical and ventricular ROIs (0.48-0.85). The results did not indicate lateralized heritability differences or greater genetic influences on the size of regions underlying higher cognitive functions. The findings provide key information for imaging genetic studies and other studies of brain phenotypes and endophenotypes. Longitudinal analysis will be needed to determine whether the degree of genetic and environmental influences changes for different ROIs from midlife to later life.


NeuroImage | 2013

Surface based analysis of diffusion orientation for identifying architectonic domains in the in vivo human cortex.

Jennifer A. McNab; Jonathan R. Polimeni; Ruopeng Wang; Jean C. Augustinack; Kyoko Fujimoto; Allison Stevens; Thomas Janssens; Reza Farivar; Rebecca D. Folkerth; Wim Vanduffel; Lawrence L. Wald

Diffusion tensor MRI is sensitive to the coherent structure of brain tissue and is commonly used to study large-scale white matter structure. Diffusion in gray matter is more isotropic, however, several groups have observed coherent patterns of diffusion anisotropy within the cerebral cortical gray matter. We extend the study of cortical diffusion anisotropy by relating it to the local coordinate system of the folded cerebral cortex. We use 1mm and sub-millimeter isotropic resolution diffusion imaging to perform a laminar analysis of the principal diffusion orientation, fractional anisotropy, mean diffusivity and partial volume effects. Data from 6 in vivo human subjects, a fixed human brain specimen and an anesthetized macaque were examined. Large regions of cortex show a radial diffusion orientation. In vivo human and macaque data displayed a sharp transition from radial to tangential diffusion orientation at the border between primary motor and somatosensory cortex, and some evidence of tangential diffusion in secondary somatosensory cortex and primary auditory cortex. Ex vivo diffusion imaging in a human tissue sample showed some tangential diffusion orientation in S1 but mostly radial diffusion orientations in both M1 and S1.


Cerebral Cortex | 2011

Genetic and Environmental Contributions to Regional Cortical Surface Area in Humans: A Magnetic Resonance Imaging Twin Study

Lisa T. Eyler; Elizabeth Prom-Wormley; Matthew S. Panizzon; Allison R. Kaup; Christine Fennema-Notestine; Michael C. Neale; Terry L. Jernigan; Bruce Fischl; Carol E. Franz; Michael J. Lyons; Michael D. Grant; Allison Stevens; Jennifer Pacheco; Michele E. Perry; J. Eric Schmitt; Larry J. Seidman; Heidi W. Thermenos; Ming T. Tsuang; Chi-Hua Chen; Wesley K. Thompson; Amy J. Jak; Anders M. Dale; William S. Kremen

Cortical surface area measures appear to be functionally relevant and distinct in etiology, development, and behavioral correlates compared with other size characteristics, such as cortical thickness. Little is known about genetic and environmental influences on individual differences in regional surface area in humans. Using a large sample of adult twins, we determined relative contributions of genes and environment on variations in regional cortical surface area as measured by magnetic resonance imaging before and after adjustment for genetic and environmental influences shared with total cortical surface area. We found high heritability for total surface area and, before adjustment, moderate heritability for regional surface areas. Compared with other lobes, heritability was higher for frontal lobe and lower for medial temporal lobe. After adjustment for total surface area, regionally specific genetic influences were substantially reduced, although still significant in most regions. Unlike other lobes, left frontal heritability remained high after adjustment. Thus, global and regionally specific genetic factors both influence cortical surface areas. These findings are broadly consistent with results from animal studies regarding the evolution and development of cortical patterning and may guide future research into specific environmental and genetic determinants of variation among humans in the surface area of particular regions.


NeuroImage | 2009

Predicting the location of entorhinal cortex from MRI

Bruce Fischl; Allison Stevens; Niranjini Rajendran; B. T. Thomas Yeo; Douglas N. Greve; Koen Van Leemput; Jonathan R. Polimeni; Sita Kakunoori; Randy L. Buckner; Jennifer Pacheco; David H. Salat; Jennifer R. Melcher; Matthew P. Frosch; Bradley T. Hyman; P. Ellen Grant; Bruce R. Rosen; Andre van der Kouwe; Graham C. Wiggins; Lawrence L. Wald; Jean C. Augustinack

Entorhinal cortex (EC) is a medial temporal lobe area critical to memory formation and spatial navigation that is among the earliest parts of the brain affected by Alzheimers disease (AD). Accurate localization of EC would thus greatly facilitate early detection and diagnosis of AD. In this study, we used ultra-high resolution ex vivo MRI to directly visualize the architectonic features that define EC rostrocaudally and mediolaterally, then applied surface-based registration techniques to quantify the variability of EC with respect to cortical geometry, and made predictions of its location on in vivo scans. The results indicate that EC can be localized quite accurately based on cortical folding patterns, within 3 mm in vivo, a significant step forward in our ability to detect the earliest effects of AD when clinical intervention is most likely to be effective.


NeuroImage | 2013

Predicting the location of human perirhinal cortex, Brodmann's area 35, from MRI.

Jean C. Augustinack; Kristen E. Huber; Allison Stevens; Michelle Roy; Matthew P. Frosch; Andre van der Kouwe; Lawrence L. Wald; Koen Van Leemput; Ann C. McKee; Bruce Fischl

The perirhinal cortex (Brodmanns area 35) is a multimodal area that is important for normal memory function. Specifically, perirhinal cortex is involved in the detection of novel objects and manifests neurofibrillary tangles in Alzheimers disease very early in disease progression. We scanned ex vivo brain hemispheres at standard resolution (1 mm × 1 mm × 1 mm) to construct pial/white matter surfaces in FreeSurfer and scanned again at high resolution (120 μm × 120 μm × 120 μm) to determine cortical architectural boundaries. After labeling perirhinal area 35 in the high resolution images, we mapped the high resolution labels to the surface models to localize area 35 in fourteen cases. We validated the area boundaries determined using histological Nissl staining. To test the accuracy of the probabilistic mapping, we measured the Hausdorff distance between the predicted and true labels and found that the median Hausdorff distance was 4.0mm for the left hemispheres (n=7) and 3.2mm for the right hemispheres (n=7) across subjects. To show the utility of perirhinal localization, we mapped our labels to a subset of the Alzheimers Disease Neuroimaging Initiative dataset and found decreased cortical thickness measures in mild cognitive impairment and Alzheimers disease compared to controls in the predicted perirhinal area 35. Our ex vivo probabilistic mapping of the perirhinal cortex provides histologically validated, automated and accurate labeling of architectonic regions in the medial temporal lobe, and facilitates the analysis of atrophic changes in a large dataset for earlier detection and diagnosis.


The Journal of Comparative Neurology | 2016

Comprehensive cellular-resolution atlas of the adult human brain

Song-Lin Ding; Joshua J. Royall; Susan M. Sunkin; Lydia Ng; Benjamin Facer; Phil Lesnar; Angie Guillozet-Bongaarts; Bergen McMurray; Aaron Szafer; Tim Dolbeare; Allison Stevens; Lee S. Tirrell; Thomas Benner; Shiella Caldejon; Rachel A. Dalley; Nick Dee; Christopher Lau; Julie Nyhus; Melissa Reding; Zackery L. Riley; David Sandman; Elaine Shen; Andre van der Kouwe; Ani Varjabedian; Michelle Write; Lilla Zöllei; Chinh Dang; James A. Knowles; Christof Koch; John Phillips

Detailed anatomical understanding of the human brain is essential for unraveling its functional architecture, yet current reference atlases have major limitations such as lack of whole‐brain coverage, relatively low image resolution, and sparse structural annotation. We present the first digital human brain atlas to incorporate neuroimaging, high‐resolution histology, and chemoarchitecture across a complete adult female brain, consisting of magnetic resonance imaging (MRI), diffusion‐weighted imaging (DWI), and 1,356 large‐format cellular resolution (1 µm/pixel) Nissl and immunohistochemistry anatomical plates. The atlas is comprehensively annotated for 862 structures, including 117 white matter tracts and several novel cyto‐ and chemoarchitecturally defined structures, and these annotations were transferred onto the matching MRI dataset. Neocortical delineations were done for sulci, gyri, and modified Brodmann areas to link macroscopic anatomical and microscopic cytoarchitectural parcellations. Correlated neuroimaging and histological structural delineation allowed fine feature identification in MRI data and subsequent structural identification in MRI data from other brains. This interactive online digital atlas is integrated with existing Allen Institute for Brain Science gene expression atlases and is publicly accessible as a resource for the neuroscience community. J. Comp. Neurol. 524:3127–3481, 2016.


NeuroImage | 2010

Improved tractography alignment using combined volumetric and surface registration

Lilla Zöllei; Allison Stevens; Kristen E. Huber; Sita Kakunoori; Bruce Fischl

Previously we introduced an automated high-dimensional non-linear registration framework, CVS, that combines volumetric and surface-based alignment to achieve robust and accurate correspondence in both cortical and sub-cortical regions (Postelnicu et al., 2009). In this paper we show that using CVS to compute cross-subject alignment from anatomical images, then applying the previously computed alignment to diffusion weighted MRI images, outperforms state-of-the-art techniques for computing cross-subject alignment directly from the DWI data itself. Specifically, we show that CVS outperforms the alignment component of TBSS in terms of degree-of-alignment of manually labeled tract models for the uncinate fasciculus, the inferior longitudinal fasciculus and the corticospinal tract. In addition, we compare linear alignment using FLIRT based on either fractional anisotropy or anatomical volumes across-subjects, and find a comparable effect. Together these results imply a clear advantage to aligning anatomy as opposed to lower resolution DWI data even when the final goal is diffusion analysis.


Hippocampus | 2014

H.M.'s contributions to neuroscience: A review and autopsy studies

Jean C. Augustinack; Andre van der Kouwe; David H. Salat; Thomas Benner; Allison Stevens; Jacopo Annese; Bruce Fischl; Matthew P. Frosch; Suzanne Corkin

H.M., Henry Molaison, was one of the worlds most famous amnesic patients. His amnesia was caused by an experimental brain operation, bilateral medial temporal lobe resection, carried out in 1953 to relieve intractable epilepsy. He died on December 2, 2008, and that night we conducted a wide variety of in situ MRI scans in a 3 T scanner at the Massachusetts General Hospital (Mass General) Athinoula A. Martinos Center for Biomedical Imaging. For the in situ experiments, we acquired a full set of standard clinical scans, 1 mm isotropic anatomical scans, and multiple averages of 440 μm isotropic anatomical scans. The next morning, H.M.s body was transported to the Mass General Morgue for autopsy. The photographs taken at that time provided the first documentation of H.M.s lesions in his physical brain. After tissue fixation, we obtained ex vivo structural data at ultra‐high resolution using 3 T and 7 T magnets. For the ex vivo acquisitions, the highest resolution images were 210 μm isotropic. Based on the MRI data, the anatomical areas removed during H.M.s experimental operation were the medial temporopolar cortex, piriform cortex, virtually all of the entorhinal cortex, most of the perirhinal cortex and subiculum, the amygdala (except parts of the dorsal‐most nuclei—central and medial), anterior half of the hippocampus, and the dentate gyrus (posterior head and body). The posterior parahippocampal gyrus and medial temporal stem were partially damaged. Spared medial temporal lobe tissue included the dorsal‐most amygdala, the hippocampal‐amygdalo‐transition‐area, ∼2 cm of the tail of the hippocampus, a small part of perirhinal cortex, a small portion of medial hippocampal tissue, and ∼2 cm of posterior parahippocampal gyrus. H.M.s impact on the field of memory has been remarkable, and his contributions to neuroscience continue with a unique dataset that includes in vivo, in situ, and ex vivo high‐resolution MRI.


Human Brain Mapping | 2011

Genetic Patterns of Correlation Among Subcortical Volumes in Humans: Results From a Magnetic Resonance Imaging Twin Study

Lisa T. Eyler; Elizabeth Prom-Wormley; Christine Fennema-Notestine; Matthew S. Panizzon; Michael C. Neale; Terry L. Jernigan; Bruce Fischl; Carol E. Franz; Michael J. Lyons; Allison Stevens; Jennifer Pacheco; Michele E. Perry; J. Eric Schmitt; Nicholas C. Spitzer; Larry J. Seidman; Heidi W. Thermenos; Ming T. Tsuang; Anders M. Dale; William S. Kremen

Little is known about genetic influences on the volume of subcortical brain structures in adult humans, particularly whether there is regional specificity of genetic effects. Understanding patterns of genetic covariation among volumes of subcortical structures may provide insight into the development of individual differences that have consequences for cognitive and emotional behavior and neuropsychiatric disease liability. We measured the volume of 19 subcortical structures (including brain and ventricular regions) in 404 twins (110 monozygotic and 92 dizygotic pairs) from the Vietnam Era Twin Study of Aging and calculated the degree of genetic correlation among these volumes. We then examined the patterns of genetic correlation through hierarchical cluster analysis and by principal components analysis. We found that a model with four genetic factors best fit the data: a Basal Ganglia/Thalamus factor; a Ventricular factor; a Limbic factor; and a Nucleus Accumbens factor. Homologous regions from each hemisphere loaded on the same factors. The observed patterns of genetic correlation suggest the influence of multiple genetic influences. There is a genetic organization among structures which distinguishes between brain and cerebrospinal fluid spaces and between different subcortical regions. Further study is needed to understand this genetic patterning and whether it reflects influences on early development, functionally dependent patterns of growth or pruning, or regionally specific losses due to genes involved in aging, stress response, or disease. Hum Brain Mapp, 2011.

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Anders M. Dale

University of California

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Carol E. Franz

University of California

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