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Impaired vigilance networks in temporal lobe epilepsy: Mechanisms and clinical implications.
Englot DJ, Morgan VL, Chang C
(2020) Epilepsia 61: 189-202
MeSH Terms: Arousal, Brain Mapping, Epilepsy, Temporal Lobe, Humans, Nerve Net, Neuroimaging
Show Abstract · Added March 18, 2020
Mesial temporal lobe epilepsy (mTLE) is a neurological disorder in which patients suffer from frequent consciousness-impairing seizures, broad neurocognitive deficits, and diminished quality of life. Although seizures in mTLE originate focally in the hippocampus or amygdala, mTLE patients demonstrate cognitive deficits that extend beyond temporal lobe function-such as decline in executive function, cognitive processing speed, and attention-as well as diffuse decreases in neocortical metabolism and functional connectivity. Given prior observations that mTLE patients exhibit impairments in vigilance, and that seizures may disrupt the activity and long-range connectivity of subcortical brain structures involved in vigilance regulation, we propose that subcortical activating networks underlying vigilance play a critical role in mediating the widespread neural and cognitive effects of focal mTLE. Here, we review evidence for impaired vigilance in mTLE, examine clinical implications and potential network underpinnings, and suggest neuroimaging strategies for determining the relationship between vigilance, brain connectivity, and neurocognition in patients and healthy controls.
Wiley Periodicals, Inc. © 2020 International League Against Epilepsy.
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6 MeSH Terms
A longitudinal neuroimaging dataset on multisensory lexical processing in school-aged children.
Lytle MN, McNorgan C, Booth JR
(2019) Sci Data 6: 329
MeSH Terms: Child, Educational Measurement, Humans, Magnetic Resonance Imaging, Neuroimaging, Neuropsychological Tests, Reading
Show Abstract · Added March 3, 2020
Here we describe the open access dataset entitled "Longitudinal Brain Correlates of Multisensory Lexical Processing in Children" hosted on OpenNeuro.org. This dataset examines reading development through a longitudinal multimodal neuroimaging and behavioral approach, including diffusion-weighted and T1-weighted structural magnetic resonance imaging (MRI), task based functional MRI, and a battery of psycho-educational assessments and parental questionnaires. Neuroimaging, psycho-educational testing, and functional task behavioral data were collected from 188 typically developing children when they were approximately 10.5 years old (session T1). Seventy children returned approximately 2.5 years later (session T2), of which all completed longitudinal follow-ups of psycho-educational testing, and 49 completed neuroimaging and functional tasks. At session T1 participants completed auditory, visual, and audio-visual word and pseudo-word rhyming judgment tasks in the scanner. At session T2 participants completed visual word and pseudo-word rhyming judgement tasks in the scanner.
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7 MeSH Terms
Automatic semantic influence on early visual word recognition in the ventral occipito-temporal cortex.
Wang J, Deng Y, Booth JR
(2019) Neuropsychologia 133: 107188
MeSH Terms: Adolescent, Adult, China, Female, Functional Neuroimaging, Humans, Language, Magnetic Resonance Imaging, Male, Neural Pathways, Occipital Lobe, Pattern Recognition, Visual, Prefrontal Cortex, Reading, Repetition Priming, Semantics, Temporal Lobe, Young Adult
Show Abstract · Added March 3, 2020
The left ventral occipitotemporal cortex (vOT) is a critical region in reading. According to the interactive account of reading, the vOT is an interface between the lower-level visual regions and higher-level language areas. One prediction of the interactive account is that orthographic activation in vOT should be automatically influenced by semantics and phonology. In the current study, we used functional magnetic resonance imaging (fMRI) and a masked priming paradigm with a relatively short duration (150 ms) to examine whether language information automatically influences vOT during Chinese reading. Participants were asked to perform a lexical decision task on target characters. We separately tested the phonological and semantic influence on orthographic processing in vOT. Brain activation analyses showed that the activation of vOT was modulated by semantic information. In addition, a functional connectivity analysis showed stronger connectivity between vOT and the left ventral inferior frontal gyrus was modulated by semantic information. These findings provided converging evidence for the existence of an automatic semantic influence on vOT during reading, supporting the interactive account. Our study did not show a phonological effect either in the activation of or connectivity with vOT. Taken together, these results reflect the unique processes of Chinese reading, which relies more on the mapping between orthography and semantics, as compared to the orthographic to phonology mapping.
Copyright © 2019 Elsevier Ltd. All rights reserved.
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18 MeSH Terms
Spatiotemporal trajectories of quantitative magnetization transfer measurements in injured spinal cord using simplified acquisitions.
Wang F, Wu TL, Li K, Chen LM, Gore JC
(2019) Neuroimage Clin 23: 101921
MeSH Terms: Animals, Behavior, Animal, Magnetic Resonance Imaging, Male, Models, Theoretical, Myelin Sheath, Neuroimaging, Recovery of Function, Saimiri, Spinal Cord Injuries, White Matter
Show Abstract · Added March 3, 2020
PURPOSE - This study aims to systematically evaluate the accuracy and precision of pool size ratio (PSR) measurements from quantitative magnetization transfer (qMT) acquisitions using simplified models in the context of assessing injury-associated spatiotemporal changes in spinal cords of non-human primates. This study also aims to characterize changes in the spinal tissue pathology in individual subjects, both regionally and longitudinally, in order to demonstrate the relationship between regional tissue compositional changes and sensorimotor behavioral recovery after cervical spinal cord injury (SCI).
METHODS - MRI scans were recorded on anesthetized monkeys at 9.4 T, before and serially after a unilateral section of the dorsal column tract. Images were acquired following saturating RF pulses at different offset frequencies. Models incorporating two pools of protons but with differing numbers of variable parameters were used to fit the data to derive qMT parameters. The results using different amounts of measured data and assuming different numbers of variable model parameters were compared. Behavioral impairments and recovery were assessed by a food grasping-retrieving task. Histological sections were obtained post mortem for validation of the injury.
RESULTS - QMT fitting provided maps of pool size ratio (PSR), the relative amounts of immobilized protons exchanging magnetization compared to the "free" water. All the selected modeling approaches detected a lesion/cyst at the site of injury as significant reductions in PSR values. The regional contrasts in the PSR maps obtained using the different fittings varied, but the 2-parameter fitting results showed strong positive correlations with results from 5-parameter modeling. 2-parameter fitting results with modest (>3) RF offsets showed comparable sensitivity for detecting demyelination in white matter and loss of macromolecules in gray matter around lesion sites compared to 5-parameter fitting with fully-sampled data acquisitions. Histology confirmed that decreases of PSR corresponded to regional demyelination around lesion sites, especially when demyelination occurred along the dorsal column on the injury side. Longitudinally, PSR values of injured dorsal column tract and gray matter horns exhibited remarkable recovery that associated with behavioral improvement.
CONCLUSION - Simplified qMT modeling approaches provide efficient and sensitive means to detect and characterize injury-associated demyelination in white matter tracts and loss of macromolecules in gray matter and to monitor its recovery over time.
Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.
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11 MeSH Terms
Adverse Vascular Risk Relates to Cerebrospinal Fluid Biomarker Evidence of Axonal Injury in the Presence of Alzheimer's Disease Pathology.
Osborn KE, Alverio JM, Dumitrescu L, Pechman KR, Alzheimer’s Disease Neuroimaging Initiative, Gifford KA, Hohman TJ, Blennow K, Zetterberg H, Jefferson AL
(2019) J Alzheimers Dis 71: 281-290
MeSH Terms: Aged, Alzheimer Disease, Axons, Biomarkers, Brain, Cerebrovascular Circulation, Cognitive Dysfunction, Correlation of Data, Female, Humans, Male, Neurofilament Proteins, Neuroimaging, Neuropsychological Tests, Risk Assessment, tau Proteins
Show Abstract · Added March 6, 2020
BACKGROUND - Vascular risk factors promote cerebral small vessel disease and neuropathological changes, particularly in white matter where large-caliber axons are located. How Alzheimer's disease pathology influences the brain's vulnerability in this regard is not well understood.
OBJECTIVE - Systemic vascular risk was assessed in relation to cerebrospinal fluid concentrations of neurofilament light, a biomarker of large-caliber axonal injury, evaluating for interactions by clinical and protein markers of Alzheimer's disease.
METHODS - Among Alzheimer's Disease Neuroimaging Initiative participants with normal cognition (n = 117), mild cognitive impairment (n = 190), and Alzheimer's disease (n = 95), linear regression related vascular risk (as measured by the modified Framingham Stroke Risk Profile) to neurofilament light, adjusting for age, sex, education, and cognitive diagnosis. Interactions were assessed by cognitive diagnosis, and by cerebrospinal fluid markers of Aβ42, hyperphosphorylated tau, and total tau.
RESULTS - Vascular risk and neurofilament light were not related in the main effect model (p = 0.08). However, interactions emerged for total tau (p = 0.01) and hyperphosphorylated tau (p = 0.002) reflecting vascular risk becoming more associated with cerebrospinal fluid neurofilament light in the context of greater concentrations of tau biomarkers. An interaction also emerged for the Alzheimer's disease biomarker profiles (p = 0.046) where in comparison to the referent 'normal' biomarker group, individuals with abnormal levels of both Aβ42 and total tau showed stronger associations between vascular risk and neurofilament light.
CONCLUSION - Older adults may be more vulnerable to axonal injury in response to higher vascular risk burdens in the context of concomitant Alzheimer's disease pathology.
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16 MeSH Terms
Atypical Clinical Manifestations of Cerebral Amyloid Angiopathy.
Akers C, Acosta LMY, Considine C, Claassen D, Kirshner H, Schrag M
(2019) Curr Neurol Neurosci Rep 19: 64
MeSH Terms: Aged, Alzheimer Disease, Brain, Cerebral Amyloid Angiopathy, Cerebral Hemorrhage, Cognitive Dysfunction, Diagnosis, Differential, Female, Humans, Lewy Body Disease, Male, Neuroimaging
Show Abstract · Added March 3, 2020
PURPOSE - Cerebral amyloid angiopathy is a vasculopathy caused by β-amyloid deposition in cerebral arterioles and capillaries. It is closely linked to Alzheimer's disease and predisposes elderly patients to intracerebral hemorrhage, transient focal neurological episodes, and cognitive impairment. Because of a predilection for symptomatic hemorrhage, particularly in the frontal lobes, cerebral amyloid angiopathy may also cause a dysexecutive syndrome.
RECENT FINDINGS - In this case series, we describe presentations of classic clinical dementia syndromes which are not are widely thought to be associated with cerebral amyloid angiopathy, namely logopenic variant primary progressive aphasia (n = 3), normal pressure hydrocephalus (n = 3), and Lewy body dementia (n = 2). In every case, after a clinical diagnosis was established, neuroimaging, brain biopsy, and/or autopsy confirmed the presence of cerebral amyloid angiopathy. Cerebral amyloid angiopathy has significant clinical implications, and its ability to mimic and/or contribute to other clinical dementia syndromes can complicate its diagnosis. This series of cases broadens the range of clinical scenarios associated with cerebral amyloid angiopathy.
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12 MeSH Terms
The relationship between domain-specific subjective cognitive decline and Alzheimer's pathology in normal elderly adults.
Shokouhi S, Conley AC, Baker SL, Albert K, Kang H, Gwirtsman HE, Newhouse PA, Alzheimer's Disease Neuroimaging Initiative
(2019) Neurobiol Aging 81: 22-29
MeSH Terms: Aged, Aged, 80 and over, Aging, Alzheimer Disease, Amyloid beta-Peptides, Aniline Compounds, Brain, Cognition, Cognitive Dysfunction, Ethylene Glycols, Fluorine Radioisotopes, Humans, Neuroimaging, Positron-Emission Tomography, Radiopharmaceuticals, tau Proteins
Show Abstract · Added March 3, 2020
We evaluated the associations of subjective (self-reported everyday cognition [ECog]) and objective cognitive measures with regional amyloid-β (Aβ) and tau accumulation in 86 clinically normal elderly subjects from the Alzheimer's Disease Neuroimaging Initiative. Regression analyses were conducted to identify whether individual ECog domains (Memory, Language, Organization, Planning, Visuospatial, and Divided Attention) were equally or differentially associated with regional [F]florbetapir and [F]flortaucipir uptake and how these associations compared to those obtained with objective cognitive measures. A texture analysis, the weighted 2-point correlation, was used as an additional approach for estimating the whole-brain tau burden without positron emission tomography intensity normalization. Although the strongest models for ECog domains included either tau (planning and visuospatial) or Aβ (memory and organization), the strongest models for all objective measures included Aβ. In Aβ-negative participants, the strongest models for all ECog domains of executive functioning included tau. Our results indicate differential associations of individual subjective cognitive domains with Aβ and tau in clinically normal adults. Detailed characterization of ECog may render a valuable prescreening tool for pathological prediction.
Copyright © 2019 Elsevier Inc. All rights reserved.
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16 MeSH Terms
Improving human cortical sulcal curve labeling in large scale cross-sectional MRI using deep neural networks.
Parvathaneni P, Nath V, McHugo M, Huo Y, Resnick SM, Woodward ND, Landman BA, Lyu I
(2019) J Neurosci Methods 324: 108311
MeSH Terms: Adult, Aged, Aged, 80 and over, Anatomic Landmarks, Cerebral Cortex, Deep Learning, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Neuroimaging
Show Abstract · Added January 31, 2020
BACKGROUND - Human cortical primary sulci are relatively stable landmarks and commonly observed across the population. Despite their stability, the primary sulci exhibit phenotypic variability.
NEW METHOD - We propose a fully automated pipeline that integrates both sulcal curve extraction and labeling. In this study, we use a large normal control population (n = 1424) to train neural networks for accurately labeling the primary sulci. Briefly, we use sulcal curve distance map, surface parcellation, mean curvature and spectral features to delineate their sulcal labels. We evaluate the proposed method with 8 primary sulcal curves in the left and right hemispheres compared to an established multi-atlas curve labeling method.
RESULTS - Sulcal labels by the proposed method reasonably well agree with manual labeling. The proposed method outperforms the existing multi-atlas curve labeling method.
COMPARISON WITH EXISTING METHOD - Significantly improved sulcal labeling results are achieved with over 12.5 and 20.6 percent improvement on labeling accuracy in the left and right hemispheres, respectively compared to that of a multi-atlas curve labeling method in eight curves (p≪0.001, two-sample t-test).
CONCLUSION - The proposed method offers a computationally efficient and robust labeling of major sulci.
Copyright © 2019 Elsevier B.V. All rights reserved.
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13 MeSH Terms
Quantification of DTI in the Pediatric Spinal Cord: Application to Clinical Evaluation in a Healthy Patient Population.
Reynolds BB, By S, Weinberg QR, Witt AA, Newton AT, Feiler HR, Ramkorun B, Clayton DB, Couture P, Martus JE, Adams M, Wellons JC, Smith SA, Bhatia A
(2019) AJNR Am J Neuroradiol 40: 1236-1241
MeSH Terms: Adolescent, Algorithms, Anisotropy, Child, Child, Preschool, Diffusion Tensor Imaging, Female, Humans, Image Processing, Computer-Assisted, Infant, Male, Neurogenesis, Neuroimaging, Retrospective Studies, Spinal Cord
Show Abstract · Added March 30, 2020
BACKGROUND AND PURPOSE - The purpose of the study is to characterize diffusion tensor imaging indices in the developing spinal cord, evaluating differences based on age and cord region. Describing the progression of DTI indices in the pediatric cord increases our understanding of spinal cord development.
MATERIALS AND METHODS - A retrospective analysis was performed on DTI acquired in 121 pediatric patients (mean, 8.6 years; range, 0.3-18.0 years) at Monroe Carell Jr. Children's Hospital at Vanderbilt from 2017 to 2018. Diffusion-weighted images (15 directions; = 750 s/mm; slice thickness, 5 mm; in-plane resolution, 1.0 × 1.0 mm) were acquired on a 3T scanner in the cervicothoracic and/or thoracolumbar cord. Manual whole-cord segmentation was performed. Images were masked and further segmented into cervical, upper thoracic, thoracolumbar, and conus regions. Analyses of covariance were performed for each DTI-derived index to investigate how age affects diffusion across cord regions, and 95% confidence intervals were calculated across age for each derived index and region. Post hoc testing was performed to analyze regional differences.
RESULTS - Analyses of covariance revealed significant correlations of age with axial diffusivity, mean diffusivity, and fractional anisotropy (all, < .001). There were also significant differences among cord regions for axial diffusivity, radial diffusivity, mean diffusivity, and fractional anisotropy (all, < .001).
CONCLUSIONS - This research demonstrates that diffusion evolves in the pediatric spinal cord during development, dependent on both cord region and the diffusion index of interest. Future research could investigate how diffusion may be affected by common pediatric spinal pathologies.
© 2019 by American Journal of Neuroradiology.
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15 MeSH Terms
Improved gray matter surface based spatial statistics in neuroimaging studies.
Parvathaneni P, Lyu I, Huo Y, Rogers BP, Schilling KG, Nath V, Blaber JA, Hainline AE, Anderson AW, Woodward ND, Landman BA
(2019) Magn Reson Imaging 61: 285-295
MeSH Terms: Adult, Algorithms, Artifacts, Brain, Computer Simulation, Diffusion Magnetic Resonance Imaging, Diffusion Tensor Imaging, Female, Gray Matter, Humans, Magnetic Resonance Imaging, Male, Memory, Short-Term, Neurites, Neuroimaging, Probability, White Matter
Show Abstract · Added January 31, 2020
Neuroimaging often involves acquiring high-resolution anatomical images along with other low-resolution image modalities, like diffusion and functional magnetic resonance imaging. Performing gray matter statistics with low-resolution image modalities is a challenge due to registration artifacts and partial volume effects. Gray matter surface based spatial statistics (GS-BSS) has been shown to provide higher sensitivity using gray matter surfaces compared to that of skeletonization approach of gray matter based spatial statistics which is adapted from tract based spatial statistics in diffusion studies. In this study, we improve upon GS-BSS incorporating neurite orientation dispersion and density imaging (NODDI) based search (denoted N-GSBSS) by 1) enhancing metrics mapping from native space, 2) incorporating maximum orientation dispersion index (ODI) search along surface normal, and 3) proposing applicability to other modalities, such as functional MRI (fMRI). We evaluated the performance of N-GSBSS against three baseline pipelines: volume-based registration, FreeSurfer's surface registration and ciftify pipeline for fMRI and simulation studies. First, qualitative mean ODI results are shown for N-GSBSS with and without NODDI based search in comparison with ciftify pipeline. Second, we conducted one-sample t-tests on working memory activations in fMRI to show that the proposed method can aid in the analysis of low resolution fMRI data. Finally we performed a sensitivity test in a simulation study by varying percentage change of intensity values within a region of interest in gray matter probability maps. N-GSBSS showed higher sensitivity in the simulation test compared to the other methods capturing difference between the groups starting at 10% change in the intensity values. The computational time of N-GSBSS is 68 times faster than that of traditional surface-based or 86 times faster than that of ciftify pipeline analysis.
Copyright © 2019 Elsevier Inc. All rights reserved.
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MeSH Terms