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Magnetic resonance imaging (MRI) is an important tool for analysis of deep brain grey matter structures. However, analysis of these structures is limited due to low intensity contrast typically found in whole brain imaging protocols. Herein, we propose a big data registration-enhancement (BDRE) technique to augment the contrast of deep brain structures using an efficient large-scale non-rigid registration strategy. Direct validation is problematic given a lack of ground truth data. Rather, we validate the usefulness and impact of BDRE for multi-atlas (MA) segmentation on two sets of structures of clinical interest: the thalamic nuclei and hippocampal subfields. The experimental design compares algorithms using T1-weighted 3 T MRI for both structures (and additional 7 T MRI for the thalamic nuclei) with an algorithm using BDRE. As baseline comparisons, a recent denoising (DN) technique and a super-resolution (SR) method are used to preprocess the original 3 T MRI. The performance of each MA segmentation is evaluated by the Dice similarity coefficient (DSC). BDRE significantly improves mean segmentation accuracy over all methods tested for both thalamic nuclei (3 T imaging: 9.1%; 7 T imaging: 15.6%; DN: 6.9%; SR: 16.2%) and hippocampal subfields (3 T T1 only: 8.7%; DN: 8.4%; SR: 8.6%). We also present DSC performance for each thalamic nucleus and hippocampal subfield and show that BDRE can help MA segmentation for individual thalamic nuclei and hippocampal subfields. This work will enable large-scale analysis of clinically relevant deep brain structures from commonly acquired T1 images.
Copyright © 2019 Elsevier Inc. All rights reserved.
PURPOSE - We sought to determine whether women with overactive bladder who required third line therapy would demonstrate greater central sensitization, indexed by temporal summation to heat pain stimuli, than those with overactive bladder.
MATERIALS AND METHODS - We recruited 39 women with overactive bladder from the urology clinic who were planning to undergo interventional therapy for medication refractory overactive bladder with onabotulinumtoxinA bladder injection or sacral neuromodulation. We also recruited 55 women with overactive bladder who were newly seen at our urology clinic or who responded to advertisements for study participation. Participants underwent quantitative sensory testing using a thermal temporal summation protocol. The primary study outcome was the degree of temporal summation as reflected in the magnitude of positive slope of the line fit to the series of 10 stimuli at a 49C target temperature. We compared the degree of temporal summation between the study groups using linear regression.
RESULTS - Women in the group undergoing third line therapy showed significantly higher standardized temporal summation slopes than those in the nontreatment group (β = 1.57, 95% CI 0.18-2.96, t = 2.25, p = 0.027). On exploratory analyses a history of incontinence surgery or hysterectomy was associated with significantly greater temporal summation.
CONCLUSIONS - In this study the degree of temporal summation was elevated in women undergoing third line overactive bladder therapy compared to women with overactive bladder who were not undergoing that therapy. These findings suggest there may be pathophysiological differences, specifically in afferent nerve function and processing, in some women with overactive bladder.
Copyright © 2018 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.
BACKGROUND - Functional dysconnectivity has been proposed as a major pathophysiological mechanism for cognitive dysfunction in schizophrenia. The hippocampus is a focal point of dysconnectivity in schizophrenia, with decreased hippocampal functional connectivity contributing to the marked memory deficits observed in patients. Normal memory function relies on the interaction of complex corticohippocampal networks. However, only recent technological advances have enabled the large-scale exploration of functional networks with accuracy and precision.
METHODS - We investigated the modularity of hippocampal resting-state functional networks in a sample of 45 patients with schizophrenia spectrum disorders and 38 healthy control subjects. Modularity was calculated for two distinct functional networks: a core hippocampal-medial temporal lobe cortex network and an extended hippocampal-cortical network. As hippocampal function differs along its longitudinal axis, follow-up analyses examined anterior and posterior networks separately. To explore effects of resting network function on behavior, we tested associations between modularity and relational memory ability. Age, sex, handedness, and parental education were similar between groups.
RESULTS - Network modularity was lower in schizophrenia patients, especially in the posterior hippocampal network. Schizophrenia patients also showed markedly lower relational memory ability compared with control subjects. We found a distinct brain-behavior relationship in schizophrenia that differed from control subjects by network and anterior/posterior division-while relational memory in control subjects was associated with anterior hippocampal-cortical modularity, schizophrenia patients showed an association with posterior hippocampal-medial temporal lobe cortex network modularity.
CONCLUSIONS - Our findings support a model of abnormal resting-state corticohippocampal network coherence in schizophrenia, which may contribute to relational memory deficits.
Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
Visual object expertise correlates with neural selectivity in the fusiform face area (FFA). Although behavioral studies suggest that visual expertise is associated with increased use of holistic and configural information, little is known about the nature of the supporting neural representations. Using high-resolution 7-T functional magnetic resonance imaging, we recorded the multivoxel activation patterns elicited by whole cars, configurally disrupted cars, and car parts in individuals with a wide range of car expertise. A probabilistic support vector machine classifier was trained to differentiate activation patterns elicited by whole car images from activation patterns elicited by misconfigured car images. The classifier was then used to classify new combined activation patterns that were created by averaging activation patterns elicited by individually presented top and bottom car parts. In line with the idea that the configuration of parts is critical to expert visual perception, car expertise was negatively associated with the probability of a combined activation pattern being classified as a whole car in the right anterior FFA, a region critical to vision for categories of expertise. Thus, just as found for faces in normal observers, the neural representation of cars in right anterior FFA is more holistic for car experts than car novices, consistent with common mechanisms of neural selectivity for faces and other objects of expertise in this area.
A primary challenge facing the development of interventions for dyslexia is identifying effective predictors of intervention response. While behavioral literature has identified core cognitive characteristics of response, the distinction of reading versus executive cognitive contributions to response profiles remains unclear, due in part to the difficulty of segregating these constructs using behavioral outputs. In the current study we used functional neuroimaging to piece apart the mechanisms of how/whether executive and reading network relationships are predictive of intervention response. We found that readers who are responsive to intervention have more typical pre-intervention functional interactions between executive and reading systems compared to nonresponsive readers. These findings suggest that intervention response in dyslexia is influenced not only by domain-specific reading regions, but also by contributions from intervening domain-general networks. Our results make a significant gain in identifying predictive bio-markers of outcomes in dyslexia, and have important implications for the development of personalized clinical interventions.
Copyright © 2018 Elsevier Ltd. All rights reserved.
Spoken and written language processing streams converge in the superior temporal sulcus (STS), but the functional and anatomical nature of this convergence is not clear. We used functional MRI to quantify neural responses to spoken and written language, along with unintelligible stimuli in each modality, and employed several strategies to segregate activations on the dorsal and ventral banks of the STS. We found that intelligible and unintelligible inputs in both modalities activated the dorsal bank of the STS. The posterior dorsal bank was able to discriminate between modalities based on distributed patterns of activity, pointing to a role in encoding of phonological and orthographic word forms. The anterior dorsal bank was agnostic to input modality, suggesting that this region represents abstract lexical nodes. In the ventral bank of the STS, responses to unintelligible inputs in both modalities were attenuated, while intelligible inputs continued to drive activation, indicative of higher level semantic and syntactic processing. Our results suggest that the processing of spoken and written language converges on the posterior dorsal bank of the STS, which is the first of a heterogeneous set of language regions within the STS, with distinct functions spanning a broad range of linguistic processes.
Copyright © 2017 Elsevier Inc. All rights reserved.
OBJECTIVE - To assess cross-sectionally whether lower cardiac index relates to lower resting cerebral blood flow (CBF) and cerebrovascular reactivity (CVR) among older adults.
METHODS - Vanderbilt Memory & Aging Project participants free of stroke, dementia, and heart failure were studied (n = 314, age 73 ± 7 years, 59% male, 39% with mild cognitive impairment). Cardiac index (liters per minute per meter squared) was quantified from echocardiography. Resting CBF (milliliters per 100 grams per minute) and hypercapnia-induced CVR were quantified from pseudo-continuous arterial spin-labeling MRI. Linear regressions with ordinary least-square estimates related cardiac index to regional CBF, with adjustment for age, education, race/ethnicity, Framingham Stroke Risk Profile score (systolic blood pressure, antihypertensive medication use, diabetes mellitus, current cigarette smoking, left ventricular hypertrophy, prevalent cardiovascular disease [CVD], atrial fibrillation), ε4 status, cognitive diagnosis, and regional tissue volume.
RESULTS - Lower cardiac index corresponded to lower resting CBF in the left (β = 2.4, = 0.001) and right (β = 2.5, = 0.001) temporal lobes. Results were similar when participants with prevalent CVD and atrial fibrillation were excluded (left temporal lobe β = 2.3, = 0.003; right temporal lobe β = 2.5, = 0.003). Cardiac index was unrelated to CBF in other regions assessed ( > 0.25) and CVR in all regions ( > 0.05). In secondary cardiac index × cognitive diagnosis interaction models, cardiac index and CBF associations were present only in cognitively normal participants and affected a majority of regions assessed with effects strongest in the left ( < 0.0001) and right ( < 0.0001) temporal lobes.
CONCLUSIONS - Among older adults without stroke, dementia, or heart failure, systemic blood flow correlates with cerebral CBF in the temporal lobe, independently of prevalent CVD, but not CVR.
© 2017 American Academy of Neurology.
OBJECTIVE - Seizures in temporal lobe epilepsy (TLE) disturb brain networks and lead to connectivity disturbances. We previously hypothesised that recurrent seizures in TLE may lead to abnormal connections involving subcortical activating structures including the ascending reticular activating system (ARAS), contributing to neocortical dysfunction and neurocognitive impairments. However, no studies of ARAS connectivity have been previously reported in patients with epilepsy.
METHODS - We used resting-state functional MRI recordings in 27 patients with TLE (67% right sided) and 27 matched controls to examine functional connectivity (partial correlation) between eight brainstem ARAS structures and 105 cortical/subcortical regions. ARAS nuclei included: cuneiform/subcuneiform, dorsal raphe, locus coeruleus, median raphe, parabrachial complex, pontine oralis, pedunculopontine and ventral tegmental area. Connectivity patterns were related to disease and neuropsychological parameters.
RESULTS - In control subjects, regions showing highest connectivity to ARAS structures included limbic structures, thalamus and certain neocortical areas, which is consistent with prior studies of ARAS projections. Overall, ARAS connectivity was significantly lower in patients with TLE than controls (p<0.05, paired t-test), particularly to neocortical regions including insular, lateral frontal, posterior temporal and opercular cortex. Diminished ARAS connectivity to these regions was related to increased frequency of consciousness-impairing seizures (p<0.01, Pearson's correlation) and was associated with impairments in verbal IQ, attention, executive function, language and visuospatial memory on neuropsychological evaluation (p<0.05, Spearman's rho or Kendell's tau-b).
CONCLUSIONS - Recurrent seizures in TLE are associated with disturbances in ARAS connectivity, which are part of the widespread network dysfunction that may be related to neurocognitive problems in this devastating disorder.
© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
OBJECTIVE - Currently, approximately 60-70% of patients with unilateral temporal lobe epilepsy (TLE) remain seizure-free 3 years after surgery. The goal of this work was to develop a presurgical connectivity-based biomarker to identify those patients who will have an unfavorable seizure outcome 1-year postsurgery.
METHODS - Resting-state functional and diffusion-weighted 3T magnetic resonance imaging (MRI) was acquired from 22 unilateral (15 right, 7 left) patients with TLE and 35 healthy controls. A seizure propagation network was identified including ipsilateral (to seizure focus) and contralateral hippocampus, thalamus, and insula, with bilateral midcingulate and precuneus. Between each pair of regions, functional connectivity based on correlations of low frequency functional MRI signals, and structural connectivity based on streamline density of diffusion MRI data were computed and transformed to metrics related to healthy controls of the same age.
RESULTS - A consistent connectivity pattern representing the network expected in patients with seizure-free outcome was identified using eight patients who were seizure-free at 1-year postsurgery. The hypothesis that increased similarity to the model would be associated with better seizure outcome was tested in 14 other patients (Engel class IA, seizure-free: n = 5; Engel class IB-II, favorable: n = 4; Engel class III-IV, unfavorable: n = 5) using two similarity metrics: Pearson correlation and Euclidean distance. The seizure-free connectivity model successfully separated all the patients with unfavorable outcome from the seizure-free and favorable outcome patients (p = 0.0005, two-tailed Fisher's exact test) through the combination of the two similarity metrics with 100% accuracy. No other clinical and demographic predictors were successful in this regard.
SIGNIFICANCE - This work introduces a methodologic framework to assess individual patients, and demonstrates the ability to use network connectivity as a potential clinical tool for epilepsy surgery outcome prediction after more comprehensive validation.
Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.