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Objective To examine the association of objectively measured, self-paced physical and cognitive activities across the first week postconcussion with symptom resolution in youth. Setting Emergency department or concussion clinics. Participants Youth aged 11 to 17 years with physician-confirmed concussion. Design Prospective cohort with repeated measures. Main measures Days from injury to symptom resolution, based on daily ratings by youth on the Post-Concussive Symptom Scale. Physical and cognitive activities were assessed using an ActiGraph and a Narrative Clip, respectively. Results A total of 83 youth participants were included (n = 54 [65%] males; mean age = 14.2 years, SD = 1.9). While self-paced daily physical and cognitive activities increased across the first week postinjury, daily postconcussion symptoms decreased. Increased daily step count was associated with an increased likelihood of early symptom resolution (hazard ratio [HR] = 1.17; 95% confidence interval [CI], 1.02-1.34). However, this association was not statistically significant after adjusting for acute postconcussion symptoms and other covariates. Greater school attendance time was associated with earlier symptom resolution (adjusted HR = 1.14; 95% CI, 1.02-1.27). Conclusion Self-paced physical and cognitive activities across the first week postinjury alone neither hastened nor prolonged concussion recovery. Youth with concussion may have some latitude to determine their activity levels.

Enzyme-responsive drug delivery systems (DDSs) have shown great potential in the diagnosis and treatment of cancer. Nitroreductase (NTR) that plays an essential role in the reduction of nitro compounds has been found to be overexpressed in tumor cells than in normal cells. Here, we present an amphiphilic polymer TNP that is flanked by an NTR responsive 4-nitrobenzyl group, hydrophobic AIE tetraphenylethylene (TPE), and polyethylene glycol hydrophilic moieties, which can be self-assembled into micelles to efficiently encapsulate the hydrophobic drug doxorubicin (DOX) in aqueous solution. In the presence of NADH, the 4-nitrobenzyl unit of TNP is reduced by NTR, leading to the decomposition of the TNP micelles and DOX release with the detection limit as low as 2.6 ng mL−1. MTT assays showed that TNP@DOX micelles possess an obvious toxicity against cancer cells, while negligible toxicity towards normal cells was observed. With the advantage of the AIE properties of TNP, the TNP@DOX micelles were able to be efficiently endocytosed by HeLa cells, and release DOX in a selective manner as determined by confocal laser scanning microscopy (CLSM) and flow cytometry (FCM) analyses. This work provides a promising nanoplatform for cancer diagnosis and treatment with controlled drug release.

The human brain is a biological organ, weighing about three pounds or 1.4 kg, that determines our behaviors, thoughts, emotions and consciousness. Although comprising only 2% of the total body weight, the brain consumes about 20% of the oxygen entering the body. With the expensive energy demand, the brain enables us to perceive and act upon the external world, as well as reflect on our internal thoughts and feelings. The brain is actually never at ‘rest’. Brain activities continue around the clock, ranging from functions enabling human–environment interactions to housekeeping during sleep, including processes such as synaptic homeostasis and memory formation. Whereas one could argue that sciences in the last century were dominated by physics and molecular biology, in the current century one of our major challenges is to elucidate how the brain works. A full understanding of brain functions and malfunctions is likely the most demanding task we will ever have.

A series of multifunctional compounds (MFCs) 1a–1e based on 1,8-naphthalimide and [12]aneN3 building blocks were designed and synthesized. They were used as not only fluorescent probes for recognition of Cu2+ ions but also as non-viral gene vectors for DNA and RNA delivery. Furthermore, their complexes with Cu2+ (1-Cu) could also selectively stain lysosome in HeLa cells. In order to achieve high performance multifunctional materials, structure-performance relationship of MFCs 1a–1e was studied. It was found that MFCs 1a–1e exhibited highly selective fluorescence turn-off for Cu2+, without interference by other metal ions in aqueous solution. The fluorescence emission of 1a–1e was quenched by a factor of 10-fold, 47-fold, 6-fold, 64-fold, and 15-fold respectively in the presence of Cu2+ ions. Due to high sensitivity, good water solubility, and low cytotoxicity, MFCs 1a–1d were successfully applied in the recognition of Cu2+ and selectively staining lysosome in HeLa cells. Most importantly, MFCs 1a and 1b had excellent HeLa cell selectivity in RNA delivery, and their performances were far better than lipofectamine 2000 and 25 kDa PEI.

PurposeRecently, we developed a novel active learning framework, qVFM, to map visual functions in the visual field. The method has been implemented and validated in measuring light sensitivity and contrast sensitivity visual field maps (VFMs) of normal observers. In this study, we evaluated the performance of the qVFM method in mapping the light sensitivity VFM of simulated patients with peripheral scotoma, glaucoma, age-related macular degeneration (AMD), and cataract.MethodsFor each simulated patient, we sampled 100 locations (60 × 60 degrees) of the visual field and compared the performance of the qVFM method with a procedure that tests each location independently (the qYN method) in a cued Yes/No task. Two different switch modules, the distribution sampling method (DSM) and parameter delivering method (PDM), were implemented in the qVFM method. Simulated runs of 1,200 trials were used to compare the accuracy and precision of the qVFM-DSM, qVFM-PDM and qYN methods.ResultsThe qVFM method with both switch modules can provide accurate, precise, and efficient assessments of the light sensitivity VFM for the simulated patients, with the qVFM-PDM method better at detecting VFM deficits in the simulated glaucoma.ConclusionsThe qVFM method can be used to characterize residual vision of simulated ophthalmic patients. The study sets the stage for further investigation with real patients and potential translation of the method into clinical practice.

PurposeAmblyopia affects not only spatial vision but also temporal vision. In this study, we aim to investigate temporal processing deficits in amblyopia.MethodsTwenty amblyopic patients (age: 27.0 ± 5.53 years, 15 males), and 25 normal observers (age: 25.6 ± 4.03 years, 15 males) were recruited in this study. Contrast thresholds in an orientation discrimination task in five target-mask stimulus onset asynchronies (SOA) conditions (16.7 ms, 33.4 ms, 50.0 ms, 83.4 ms, and ∞/no noise) were measured. An elaborated perceptual template model (ePTM) was fit to the behavioral data to derive the temporal profile of visual processing for each participant.ResultsThere were significant threshold differences between the amblyopic and normal eyes [F(1,43) = 10.6, p = 0.002] and a significant group × SOA interaction [F(2.75,118) = 4.98, p = 0.004], suggesting different temporal processing between the two groups. The ePTM fitted the data well (χ2 test, all ps > 0.50). Compared to the normal eye, the amblyopic eye had a lower template gain (p = 0.046), and a temporal window with lower peak and broader width (all ps < 0.05). No significant correlation was found between the observed temporal deficits and visual acuity in amblyopia (ps > 0.50). Similar results were found in the anisometropic amblyopia subgroup. No significant difference was found between the fellow eyes of the monocular amblyopia and the normal eyes.ConclusionAmblyopia is less efficient in processing dynamic visual stimuli. The temporal deficits in amblyopia, represented by a flattened temporal window, are likely independent of spatial vision deficits.

Purpose To explore whether subtle changes in visual quality can be detected using different measures of visual function against the quick contrast sensitivity function test (quick CSF). Methods Sixty participants, aged 17 to 34 years, were enrolled. Participants' vision was degraded by 0.25 D undercorrection (0.25 D), 60% neutral density filter brightness reduction (60% ND), and 0.8 Bangerter foil optical diffusion (0.8BAN). Visual function tests including visual acuity and contrast sensitivity (CSV-1000E and quick CSF) were measured with participant's best-corrected vision and under simulated visual degradation conditions. Test sensitivities in detecting differences were compared. Results Statistically significant visual acuity degradation was observed in the 0.8BAN condition only (Pcorrected < 0.001). With CSV-1000E and outliers removed, significant CS degradation was observed in all spatial frequencies, area under log CSF (AULCSF) in the 0.8BAN condition (Pcorrected < 0.001 for all), medium and high spatial frequencies and AULCSF in the 60%ND condition (Pcorrected,6cpd = 0.002, Pcorrected,12cpd = 0.005, Pcorrected,18cpd = 0.001, Pcorrected,AULCSF < 0.001) and the 0.25 D condition (Pcorrected,6cpd = 0.011, Pcorrected,12cpd = 0.013, Pcorrected,18cpd = 0.015, Pcorrected,AULCSF < 0.001). With the quick CSF, significant CS degradation was observed in all simulated visual conditions in all spatial frequencies, cutoff frequency and AULCSF (Pcorrected < 0.001 for all). Test-retest reliability of the quick CSF method was high; coefficient of repeatability ranged from 0.14 to 0.18 logCS. Conclusions Compared with visual acuity and chart-based CS tests, the quick CSF method provided more reliable and sensitive measures to detect small visual changes. Translational Relevance The quick CSF method can provide sensitive and reliable measures to monitor disease progression and assess treatment outcomes.

Aim: This pilot study explored whether childhood stroke impairs performance on theory of mind (ToM) tasks and whether ToM task performance correlates with resting state connectivity in brain regions linked with social cognition. Method: We performed a case-control study of 10 children with stroke and 10 age- and gender-matched controls. They completed 2 ToM tasks, and resting state connectivity was measured with functional magnetic resonance imaging (MRI). Results: Children with stroke performed worse than controls on conative ToM tasks. Resting state connectivity in the central executive network was significantly higher and connectivity between right and left inferior parietal lobules was significantly decreased in children with stroke. Resting state activity and ToM performance were not significantly correlated. Interpretation: Childhood stroke results in poorer performance on specific ToM tasks. Stroke is associated with changes in resting state connectivity in networks linked with social cognition including ToM. Although the basis for these changes in connectivity is not well understood, these results may provide preliminary insights into potential mechanisms affecting social cognition after stroke. The findings suggest that further study of the effect of childhood stroke on network connectivity may yield insights as to how stroke affects cognitive functions in children.

A recurrent theme of both cognitive and network neuroscience is that the brain has a consistent subnetwork structure that maps onto functional specialization for different cognitive tasks, such as vision, motor skills, and attention. Understanding how regions in these subnetworks relate is thus crucial to understanding the emergence of cognitive processes. However, the organizing principles that guide how regions within subnetworks communicate, and whether there is a common set of principles across subnetworks, remains unclear. This is partly due to available tools not being suited to precisely quantify the role that different organizational principles play in the organization of a subnetwork. Here, we apply a joint modeling technique – the correlation generalized exponential random graph model (cGERGM) – to more completely quantify subnetwork structure. The cGERGM models a correlation network, such as those given in functional connectivity, as a function of activation motifs – consistent patterns of coactivation (i.e., connectivity) between collections of nodes that describe how the regions within a network are organized (e.g., clustering) – and anatomical properties – relationships between the regions that are dictated by anatomy (e.g., Euclidean distance). By jointly modeling all features simultaneously, the cGERGM models the unique variance accounted for by each feature, as well as a point estimate and standard error for each, allowing for significance tests against a random graph and between graphs. Across eight functional subnetworks, we find remarkably consistent organizational properties guiding subnetwork architecture, suggesting a fundamental organizational basis for subnetwork communication. Specifically, all subnetworks displayed greater clustering than would be expected by chance, but lower preferential attachment (i.e., hub use). These findings suggest that human functional subnetworks follow a segregated highway structure, in which tightly clustered subcommunities develop their own channels of communication rather than relying on hubs.

Typical fMRI studies have focused on either the mean trend in the blood-oxygen-level-dependent (BOLD) time course or functional connectivity (FC). However, other statistics of the neuroimaging data may contain important information. Despite studies showing links between the variance in the BOLD time series (BV) and age and cognitive performance, a formal framework for testing these effects has not yet been developed. We introduce the Variance Design General Linear Model (VDGLM), a novel framework that facilitates the detection of variance effects. We designed the framework for general use in any fMRI study by modeling both mean and variance in BOLD activation as a function of experimental design. The flexibility of this approach allows the VDGLM to i) simultaneously make inferences about a mean or variance effect while controlling for the other and ii) test for variance effects that could be associated with multiple conditions and/or noise regressors. We demonstrate the use of the VDGLM in a working memory application and show that engagement in a working memory task is associated with whole-brain decreases in BOLD variance., 18 pages, 7 figures

Previous studies have demonstrated that orientation-specific deprivation in early life can lead to neural deficits of spatial vision in certain space, and can even result in meridional amblyopia (MA). Individuals with astigmatism are the optimal and natural models for exploring this asymmetric development of spatial vision in the human visual system. This study aims to assess the contrast sensitivity function (CSF) and EEG signals along two principal meridians in participants with regular astigmatism when being optimal optical corrected. Twelve participants with astigmatism (AST group, 20 eyes) and thirteen participants with (MA group, 19 eyes) were recruited in the current study. CSFs and spatial sweep visual evoked potentials (sVEP) were measured with vertical and horizontal sinewave gratings along two principal meridians monocularly. Area under log CSF (AULCSF), spatial frequency threshold corresponding to 80% contrast gratings (SF threshold at 80% ctr), and CSF acuity were calculated from CSF test. In addition, sVEP amplitudes and thresholds were calculated with the recursive least square method. Participants with astigmatism exhibited marked vertical-horizontal resolution disparities even after they were corrected with optimal optical corrections. CSF tests showed that AULCSF along weak meridian (measured with horizontal gratings) was lower than that along strong meridian (measured with vertical gratings) in both groups. Significant meridional disparity of CSF acuity was also found in both groups. In addition, the MA group showed larger meridional disparity compared to the AST group. Spatial sVEP thresholds also supported the existence of marked meridional disparity. Our results suggest that meridian-specific partial deprivation in early life might lead to monocularly asymmetric development of spatial vision in the human visual system. In terms of application, we tested the feasibility and reliability of adopting psychophysical and EEG scalings to investigate the asymmetric development of spatial vision related to astigmatism. These paradigms are potentially applicable to reduce and even eliminate the meridional disparity in the primary visual cortex by adopting perceptual learning or other vision-related interventions.

The mapping between visual inputs on the retina and neuronal activations in the visual cortex, i.e., retinotopic map, is an essential topic in vision science and neuroscience. Human retinotopic maps can be revealed by analyzing the functional magnetic resonance imaging (fMRI) signal responses to designed visual stimuli in vivo. Neurophysiology studies summarized that visual areas are topological (i.e., nearby neurons have receptive fields at nearby locations in the image). However, conventional fMRI-based analyses frequently generate non-topological results because they process fMRI signals on a voxel-wise basis, without considering the neighbor relations on the surface. Here we propose a topological receptive field (tRF) model which imposes the topological condition when decoding retinotopic fMRI signals. More specifically, we parametrized the cortical surface to a unit disk, characterized the topological condition by tRF, and employed an efficient scheme to solve the tRF model. We tested our framework on both synthetic and human fMRI data. Experimental results showed that the tRF model could remove the topological violations, improve model explaining power, and generate biologically plausible retinotopic maps. The proposed framework is general and can be applied to other sensory maps.

Made available in DSpace on 2021-06-25T10:13:53Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-04-01 Background: Neurodegeneration is a complex cellular process linked to prompt changes in myelin integrity and gradual neuron loss. Current imaging techniques offer estimations of myelin volumes in lesions/remyelinated areas but are limited to detect subtle injury. Purpose: To investigate whether measurements detected by a signal hierarchically isolated as a function of time-to-echo (SHIFT) MRI technique can determine changes in myelin integrity and fiber axolemma. Study Type: Prospective animal model. Animal Model: Surgically demyelinated spinal cord (SC) injury model in rodents (n = 6). Field Strength/Sequence: Gradient-echo spin-echo at 3T. Assessment: Multicompartment T2 relaxations were computed by SHIFT MRI in 75-microns-resolution images of the SC injury penumbra region 2 weeks post-trauma. G-ratio and axolemma delamination were assessed by transmission electron microscopy (TEM) in intact and injured samples. SC myelinated nerve fraction was computed by SHIFT MRI prospectively and assessed histologically. Statistical Tests: Relations between SHIFT-isolated T2-components and TEM measurements were studied using linear regression and t-tests. Pearson's correlation and significance were computed to determine the SHIFT's sensitivity to detect myelinated fibers ratio in gray matter. Regularized least-squares-based ranking analysis was employed to determine SHIFT MRI's ability to discern intact and injured myelinated nerves. Results: Biexponential signals isolated by SHIFT MRI for intact vs. lesion penumbra exhibited changes in T2, shifting from intermediate components (25 ± 2 msec) to long (43 ± 11 msec) in white matter, and similarly in gray matter regions-of-interest (31 ± 2 to 46 ± 16 msec). These changes correlated highly with TEM g-ratio and axon delamination measurements (P < 0.05). Changes in short T2 components were observed but not statistically significant (8.5 ± 0.5 to 7 ± 3 msec, P = 0.445, and 4.0 ± 0.9 to 7 ± 3 msec, P = 0.075, respectively). SHIFT MRI's ability to detect myelinated fibers within gray matter was confirmed (P < 0.001). Data Conclusion: Changes detected by SHIFT MRI are associated with abnormal intermembrane spaces formed upon mild injury, directly correlated with early neuro integrity loss. Level of Evidence 1. Technical Efficacy Stage 2. Center for Neuroregneration Department of Neurosurgery Houston Methodist Research Institute Houston Methodist Hospital Department of Biological Physics Universidade Estadual Paulista UNESP Division of Arts and Sciences NYU Shanghai NYU-ECNU Institute of Cognitive Neuroscience at NYU Shanghai Center for Neural Science and Department of Psychology New York University Department of Biological Physics Universidade Estadual Paulista UNESP

Retinotopic mapping, the mapping of visual input on the retina to cortical neurons, is an important topic in vision science. Typically, cortical neurons are related to visual input on the retina using functional magnetic resonance imaging (fMRI) of cortical responses to slowly moving visual stimuli on the retina. Although it is well known from neurophysiology studies that retinotopic mapping is locally diffeomorphic (i.e., smooth, differentiable, and invertible) within each local area, the retinotopic maps from fMRI are often not diffeomorphic, especially near the fovea, because of the low signal-noise ratio of fMRI. The aim of this study is to develop and solve a mathematical model that produces diffeomorphic retinotopic mapping from fMRI data. Specifically, we adopt a geometry concept, the Beltrami coefficient, as the tool to define diffeomorphism, and model the problem in an optimization framework. Efficient numerical methods are proposed to solve the model. Experimental results with both synthetic and real retinotopy data demonstrate that the proposed method is superior to conventional smoothing methods.

Nitric oxide (NO) is a messenger molecule in organisms, participating in the regulation of many biological processes. The abnormal expression of NO is often observed in a variety of diseases, including cerebral ischemia, atherosclerosis, and cancer. However, a suitable tool that can directly and sensitively detect NO in vitro and in vivo is important for understanding its various biological functions. In this report, a new fluorescent probe for nitric oxide, DHP-4, was prepared, based on dihydropyridine-coumarin. DHP-4 was able to greatly enhance the fluorescence of NO, but did not affect the fluorescence emissions of other reactive oxygen species and nitrogen species, demonstrating its highly selective and sensitive response to NO. The probe generated stable optical signals in a buffer solution at pH values ranging from 3 to 10. In addition, DHP-4 could detect NO directly, showed low cellular toxicity, and was successfully applied to determine NO in Raw 264.7 cells, indicating its great potential as a tool for investigating the biological roles of NO in vivo.

Current clinical evaluation, which focuses on central vision, could be improved through characterization of residual vision with peripheral testing of visual acuity, contrast sensitivity, color vision, crowding, and reading speed. Assessing visual functions in addition to light sensitivity, a comprehensive visual field map (VFM) would be valuable for detecting and managing eye diseases. In a previous study, we developed a Bayesian adaptive qVFM method that combines a global module for preliminary assessment of the VFM's shape and a local module for assessment at individual retinal locations. The method was validated in measuring the light sensitivity VFM. In this study, we extended the qVFM method to measure contrast sensitivity across the visual field. In both simulations and psychophysics, we sampled 64 visual field locations (48 x 48 deg) and compared the qVFM method with a procedure that tested each retinal location independently (qFC; Lesmes et al., 2015). In each trial, subjects were required to identify a single optotype (size: 2.5 x 2.5 deg), one of 10 filtered Sloan letters. To compare the accuracy and precision of the two methods, three simulated eyes were tested in 1,280 trials with each method. In addition, data were collected from 10 eyes (5 OS, 5 OD) of five normal observers. For simulations, the average RMSE of the estimated contrast sensitivity with the qVFM and qFC methods were 0.057 and 0.100 after 320 trials, and 0.037 and 0.041 after 1,280 trials [all in log10 units, represent as log(sensitivity)], respectively. The average SD of the qVFM and qFC estimates were 0.054 and 0.096 after 320 trials, and 0.032 and 0.041 after 1,280 trials, respectively. The within-run variability (68.2% HWCIs) were comparable to the cross-run variability (SD). In the psychophysics experiment, the average HWCI of the estimated contrast sensitivity from the qVFM and qFC methods across the visual field decreased from 0.33 on the first trial to 0.072 and 0.16 after 160, and to 0.060 and 0.10 after 320 trials. The RMSE between the qVFM and qFC estimates started at 0.26, decreased to 0.12 after 160 and to 0.11 after 320 qVFM trials. The qVFM provides an accurate, precise, and efficient mapping of contrast sensitivity across the entire visual field. The method might find potential clinical applications in monitoring vision loss, evaluating therapeutic interventions, and developing effective rehabilitation for visual diseases.

Purpose Aging affects a variety of visual functions. In this study, we aim to quantitatively investigate the temporal characteristics of visual processing in aging. Methods Twelve younger (24.1 ± 1.6 years) and 12 older observers (58.4 ± 3.6 years) participated in the study. All participants had normal or corrected-to-normal vision. The contrast thresholds of the participants were measured using an orientation discrimination task with white external noise masks. The target-mask stimulus onset asynchronies were 16.7 ms, 33.4 ms, 50.0 ms, 83.4 ms, and ∞ (no external noise masks) in separate conditions. The signal stimulus was carefully chosen such that it was equally visible for the younger and older participants. An elaborated perceptual template model (ePTM) was fit to the data of each participant. Results Without masks, there was no difference in contrast thresholds between the younger and older groups (P = 0.707). With masks, contrast thresholds in the older group elevated more than those in the younger group, and the pattern of threshold elevation differed in the two groups. The ePTM fitted the data well, with the older observers having lower template gains than the younger observers (P = 3.58 × 10-6). A further analysis of the weight parameters of the temporal window revealed that the older observers had a flatter temporal window than the younger observers (P = 0.025). Conclusions Age-related temporal processing deficits were found in older observers with normal contrast sensitivity to the signal stimuli. The deficits were accounted for by the inferior temporal processing window of the visual system in aging.

The mapping between the visual input on the retina to the cortical surface, i.e., retinotopic mapping, is an important topic in vision science and neuroscience. Human retinotopic mapping can be revealed by analyzing cortex functional magnetic resonance imaging (fMRI) signals when the subject is under specific visual stimuli. Conventional methods process, smooth, and analyze the retinotopic mapping based on the parametrization of the (partial) cortical surface. However, the retinotopic maps generated by this approach frequently contradict neuropsychology results. To address this problem, we propose an integrated approach that parameterizes the cortical surface, such that the parametric coordinates linearly relates the visual coordinate. The proposed method helps the smoothing of noisy retinotopic maps and obtains neurophysiological insights in human vision systems. One key element of the approach is the Error-Tolerant Teichmuller Map, which uniforms the angle distortion and maximizes the alignments to self-contradicting landmarks. We validated our overall approach with synthetic and real retinotopic mapping datasets. The experimental results show the proposed approach is superior in accuracy and compatibility. Although we focus on retinotopic mapping, the proposed framework is general and can be applied to process other human sensory maps., submitted to MICCAI

Human visual cortex is organized into several functional re-gions/areas. Identifying these visual areas of the human brain (i.e., V1, V2, V4, etc) is an important topic in neurophysiology and vision science. Retinotopic mapping via functional magnetic resonance imaging (fMRI) provides a noninvasive way of defining the boundaries of the visual areas. It is well known from neurophysiology studies that retino-topic mapping is diffeomorphic within each local area (i.e. locally smooth, differentiable, and invertible). However, due to the low signal-noise ratio of fMRI, the retinotopic maps from fMRI are often not diffeomorphic, making it difficult to delineate the boundaries of visual areas. The purpose of this work is to generate diffeomorphic retinotopic maps and improve the accuracy of the retinotopic atlas from fMRI measurements through the development of a specifically designed registration procedure. Although there are sophisticated existing cortical surface registration methods, most of them cannot fully utilize the features of retinotopic mapping. By considering unique retinotopic mapping features, we form a qua-siconformal geometry-based registration model and solve it with efficient numerical methods. We compare our registration with several popular methods on synthetic data. The results demonstrate that the proposed registration is superior to conventional methods for the registration of retinotopic maps. The application of our method to a real retinotopic mapping dataset also results in much smaller registration errors.

BACKGROUND: Sequence optimization in neonates might improve detection sensitivity of abnormalities for a variety of conditions. However this has been historically challenging because tissue properties such as the longitudinal relaxation time and proton density differ significantly between neonates and adults. OBJECTIVE: To optimize the magnetization-prepared rapid gradient echo (MP-RAGE) sequence to enhance both signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) efficiencies. MATERIALS AND METHODS: We optimized neonatal MP-RAGE sequence through (1) reducing receive bandwidth to decrease noise, (2) shortening acquisition train length (acquisition number per repetition time or total number of read-out radiofrequency rephrasing pulses) using slice partial Fourier acquisition and (3) simulating the solution of Bloch’s equation under optimal receive bandwidth and acquisition train length. Using the optimized sequence parameters, we scanned 12 healthy full-term infants within 2 weeks of birth and four preterm infants at 40 weeks’ corrected age. RESULTS: Compared with a previously published neonatal protocol, we were able to reduce the total scan time by 60% and increase the average SNR efficiency by 160% (P

The insula plays an important role in response inhibition. Most relevant here, it has been proposed that the dorsal anterior insular cortex (dAIC) plays a central role in a salience network that is responsible for switching between the default mode network and the executive control network. However, the insula’s role in sexually motivated response inhibition has not yet been studied. In the present study, eighty-five 18-30 year-old sexually active men who have sex with men (MSM) performed an erotic Go/NoGo task while in an MRI scanner. Participants’ real-world sexual risk-taking (frequency of condomless anal intercourse over the past 90 days) was then correlated with their neural activity during the task. We found greater activity in bilateral anterior insular cortex (both dorsal and ventral) on contrasts with stronger motivational information (attractive naked male pictures versus pictures of clothed, middle-aged females) and on contrasts requiring greater response inhibition (NoGo versus Go). We also found that activity in the right dAIC was negatively correlated with participants’ real-world sexual risk-taking. Our results confirmed the involvement of the insular cortex in motivated response inhibition. Especially, the decreased right dAIC activity may reduce the likelihood that the executive control network will come online when individuals are faced with situations requiring inhibitory control and thus lead them to make more risky choices.

Many studies have focused on patients with schizophrenia with or without auditory verbal hallucinations (AVHs), but due to the complexity of schizophrenia, biologically based diagnosis of patients with schizophrenia remains unsolved. The objectives of this study are to classify between first-episode drug-naïve patients with schizophrenia and healthy controls, and to classify between patients with and without AVHs. Resting state fMRI data from 41 patients with schizophrenia (22 with and 19 without AVHs) and 23 normal controls (NC) were included to compute functional connectivity between brain regions. Classifiers based on support vector machine (SVM) were developed to classify patients with schizophrenia from NC, as well as between the two subgroups of patients. The classification accuracy was evaluated with a leave-one-out cross-validation (LOOCV) strategy. The accuracy in discriminating both subgroups of patients from NC was 81.3%, with 92.0% (sensitivity) and 65.2% (specificity) for the patients and NC, respectively. The classification accuracy in discriminating patients with and without AVHs was 75.6%, with 77.3% (sensitivity) and 73.9% (specificity) for patients with and without AVHs, respectively. The results suggest that functional connectivity provided good discriminative power not only for identifying patients with schizophrenia among NC, but also in discriminating patients with schizophrenia with and without AVHs., Highlights • Normal controls, schizophrenia patients with and without AVHs were successfully classified. • Using LOOCV, the classifier achieved an accuracy of groups of 81.3% for all the three groups of subjects. • Patients with AVHs were differentiated with those without AVHs with an accuracy of 75.6%. • The proposed may help with the clinical diagnosis of schizophrenia patients.

Purpose The goal of this study is to develop a hierarchical Bayesian model (HBM) to better quantify uncertainty in visual acuity (VA) tests by incorporating the relationship between VA threshold and range across multiple individuals and tests. Methods The three-level HBM consisted of multiple two-dimensional Gaussian distributions of hyperparameters and parameters of the VA behavioral function (VABF) at the population, individual, and test levels. The model was applied to a dataset of quantitative VA (qVA) assessments of 14 eyes in 4 Bangerter foil conditions. We quantified uncertainties of the estimated VABF parameters (VA threshold and range) from the HBM and compared them with those from the qVA. Results The HBM recovered covariances between VABF parameters and provided better fits to the data than the qVA. It reduced the uncertainty of their estimates by 4.2% to 45.8%. The reduction of uncertainty, on average, resulted in 3 fewer rows needed to reach a 95% accuracy in detecting a 0.15 logMAR change of VA threshold or both parameters than the qVA. Conclusions The HBM utilized knowledge across individuals and tests in a single model and provided better quantification of the uncertainty of the estimated VABF, especially when the number of tested rows was relatively small. Translational Relevance The HBM can increase the accuracy in detecting VA changes. Further research is necessary to evaluate its potential in clinical populations.

Retinotopic mapping, i.e., the mapping between visual inputs on the retina and neuronal activations in cortical visual areas, is one of the central topics in visual neuroscience. For human observers, the mapping is obtained by analyzing functional magnetic resonance imaging (fMRI) signals of cortical responses to slowly moving visual stimuli on the retina. Although it is well known from neurophysiology that the mapping is topological (i.e., the topology of neighborhood connectivity is preserved) within each visual area, retinotopic maps derived from the state-of-the-art methods are often not topological because of the low signal-to-noise ratio and spatial resolution of fMRI. The violation of topological condition is most severe in cortical regions corresponding to the neighborhood of the fovea (e.g., < 1 degree eccentricity in the Human Connectome Project (HCP) dataset), significantly impeding accurate analysis of retinotopic maps. This study aims to directly model the topological condition and generate topology-preserving and smooth retinotopic maps. Specifically, we adopted the Beltrami coefficient, a metric of quasiconformal mapping, to define the topological condition, developed a mathematical model to quantify topological smoothing as a constrained optimization problem, and elaborated an efficient numerical method to solve the problem. The method was then applied to V1, V2, and V3 simultaneously in the HCP dataset. Experiments with both simulated and real retinotopy data demonstrated that the proposed method could generate topological and smooth retinotopic maps., Author summary Retinotopic maps of human observers derived from state-of-the-art methods are often not topological because of the low signal-to-noise ratio and spatial resolution of fMRI. The proposed topological smoothing method can generate topology-preserving and smooth retinotopic maps in V1, V2, and V3 simultaneously from retinotopy fMRI data.

Visual perceptual learning through practice or training can significantly improve performance on visual tasks. Originally seen as a manifestation of plasticity in the primary visual cortex, perceptual learning is more readily understood as improvements in the function of brain networks that integrate processes, including sensory representations, decision, attention, and reward, and balance plasticity with system stability. This review considers the primary phenomena of perceptual learning, theories of perceptual learning, and perceptual learning's effect on signal and noise in visual processing and decision. Models, especially computational models, play a key role in behavioral and physiological investigations of the mechanisms of perceptual learning and for understanding, predicting, and optimizing human perceptual processes, learning, and performance. Performance improvements resulting from reweighting or readout of sensory inputs to decision provide a strong theoretical framework for interpreting perceptual learning and transfer that may prove useful in optimizing learning in real-world applications.

The gold standard of a successful amblyopia treatment is full recovery of visual acuity (VA) in the amblyopic eye, but there has been no systematic study on both monocular and binocular visual functions. In this research, we aimed to quantify visual qualities with a variety of perceptual tasks in subjects with treated amblyopia. We found near stereoacuity and pAE dominance in binocular rivalry in “treated” amblyopia were largely comparable to those of normal subjects. CSF of the pAE remained deficient in high spatial frequencies. The binocular contrast summation ratio is significantly lower than normal standard. The interocular balance point is 34%, indicating that contrast in pAE is much less effective as the same contrast in pFE in binocular phase combination. Although VA, stereoacuity and binocular rivalry at low spatial frequency in treated amblyopes were normal or nearly normal, the pAE remained “lazy” in high frequency domain, binocular contrast summation, and interocular phase combination. Our results suggest that structured monocular and binocular training are necessary to fully recover deficient functions in amblyopia.

The sense of vision allows us to discriminate fine details across a wide range of tasks. How to improve this perceptual skill, particularly within a short training session, is of substantial interest. Emerging evidence suggests that mixing easy trials can quickly improve performance in hard trials, but it is equivocal whether the improvement is short-lived or long-lasting, and additionally what accounts for this improvement. Here, by tracking objective performance (accuracy) and subjective experience (ratings of target visibility and choice confidence) over time and in a large sample of participants, we demonstrate the coexistence of transient and sustained effects of mixing easy trials, which differ markedly in their timescales, in their effects on subjective awareness, and in individual differences. In particular, whereas the transient effect was found to be ubiquitous and manifested similarly across objective and subjective measures, the sustained effect was limited to a subset of participants with weak convergence from objective and subjective measures. These results indicate that mixture of easy trials enables two distinct, co-existing forms of rapid perceptual improvements in hard trials, as mediated by robust priming and fragile learning. Placing constraints on theory of brain plasticity, this finding may also have implications for alleviating visual deficits.

The three-dimension Fast Low Angle SHot Magnetic Resonance Imaging (3D FLASH) sequence has been widely adopted in medical diagnostic imaging because of its availability, simplicity, and high spatial resolution. To improve the quality of structural brain images acquired with the 3D FLASH sequence, we developed a parameter optimization scheme and image inhomogeneity correction methods. The optimal imaging parameters were determined by maximizing gray-matter and white-matter CNR efficiency. Compared to protocols based on published parameters, applying the proposed optimal imaging parameters increased CNR efficiency by > 10%. Image inhomogeneity, including signal and CNR inhomogeneity, was corrected by the choice of an optimal flip angle, estimated transmit function, and estimated receive sensitivity. As a result, our optimization and image inhomogeneity correction greatly improved the quality of images acquired with the 3D FLASH sequence.

Cross-modal learning requires the use of information from different sensory modalities. This study investigated how the prior visual experience of late blind individuals could modulate neural processes associated with learning of sound localization. Learning was realized by standardized training on sound localization processing, and experience was investigated by comparing brain activations elicited from a sound localization task in individuals with (late blind, LB) and without (early blind, EB) prior visual experience. After the training, EB showed decreased activation in the precuneus, which was functionally connected to a limbic-multisensory network. In contrast, LB showed the increased activation of the precuneus. A subgroup of LB participants who demonstrated higher visuospatial working memory capabilities (LB-HVM) exhibited an enhanced precuneus-lingual gyrus network. This differential connectivity suggests that visuospatial working memory due to the prior visual experience gained via LB-HVM enhanced learning of sound localization. Active visuospatial navigation processes could have occurred in LB-HVM compared to the retrieval of previously bound information from long-term memory for EB. The precuneus appears to play a crucial role in learning of sound localization, disregarding prior visual experience. Prior visual experience, however, could enhance cross-modal learning by extending binding to the integration of unprocessed information, mediated by the cognitive functions that these experiences develop. Electronic supplementary material The online version of this article (doi:10.1007/s10548-017-0549-z) contains supplementary material, which is available to authorized users.

A water soluble Hantzsch ester derivative of coumarin, DHPS, was synthesized and successfully applied in the fluorescent sensing nitric oxide (NO) in aqueous solution. The fluorescence of probe DHPS is extremely weak, while its fluorescence was greatly switched on upon the addition of NO solution and showed high selectivity and sensitivity to NO. The limitation of the detection was calculated to be 18nM. The NO-induced aromatization of dihydropyridine in DHPS to pyridine derivative (PYS) proved to be the switching mechanism for the fluorescent sensing process, which was confirmed through spectra characterization and computation study. Cytotoxicity assay demonstrated both DHPS and PYS are biocompatible, the DHPS was successfully applied to track the endogenously produced NO in the RAW 264.7 cells.

The ability to expand and contract one's mental horizons allows people to regulate toward ends that are both distant and near. One challenge that people face when regulating toward distant relative to near ends is the lack of information about detailed specifics. In response, construal level theory (CLT) proposes that people engage in high-level construal-a representational process that highlights the essential properties of events that are invariant across potential instantiations. To tailor responses to more immediate events, however, CLT proposes that people engage in low-level construal-a representational process that highlights idiosyncratic specifics that distinguish events from one another. The present article uses network neuroscience to investigate the neurocognitive mechanisms for these representational processes. While undergoing fMRI, participants were instructed to think about the distant versus near future, and completed tasks that directly manipulated high-level versus low-level construal. Thinking about the distant future and engaging in high-level construal both promoted integration across the network (indexed by global efficiency). Thinking about the near future and engaging in low-level construal promoted segregation within the network (indexed by clustering coefficient). These are the first findings to document how the brain reconfigures to support the expansion versus contraction of one's mental horizons, and provides new insight into the neural mechanisms that help people regulate toward distant versus near ends. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

IntroductionAlthough current guidelines for the early clinical management of sports-related concussion (SRC) call for a gradual return-to-activity, the optimal level of rest needed to promote recovery remains unknown. This paper describes the protocol of the Rest Evaluation for Active Concussion Treatment (ReAct) study which objectively measures physical and cognitive rest following SRC and its relation to recovery among youth athletes.Methods and analysisYouth athletes aged 11–17 years are recruited preinjury and enrolled within 72 hours following a physician-diagnosed concussion. Injury information and acute clinical presentation are assessed at the time of injury. Youth participants are prospectively followed to objectively monitor daily physical and cognitive rest using two electronic devices: ActiGraph (to measure physical rest and sleep) and Narrative Clip (to measure cognitive rest), along with self-reported postconcussive symptoms using daily surveys. Other concussion outcomes, including functional outcomes, are assessed by surveying youth and their parents at three time points: (1) within 72 hours of injury, (2) at day 7 postenrolment and (3) at symptom resolution (or a maximum of 45 days postconcussion).Ethics and disseminationThis study has received ethical approval from the Institutional Review Board (IRB) at the participating institution (IRB at Nationwide Children’s Hospital, IRB16-00613). The results of the study will be presented at national and international scientific conferences and published in peer-reviewed journals.

Neuroadaptations caused by chronic methamphetamine (MA) use are likely major contributors to high relapse rate following treatment. Thus, focusing intervention efforts at pre-empting addiction in vulnerable populations, thereby preventing MA-use-induced neurological changes that make recovery so challenging, may prove more effective than targeting chronic users. One approach is studying casual/recreational users, not diagnosed with substance use disorder. This group may be at high risk for addiction due to their experience with MA. On the other hand, they may be resilient against addiction since they were able to maintain casual use over the years and not become addicted. Understanding their neuro-cognitive characteristics during decision-making and risk-taking would help solve this dilemma and, may help identify intervention strategies. Unfortunately, research on neuro-cognitive characteristics of casual MA users is currently lacking. In this work we begin to address this deficit. This study was part of a larger investigation of neural correlates of risky sexual decision-making in men who have sex with men. While undergoing functional magnetic resonance imaging, 31 casual MA users and 66 non-users performed the CUPS task, in which they decided to accept or refuse a series of mixed gambles. Convergent results from whole brain, region of interest and psychophysiological interaction (PPI) analyses are presented. Whole brain analysis identified an amygdala-striatal cluster with weaker activation in casual MA users compared to non-users during decision-making. Activity in that cluster inversely correlated with decisions to gamble: lower activation corresponded to higher risk taking. Using this cluster as a seed in PPI analyses, we identified a wide range of neural network differences between casual MA users and non-users. Parametric whole brain analyses identified clusters in the ventral striatum, posterior insula and precuneus where activations modulated by risk and reward were significantly weaker in casual MA users than in non-users. The striatal cluster identified in these analyses overlapped with the amygdala-striatal cluster. This work identified neural differences in casual MA users' reward processing and outcome learning systems which may underlie their increased real-world risk-taking. It suggests that while making decisions casual MA users focus primarily on potential gain unlike non-users who also take the riskiness of the choice into consideration., Highlights • Neurocognitive processes of casual meth users, not yet addicted but at high risk. • Convergent results from whole brain, psychophysiological interaction and ROI. • Isolated key deficits in reward processing and outcome learning. • Identified deficits may contribute to increased lab and real-world risk-taking.