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INTRODUCTION: The rapid development of the space industry requires a deeper understanding of spaceflight's impact on the brain. MRI research reports brain volume changes following spaceflight in astronauts, potentially affecting cognition. Recently, we have demonstrated that this evidence of volumetric changes, as measured by typical T1-weighted sequences (e.g., magnetization-prepared rapid gradient echo sequence; MPRAGE), is error-prone due to the microgravity-related redistribution of cerebrospinal fluid in the brain. More modern neuroimaging methods, particularly dual-echo MPRAGE (DEMPRAGE) and magnetization-prepared rapid gradient echo sequence utilizing two inversion pulses (MP2RAGE), have been suggested to be resilient to this error. Here, we tested if these imaging modalities offered consistent segmentation performance improvements in some commonly employed neuroimaging software packages. METHODS: We conducted manual gray matter tissue segmentation in traditional T1w MRI images to utilize for comparison. Automated tissue segmentation was performed for traditional T1w imaging, as well as on DEMPRAGE and MP2RAGE images from the same subjects. Statistical analysis involved a comparison of total gray matter volumes for each modality, and the extent of tissue segmentation agreement was assessed using a test of similarity (Dice coefficient). RESULTS: Neither DEMPRAGE nor MP2RAGE exhibited consistent segmentation performance across all toolboxes tested. DISCUSSION: This research indicates that customized data collection and processing methods are necessary for reliable and valid structural MRI segmentation in astronauts, as current methods provide erroneous classification and hence inaccurate claims of neuroplastic brain changes in the astronaut population. [ABSTRACT FROM AUTHOR]

Purpose: To demonstrate the feasibility of motion compensating diffusion gradient schemes in the acquisition of quality diffusion tensor images (DTI) of the brain during continuous gross head motion. Methods: Five healthy subjects were scanned using a clinical 3 T MRI with and without continuous head motion. For one volunteer, DTI data was acquired using standard (M0) diffusion‐weighted (DW) gradients, and first (M1) and second (M2) order gradient schemes that were previously developed for use in cardiac DTI. In four additional volunteers, DTI data was acquired with M0 and M2 gradients. DTI parameters were calculated and compared with established retrospective motion corrections. Results: In the absence of motion, DTI parameters calculated from M0, M1, and M2 data were consistent. In the presence of motion, up to 44% of DW images acquired with M0 gradients were corrupted by signal dropout, compared to 0% of the M2 images. In voxelwise comparisons, DTI parameters calculated using motion‐M0 data were elevated compared to reference data. Retrospective corrections for extreme motion applied to motion‐M0 data did not improve consistency with reference data in cases where motion corrupted >15% of DW images. In contrast, DTI parameters calculated with motion‐M2 data were consistent with reference data. Conclusion: This proof‐of‐principle study demonstrates that motion compensating diffusion gradients can mitigate artifacts because of continuous motion in DTI of the brain and offers promise for improved DTI accessibility. Further study will be necessary to determine the robustness of the approach in patient populations with high susceptibility to head motion. [ABSTRACT FROM AUTHOR]

Cerebral amyloid angiopathy (CAA) is characterized by amyloid-β aggregation in the media and adventitia of the leptomeningeal and cortical blood vessels. CAA is one of the strongest vascular contributors to Alzheimer's disease (AD). It frequently co-occurs in AD patients, but the relationship between CAA and AD is incompletely understood. CAA may drive AD risk through damage to the neurovascular unit and accelerate parenchymal amyloid and tau deposition. Conversely, early AD may also drive CAA through cerebrovascular remodeling that impairs blood vessels from clearing amyloid-β. Sole reliance on autopsy examination to study CAA limits researchers' ability to investigate CAA's natural disease course and the effect of CAA on cognitive decline. Neuroimaging allows for in vivo assessment of brain function and structure and can be leveraged to investigate CAA staging and explore its associations with AD. In this review, we will discuss neuroimaging modalities that can be used to investigate markers associated with CAA that may impact AD vulnerability including hemorrhages and microbleeds, blood-brain barrier permeability disruption, reduced cerebral blood flow, amyloid and tau accumulation, white matter tract disruption, reduced cerebrovascular reactivity, and lowered brain glucose metabolism. We present possible areas for research inquiry to advance biomarker discovery and improve diagnostics. [ABSTRACT FROM AUTHOR]

Rapid development of artificial intelligence techniques significantly promotes important medical imaging applications such as disease diagnosis, medical image analysis and cross-modality synthesis. It is valuable to synthesize Computed Tomography (CT) scans of human brains from Magnetic Resonance Imaging (MRI) scans because CT images contain particular information for diseases such as malignant tumors, cerebrovascular malformations and aneurysms. Although there has been many studies trying to apply machine learning methods (e.g., fully convolutional neural networks and generative adversarial networks) to predict CT images based on MRI, there are still opportunities to increase the quality of synthesized CT images using the latest machine learning algorithms. In this study, we aim to synthesize high-credibility human brain CT images from MRI images using machine learning approaches. We build a dataset of both CT and MRI images of 41 patients from The Cancer Imaging Archive. A data pre-processing pipeline is designed to guarantee that the processed images are suitable as inputs to machine learning algorithms. The pipeline includes (1) pairing MRI and CT scans according to a certain time interval between CT and MRI exams of the same patient, (2) registering all MRI images to a standard MRI template, (3) registering all CT images to paired MRI images, (4) intensity normalization and (5) extracting 2D slices from 3D CT and MRI volumes. Three deep neural networks with encoder–decoder structure are selected and implemented including U-Net, U-Net++ and pix2pix to synthesize human brain CT images from MRI images. Experimental results illustrate that U-Net++ shows better performance than U-Net and pix2pix in synthesizing CT images from MRI by achieving a Mean Squared Error of 0.025, a Mean Absolute Error of 0.082 and a Peak Signal-to-Noise Ratio of 67.90, respectively. The trained machine learning models from this work can be applied in future human brain CT image prediction where CT images are absent and MRI images are available for specific patients, thereby supporting disease diagnosis based on CT images. [ABSTRACT FROM AUTHOR]

Purpose: To integrate 3D CEST EPI with an unevenly segmented RF irradiation module and preliminarily demonstrate it in the clinical setting. Methods: A CEST MRI with unevenly segmented RF saturation was implemented, including a long primary RF saturation to induce the steady‐state CEST effect, maintained with repetitive short secondary RF irradiation between readouts. This configuration reduces relaxation‐induced blur artifacts during acquisition, allowing fast 3D spatial coverage. Numerical simulations were performed to select parameters such as flip angle (FA), short RF saturation duration (Ts2), and the number of readout segments. The sequence was validated experimentally with data from a phantom, healthy volunteers, and a brain tumor patient. Results: Based on the numerical simulation and l‐carnosine gel phantom experiment, FA, Ts2, and the number of segments were set to 20°, 0.3 s, and the range from 4 to 8, respectively. The proposed method minimized signal modulation in the human brain images in the kz direction during the acquisition and provided the blur artifacts‐free CEST contrast over the whole volume. Additionally, the CEST contrast in the tumor tissue region is higher than in the contralateral normal tissue region. Conclusions: It is feasible to implement a highly accelerated 3D EPI CEST imaging with unevenly segmented RF irradiation. [ABSTRACT FROM AUTHOR]

Purpose: To improve the image reconstruction for prospective motion correction (PMC) of simultaneous multislice (SMS) EPI of the brain, an update of receiver phase and resampling of coil sensitivities are proposed and evaluated. Methods: A camera‐based system was used to track head motion (3 translations and 3 rotations) and dynamically update the scan position and orientation. We derived the change in receiver phase associated with a shifted field of view (FOV) and applied it in real‐time to each k‐space line of the EPI readout trains. Second, for the SMS reconstruction, we adapted resampled coil sensitivity profiles reflecting the movement of slices. Single‐shot gradient‐echo SMS‐EPI scans were performed in phantoms and human subjects for validation. Results: Brain SMS‐EPI scans in the presence of motion with PMC and no phase correction for scan plane shift showed noticeable artifacts. These artifacts were visually and quantitatively attenuated when corrections were enabled. Correcting misaligned coil sensitivity maps improved the temporal SNR (tSNR) of time series by 24% (p = 0.0007) for scans with large movements (up to ˜35 mm and 30°). Correcting the receiver phase improved the tSNR of a scan with minimal head movement by 50% from 50 to 75 for a United Kingdom biobank protocol. Conclusion: Reconstruction‐induced motion artifacts in single‐shot SMS‐EPI scans acquired with PMC can be removed by dynamically adjusting the receiver phase of each line across EPI readout trains and updating coil sensitivity profiles during reconstruction. The method may be a valuable tool for SMS‐EPI scans in the presence of subject motion. [ABSTRACT FROM AUTHOR]

Copyright of Radiology News Journal / Radiološki Vjesnik is the property of Croatian Association of Radiation Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Amine‐weighted chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) is particularly valuable as an amine‐ and pH‐sensitive imaging technique in brain tumors, targeting the intrinsically high concentration of amino acids with exchangeable amine protons and reduced extracellular pH in brain tumors. Amine‐weighted CEST MRI contrast is dependent on the glioma genotype, likely related to differences in degree of malignancy and metabolic behavior. Amine‐weighted CEST MRI may provide complementary value to anatomic imaging in conventional and exploratory therapies in brain tumors, including chemoradiation, antiangiogenic therapies, and immunotherapies. Continual improvement and clinical testing of amine‐weighted CEST MRI has the potential to greatly impact patients with brain tumors by understanding vulnerabilities in the tumor microenvironment that may be therapeutically exploited. [ABSTRACT FROM AUTHOR]

The development of ultra high field fMRI signal readout strategies and contrasts has led to the possibility of imaging the human brain in vivo and non-invasively at increasingly higher spatial resolutions of cortical layers and columns. One emergent layer-fMRI acquisition method with increasing popularity is the cerebral blood volume sensitive sequence named vascular space occupancy (VASO). This approach has been shown to be mostly sensitive to locally-specific changes of laminar microvasculature, without unwanted biases of trans-laminar draining veins. Until now, however, VASO has not been applied in the technically challenging cortical area of the auditory cortex. Here, we describe the main challenges we encountered when developing a VASO protocol for auditory neuroscientific applications and the solutions we have adopted. With the resulting protocol, we present preliminary results of laminar responses to sounds and as a proof of concept for future investigations, we map the topographic representation of frequency preference (tonotopy) in the auditory cortex. [ABSTRACT FROM AUTHOR]

MRI is undoubtedly the cornerstone of brain tumor imaging, playing a key role in all phases of patient management, starting from diagnosis, through therapy planning, to treatment response and/or recurrence assessment. Currently, neuroimaging can describe morphologic and non-morphologic (functional, hemodynamic, metabolic, cellular, microstructural, and sometimes even genetic) characteristics of brain tumors, greatly contributing to diagnosis and follow-up. Knowing the technical aspects, strength and limits of each MR technique is crucial to correctly interpret MR brain studies and to address clinicians to the best treatment strategy. This article aimed to provide an overview of neuroimaging in the assessment of adult primary brain tumors. We started from the basilar role of conventional/morphological MR sequences, then analyzed, one by one, the non-morphological techniques, and finally highlighted future perspectives, such as radiomics and artificial intelligence. [ABSTRACT FROM AUTHOR]

Stories in general, and peak moments within a single story in particular, can evoke strong responses across recipients. Between the content of a story and these shared audience responses lies an explanatory gap that neuroimaging can help close. Accordingly, this study examined how the brains of an audience responded during a story. We performed two types of analyses: First, we correlated the story's physical characteristics to brain activity. Second, we reverse-correlated moments of peak brain engagement to story segments. We found that activity peaks in the temporo-parietal junction identify socially engaging points within the story, such as a pie-in-the-face scene, hyperbole, and sexual references. We discussed how these results and reverse correlation neuroimaging more broadly advance communication science. [ABSTRACT FROM AUTHOR]

Copyright of Acibadem Saglik Bilimleri Dergisi is the property of Acibadem University Medical School and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Amide proton transfer‐weighted (APTw) MR imaging shows promise as a biomarker of brain tumor status. Currently used APTw MRI pulse sequences and protocols vary substantially among different institutes, and there are no agreed‐on standards in the imaging community. Therefore, the results acquired from different research centers are difficult to compare, which hampers uniform clinical application and interpretation. This paper reviews current clinical APTw imaging approaches and provides a rationale for optimized APTw brain tumor imaging at 3 T, including specific recommendations for pulse sequences, acquisition protocols, and data processing methods. We expect that these consensus recommendations will become the first broadly accepted guidelines for APTw imaging of brain tumors on 3 T MRI systems from different vendors. This will allow more medical centers to use the same or comparable APTw MRI techniques for the detection, characterization, and monitoring of brain tumors, enabling multi‐center trials in larger patient cohorts and, ultimately, routine clinical use. [ABSTRACT FROM AUTHOR]

Vestibular information is ubiquitous and often processed jointly with visual, somatosensory and proprioceptive information. Among the cortical brain regions associated with human vestibular processing, area OP2 in the parietal operculum has been proposed as vestibular core region. However, delineating responses uniquely to vestibular stimulation in this region using neuroimaging is challenging for several reasons: First, the parietal operculum is a cytoarchitectonically heterogeneous region responding to multisensory stimulation. Second, artificial vestibular stimulation evokes confounding somatosensory and nociceptive responses blurring responses contributing to vestibular perception. Furthermore, immediate effects of vestibular stimulation on the organization of functional networks have not been investigated in detail yet. Using high resolution neuroimaging in a task-based and functional connectivity approach, we compared two equally salient stimuli—unilateral galvanic vestibular (GVS) and galvanic nociceptive stimulation (GNS)—to disentangle the processing of both modalities in the parietal operculum and characterize their effects on functional network architecture. GNS and GVS gave joint responses in area OP1, 3, 4, and the anterior and middle insula, but not in area OP2. GVS gave stronger responses in the parietal operculum just adjacent to OP3 and OP4, whereas GNS evoked stronger responses in area OP1, 3 and 4. Our results underline the importance of considering this common pathway when interpreting vestibular neuroimaging experiments and underpin the role of area OP2 in central vestibular processing. Global network changes were found during GNS, but not during GVS. This lack of network reconfiguration despite the saliency of GVS may reflect the continuous processing of vestibular information in the awake human. [ABSTRACT FROM AUTHOR]

Key Points: • Prediction of neurological outcome after cardiac arrest is a major ethical challenge. • Diffusion tensor imaging (DTI) is a promising prognostic tool in comatose patients assessing brain microstructural damages. • The combination of clinical data with whole-brain fractional anisotropy and mean diffusivity values appears more accurate to predict poor outcome. [ABSTRACT FROM AUTHOR]

Structural hippocampal abnormalities are common in many neurological and psychiatric disorders, and variation in hippocampal measures is related to cognitive performance and other complex phenotypes such as stress sensitivity. Hippocampal subregions are increasingly studied, as automated algorithms have become available for mapping and volume quantification. In the context of the Enhancing Neuro Imaging Genetics through Meta Analysis Consortium, several Disease Working Groups are using the FreeSurfer software to analyze hippocampal subregion (subfield) volumes in patients with neurological and psychiatric conditions along with data from matched controls. In this overview, we explain the algorithm's principles, summarize measurement reliability studies, and demonstrate two additional aspects (subfield autocorrelation and volume/reliability correlation) with illustrative data. We then explain the rationale for a standardized hippocampal subfield segmentation quality control (QC) procedure for improved pipeline harmonization. To guide researchers to make optimal use of the algorithm, we discuss how global size and age effects can be modeled, how QC steps can be incorporated and how subfields may be aggregated into composite volumes. This discussion is based on a synopsis of 162 published neuroimaging studies (01/2013–12/2019) that applied the FreeSurfer hippocampal subfield segmentation in a broad range of domains including cognition and healthy aging, brain development and neurodegeneration, affective disorders, psychosis, stress regulation, neurotoxicity, epilepsy, inflammatory disease, childhood adversity and posttraumatic stress disorder, and candidate and whole genome (epi‐)genetics. Finally, we highlight points where FreeSurfer‐based hippocampal subfield studies may be optimized. [ABSTRACT FROM AUTHOR]

Purpose: Functional magnetic resonance imaging (fMRI) during infancy poses challenges due to practical, methodological, and analytical considerations. The aim of this study was to implement a hardware‐related approach to increase subject compliance for fMRI involving awake infants. To accomplish this, we designed, constructed, and evaluated an adaptive 32‐channel array coil. Methods: To allow imaging with a close‐fitting head array coil for infants aged 1‐18 months, an adjustable head coil concept was developed. The coil setup facilitates a half‐seated scanning position to improve the infant's overall scan compliance. Earmuff compartments are integrated directly into the coil housing to enable the usage of sound protection without losing a snug fit of the coil around the infant's head. The constructed array coil was evaluated from phantom data using bench‐level metrics, signal‐to‐noise ratio (SNR) performances, and accelerated imaging capabilities for both in‐plane and simultaneous multislice (SMS) reconstruction methodologies. Furthermore, preliminary fMRI data were acquired to evaluate the in vivo coil performance. Results: Phantom data showed a 2.7‐fold SNR increase on average when compared with a commercially available 32‐channel head coil. At the center and periphery regions of the infant head phantom, the SNR gains were measured to be 1.25‐fold and 3‐fold, respectively. The infant coil further showed favorable encoding capabilities for undersampled k‐space reconstruction methods and SMS techniques. Conclusions: An infant‐friendly head coil array was developed to improve sensitivity, spatial resolution, accelerated encoding, motion insensitivity, and subject tolerance in pediatric MRI. The adaptive 32‐channel array coil is well‐suited for fMRI acquisitions in awake infants. [ABSTRACT FROM AUTHOR]

Research in ultrahigh magnetic field strength combined with ultrahigh and ultrafast gradient technology has provided enormous gains in sensitivity, resolution, and contrast for neuroimaging. This article provides an overview of the technical advantages and challenges of performing clinical neuroimaging studies at ultrahigh magnetic field strength combined with ultrahigh and ultrafast gradient technology. Emerging clinical applications of 7-T MRI and state-of-the-art gradient systems equipped with up to 300 mT/m gradient strength are reviewed, and the impact and benefits of such advances to anatomical, structural and functional MRI are discussed in a variety of neurological conditions. Finally, an outlook and future directions for ultrahigh field MRI combined with ultrahigh and ultrafast gradient technology in neuroimaging are examined. [ABSTRACT FROM AUTHOR]

Purpose: To develop an image‐based motion‐robust diffusion MRI (dMRI) acquisition framework that is able to minimize motion artifacts caused by rigid and nonrigid motion, applicable to both brain and tongue dMRI. Methods: We developed a novel prospective motion‐correction technique in dMRI using a phase image–based real‐time motion‐detection method (PITA‐MDD) with re‐acquisition of motion‐corrupted images. The prospective PITA‐MDD acquisition technique was tested in the brains and tongues of volunteers. The subjects were instructed to move their heads or swallow, to induce motion. Motion‐detection efficacy was validated against visual inspection as the gold standard. The effect of the PITA‐MDD technique on diffusion‐parameter estimates was evaluated by comparing reconstructed fiber tracts using tractography with and without re‐acquisition. Results: The prospective PITA‐MDD technique was able to effectively and accurately detect motion‐corrupted data as compared with visual inspection. Tractography results demonstrated that PITA‐MDD motion detection followed by re‐acquisition helps in recovering lost and misshaped fiber tracts in the brain and tongue that would otherwise be corrupted by motion and yield erroneous estimates of the diffusion tensor. Conclusion: A prospective PITA‐MDD technique was developed for dMRI acquisition, providing improved dMRI image quality and motion‐robust diffusion estimation of the brain and tongue. [ABSTRACT FROM AUTHOR]

Purpose: To develop an ultrafast 3D gradient echo–based MRI method with constant TE and high tolerance to B0 inhomogeneity, dubbed ERASE (equal‐TE rapid acquisition with sequential excitation), and to introduce its use in BOLD functional MRI (fMRI). Theory and Methods: Essential features of ERASE, including spin behavior, were characterized, and a comparison study was conducted with conventional EPI. To demonstrate high tolerance to B0 inhomogeneity, in vivo imaging of the mouse brain with a fiber‐optic implant was performed at 9.4 T, and human brain imaging (including the orbitofrontal cortex) was performed at 3 T and 7 T. To evaluate the performance of ERASE in BOLD‐fMRI, the characteristics of SNR and temporal SNR were analyzed for in vivo rat brains at 9.4 T in comparison with multislice gradient‐echo EPI. Percent signal changes and t‐scores are also presented. Results: For both mouse brain and human brain imaging, ERASE exhibited a high tolerance to magnetic susceptibility artifacts, showing much lower distortion and signal dropout, especially in the regions involving large magnetic susceptibility effects. For BOLD‐fMRI, ERASE provided higher temporal SNR and t‐scores than EPI, but exhibited similar percent signal changes in in vivo rat brains at 9.4 T. Conclusion: When compared with conventional EPI, ERASE is much less sensitive, not only to EPI‐related artifacts such as Nyquist ghosting, but also to B0 inhomogeneity including magnetic susceptibility effects. It is promising for use in BOLD‐fMRI, providing higher temporal SNR and t‐scores with constant TE when compared with EPI, although further optimization is needed for human fMRI. [ABSTRACT FROM AUTHOR]

Exercise improves both physical and mental health and increases neurogenesis in the dendate gyrus (DG) of the hippocampus. The aim of this study was to examine whether exercising, as compared to no change in regular physical activity, would impact on hippocampal volume, and in particular the core hippocampal structures, DG and cornu ammonis (CA) subfields, and whether any changes would be moderated by age. Thirty nine previously sedentary healthy participants were randomized to either a standardized progressive aerobic exercise program or to "no change" for 16 weeks. Mental health including profile of mood states (POMS), was assessed before and every 4 weeks during the program. Magnetic resonance imaging to examine hippocampal subfields was carried out before and after the program. Aerobic exercise resulted in a significant improvement of the POMS item 'vigour' compared to those in the control group. Overall left hippocampal and left CA4-DG volumes increased significantly in the exercise group while no significant changes were seen in the control group. Older adults in the control group demonstrated significant reductions in CA4-DG subfields over the study, whereas older adults in the exercise group did not show volume decline. These findings reinforce the literature that exercise has a beneficial effect on mental health and can prevent age-related volume decline. Exercise to Improve Resilience, https://register.clinicaltrials.gov/prs/app/action/LoginUser?ts=1&cx=-jg9qo4, NCT02541136, Rec Ref 2011/45/13. [ABSTRACT FROM AUTHOR]

Positron emission tomography (PET) is a non-invasive imaging technology employed to describe metabolic, physiological, and biochemical processes in vivo. These include receptor availability, metabolic changes, neurotransmitter release, and alterations of gene expression in the brain. Since the introduction of dedicated small-animal PET systems along with the development of many novel PET imaging probes, the number of PET studies using rats and mice in basic biomedical research tremendously increased over the last decade. This article reviews challenges and advances of quantitative rodent brain imaging to make the readers aware of its physical limitations, as well as to inspire them for its potential applications in preclinical research. In the first section, we briefly discuss the limitations of small-animal PET systems in terms of spatial resolution and sensitivity and point to possible improvements in detector development. In addition, different acquisition and post-processing methods used in rodent PET studies are summarized. We further discuss factors influencing the test-retest variability in small-animal PET studies, e.g., different receptor quantification methodologies which have been mainly translated from human to rodent receptor studies to determine the binding potential and changes of receptor availability and radioligand affinity. We further review different kinetic modeling approaches to obtain quantitative binding data in rodents and PET studies focusing on the quantification of endogenous neurotransmitter release using pharmacological interventions. While several studies have focused on the dopamine system due to the availability of several PET tracers which are sensitive to dopamine release, other neurotransmitter systems have become more and more into focus and are described in this review, as well. We further provide an overview of latest genome engineering technologies, including the CRISPR/Cas9 and DREADD systems that may advance our understanding of brain disorders and function and how imaging has been successfully applied to animal models of human brain disorders. Finally, we review the strengths and opportunities of simultaneous PET/magnetic resonance imaging systems to study drug-receptor interactions and challenges for the translation of PET results from bench to bedside. [ABSTRACT FROM AUTHOR]

Purpose: Subject motion in MRI remains an unsolved problem; motion during image acquisition may cause blurring and artifacts that severely degrade image quality. In this work, we approach motion correction as an image‐to‐image translation problem, which refers to the approach of training a deep neural network to predict an image in 1 domain from an image in another domain. Specifically, the purpose of this work was to develop and train a conditional generative adversarial network to predict artifact‐free brain images from motion‐corrupted data. Methods: An open source MRI data set comprising T2*‐weighted, FLASH magnitude, and phase brain images for 53 patients was used to generate complex image data for motion simulation. To simulate rigid motion, rotations and translations were applied to the image data based on randomly generated motion profiles. A conditional generative adversarial network, comprising a generator and discriminator networks, was trained using the motion‐corrupted and corresponding ground truth (original) images as training pairs. Results: The images predicted by the conditional generative adversarial network have improved image quality compared to the motion‐corrupted images. The mean absolute error between the motion‐corrupted and ground‐truth images of the test set was 16.4% of the image mean value, whereas the mean absolute error between the conditional generative adversarial network‐predicted and ground‐truth images was 10.8% The network output also demonstrated improved peak SNR and structural similarity index for all test‐set images. Conclusion: The images predicted by the conditional generative adversarial network have quantitatively and qualitatively improved image quality compared to the motion‐corrupted images. [ABSTRACT FROM AUTHOR]

Absolute quantification of PET brain imaging requires the measurement of an arterial input function (AIF), typically obtained invasively via an arterial cannulation. We present an approach to automatically calculate an image-derived input function (IDIF) and cerebral metabolic rates of glucose (CMRGlc) from the [18F]FDG PET data using an integrated PET/MRI system. Ten healthy controls underwent test–retest dynamic [18F]FDG-PET/MRI examinations. The imaging protocol consisted of a 60-min PET list-mode acquisition together with a time-of-flight MR angiography scan for segmenting the carotid arteries and intermittent MR navigators to monitor subject movement. AIFs were collected as the reference standard. Attenuation correction was performed using a separate low-dose CT scan. Assessment of the percentage difference between area-under-the-curve of IDIF and AIF yielded values within ±5%. Similar test–retest variability was seen between AIFs (9 ± 8) % and the IDIFs (9 ± 7) %. Absolute percentage difference between CMRGlc values obtained from AIF and IDIF across all examinations and selected brain regions was 3.2% (interquartile range: (2.4–4.3) %, maximum < 10%). High test–retest intravariability was observed between CMRGlc values obtained from AIF (14%) and IDIF (17%). The proposed approach provides an IDIF, which can be effectively used in lieu of AIF. [ABSTRACT FROM AUTHOR]

In the treatment of brain tumors, surgical intervention remains a common and effective therapeutic option. Recent advances in neuroimaging have provided neurosurgeons with new tools to overcome the challenge of differentiating healthy tissue from tumor-infiltrated tissue, with the aim of increasing the likelihood of maximizing the extent of resection volume while minimizing injury to functionally important regions. Novel applications of diffusion tensor imaging (DTI), and DTI-derived tractography (DDT) have demonstrated that preoperative, non-invasive mapping of eloquent cortical regions and functionally relevant white matter tracts (WMT) is critical during surgical planning to reduce postoperative deficits, which can decrease quality of life and overall survival. In this review, we summarize the latest developments of applying DTI and tractography in the context of resective surgery and highlight its utility within each stage of the neurosurgical workflow: preoperative planning and intraoperative management to improve postoperative outcomes. [ABSTRACT FROM AUTHOR]

Introduction: Subject movements lead to severe artifacts in magnetic resonance (MR) brain imaging. In this study we evaluate the diagnostic image quality in T1-weighted, T2-weighted, and time-of-flight angiographic MR sequences when using a flexible, navigator-based prospective motion correction system (iMOCO). Methods: Five healthy volunteers were scanned during different movement scenarios with and without (+/-) iMOCO activated. An experienced neuroradiologist graded images for image quality criteria (grey-white-matter discrimination, basal ganglia, and small structure and vessel delineation), and general image quality on a four-grade scale. Results: In scans with deliberate motion, there was a significant improvement in the image quality with iMOCO compared to the scans without iMOCO in both general image impression (T1 p<0.01, T2 p<0.01, TOF p = 0.03) and in anatomical grading (T1 p<0.01, T2 p<0.01, TOF p = 0.01). Subjective image quality was considered non-diagnostic in 91% of the scans with motion -iMOCO, but only in 4% of the scans with motion +iMOCO. iMOCO performed best in the T1-weighted sequence and least well in the angiography sequence. iMOCO was not shown to have any negative effect on diagnostic image quality, as no significant difference in diagnostic quality was seen between scans -iMOCO and +iMOCO with no deliberate movement. Conclusion: The evaluation showed that iMOCO enables substantial improvements in image quality in scans affected by subject movement, recovering important diagnostic information in an otherwise unusable scan. [ABSTRACT FROM AUTHOR]

The thalamocingulate tract is a key component of the Papez circuit that connects the anterior thalamic nucleus (ATN) to the cingulum bundle. While the other white matter connections, consisting of the fornix, cingulum bundle and mammillothalamic tract, were well defined in Papez's original 1937 paper, the anatomy of the thalamocingulate pathway was mentioned only in passing. Subsequent research has been unable to clarify the precise anatomical trajectory of this tract. In particular, the site of thalamocingulate tract interactions with the cingulum bundle have been inconsistently reported. This review aims to synthesize research on this least studied component of the Papez circuit. A systemic approach to reviewing historical anatomical dissection and neuronal tracing studies as well as contemporary diffusion magnetic resonance imaging studies of the thalamocingulate tract was undertaken across species. We found that although inconsistent, prior research broadly encompasses two differing descriptions of how the ATN interfaces with the cingulum after passing laterally through the anterior limb of the internal capsule. The first group of studies show that the pathway turns medially and rostrally and passes to the anterior cingulate region (Brodmann areas 24, 33, and 32) only. A second group suggests that the thalamocingulate tract interfaces with both the anterior and posterior cingulate (Brodmann areas 23 and 31) and retrosplenial region (Brodmann area 29). We discuss potential reasons for these discrepancies such as altering methodologies and species differences. We also discuss how these inconsistencies may be resolved in further research with refinements of terminology for the cingulate cortex and the thalamocingulate tract. Understanding the precise anatomical course of the last remaining unresolved final white matter tract in the Papez circuit may facilitate accurate investigation of the role of the complete Papez circuit in emotion and memory. [ABSTRACT FROM AUTHOR]

Improved understanding of neuroimaging signal changes and their relation to patient outcomes after ischemic stroke is needed to improve ability to predict motor improvement and make therapy recommendations. The posterior limb of the internal capsule (PLIC) is a hub of afferent and efferent motor signaling and this work proposes new, image-based methods for prognosis based on interhemispheric differences in the PLIC. In this work, nine acute supratentorial ischemic stroke patients with motor impairment received a baseline, 203-direction diffusion brain MRI and a clinical assessment 3–12 days post-stroke and were compared to nine age-matched healthy controls. Asymmetries based on the mean and Kullback-Leibler divergence in the ipsilesional and contralesional PLIC were calculated for diffusion tensor imaging (DTI) and diffusion spectrum imaging (DSI) measures from the baseline MRI. Predictions of upper extremity Fugl-Meyer (FM) scores at 5-weeks follow-up from baseline measures of PLIC asymmetry in diffusion tensor imaging (DTI) and diffusion spectrum imaging (DSI) models were evaluated. For the stroke participants, the baseline asymmetry measures in the PLIC for the orientation dispersion index of the neurite orientation dispersion and density imaging (NODDI) model were highly correlated with upper extremity FM outcomes (r 2 = 0.83). Use of DSI and the NODDI orientation dispersion index parameter shows promise of being more predictive of stroke recovery and to help better understand white matter changes in stroke, beyond DTI measures. The new finding that baseline interhemispheric differences in the PLIC calculated from the orientation dispersion index of the NODDI model are highly correlated with upper extremity functional outcomes may lead to improved image-based motor-outcome prediction after middle cerebral artery ischemic stroke. [ABSTRACT FROM AUTHOR]

Depression is one of the most common and important neuropsychiatric symptoms in Parkinson’s disease and often becomes worse as Parkinson’s disease progresses. However, the underlying mechanisms of depression in Parkinson’s disease are not clear. The aim of our study was to find genetic features related to depression in Parkinson’s disease using an imaging genetics approach and to construct an analytical model for predicting the degree of depression in Parkinson’s disease. The neuroimaging and genotyping data were obtained from an openly accessible database. We computed imaging features through connectivity analysis derived from tractography of diffusion tensor imaging. The imaging features were used as intermediate phenotypes to identify genetic variants according to the imaging genetics approach. We then constructed a linear regression model using the genetic features from imaging genetics approach to describe clinical scores indicating the degree of depression. As a comparison, we constructed other models using imaging features and genetic features based on references to demonstrate the effectiveness of our imaging genetics model. The models were trained and tested in a five-fold cross-validation. The imaging genetics approach identified several brain regions and genes known to be involved in depression, with the potential to be used as meaningful biomarkers. Our proposed model using imaging genetic features predicted and explained the degree of depression in Parkinson’s disease appropriately (adjusted R2 larger than 0.6 over five training folds) and with a lower error and higher correlation than with other models over five test folds. [ABSTRACT FROM AUTHOR]

Objectives: To describe the spectrum of brainstem malformations associated to mutations in the tubulin genes taking advantage of magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI).Methods: Fifteen patients (six males; median age, 1.25 years; range, 1 month to 31 years) with mutations in the tubulin genes (TUBA1A = 8, TUBB2B = 4, TUBB3 = 3) studied with MRI and DTI were included in the study. Brain MR exams were reviewed to describe the malformative aspects of the brainstem. Malformations of the supratentorial brain and cerebellum were also recorded. Tractography was performed in seven selected cases.Results: Fourteen patients (93%) showed complex malformations of the brainstem. Most common findings, apparent on anatomical MR sequences, were brainstem asymmetry (12 cases, 5 of which with a crossed pattern characterised by a hypertrophic right medulla oblongata and hypertrophic left pons), short and small pons on midline (10 cases) and anterior brainstem clefting (6 cases). DTI revealed abnormal transverse pontine fibres (13 cases), fusion of corticospinal tracts and medial lemnisci (9 cases) and a small decussation of the superior cerebellar peduncles (7 cases).Conclusions: Conventional/anatomical MRI and DTI reveal a complex pattern of brainstem malformations associated with tubulin genes mutations.Key Points: • Brainstem malformations affect 93% patients with mutated tubulin genes • MRI shows homolateral and crossed brainstem asymmetries, clefts and pons hypoplasia • DTI demonstrates irregular representation of transverse pontine fibres and fusion of corticospinal tracts. [ABSTRACT FROM AUTHOR]

Background: Differential diagnosis of elevated high sensitive Troponin T (hsTnT) in acute ischemic stroke includes myocardial infarction (MI) and neurogenic stunned myocardium (NSM). The aim of this study was to identify factors associated with baseline hsTnT levels and MI or NSM in acute ischemic stroke. Methods: We studied 204 consecutive patients of the prospective acquired Bern Stroke Database with acute ischemic stroke diagnosed by brain MR. All patient histories and cardiac examinations were reviewed retrospectively. Volumetry of lesions on diffusion and perfusion weighted brain imaging (circular singular value decomposition, Tmax >6sec) was performed. Voxel based analysis was performed to identify brain areas associated with hsTnT elevation. Linear regression analysis was used to identify predictors of baseline hsTnT levels and myocardial infarction. Results: Elevated hsTnT was observed in 58 of the 204 patients (28.4%). The mean age was 68.3 years in the normal hsTnT group and 69.7 years in the elevated hsTnT group. Creatinine (p<0.001, OR 6.735, 95% CI 58.734–107.423), baseline NIHSS score (p = 0.029, OR 2.207, 95% CI 0.675–12.096), ST segment depression (p = 0.025, OR 2.259, 95% CI 2.419–35.838), and negative T waves in baseline ECG (p = 0.002, OR 3.209, 95% CI 13.007–54.564) were associated with hsTnT elevation, while infarct location and size were not. Coronary angiography was performed in 30 of the 204 patients (14.7%) and myocardial infarction was diagnosed in 7 of them (23.3%). Predictive factors for myocardial infarction could not be identified. Conclusion: Elevated baseline baseline hsTnT was associated with NIHSS, creatinine, ST segment depression and inverted T waves, but not with stroke location or size. None of the factors was helpful to differentiate MI and NSM. Therefore, ancillary investigations such as coronary angiography, cardiac MRI or both may be needed to solve the differential diagnosis. [ABSTRACT FROM AUTHOR]

Objectives: Unilateral spatial neglect (USN) is the incapacity to respond to stimuli presented opposite to a dysfunctional cerebral hemisphere. It is usually caused by non‐dominant hemisphere lesions, leads to poorer prognosis and might be underdiagnosed. The objectives of the study were to ascertain the presence of USN in acute stroke patients and analyze the possible degree of underdiagnosis in a Stroke Unit. Materials and Methods: Prospective study of consecutive non‐dominant hemisphere stroke patients within a period of 21 months. "Line Bisection" and "Triangles Cancellation" tests were used for USN screening and "Circle Gap Detection Task" to confirm the USN. The results were compared with routine Stroke Unit assessment using the NIHSS to determine the possible degree of underdiagnosis. Results: A total of 62 subjects, 38 women (61.29%), mean age of 74.05 (SD 10.5) years, were included. USN was diagnosed in 25 cases (40.3%) but 56% of them were not detected in routine evaluation using the NIHSS. Conclusions: Unilateral spatial neglect, a common cognitive deficit after acute stroke, is greatly underdiagnosed in routine Stroke Unit assessment. The use of simple USN‐specific screening tools would improve diagnosis and therefore the possibility of implementing appropriate rehabilitation strategies. [ABSTRACT FROM AUTHOR]

Purpose: In dual modality positron emission tomography (PET)/magnetic resonance imaging (MRI), attenuation correction (AC) methods are continually improving. Although a new AC can sometimes be generated from existing MR data, its application requires a new reconstruction. We evaluate an approximate 2D projection method that allows offline image-based reprocessing.Procedure: 2-Deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) brain scans were acquired (Siemens HR+) for six subjects. Attenuation data were obtained using the scanner's transmission source (SAC). Additional scanning was performed on a Siemens mMR including production of a Dixon-based MR AC (MRAC). The MRAC was imported to the HR+ and the PET data were reconstructed twice: once using native SAC (ground truth); once using the imported MRAC (imperfect AC). The re-projection method was implemented as follows. The MRAC PET was forward projected to approximately reproduce attenuation-corrected sinograms. The SAC and MRAC images were forward projected and converted to attenuation-correction factors (ACFs). The MRAC ACFs were removed from the MRAC PET sinograms by division; the SAC ACFs were applied by multiplication. The regenerated sinograms were reconstructed by filtered back projection to produce images (SUBAC PET) in which SAC has been substituted for MRAC. Ideally SUBAC PET should match SAC PET. Via coregistered T1 images, FreeSurfer (FS; MGH, Boston) was used to define a set of cortical gray matter regions of interest. Regional activity concentrations were extracted for SAC PET, MRAC PET, and SUBAC PET.Results: SUBAC PET showed substantially smaller root mean square error than MRAC PET with averaged values of 1.5 % versus 8.1 %.Conclusions: Re-projection is a viable image-based method for the application of an alternate attenuation correction in neuroimaging. [ABSTRACT FROM AUTHOR]

Anesthetized rodent models are ubiquitous in pre-clinical neuroimaging studies. However, because the associated cerebral morphology and experimental methodology results in a profound negative brain-core temperature differential, cerebral temperature changes during functional activation are likely to be principally driven by local inflow of fresh, core-temperature, blood. This presents a confound to the interpretation of blood-oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) data acquired from such models, since this signal is also critically temperaturedependent. Nevertheless, previous investigation on the subject is surprisingly sparse. Here, we address this issue through use of a novel multi-modal methodology in the urethane anesthetized rat. We reveal that sensory stimulation, hypercapnia and recurrent acute seizures induce significant increases in cortical temperature that are preferentially correlated to changes in total hemoglobin concentration (Hbt), relative to cerebral blood flow and oxidative metabolism. Furthermore, using a phantom-based evaluation of the effect of such temperature changes on the BOLD fMRI signal, we demonstrate a robust inverse relationship between both variables. These findings suggest that temperature increases, due to functional hyperemia, should be accounted for to ensure accurate interpretation of BOLD fMRI signals in pre-clinical neuroimaging studies. [ABSTRACT FROM AUTHOR]

Abstract: Diffusion-weighted imaging (DWI) has revolutionised stroke imaging since its introduction in the mid-1980s, and it has also become a pillar of current neuroimaging. Diffusion abnormalities represent alterations in the random movement of water molecules in tissues, revealing their microarchitecture, and occur in many neurological conditions. DWI provides useful information, increasing the sensitivity of MRI as a diagnostic tool, narrowing the differential diagnosis, providing prognostic information, aiding in treatment planning and evaluating response to treatment. Recently, there have been several technical improvements in DWI, leading to reduced acquisition time and artefacts and enabling the development of diffusion tensor imaging (DTI) as a tool for assessing white matter. We aim to review the main clinical uses of DWI, focusing on the physiological mechanisms that lead to diffusion abnormalities. Common pitfalls will also be addressed.Teaching Points: • DWI includes EPI, TSE, RESOLVE or EPI combined with reduced volume excitation.• DWI is the most sensitive sequence in stroke diagnosis and provides information about prognosis.• DWI helps in the detection of intramural haematomas (arterial dissection).• In diffusion imaging, ADC is inversely proportional to tumour cellularity.• DWI and DTI derived parameters can be used as biomarkers in different pathologies. [ABSTRACT FROM AUTHOR]

The hippocampus plays important roles in memory processing. However, the hippocampus is not a homogeneous structure, which consists of several subfields. The hippocampal subfields are differently affected by many neurodegenerative diseases, especially mild cognitive impairment (MCI). Amnestic mild cognitive impairment (aMCI) and subcortical vascular mild cognitive impairment (svMCI) are the two subtypes of MCI. aMCI is characterized by episodic memory loss, and svMCI is characterized by extensive white matter hyperintensities and multiple lacunar infarctions on magnetic resonance imaging. The primary cognitive impairment in svMCI is executive function, attention, and semantic memory. Some variations or disconnections within specific large-scale brain networks have been observed in aMCI and svMCI patients. The aim of this study was to investigate abnormalities in structural covariance networks (SCNs) between hippocampal subfields and the whole cerebral cortex in aMCI and svMCI patients, and whether these abnormalities are different between the two groups. Automated segmentation of hippocampal subfields was performed with FreeSurfer 5.3, and we selected five hippocampal subfields as the seeds of SCN analysis: CA1, CA2/3, CA4/dentate gyrus (DG), subiculum, and presubiculum. SCNs were constructed based on these hippocampal subfield seeds for each group. Significant correlations between hippocampal subfields, fusiform gyrus (FFG), and entorhinal cortex (ERC) in gray matter volume were found in each group. We also compared the differences in the strength of structural covariance between any two groups. In the aMCI group, compared to the normal controls (NC) group, we observed an increased association between the left CA1/CA4/DG/subiculum and the left temporal pole. Additionally, the hippocampal subfields (bilateral CA1, left CA2/3) significantly covaried with the orbitofrontal cortex in the svMCI group compared to the NC group. In the aMCI group compared to the svMCI group, we observed decreased association between hippocampal subfields and the right FFG, while we also observed an increased association between the bilateral subiculum/presubiculum and bilateral ERC. These findings provide new evidence that there is altered whole-brain structural covariance of the hippocampal subfields in svMCI and aMCI patients and provide insights to the pathological mechanisms of different MCI subtypes. [ABSTRACT FROM AUTHOR]

Neurodevelopmental disorders are associated with atypical development and maturation of brain networks. A recent focus on human connectomics research and the growing popularity of open science initiatives has created the ideal climate in which to make real progress toward understanding the neurobiology of disorders affecting youth. Here we outline future directions for neuroscience researchers examining brain networks in neurodevelopmental disorders, highlighting gaps in the current literature. We emphasize the importance of leveraging large neuroimaging and phenotypic data sets recently made available to the research community, and we suggest specific novel methodological approaches, including analysis of brain dynamics and structural connectivity, that have the potential to produce the greatest clinical insight. Transdiagnostic approaches will also become increasingly necessary as the Research Domain Criteria framework put forth by the National Institute of Mental Health permeates scientific discourse. During this exciting era of big data and increased computational sophistication of analytic tools, the possibilities for significant advancement in understanding neurodevelopmental disorders are limitless. [ABSTRACT FROM AUTHOR]

The thalamic-prefrontal peduncle (TPP) is a large bundle connecting the thalamus and prefrontal cortex. The definitive structure and function of the TPP are still controversial. To investigate the connectivity and segmentation patterns of the TPP, we employed diffusion spectrum imaging with generalized q-sampling reconstruction to perform both subject-specific and template-based analyses. Our results confirmed the trajectory and spatial relationship of the TPP in the human brain and identified the connection areas in the prefrontal cortex. The TPP-connecting areas identified based on Brodmann areas (BAs) were BAs 8-11 and 45-47. Based on the automated anatomical atlas, these areas were the medial superior frontal gyrus, superior frontal gyrus, middle frontal gyrus, pars triangularis, pars orbitalis, anterior orbital gyrus, and lateral orbital gyrus. In addition, we identified the TPP connection areas in the thalamus, including the anterior and medial nuclei, and the lateral dorsal/lateral posterior nuclei. TPP fibers connected the thalamus with the ipsilateral prefrontal BAs 11, 47, 10, 46, 45, 9, and 8 seriatim from medial to lateral, layer by layer. Our results provide further details of the thalamic-prefrontal peduncle structure, and may aid future studies and a better understanding of the functional roles of the TPP in the human brain. [ABSTRACT FROM AUTHOR]

Recent advances in neuroimaging technology have shown that rich club organization in human brain networks plays a crucial role in global communication and cognitive functionality. In this study, we investigated rich club organization within white matter structural brain networks in two common types of dementia, Alzheimer's disease (AD) and subcortical vascular dementia (SVaD). We recruited 30 AD patients ([11C] Pittsburgh compound-B (PiB) PET positive), 39 SVaD patients (PiB negative), and 72 age-, gender-, and education-matched cognitively normal (CN) subjects. Rich club organization was significantly disrupted in both dementia patient groups, which exhibited higher rich club coefficients than the CN group. Rich club organization in the patient groups was primarily disrupted over the left frontal and left middle temporal areas when compared to the CN group. The number of rich club nodes was significantly reduced in the dementia groups, which was more severe in SVaD (p = 0.0107, permutation-based t-test). Although rich club organization was disrupted both in the patient groups, its disruption pattern is different between them. The rich-club connections normalized by degree-and-strength preserved random networks were significantly increased in the dementia groups with SVaD more severely, and feeder connections were reduced more significantly than in AD. Furthermore, SVaD patients exhibited more sporadic disruption in white matter connectivity than AD patients, with local connections showing a more significant degree of deterioration. Combined with the distinct disruption in rich club nodes, these findings may imply a differing role for rich club organization in AD and SVaD, due to different pathological mechanisms. [ABSTRACT FROM AUTHOR]

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Objective: A new technique for 2D gradient-recalled echo echo-planar imaging (GE-EPI) termed 'variable slice thickness' (VAST) is proposed, which reduces signal losses caused by through-slice susceptibility artifacts, while keeping the volume repetition time (TR) manageable. The slice thickness is varied across the brain, with thinner slices being used in the inferior brain regions where signal voids are most severe. Materials and methods: Various axial slice thickness schemes with identical whole-brain coverage were compared to regular EPI, which may either suffer from unfeasibly long TR if appropriately thin slices are used throughout, or signal loss if no counter-measures are taken. Evaluation is based on time-course signal-to-noise (tSNR) maps from resting state data and a statistical group-level region of interest (ROI) analysis on breath-hold fMRI measurements. Results: The inferior brain region signal voids with static B0 inhomogeneities could be markedly reduced with VAST GE-EPI in contrast to regular GE-EPI. ROI-averaged event-related signal changes showed 48% increase in VAST compared to GE-EPI with regular 'thick' slices. tSNR measurements proved the comparable signal robustness of VAST in comparison to regular GE-EPI with thin slices. Conclusion: A novel acquisition strategy for functional 2D GE-EPI at ultrahigh magnetic field is presented to reduce susceptibility-induced signal voids and keep TR sufficiently short for whole-brain coverage. [ABSTRACT FROM AUTHOR]

Neuroscientists have long debated whether some regions of the human brain are exclusively engaged in a single specific mental process. Consistent with this view, fMRI has revealed cortical regions that respond selectively to certain stimulus classes such as faces. However, results from multivoxel pattern analyses (MVPA) challenge this view by demonstrating that category-selective regions often contain information about "nonpreferred" stimulus dimensions. But is this nonpreferred information causally relevant to behavior? Here we report a rare opportunity to test this question in a neurosurgical patient implanted for clinical reasons with strips of electrodes along his fusiform gyri. Broadband gamma electrocorticographic responses in multiple adjacent electrodes showed strong selectivity for faces in a region corresponding to the fusiform face area (FFA), and preferential responses to color in a nearby site, replicating earlier reports. To test the causal role of these regions in the perception of nonpreferred dimensions, we then electrically stimulated individual sites while the patient viewed various objects. When stimulated in the FFA, the patient reported seeing an illusory face (or "facephene"), independent of the object viewed. Similarly, stimulation of colorpreferring sites produced illusory "rainbows." Crucially, the patient reported no change in the object viewed, apart from the facephenes and rainbows apparently superimposed on them. The functional and anatomical specificity of these effects indicate that some cortical regions are exclusively causally engaged in a single specific mental process, and prompt caution about the widespread assumption that any information scientists can decode from the brain is causally relevant to behavior. [ABSTRACT FROM AUTHOR]

Human brain is structurally and functionally asymmetrical and the asymmetries of brain phenotypes have been shown to change in normal aging. Recent advances in graph theoretical analysis have showed topological lateralization between hemispheric networks in the human brain throughout the lifespan. Nevertheless, apparent discrepancies of hemispheric asymmetry were reported between the structural and functional brain networks, indicating the potentially complex asymmetry patterns between structural and functional networks in aging population. In this study, using multimodal neuroimaging (resting-state fMRI and structural diffusion tensor imaging), we investigated the characteristics of hemispheric network topology in 76 (male/female = 15/61, age = 70.08 ± 5.30 years) community-dwelling older adults. Hemispheric functional and structural brain networks were obtained for each participant. Graph theoretical approaches were then employed to estimate the hemispheric topological properties. We found that the optimal small-world properties were preserved in both structural and functional hemispheric networks in older adults. Moreover, a leftward asymmetry in both global and local levels were observed in structural brain networks in comparison with a symmetric pattern in functional brain network, suggesting a dissociable process of hemispheric asymmetry between structural and functional connectome in healthy older adults. Finally, the scores of hemispheric asymmetry in both structural and functional networks were associated with behavioral performance in various cognitive domains. Taken together, these findings provide new insights into the lateralized nature of multimodal brain connectivity, highlight the potentially complex relationship between structural and functional brain network alterations, and augment our understanding of asymmetric structural and functional specializations in normal aging. [ABSTRACT FROM AUTHOR]

The neuropsychological aspects of multiple sclerosis (MS) have evolved over the past three decades. What was once thought to be a rare occurrence, cognitive dysfunction is now viewed as one of the most disabling symptoms of the disease, with devastating effects on patients’ quality of life. This selective review will highlight major innovations and scientific discoveries in the areas of neuropathology, neuroimaging, diagnosis, and treatment that pertain to our understanding of the neuropsychological aspects of MS. Specifically, we focus on the recent discovery that MS produces pathogical lesions of gray matter (GM) that have consequences for cognitive functions. Methods for imaging these GM lesions in MS are discussed along with multimodal imaging studies that integrate structural and functional imaging methods to provide a better understanding of the relationship between cognitive test performance and functional reserve. Innovations in the screening and comprehensive assessment of cognitive disorders are presented along with recent research that examines cognitive dysfunction in pediatric MS. Results of innovative outcome studies in cognitive rehabilitation are discussed. Finally, we highlight trends for potential future innovations over the next decade. (JINS, 2017, 23, 832–842) [ABSTRACT FROM AUTHOR]

Neuroimaging and neuropsychological studies have identified the involvement of the right posterior region in the processing of visual words. Interestingly, in contrast, ERP studies of the N170 typically demonstrate selectivity for words more strikingly over the left hemisphere. Why is right hemisphere selectivity for words during the N170 epoch typically not observed, despite the clear involvement of this region in word processing? One possibility is that amplitude differences measured on averaged ERPs in previous studies may have been obscured by variation in peak latency across trials. This study examined this possibility by using single-trial analysis. Results show that words evoked greater single-trial N170s than control stimuli in the right hemisphere. Additionally, we observed larger trial-to-trial variability on N170 peak latency for words as compared to control stimuli over the right hemisphere. Results demonstrate that, in contrast to much of the prior literature, the N170 can be selective to words over the right hemisphere. This discrepancy is explained in terms of variability in trial-to-trial peak latency for responses to words over the right hemisphere. [ABSTRACT FROM AUTHOR]

The perceptual representation of individual faces is often explained with reference to a norm-based face space. In such spaces, individuals are encoded as vectors where identity is primarily conveyed by direction and distinctiveness by eccentricity. Here we measured human fMRI responses and psychophysical similarity judgments of individual face exemplars, which were generated as realistic 3D animations using a computer-graphics model. We developed and evaluated multiple neurobiologically plausible computational models, each of which predicts a representational distance matrix and a regional-mean activation profile for 24 face stimuli. In the fusiform face area, a face-space coding model with sigmoidal ramp tuning provided a better account of the data than one based on exemplar tuning. However, an image-processing model with weighted banks of Gabor filters performed similarly. Accounting for the data required the inclusion of a measurement-level population averaging mechanism that approximates how fMRI voxels locally average distinct neuronal tunings. Our study demonstrates the importance of comparing multiple models and of modeling the measurement process in computational neuroimaging. [ABSTRACT FROM AUTHOR]

Rationale: Cannabis use is associated with neuroanatomical alterations in the hippocampus. While the hippocampus is composed of multiple subregions, their differential vulnerability to cannabis dependence remains unknown. Objectives: The objective of the study is to investigate gray matter alteration in each of the hippocampal subregions (presubiculum, subiculum, cornu ammonis (CA) subfields CA1-4, and dentate gyrus (DG)) as associated with cannabis use and dependence. Methods: A total of 35 healthy controls (HC), 22 non-dependent (CB-nondep), and 39 dependent (CB-dep) cannabis users were recruited. We investigated group differences in hippocampal subregion volumes between HC, CB-nondep, and CB-dep users. We further explored the association between CB use variables (age of onset of regular use, monthly use, lifetime use) and hippocampal subregions in CB-nondep and CB-dep users separately. Results: The CA1, CA2/3, CA4/DG, as well as total hippocampal gray matter were reduced in volume in CB-dep but not in CB-nondep users, relative to HC. The right CA2/3 and CA4/DG volumes were also negatively associated with lifetime cannabis use in CB-dep users. Conclusions: Our results suggest a regionally and dependence-specific influence of cannabis use on the hippocampus. Hippocampal alteration in cannabis users was specific to the CA and DG regions and confined to dependent users. [ABSTRACT FROM AUTHOR]

The investigation of specific white matter areas is a growing field in neurological research and is typically achieved through the use of atlases. However, the definition of anatomically based regions remains challenging for the white matter and thus hinders region-specific analysis in individual subjects. In this article, we focus on creating a whole white matter parcellation method for individual subjects where these areas can be associated to cortex regions. This is done by combining cortex parcellation and fiber tracking data. By tracking fibers out of each cortex region and labeling the fibers according to their origin, we populate a candidate image. We then derive the white matter parcellation by classifying each white matter voxel according to the distribution of labels in the corresponding voxel from the candidate image. The parcellation of the white matter with the presented method is highly reliable and is not as dependent on registration as with white matter atlases. This method allows for the parcellation of the whole white matter into individual cortex region associated areas and, therefore, associates white matter alterations to cortex regions. In addition, we compare the results from the presented method to existing atlases. The areas generated by the presented method are not as sharply defined as the areas in most existing atlases; however, they are computed directly in the DWI space of the subject and, therefore, do not suffer from distortion caused by registration. The presented approach might be a promising tool for clinical and basic research to investigate modalities or system specific micro structural alterations of white matter areas in a quantitative manner. [ABSTRACT FROM AUTHOR]

Sporadic cerebral amyloid angiopathy is a common, well-defined small vessel disease and a largely untreatable cause of intracerebral haemorrhage and contributor to age-related cognitive decline. The term 'cerebral amyloid angiopathy' now encompasses not only a specific cerebrovascular pathological finding, but also different clinical syndromes (both acute and progressive), brain parenchymal lesions seen on neuroimaging and a set of diagnostic criteria-the Boston criteria, which have resulted in increasingly detected disease during life. Over the past few years, it has become clear that, at the pathophysiological level, cerebral amyloid angiopathy appears to be in part a protein elimination failure angiopathy and that this dysfunction is a feed-forward process, which potentially leads to worsening vascular amyloid-β accumulation, activation of vascular injury pathways and impaired vascular physiology. From a clinical standpoint, cerebral amyloid angiopathy is characterized by individual focal lesions (microbleeds, cortical superficial siderosis, microinfarcts) and large-scale alterations (white matter hyperintensities, structural connectivity, cortical thickness), both cortical and subcortical. This review provides an interdisciplinary critical outlook on various emerging and changing concepts in the field, illustrating mechanisms associated with amyloid cerebrovascular pathology and neurological dysfunction. [ABSTRACT FROM AUTHOR]