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Connectional topography mapping has been gaining widespread attention in human brain imaging studies. However, existing methods might not effectively utilize the information from neuroimaging data, thus hindering the understanding of the underlying connectional organization in the brain and uncovering the optimal clustering number from the data. In this study, we propose a novel method for the automated construction of inherent functional connectivity topography in a data‐driven manner by leveraging the power of co‐clustering‐based on resting state fMRI (rs‐fMRI) data. We propose the co‐clustering‐based method not only for concurrently parcellating two interconnected brain regions of interest (ROIs) under consideration into functionally homogenous subregions, but also for estimating the connectivity between these subregions from the two brain ROIs. In particular, we first model the connectional topography mapping as a co‐clustering‐based bipartite graph partitioning problem for constructing the inherent functional connectivity topography between the two interconnected brain ROIs. We also adopt an objective criterion, that is, silhouette width index measuring clustering quality, for determining the optimal number of clusters. The proposed method has been validated for mapping thalamocortical connectional topography based on rs‐fMRI data of 57 subjects. Validation results have demonstrated that our method identified the optimal solution with five pairs of mutually connected subregions of the thalamocortical system from the rs‐fMRI data, and could yield more meaningful, interpretable, and homogenous connectional topography than existing methods. The proposed method was further validated by the high symmetry of the mapped connectional topography between two hemispheres., A novel method was proposed for the automated construction of inherent functional connectivity topography in a data‐driven manner by leveraging the power of co‐clustering‐based on resting state fMRI (rs‐fMRI) data. The proposed the co‐clustering‐based method not only concurrently parcellates two interconnected brain regions of interest (ROIs) under consideration into functionally homogenous subregions, but also estimates the connectivity between these subregions from the two brain ROIs. Validation results have demonstrated that our method could yield more meaningful, interpretable, and homogenous connectional topography than existing methods.

Three‐dimensional (3D) Magnetic resonance fingerprinting (MRF) permits whole‐brain volumetric quantification of T1 and T2 relaxation values, potentially replacing conventional T1‐weighted structural imaging for common brain imaging analysis. The aim of this study was to evaluate the repeatability and reproducibility of 3D MRF in evaluating brain cortical thickness and subcortical volumetric analysis in healthy volunteers using conventional 3D T1‐weighted images as a reference standard. Scan‐rescan tests of both 3D MRF and conventional 3D fast spoiled gradient recalled echo (FSPGR) were performed. For each sequence, the regional cortical thickness and volume of the subcortical structures were measured using standard automatic brain segmentation software. Repeatability and reproducibility were assessed using the within‐subject coefficient of variation (wCV), intraclass correlation coefficient (ICC), and mean percent difference and ICC, respectively. The wCV and ICC of cortical thickness were similar across all regions with both 3D MRF and FSPGR. The percent relative difference in cortical thickness between 3D MRF and FSPGR across all regions was 8.0 ± 3.2%. The wCV and ICC of the volume of subcortical structures across all structures were similar between 3D MRF and FSPGR. The percent relative difference in the volume of subcortical structures between 3D MRF and FSPGR across all structures was 7.1 ± 3.6%. 3D MRF measurements of human brain cortical thickness and subcortical volumes are highly repeatable, and consistent with measurements taken on conventional 3D T1‐weighted images. A slight, consistent bias was evident between the two, and thus careful attention is required when combining data from MRF and conventional acquisitions., Three‐dimensional (3D) Magnetic resonance fingerprinting (MRF) permits whole‐brain volumetric quantification of T1 and T2 relaxation values, potentially replacing conventional T1‐weighted structural imaging for common brain imaging analysis. The aim of this study was to evaluate the repeatability and reproducibility of 3D MRF in evaluating brain cortical thickness and subcortical volumetric analysis. 3D MRF measurements of human brain cortical thickness and subcortical volumes are highly repeatable, and consistent with measurements taken on conventional 3D T1‐weighted images.

PURPOSE: To combine multi-slice chemical exchange saturation transfer (CEST) imaging with quasi-steady-state (QUASS) processing and demonstrate the feasibility of fast QUASS CEST MRI at 3 T. METHODS: Fast multi-slice EPI CEST imaging was developed with concatenated slice acquisition after single radio-frequency irradiation. The multi-slice CEST signal evolution was described by the spin-lock relaxation during saturation duration [Formula: see text] and longitudinal relaxation during the relaxation delay time [Formula: see text] and post-label delay (PLD), from which the QUASS CEST was generalized to fast multi-slice acquisition. In addition, numerical simulations, phantom, and normal human subjects scans were performed to compare the conventional apparent and QUASS CEST measurements with different [Formula: see text] , and PLD. RESULTS: The numerical simulation showed that the apparent CEST effect strongly depends on [Formula: see text] , and PLD, while the QUASS CEST algorithm minimizes such dependences. In the L-carnosine gel phantom, the proposed QUASS CEST effects (2.68±0.12% [mean ± SD]) were higher than the apparent CEST effects [Formula: see text]. In the human brain imaging, Bland-Altman analysis bias of the proposed QUASS CEST effects was much smaller than the PLD-corrected apparent CEST effects (0.03% vs. −0.54%), indicating the proposed fast multi-slice CEST imaging is robust and accurate. CONCLUSIONS: The QUASS processing enables fast multi-slice CEST imaging with minimal loss in the measurement of the CEST effect.

Psychedelics are reawakening interest from psychiatry, cognitive neuroscience and the general public with impressive outcomes in small-scale clinical trials, intriguing human brain imaging work and high-impact journalism.This brief opinion piece offers a perspective on how psychedelics work in the brain that may help contextualize these developments. It attempts to link various scales of action, from the molecular (serotonin 2A receptor agonism) through to the anatomical and functional (heightened plasticity) and up to the dynamic (increased brain entropy), systems level (network disintegration and desegregation) and experiential.It is proposed that psychedelics initiate a cascade of neurobiological changes that manifest at multiple scales and ultimately culminate in the relaxation of high-level beliefs. The purpose of psychedelic therapy is to harness the opportunity afforded by this belief-relaxation to achieve a healthy revision of pathological beliefs.

Metadata are what makes databases searchable. Without them, researchers would have difficulty finding data with features they are interested in. Brain imaging genetics is at the intersection of two disciplines, each with dedicated dictionaries and ontologies facilitating data search and analysis. Here, we present the genetics Brain Imaging Data Structure extension, consisting of metadata files for human brain imaging data to which they are linked, and describe succinctly the genomic and transcriptomic data associated with them, which may be in different databases. This extension will facilitate identifying micro-scale molecular features that are linked to macro-scale imaging repositories, facilitating data aggregation across studies.

Alterations to cerebral white matter tracts have been associated with cognitive decline in aging and Alzheimer’s disease (AD). In particular, the fornix has been implicated as especially vulnerable given that it represents the primary outflow tract of the hippocampus. Despite this, little work has focused on the fornix using a potential early marker of white matter degeneration—myelin water fraction (MWF; an in vivo marker of myelin content). Therefore, we sought to (1) clarify associations between MWF in the fornix and memory functioning, and (2) examine whether fornix MWF relates to memory performance above and beyond hippocampal volume and conventional imaging measures of white matter that may not be as specific to alterations in myelin content. Forty nondemented older adults (mean age = 72.9 years) underwent an MRI exam and neuropsychological assessment. Multicomponent driven equilibrium single pulse observation of T1 and T2 (mcDESPOT) was used to quantify fornix MWF and diffusion tensor imaging (DTI) was used to measure fornix fractional anisotropy (FA). Adjusting for age, sex, education, and vascular risk factors, linear regression models revealed that, lower fornix MWF was significantly associated with poorer memory functioning (β = 0.405, p = .007) across our sample of older adults. Notably, fornix MWF remained a significant predictor of memory functioning (β = 0.380, p = .015) even after adjusting for fornix DTI FA and hippocampal volume (in addition to the above covariates). Given the observed associations between myelin and memory in older adults without dementia, MWF may be a useful early marker of dementia risk.

The motivation to seek and consume water is an essential component of human fluid–electrolyte homeostasis, optimal function, and health. This review describes the evolution of concepts regarding thirst and drinking behavior, made possible by magnetic resonance imaging, animal models, and novel laboratory techniques. The earliest thirst paradigms focused on single factors such as dry mouth and loss of water from tissues. By the end of the 19th century, physiologists proposed a thirst center in the brain that was verified in animals 60 years later. During the early- and mid-1900s, the influences of gastric distention, neuroendocrine responses, circulatory properties (i.e., blood pressure, volume, concentration), and the distinct effects of intracellular dehydration and extracellular hypovolemia were recognized. The majority of these studies relied on animal models and laboratory methods such as microinjection or lesioning/oblation of specific brain loci. Following a quarter century (1994–2019) of human brain imaging, current research focuses on networks of networks, with thirst and satiety conceived as hemispheric waves of neuronal activations that traverse the brain in milliseconds. Novel technologies such as chemogenetics, optogenetics, and neuropixel microelectrode arrays reveal the dynamic complexity of human thirst, as well as the roles of motivation and learning in drinking behavior.

Imagine you were asked to investigate the workings of an engine, but to do so without ever opening the hood. Now imagine the engine fueled the human mind. This is the challenge faced by cognitive neuroscientists worldwide aiming to understand the neural bases of our psychological functions. Luckily, human ingenuity comes to the rescue., Imagine you were asked to investigate the workings of an engine, but to do so without ever opening the hood. Now imagine the engine fueled the human mind. This is the challenge faced by cognitive neuroscientists worldwide aiming to understand the neural bases of our psychological functions. Luckily, human ingenuity comes to the rescue. Around the same time as the Society for Neuroscience was being established in the 1960s, the first tools for measuring the human brain at work were becoming available. Noninvasive human brain imaging and neurophysiology have continued developing at a relentless pace ever since. In this 50 year anniversary, we reflect on how these methods have been changing our understanding of how brain supports mind.

A key challenge for neuroscience is to develop generative, causal models of the human nervous system in an individualized, data-driven manner. Previous initiatives have either constructed biologically-plausible models that are not constrained by individual-level human brain activity or used data-driven statistical characterizations of individuals that are not mechanistic. We aim to bridge this gap through the development of a new modeling approach termed Mesoscale Individualized Neurodynamic (MINDy) modeling, wherein we fit nonlinear dynamical systems models directly to human brain imaging data. The MINDy framework is able to produce these data-driven network models for hundreds to thousands of interacting brain regions in just 1-3 minutes per subject. We demonstrate that the models are valid, reliable, and robust. We show that MINDy models are predictive of individualized patterns of resting-state brain dynamical activity. Furthermore, MINDy is better able to uncover the mechanisms underlying individual differences in resting state activity than functional connectivity methods.

Contains fulltext : 204554.pdf (Publisher’s version ) (Open Access) The Brain Imaging Data Structure (BIDS) project is a rapidly evolving effort in the human brain imaging research community to create standards allowing researchers to readily organize and share study data within and between laboratories. Here we present an extension to BIDS for electroencephalography (EEG) data, EEG-BIDS, along with tools and references to a series of public EEG datasets organized using this new standard. 5 p.

Schizophrenia is a heterogeneous and poorly understood mental disorder that is presently defined solely by its behavioral symptoms. Advances in genetic, epidemiological and brain imaging techniques in the past half century, however, have significantly advanced our understanding of the underlying biology of the disorder. In spite of these advances clinical research remains limited in its power to establish the causal relationships that link etiology with pathophysiology and symptoms. In this context, animal models provide an important tool for causally testing hypotheses about biological processes postulated to be disrupted in the disorder. While animal models can exploit a variety of entry points towards the study of schizophrenia, here we describe an approach that seeks to closely approximate functional alterations observed with brain imaging techniques in patients. By modeling these intermediate pathophysiological alterations in animals, this approach offers an opportunity to (1) tightly link a single functional brain abnormality with its behavioral consequences, and (2) to determine whether a single pathophysiology can causally produce alterations in other brain areas that have been described in patients. In this review we first summarize a selection of well-replicated biological abnormalities described in the schizophrenia literature. We then provide examples of animal models that were studied in the context of patient imaging findings describing enhanced striatal dopamine D2 receptor function, alterations in thalamo-prefrontal circuit function, and metabolic hyperfunction of the hippocampus. Lastly, we discuss the implications of findings from these animal models for our present understanding of schizophrenia, and consider key unanswered questions for future research in animal models and human patients.

Why vestibular compensation (VC) after an acute unilateral vestibular loss is the neuro-otologist’s best friend is the question at the heart of this paper. The different plasticity mechanisms underlying VC are first reviewed, and the authors present thereafter the dual concept of vestibulo-centric versus distributed learning processes to explain the compensation of deficits resulting from the static versus dynamic vestibular imbalance. The main challenges for the plastic events occurring in the vestibular nuclei (VN) during a post-lesion critical period are neural protection, structural reorganization and rebalance of VN activity on both sides. Data from animal models show that modulation of the ipsilesional VN activity by the contralateral drive substitutes for the normal push–pull mechanism. On the other hand, sensory and behavioural substitutions are the main mechanisms implicated in the recovery of the dynamic functions. These newly elaborated sensorimotor reorganizations are vicarious idiosyncratic strategies implicating the VN and multisensory brain regions. Imaging studies in unilateral vestibular loss patients show the implication of a large neuronal network (VN, commissural pathways, vestibulo-cerebellum, thalamus, temporoparietal cortex, hippocampus, somatosensory and visual cortical areas). Changes in gray matter volume in these multisensory brain regions are structural changes supporting the sensory substitution mechanisms of VC. Finally, the authors summarize the two ways to improve VC in humans (neuropharmacology and vestibular rehabilitation therapy), and they conclude that VC would follow a “top-down” strategy in patients with acute vestibular lesions. Future challenges to understand VC are proposed.

It has been nearly 10 years since Ghazanfar and Schroeder (2006) proposed that the neocortex is essentially multisensory in nature. However, it is only recently that sufficient and hard evidence that supports this proposal has accrued. We review evidence that activity within the human primary visual cortex plays an active role in multisensory processes and directly impacts behavioural outcome. This evidence emerges from a full pallet of human brain imaging and brain mapping methods with which multisensory processes are quantitatively assessed by taking advantage of particular strengths of each technique as well as advances in signal analyses. Several general conclusions about multisensory processes in primary visual cortex of humans are supported relatively solidly. First, haemodynamic methods (fMRI/PET) show that there is both convergence and integration occurring within primary visual cortex. Second, primary visual cortex is involved in multisensory processes during early post-stimulus stages (as revealed by EEG/ERNERFs as well as TMS). Third, multisensory effects in primary visual cortex directly impact behaviour and perception, as revealed by correlational (EEG/ERPs/ERFs) as well as more causal measures (TMS/tACS). While the provocative claim of Ghazanfar and Schroeder (2006) that the whole of neocortex is multisensory in function has yet to be demonstrated, this can now be considered established in the case of the human primary visual cortex. (C) 2015 Elsevier Ltd. All rights reserved.

Human brain imaging can help improve our understanding of mechanisms underlying brain function and how they drive behavior in health and disease. Such knowledge may eventually help us to devise better treatments for psychiatric disorders. However, the brain imaging literature in psychiatry and especially eating disorders has been inconsistent, and studies are often difficult to replicate. The extent or severity of extremes of eating and state of illness, which are often associated with differences in, for instance hormonal status, comorbidity, and medication use, commonly differ between studies and likely add to variation across study results. Those effects are in addition to the well-described problems arising from differences in task designs, data quality control procedures, image data preprocessing and analysis or statistical thresholds applied across studies. Which of those factors are most relevant to improve reproducibility is still a question for debate and further research. Here we propose guidelines for brain imaging research in eating disorders to acquire valid results that are more reliable and clinically useful.

BACKGROUND: Mobile computed tomography (CT) with a cone-beam source is increasingly used in the clinical field. Mobile cone-beam CT (CBCT) has great merits; however, its clinical utility for brain imaging has been limited due to problems including scan time and image quality. OBJECTIVE: The aim of this study was to develop a dedicated mobile volumetric CBCT for obtaining brain images, and to optimize the imaging protocol using a brain phantom. METHODS: The mobile volumetric CBCT system was evaluated with regards to scan time and image quality, measured as signal-to-noise-ratio (SNR), contrast-to-noise-ratio (CNR), spatial resolution (10% MTF), and effective dose. Brain images were obtained using a CT phantom. RESULTS: The CT scan took 5.14 s at 360 projection views. SNR and CNR were 5.67 and 14.5 at 120 kV/10 mA. SNR and CNR values showed slight improvement as the x-ray voltage and current increased ( p< 0.001). Effective dose and 10% MTF were 0.92 mSv and 360 µm at 120 kV/10 mA. Various intracranial structures were clearly visible in the brain phantom images. CONCLUSIONS: Using this CBCT under optimal imaging acquisition conditions, it is possible to obtain human brain images with low radiation dose, reproducible image quality, and fast scan time.

Brain aging and associated neurodegeneration constitute a major societal challenge as well as one for the neuroimaging community. A full understanding of the physiological mechanisms underlying neurodegeneration still eludes medical researchers, fuelling the development of in vivo neuroimaging markers. Hence it is increasingly recognized that our understanding of neurodegenerative processes likely will depend upon the available information provided by imaging techniques. At the same time, the imaging techniques are often developed in response to the desire to observe certain physiological processes. In this context, functional MRI (fMRI), which has for decades provided information on neuronal activity, has evolved into a large family of techniques well suited for in vivo observations of brain physiology. Given the rapid technical advances in fMRI in recent years, this review aims to summarize the physiological basis of fMRI observations in healthy aging as well as in age-related neurodegeneration. This review focuses on in-vivo human brain imaging studies in this review and on disease features that can be imaged using fMRI methods. In addition to providing detailed literature summaries, this review also discusses future directions in the study of brain physiology using fMRI in the clinical setting.

The purpose of this study was to develop an analytical expression for a fractional motion (FM) diffusion model to characterize diffusion-induced signal attenuation in a twice-refocused spin-echo (TRSE) sequence that is resilient to eddy currents, and to demonstrate its applicability to human brain imaging in vivo. Based on the FM theory, which provides a unified statistical description for Langevin motions, the diffusion-weighted (DW) MR signal was measured with a TRSE sequence that balances the concomitant gradients. The analytical expression was fitted to a set of DW images acquired with 14 b-values (0-4000 s/mm2 ) from a total of 10 healthy human subjects at 3 T, yielding three FM parameter maps based on anomalous diffusion coefficient Dφ, ψ , diffusion increment variance φ, and diffusion correlation ψ, respectively. These parameters were used to characterize different brain regions in gray matter (GM), white matter (WM), and cerebrospinal fluid. The analytical expression for the TRSE-based FM model accurately described diffusion signal attenuation in healthy brain tissues at high b-values. TRSE's robustness against eddy currents was illustrated by comparing results from an expression for a conventional Stejskal-Tanner sequence. The TRSE-based FM model also produced consistent GM-WM contrast (p < 0.01) across all brain regions studied, whereas the consistency was not observed with the Stejskal-Tanner-based FM model. This new analytical expression is expected to enable further investigations to probe tissue structures by exploiting anomalous diffusion properties without being hindered by eddy-current perturbations at high b-values.

Some of the health risks of inhaling fine and ultrafine pollutant particles are well-established, such as asthma, lung cancer, and, most recently, heart disease. But a growing body of evidence suggests that such exposure can also harm the brain, accelerating cognitive aging, and may even increase risk of Alzheimer9s disease and other forms of dementia. The link between air pollution and dementia remains controversial—even its proponents warn that more research is needed to confirm a causal connection and work out just how the particles might enter the brain and make mischief there. But a growing number of epidemiological studies from around the world, new findings from animal models and human brain imaging studies, and increasingly sophisticated techniques for modeling PM2.5 exposures have raised alarms. Indeed, in an 11-year epidemiological study to be published next week in Translational Psychiatry, University of Southern California (USC) researchers will report that living in places with PM2.5 exposures higher than the Environmental Protection Agency9s standard of 12 μg/m3 nearly doubled dementia risk in older women. If the finding holds up in the general population, air pollution could account for roughly 21% of dementia cases worldwide, says the study9s lead author, epidemiologist Jiu-Chiuan Chen of the Keck School of Medicine at USC.

Using the α7-nAChR radiotracer, [(18)F]ASEM, we present the first successful human positron emission tomography (PET) studies. Rodent occupancy with three clinically employed α7-nAChR drugs confirms the specificity of the radiotracer.Five healthy male subjects were imaged for 90 min following IV [(18)F]ASEM. Two subjects were scanned for the second time (test/retest; TRV). Mouse biodistribution of [(18)F]ASEM was carried out in CD1 mice injected with using human equivalent doses of DMXB-A, EVP-6124, and varenicline to block specific binding.[(18)F]ASEM readily entered the brain and peaked at 15 min post-injection with reversible kinetics and a peak %SUV of about 400 %. The regional human brain distribution of [(18)F]ASEM matched previous in vitro data and baboon PET results. The precuneus, parietal, occipital, cingulate cortexes, putamen, and thalamus showed high values of distribution volume (20 ml/ml) and binding potentials1 with TRV averaged 10.8 ± 5.1 %. In mouse distribution studies, there was significant dose-dependent blockade in the mouse brain with DMXB-A as well as the other two α7-nAChR drugs.The characteristics of [(18)F]ASEM are consistent with the ability to quantify α7-nAChR in the human brain. [(18)F]ASEM is suitable for imaging neuropsychiatric disorders and target engagement (receptor occupancy) of potential α7-nAChR drugs.

We present a concept for integrating focused ultrasound (FUS) with electrophysiological neuroimaging, in order to achieve high spatio-temporal resolution brain imaging. This approach, which we are tentatively calling acousto-electrophysiological neuroimaging, leverages on the spatial focality and noninvasiveness of FUS and may potentially lead to a noninvasive human brain imaging modality with high resolution in both space and time domains. By use of modulated FUS, spatial selectivity can be accomplished for high resolution electrophysiological neuroimaging. Frequency shifting in resulting magnetic signals (using modulated focused ultrasound) may potentially open the door for a room temperature magnetoencephalography (MEG) device.

The introduction of hybrid positron emission/magnetic resonance tomography (PET/MR) in diagnostic clinical imaging was a major step in the evolution of ever-more sophisticated imaging systems combining two strategies formerly regarded as technically incompatible in a single device. The advent of PET/MR opened up many new avenues in clinical and research environments, mainly by providing multi-modality images obtained during a single examination. Ideally, simultaneous data acquisition with hybrid PET/MR should warrant exact image co-registration of all multi-modality image volumes provided by both systems. This assumes that there is negligible mutual electronic, technical and logistical interference on the respective simultaneous measurements. Recently, such hybrid dedicated head and whole-body systems were successfully applied in an increasing number of cases. When employed for brain imaging, PET/MR has the potential to provide high-resolution multi-modality datasets. However, it also demands careful consideration of the multitude of features offered, as well as the limitations. There are open issues that have to be considered, such as the handling of patient motion during extended periods of data acquisition, optimized sampling of derived images to ease the visual interpretation and quantitative evaluation of co-registered images. This paper will briefly summarize the current status of PET/MR within the framework of developments for image co-registration and discuss current limitations and future perspectives.

Encoding higher spatial resolution in simultaneous multi-slice (SMS) EPI is highly dependent on gradient performance, high density receiver coil arrays and pulse sequence optimization. We simulate gradient amplitude and slew rate determination of EPI imaging performance in terms of minimum TE, echo spacing (ES) and spatial resolution. We discuss the effects of image zooming in pulse sequences that have been used for sub-millimeter resolutions and the trade-offs in using partial Fourier and parallel imaging to reduce TE, PSF and ES. Using optimizations for SMS EPI pulse sequences with available gradient and receiver hardware, experimental results in ultra-high resolution (UHR) (0.45-0.5mm isotropic) SMS-EPI fMRI and mapping ocular dominance columns (ODC) in human brain at 0.5 mm isotropic resolution are demonstrated. We discuss promising future directions of UHR fMRI.

Human brain imaging has identified structural changes in gray and white matter that occur with learning. However, ascribing imaging measures to underlying cellular and molecular events is challenging. Here we review human neuroimaging findings of structural plasticity and then discuss cellular and molecular level changes that could underlie observed imaging effects. Greater dialog between researchers in these different fields would help to facilitate cross-talk between cellular and systems level explanations of how learning sculpts brain structure. © 2012 Nature America, Inc. All rights reserved.

Human neuroimaging studies and complementary animal experiments now identify the gross elements of the brain involved in the chronification of pain. We briefly review these advances in relation to somatic and orofacial persistent pain conditions. First, we emphasize the importance of reverse translational research for understanding chronic pain—that is, the power of deriving hypotheses directly from human brain imaging of clinical conditions that can be invasively and mechanistically studied in animal models. We then review recent findings demonstrating the importance of the emotional brain (i.e., the corticolimbic system) in the modulation of acute pain and in the prediction and amplification of chronic pain, contrasting this evidence with recent findings regarding the role of central sensitization in pain chronification, especially for orofacial pain. We next elaborate on the corticolimbic circuitry and underlying mechanisms that determine the transition to chronic pain. Given this knowledge, we advance a new mechanistic definition of chronic pain and discuss the clinical implications of this new definition as well as novel therapeutic potentials suggested by these advances.

Purpose Relaxation times, transmit homogeneity, signal-to-noise ratio (SNR) and parallel imaging g-factor were determined in the human brain at 3T, 7T, and 9.4T, using standard, tight-fitting coil arrays. Methods The same human subjects were scanned at all three field strengths, using identical sequence parameters and similar 31- or 32-channel receive coil arrays. The SNR of three-dimensional (3D) gradient echo images was determined using a multiple replica approach and corrected with measured flip angle and T2* distributions and the T1 of white matter to obtain the intrinsic SNR. The g-factor maps were derived from 3D gradient echo images with several GRAPPA accelerations. Results As expected, T1 values increased, T2* decreased and the B1-homogeneity deteriorated with increasing field. The SNR showed a distinctly supralinear increase with field strength by a factor of 3.10 ± 0.20 from 3T to 7T, and 1.76 ± 0.13 from 7T to 9.4T over the entire cerebrum. The g-factors did not show the expected decrease, indicating a dominating role of coil design. Conclusion In standard experimental conditions, SNR increased supralinearly with field strength (SNR ∼ B01.65). To take full advantage of this gain, the deteriorating B1-homogeneity and the decreasing T2* have to be overcome. Magn Reson Med, 2015. © 2015 Wiley Periodicals, Inc.

Determining the susceptibility distribution from the magnetic field measured in a magnetic resonance (MR) scanner is an ill-posed inverse problem, because of the presence of zeroes in the convolution kernel in the forward problem. An algorithm called morphology enabled dipole inversion (MEDI), which incorporates spatial prior information, has been proposed to generate a quantitative susceptibility map (QSM). The accuracy of QSM can be validated experimentally. However, there is not yet a rigorous mathematical demonstration of accuracy for a general regularized approach or for MEDI specifically. The error in the susceptibility map reconstructed by MEDI is expressed in terms of the acquisition noise and the error in the spatial prior information. A detailed analysis demonstrates that the error in the susceptibility map reconstructed by MEDI is bounded by a linear function of these two error sources. Numerical analysis confirms that the error of the susceptibility map reconstructed by MEDI is on the same order of the noise in the original MRI data, and comprehensive edge detection will lead to reduced model error in MEDI. Additional phantom validation and human brain imaging demonstrated the practicality of the MEDI method.

Audiovisual processing was studied in a functional magnetic resonance imaging study using the McGurk effect. Perceptual responses and the brain activity patterns were measured as a function of audiovisual delay. In several cortical and subcortical brain areas, BOLD responses correlated negatively with the perception of the McGurk effect. No brain areas with positively correlated BOLD responses were found. This was unexpected as most studies of audiovisual integration use additivity and super additivity - that is, increased BOLD responses after audiovisual stimulation compared with auditory-only and visual-only stimulation - as criteria for audiovisual integration. We argue that brain areas that show decreased BOLD responses that correlate with an integrated audiovisual percept should not be neglected from consideration as possibly involved in audiovisual integration. NeuroReport 21: 1146-1151 (C) 2010 Wolters Kluwer Health vertical bar Lippincott Williams & Wilkins.

A novel method based on average Hamiltonian theory to design selective pulses is reported. With this tool, it is first shown how to shape the radiofrequency and gradient pulses to generate a desired rotation matrix, which is independent of the position through the slice of interest. After theoretical examination of the concept, it is applied to the strongly modulating pulses' recipe developed by the same authors and initially designed to be nonselective, to mitigate the amplitude of (excitation) radiofrequency field and amplitude of static (polarizing) field inhomogeneity problems at high field. Two in vivo human brain imaging experiments at 7 T are reported to prove the validity of the technique.

Phantom-based evaluation of geometric distortions in functional MRI and diffusion tensor imaging (DTI) was investigated. An acrylic water-filled phantom with a grid structure was designed and manufactured to provide accurate geometric information over the volume measured in human brain imaging. The grid structures were well detected in data acquired using a 3-T MRI scanner with echo-planar imaging (EPI) sequences commonly applied in functional MRI and DTI. A method for quantifying distortions in the phantom data was presented and applied for the images. The validity of the phantom for EPI was evaluated by quantitatively comparing the distortions present in and induced by the phantom and a human brain when imaged under identical conditions. The results suggest that the new phantom can reveal geometric distortions easily undermined by standard MRI phantoms. For example, prominent variability in the distortions was found as a function of the orientation of the diffusion-sensitizing gradient. Possible future applications for this type of phantom include quality assurance and calibration of the hardware and software used in EPI-based functional MRI and DTI. Magn Reson Med 57:754–763, 2007. © 2007 Wiley-Liss, Inc.

BackgroundIncreasing evidence suggests that autism is associated with abnormal white-matter (WM) anatomy and impaired brain ‘connectivity’. While myelin plays a critical role in synchronized brain communication, its aetiological role in autistic symptoms has only been indirectly addressed by WM volumetric, relaxometry and diffusion tensor imaging studies. A potentially more specific measure of myelin content, termed myelin water fraction (MWF), could provide improved sensitivity to myelin alteration in autism.MethodWe performed a cross-sectional imaging study that compared 14 individuals with autism and 14 age- and IQ-matched controls. T1 relaxation times (T1), T2 relaxation times (T2) and MWF values were compared between autistic subjects, diagnosed using the Autism Diagnostic Interview – Revised (ADI-R), with current symptoms assessed using the Autism Diagnostic Observation Schedule (ADOS) and typical healthy controls. Correlations between T1, T2 and MWF values with clinical measures [ADI-R, ADOS, and the Autism Quotient (AQ)] were also assessed.ResultsIndividuals with autism showed widespread WM T1 and MWF differences compared to typical controls. Within autistic individuals, worse current social interaction skill as measured by the ADOS was related to reduced MWF although not T1. No significant differences or correlations with symptoms were observed with respect to T2.ConclusionsAutistic individuals have significantly lower global MWF and higher T1, suggesting widespread alteration in tissue microstructure and biochemistry. Areas of difference, including thalamic projections, cerebellum and cingulum, have previously been implicated in the disorder; however, this is the first study to specifically indicate myelin alteration in these regions.

The field of basal ganglia research is exploding on every level - from discoveries at the molecular level to those based on human brain imaging. A remarkable series of new findings support the view that the basal ganglia are essential for some forms of learning-related plasticity. Other new findings are challenging some of the basic tenets of the field as it now stands. Combined with the new evidence on learning-related functions of the basal ganglia, these studies suggest that the basal ganglia are parts of a brain-wide set of adaptive neural systems promoting optimal motor and cognitive control.

Recent results from anatomical, physiological and imaging experiments cast doubt on the existence of some areas in the primate visual brain and call for a much overdue re-assessment of what is a conceptually highly unsatisfactory view of how the primate visual brain is organized, a view that has survived more or less unscathed for at least 15 years and has been embraced uncritically by a significant element in the human brain imaging community. That view can be summarized as follows: that there are areas in the visual brain that represent only one quadrant of the visual field, leaving the other quadrant of the hemifield unrepresented, or represented in another area, leading to what Jon Kaas has called ‘improbable areas'. It is not the improbability of such a view that is surprising; rather, it is its ready acceptance on the basis of questionable evidence.

This article describes recent research on sensory irritants that should prove helpful to setting occupational exposure limits (OELs) for this class of chemicals. In addition, background information is provided to assist in recognizing the relevance and importance of this type of work. Research conducted by Dr. Steven Youngentob and others addresses the recovery of olfactory function following exposure to high concentrations of sensory irritants. Their research has combined several different experimental methods to gain insight on how olfactory receptor neurons (ORNs) are replaced. Other important work relevant to setting OELs has been conducted by Professor Gerd Kobal, who has relied on human brain imaging during chemosensory stimulation. Commentary on these two approaches is followed by suggestions on how to address the relative lack of detailed normative information on human responses to odors and irritants.

The article contributes to the quest to relate global data on brain and behavior (e.g. from PET, Positron Emission Tomography, and fMRI, functional Magnetic Resonance Imaging) to the underpinning neural networks. Models tied to human brain imaging data often focus on a few “boxes” based on brain regions associated with exceptionally high blood flow, rather than analyzing the cooperative computation of multiple brain regions. For analysis directly at the level of such data, a schema-based model may be most appropriate. To further address neurophysiological data, the Synthetic PET imaging method uses computational models of biological neural circuitry based on animal data to predict and analyze the results of human PET studies. This technique makes use of the hypothesis that rCBF (regional cerebral blood flow) is correlated with the integrated synaptic activity in a localized brain region. We also describe the possible extension of the Synthetic PET method to fMRI. The second half of the paper then exemplifies this general research program with two case studies, one on visuo-motor processing for control of grasping (Section 3 in which the focus is on Synthetic PET) and the imitation of motor skills (Sections 4 and 5, with a focus on Synthetic fMRI). Our discussion of imitation pays particular attention to data on the mirror system in monkey (neural circuitry which allows the brain to recognize actions as well as execute them). Finally, Section 6 outlines the immense challenges in integrating models of different portions of the nervous system which address detailed neurophysiological data from studies of primates and other species; summarizes key issues for developing the methodology of Synthetic Brain Imaging; and shows how comparative neuroscience and evolutionary arguments will allow us to extend Synthetic Brain Imaging even to language and other cognitive functions for which few or no animal data are available.

The advent of new technology has led to a proliferation of studies examining the functional roles of discrete prefrontal cortical areas. This has created a need for more precise information regarding the morphological characteristics of this region. Existing architectonic maps of human and monkey brains are not compatible with regard to areal delineations and topography, creating significant difficulty in interpreting comparative data. Therefore, we have re-examined the comparative morphological organization of the prefrontal cortex in humans and rhesus monkeys. Our analysis indicates that the architectonic areas in both species correspond in terms of morphological features as well as topographical locations. We have developed a common organizational schema for these areas, thereby allowing for a resolution of previous discrepancies. Moreover, in monkeys a connectional analysis has revealed that each of the newly designated areas is characterized by a unique pattern of cortical relationships. The present organizational schema provides a framework for interrelating findings such as those obtained from human brain imaging studies with those from behavioural investigations of non-human primates.

The authors obtained brain images with patients in the upright position using a newly designed and constructed vertical MR system. They found little gravitational effect on brain structures, even in the case of a severely atrophied brain. Their vertical system was practical for routine clinical usage and might provide information regarding gravitational effects on regional perfusion and other aspects of brain physiology.

Sharing scientific data containing complex information requires new concepts and new technology. NEUROGENERATOR is a database generator for the neuroimaging community. A database generator is a database that generates new databases. The scientists submit raw PET and fMRI data to NEUROGENERATOR, which then processes the data in a uniform way to create databases of homogeneous data suitable for data sharing, met-analysis and modelling the human brain at the systems level. These databases are then distributed to the scientists.

Although the complimentary roles of heart and brain in anxiety have been recognised for centuries, the precise contribution of each and more importantly perhaps their interplay has proved difficult to describe. Recent data from human brain imaging and cardiovascular physiology studies are beginning to delineate the mechanistic pathways of anxiety disorders in general and panic in particular. Evidence for a dysfunction of brain gamma-amino butyric acid-A and serotonin (5HT) systems in both panic and cardiovascular regulation is reviewed along with new evidence for altered sympathetic nervous system activity in the heart and periphery. Testable hypotheses and research ideas are suggested.

Investigation of the basic mechanisms of chronic pain not only provides insights into how the brain processes and modulates sensory information but also provides the basis for designing novel treatments for currently intractable clinical conditions. Human brain imaging studies have revealed new roles of cortical neuronal networks in chronic pain, including its unpleasant quality, and mouse studies have provided molecular and synaptic mechanisms underlying relevant cortical plasticity. This review paper will critically examine the current literature and propose a cortical network model for chronic pain.

Quantitative mapping of water content, especially in the human brain, has the potential to provide important information for the study and diagnosis of diseases associated with a focal or global change in tissue water homeostasis. In the current work, an imaging method for the precise and accurate quantification of tissue water content is presented. The method allows the acquisition of water content maps with voxel dimensions of 1x1x2 mm(3) and full brain coverage in less than 10 min on a standard clinical 1.5 T scanner. The precision was optimised for human brain imaging and possible sources of systematic error were carefully investigated, demonstrating the ability of the method to quantify water content with high accuracy and precision. The approach was validated in phantom experiments and quantitative cerebral water content maps of a group of 10 healthy volunteers were obtained.

A 32-channel 3T receive-only phased-array head coil was developed for human brain imaging. The helmet-shaped array was designed to closely fit the head with individual overlapping circular elements arranged in patterns of hexagonal and pentagonal symmetry similar to that of a soccer ball. The signal-to-noise ratio (SNR) and noise amplification (g-factor) in accelerated imaging applications were quantitatively evaluated in phantom and human images and compared with commercially available head coils. The 32-channel coil showed SNR gains of up to 3.5-fold in the cortex and 1.4-fold in the corpus callosum compared to a (larger) commercial eight-channel head coil. The experimentally measured g-factor performance of the helmet array showed significant improvement compared to the eight-channel array (peak g-factor 59% and 26% of the eight-channel values for four- and fivefold acceleration). The performance of the arrays is demonstrated in high-resolution and highly accelerated brain images.

We investigated the neuronal processing of the physiologically particularly important precision grip (opposition of index finger and thumb) by the combination of functional magnetic resonance imaging (fMRI) and an MR-compatible haptic interface. Ten healthy subjects performed isometric precision grip force generation with visual task instruction and real-time visual feedback in a block design. In a 2 x 2 two-factorial design, both the timing and force could be either constant or varying (identical average timing and force). As we expected only small changes in the fMRI response for the different fine-graded motor control conditions, we maximized the sensitivity of the data analysis and implemented a volumes of interest (VOI) restricted general linear model analysis including non-explanatory force regressors to eliminate directly force-related low-level activations. The VOIs were defined based on previous studies. We found significant associations: timing variation (variable vs. constant) and primary motor area (M1) and dorsal premotor area (PMd); force variation (variable vs. constant) and primary somatosensory area (S1), anterior intraparietal area (AIP) and PMd; interaction of timing and force and supplementary motor area (SMA) and AIP. We conclude that SMA and AIP integrate fine-graded higher-level timing and force control during precision grip. M1, S1 and PMd process lower-level timing and force control, yet not their integration. These results are the basis for a detailed assessment of manual motor control in a variety of motor diseases. The detailed behavioural assessment by our MR-compatible haptic interface is particularly valuable in patients due to expected larger inter-individual variation in motor performance.