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Real-time fMRI (rtfMRI) allows immediate access to experimental results by analyzing data as fast as they are acquired. It was devised soon after the inception of fMRI and has undergone a rapid development since then. The availability of results during the ongoing experiment facilitates a variety of applications such as quality assurance or fast functional localization. RtfMRI can also be used as a brain–computer interface (BCI) with high spatial resolution and whole-brain coverage, overcoming limitations of EEG based BCIs. This review will focus on the application of rtfMRI BCIs to neurofeedback, i.e., the online feedback of the blood oxygen level dependent (BOLD) response. I will motivate its development and place its beginnings into the contemporary scientific context by providing an account of our early work at the University of Tübingen, followed by a review of the accomplishments and the current state of rtfMRI neurofeedback. RtfMRI neurofeedback has been used to train self-regulation of the local BOLD response in various different brain areas and to study consequential behavioral effects. Behavioral effects such as modulation of pain, reaction time, linguistic or emotional processing have been shown in healthy and/or patient populations. RtfMRI neurofeedback presents a new paradigm for studying the relation between brain behavior and physiology, because the latter can be regarded as the independent variable (unlike in conventional neuroimaging studies where behavior is the independent variable). The initial results in patient populations improving pain, tinnitus, depression or modulating perception in schizophrenia are encouraging and merit further controlled clinical studies.

The morphology of cortical grey matter is commonly assessed using T1-weighted MRI together with automated computerised methods such as voxel-based morphometry (VBM) and cortical thickness measures. In the presented study we investigate how grey matter changes identified using voxel-based cortical thickness (VBCT) measures compare with local grey matter volume changes identified using VBM. We use data from a healthy aging population to perform the comparison, focusing on brain regions where age-related changes have been observed in previous studies. Our results show that overall, in healthy aging, VBCT and VBM yield very consistent results but VBCT provides a more sensitive measure of age-associated decline in grey matter compared with VBM. Our findings suggest that while VBCT selectively investigates cortical thickness, VBM provides a mixed measure of grey matter including cortical surface area or cortical folding, as well as cortical thickness. We therefore propose that used together, these techniques can separate the underlying grey matter changes, highlighting the utility of combining these complementary methods.

Traumatic spinal cord injury occurs when an external physical impact damages the spinal cord and leads to permanent neurological dysfunction and disability, and it is associated with a high socioeconomic burden. Conventional MRI plays a crucial role in the diagnostic workup as it reveals extrinsic compression of the spinal cord and disruption of the discoligamentous complex. Additionally, it can reveal macrostructural evidence of primary intramedullary damage such as haemorrhage, oedema, post-traumatic cystic cavities, and tissue bridges. Quantitative MRI, such as magnetisation transfer, magnetic resonance relaxation mapping, and diffusion imaging, enables the tracking of secondary changes across the neuraxis at the microstructural level. Both conventional MRI and quantitative MRI metrics, obtained early after spinal cord injury, are predictive of clinical outcome. Thus, neuroimaging biomarkers could serve as surrogate endpoints for more efficient future trials targeting acute and chronic spinal cord injury. The adoption of neuroimaging biomarkers in centres for spinal cord injury might lead to personalised patient care.

Key Points Neurofeedback is a type of biofeedback in which neural activity is measured and presented through one or more sensory channels to the participant in real time to facilitate self-regulation of the putative neural substrates that underlie a particular behaviour or pathology Animal and human brain self-regulation has been demonstrated using various invasive and non-invasive recording methods and with different features of the brain signals, such as frequency spectra, functional connectivity or spatiotemporal patterns of brain activity Neurofeedback provides the possibility of endogenously manipulating brain activity as an independent variable, making it a powerful neuroscientific tool Neurofeedback training results in specific neural changes relevant to the trained brain circuit and the associated behavioural changes. These changes have been shown to last anywhere from hours to months after training and to correlate with changes in grey and white matter structure The underlying neural circuitry relating to the process of brain self-regulation is becoming clearer. Accumulating evidence suggests the involvement of the thalamus and the dorsolateral prefrontal, posterior parietal and occipital cortices in neurofeedback control, and the dorsal and ventral striatum, anterior cingulate cortex and anterior insula in neurofeedback reward processing Psychological factors, such as the differential influence of feedback, reward and experimental instructions, and other factors, such as sense of agency and locus of control, are now being investigated for their effects on neurofeedback The demonstration of robust clinical effects remains a major hurdle in neurofeedback research. The results of randomized controlled trials in attention deficit and hyperactivity disorder and stroke rehabilitation have been mixed, and have been affected by differences in study design, difficulty of identifying responders and the scarcity of homogenous patient populations Future neurofeedback research will probably clarify the psychological and neural mechanisms that may help to address issues in clinical translation In neurofeedback, an individual receives online feedback of their neural activity to facilitate self-regulation of a brain region and, as a result, a particular behaviour or pathology. In this Review, the authors examine how this technique has been used and its underlying mechanisms. Neurofeedback is a psychophysiological procedure in which online feedback of neural activation is provided to the participant for the purpose of self-regulation. Learning control over specific neural substrates has been shown to change specific behaviours. As a progenitor of brain–machine interfaces, neurofeedback has provided a novel way to investigate brain function and neuroplasticity. In this Review, we examine the mechanisms underlying neurofeedback, which have started to be uncovered. We also discuss how neurofeedback is being used in novel experimental and clinical paradigms from a multidisciplinary perspective, encompassing neuroscientific, neuroengineering and learning-science viewpoints.

Pathophysiological changes in the spinal cord white and grey matter resulting from injury can be observed with MRI techniques. These techniques provide sensitive markers of macrostructural and microstructural tissue integrity, which correlate with histological findings. Spinal cord MRI findings in traumatic spinal cord injury (tSCI) and nontraumatic spinal cord injury — the most common form of which is degenerative cervical myelopathy (DCM) — have provided important insights into the pathophysiological processes taking place not just at the focal injury site but also rostral and caudal to the spinal injury. Although tSCI and DCM have different aetiologies, they show similar degrees of spinal cord pathology remote from the injury site, suggesting the involvement of similar secondary degenerative mechanisms. Advanced quantitative MRI protocols that are sensitive to spinal cord pathology have the potential to improve diagnosis and, more importantly, predict outcomes in patients with tSCI or nontraumatic spinal cord injury. This Review describes the insights into tSCI and DCM that have been revealed by neuroimaging and outlines current activities and future directions for the field.

A fundamental tenet of neuroscience is that cortical functional differentiation is related to the cross-areal differences in cyto-, receptor-, and myeloarchitectonics that are observed in ex-vivo preparations. An ongoing challenge is to create noninvasive magnetic resonance (MR) imaging techniques that offer sufficient resolution, tissue contrast, accuracy and precision to allow for characterization of cortical architecture over an entire living human brain. One exciting development is the advent of fast, high-resolution quantitative mapping of basic MR parameters that reflect cortical myeloarchitecture. Here, we outline some of the theoretical and technical advances underlying this technique, particularly in terms of measuring and correcting for transmit and receive radio frequency field inhomogeneities. We also discuss new directions in analytic techniques, including higher resolution reconstructions of the cortical surface. We then discuss two recent applications of this technique. The first compares individual and group myelin maps to functional retinotopic maps in the same individuals, demonstrating a close relationship between functionally and myeloarchitectonically defined areal boundaries (as well as revealing an interesting disparity in a highly studied visual area). The second combines tonotopic and myeloarchitectonic mapping to localize primary auditory areas in individual healthy adults, using a similar strategy as combined electrophysiological and post-mortem myeloarchitectonic studies in non-human primates. •We present an overview of high-resolution quantitative R1 (1/T1) mapping techniques.•High R1 cortical areas colocalize with functionally defined highly myelinated areas.•In-vivo R1 maps give promising insights into individual anatomical differences.

In patients with chronic spinal cord injury, imaging of the spinal cord and brain above the level of the lesion provides evidence of neural degeneration; however, the spatial and temporal patterns of progression and their relation to clinical outcomes are uncertain. New interventions targeting acute spinal cord injury have entered clinical trials but neuroimaging outcomes as responsive markers of treatment have yet to be established. We aimed to use MRI to assess neuronal degeneration above the level of the lesion after acute spinal cord injury. In our prospective longitudinal study, we enrolled patients with acute traumatic spinal cord injury and healthy controls. We assessed patients clinically and by MRI at baseline, 2 months, 6 months, and 12 months, and controls by MRI at the same timepoints. We assessed atrophy in white matter in the cranial corticospinal tracts and grey matter in sensorimotor cortices by tensor-based analyses of T1-weighted MRI data. We used cross-sectional spinal cord area measurements to assess atrophy at cervical level C2/C3. We used myelin-sensitive magnetisation transfer (MT) and longitudinal relaxation rate (R1) maps to assess microstructural changes associated with myelin. We also assessed associations between MRI parameters and clinical improvement. All analyses of brain scans done with statistical parametric mapping were corrected for family-wise error. Between Sept 17, 2010, and Dec 31, 2012, we recruited 13 patients and 18 controls. In the 12 months from baseline, patients recovered by a mean of 5·27 points per log month (95% CI 1·91–8·63) on the international standards for the neurological classification of spinal cord injury (ISNCSCI) motor score (p=0·002) and by 10·93 points per log month (6·20–15·66) on the spinal cord independence measure (SCIM) score (p<0·0001). Compared with controls, patients showed a rapid decline in cross-sectional spinal cord area (patients declined by 0·46 mm per month compared with a stable cord area in controls; p<0·0001). Patients had faster rates than controls of volume decline of white matter in the cranial corticospinal tracts at the level of the internal capsule (right Z score 5·21, p=0·0081; left Z score 4·12, p=0·0004) and right cerebral peduncle (Z score 3·89, p=0·0302) and of grey matter in the left primary motor cortex (Z score 4·23, p=0·041). Volume changes were paralleled by significant reductions of MT and R1 in the same areas and beyond. Improvements in SCIM scores at 12 months were associated with a reduced loss in cross-sectional spinal cord area over 12 months (Pearson's correlation 0·77, p=0·004) and reduced white matter volume of the corticospinal tracts at the level of the right internal capsule (Z score 4·30, p=0·0021), the left internal capsule (Z score 4·27, p=0·0278), and left cerebral peduncle (Z score 4·05, p=0·0316). Improvements in ISNCSCI motor scores were associated with less white matter volume change encompassing the corticospinal tract at the level of the right internal capsule (Z score 4·01, p<0·0001). Extensive upstream atrophic and microstructural changes of corticospinal axons and sensorimotor cortical areas occur in the first months after spinal cord injury, with faster degenerative changes relating to poorer recovery. Structural volumetric and microstructural MRI protocols remote from the site of spinal cord injury could serve as neuroimaging biomarkers in acute spinal cord injury. SRH Holding, Swiss National Science Foundation, Clinical Research Priority Program “NeuroRehab” University of Zurich, Wellcome Trust.

Neuroscience and clinical researchers are increasingly interested in quantitative magnetic resonance imaging (qMRI) due to its sensitivity to micro-structural properties of brain tissue such as axon, myelin, iron and water concentration. We introduce the hMRI-toolbox, an open-source, easy-to-use tool available on GitHub, for qMRI data handling and processing, presented together with a tutorial and example dataset. This toolbox allows the estimation of high-quality multi-parameter qMRI maps (longitudinal and effective transverse relaxation rates R1 and R2⋆, proton density PD and magnetisation transfer MT saturation) that can be used for quantitative parameter analysis and accurate delineation of subcortical brain structures. The qMRI maps generated by the toolbox are key input parameters for biophysical models designed to estimate tissue microstructure properties such as the MR g-ratio and to derive standard and novel MRI biomarkers. Thus, the current version of the toolbox is a first step towards in vivo histology using MRI (hMRI) and is being extended further in this direction. Embedded in the Statistical Parametric Mapping (SPM) framework, it benefits from the extensive range of established SPM tools for high-accuracy spatial registration and statistical inferences and can be readily combined with existing SPM toolboxes for estimating diffusion MRI parameter maps. From a user's perspective, the hMRI-toolbox is an efficient, robust and simple framework for investigating qMRI data in neuroscience and clinical research. [Display omitted]

Dorsolateral prefrontal cortex (DLPFC) is recruited during visual working memory (WM) when relevant information must be maintained in the presence of distracting information. The mechanism by which DLPFC might ensure successful maintenance of the contents of WM is, however, unclear; it might enhance neural maintenance of memory targets or suppress processing of distracters. To adjudicate between these possibilities, we applied time-locked transcranial magnetic stimulation (TMS) during functional MRI, an approach that permits causal assessment of a stimulated brain region's influence on connected brain regions, and evaluated how this influence may change under different task conditions. Participants performed a visual WM task requiring retention of visual stimuli (faces or houses) across a delay during which visual distracters could be present or absent. When distracters were present, they were always from the opposite stimulus category, so that targets and distracters were represented in distinct posterior cortical areas. We then measured whether DLPFC-TMS, administered in the delay at the time point when distracters could appear, would modulate posterior regions representing memory targets or distracters. We found that DLPFC-TMS influenced posterior areas only when distracters were present and, critically, that this influence consisted of increased activity in regions representing the current memory targets. DLPFC-TMS did not affect regions representing current distracters. These results provide a new line of causal evidence for a top-down DLPFC-based control mechanism that promotes successful maintenance of relevant information in WM in the presence of distraction.

Functional magnetic resonance imaging (fMRI) studies that require high-resolution whole-brain coverage have long scan times that are primarily driven by the large number of thin slices acquired. Two-dimensional multiband echo-planar imaging (EPI) sequences accelerate the data acquisition along the slice direction and therefore represent an attractive approach to such studies by improving the temporal resolution without sacrificing spatial resolution. In this work, a 2D multiband EPI sequence was optimized for 1.5mm isotropic whole-brain acquisitions at 3T with 10 healthy volunteers imaged while performing simultaneous visual and motor tasks. The performance of the sequence was evaluated in terms of BOLD sensitivity and false-positive activation at multiband (MB) factors of 1, 2, 4, and 6, combined with in-plane GRAPPA acceleration of 2× (GRAPPA 2), and the two reconstruction approaches of Slice-GRAPPA and Split Slice-GRAPPA. Sensitivity results demonstrate significant gains in temporal signal-to-noise ratio (tSNR) and t-score statistics for MB 2, 4, and 6 compared to MB 1. The MB factor for optimal sensitivity varied depending on anatomical location and reconstruction method. When using Slice-GRAPPA reconstruction, evidence of false-positive activation due to signal leakage between simultaneously excited slices was seen in one instance, 35 instances, and 70 instances over the ten volunteers for the respective accelerations of MB 2×GRAPPA 2, MB 4×GRAPPA 2, and MB 6×GRAPPA 2. The use of Split Slice-GRAPPA reconstruction suppressed the prevalence of false positives significantly, to 1 instance, 5 instances, and 5 instances for the same respective acceleration factors. Imaging protocols using an acceleration factor of MB 2×GRAPPA 2 can be confidently used for high-resolution whole-brain imaging to improve BOLD sensitivity with very low probability for false-positive activation due to slice leakage. Imaging protocols using higher acceleration factors (MB 3 or MB 4×GRAPPA 2) can likely provide even greater gains in sensitivity but should be carefully optimized to minimize the possibility of false activations. •MB factors 1, 2, 4, and 6 and two reconstructions were evaluated for fMRI performance.•MB accelerations 2, 4, and 6 improved BOLD sensitivity metrics over MB 1.•False-positive activation due to signal leakage was seen at high accelerations.•Use of Split Slice-GRAPPA reconstruction significantly reduces false positives.