Disambiguating the role of blood flow and global signal with partial information decomposition

Global signal (GS) is an ubiquitous construct in resting state functional magnetic resonance imaging (rs-fMRI), associated to nuisance, but containing by definition most of the neuronal signal. Global signal regression (GSR) effectively removes the impact of physiological noise and other artifacts, but at the same time it alters correlational patterns in unpredicted ways. Performing GSR taking into account the underlying physiology (mainly the blood arrival time) has been proven to be beneficial. From these observations we aimed to: 1) characterize the effect of GSR on network-level functional connectivity in a large dataset; 2) assess the complementary role of global signal and vessels; and 3) use the framework of partial information decomposition to further look into the joint dynamics of the global signal and vessels, and their respective influence on the dynamics of cortical areas. We observe that GSR affects intrinsic connectivity networks in the connectome in a non-uniform way. Furthermore, by estimating the predictive information of blood flow and the global signal using partial information decomposition, we observe that both signals are present in different amounts across intrinsic connectivity networks. Simulations showed that differences in blood arrival time can largely explain this phenomenon, while using hemodynamic and calcium mouse recordings we were able to confirm the presence of vascular effects, as calcium recordings lack hemodynamic information. With these results we confirm network-specific effects of GSR and the importance of taking blood flow into account for improving de-noising methods. Additionally, and beyond the mere issue of data denoising, we quantify the diverse and complementary effect of global and vessel BOLD signals on the dynamics of cortical areas

Respiratory challenge MRI: practical aspects

Respiratory challenge MRI is the modification of arterial oxygen (PaO2) and/or carbon dioxide (PaCO2) concentration to induce a change in cerebral function or metabolism which is then measured by MRI. Alterations in arterial gas concentrations can lead to profound changes in cerebral haemodynamics which can be studied using a variety of MRI sequences. Whilst such experiments may provide a wealth of information, conducting them can be complex and challenging. In this paper we review the rationale for respiratory challenge MRI including the effects of oxygen and carbon dioxide on the cerebral circulation. We also discuss the planning, equipment, monitoring and techniques that have been used to undertake these experiments. We finally propose some recommendations in this evolving area for conducting these experiments to enhance data quality and comparison between techniques

New insights into the impact of neuro-inflammation in rheumatoid arthritis.

Rheumatoid arthritis (RA) is considered to be, in many respects, an archetypal autoimmune disease that causes activation of pro-inflammatory pathways resulting in joint and systemic inflammation. RA remains a major clinical problem with the development of several new therapies targeted at cytokine inhibition in recent years. In RA, biologic therapies targeted at inhibition of tumor necrosis factor alpha (TNFα) have been shown to reduce joint inflammation, limit erosive change, reduce disability and improve quality of life. The cytokine TNFα has a central role in systemic RA inflammation and has also been shown to have pro-inflammatory effects in the brain. Emerging data suggests there is an important bidirectional communication between the brain and immune system in inflammatory conditions like RA. Recent work has shown how TNF inhibitor therapy in people with RA is protective for Alzheimer's disease. Functional MRI studies to measure brain activation in people with RA to stimulus by finger joint compression, have also shown that those who responded to TNF inhibition showed a significantly greater activation volume in thalamic, limbic, and associative areas of the brain than non-responders. Infections are the main risk of therapies with biologic drugs and infections have been shown to be related to disease flares in RA. Recent basic science data has also emerged suggesting that bacterial components including lipopolysaccharide induce pain by directly activating sensory neurons that modulate inflammation, a previously unsuspected role for the nervous system in host-pathogen interactions. In this review, we discuss the current evidence for neuro-inflammation as an important factor that impacts on disease persistence and pain in RA

Separating vascular and neuronal effects of age on fMRI BOLD signals.

Accurate identification of brain function is necessary to understand the neurobiology of cognitive ageing, and thereby promote well-being across the lifespan. A common tool used to investigate neurocognitive ageing is functional magnetic resonance imaging (fMRI). However, although fMRI data are often interpreted in terms of neuronal activity, the blood oxygenation level-dependent (BOLD) signal measured by fMRI includes contributions of both vascular and neuronal factors, which change differentially with age. While some studies investigate vascular ageing factors, the results of these studies are not well known within the field of neurocognitive ageing and therefore vascular confounds in neurocognitive fMRI studies are common. Despite over 10 000 BOLD-fMRI papers on ageing, fewer than 20 have applied techniques to correct for vascular effects. However, neurovascular ageing is not only a confound in fMRI, but an important feature in its own right, to be assessed alongside measures of neuronal ageing. We review current approaches to dissociate neuronal and vascular components of BOLD-fMRI of regional activity and functional connectivity. We highlight emerging evidence that vascular mechanisms in the brain do not simply control blood flow to support the metabolic needs of neurons, but form complex neurovascular interactions that influence neuronal function in health and disease. This article is part of the theme issue 'Key relationships between non-invasive functional neuroimaging and the underlying neuronal activity'.This work is supported by the British Academy (PF160048), the Guarantors of Brain (G101149), the Wellcome Trust (103838), the Medical Research Council (SUAG/051 G101400; and SUAG/046 G101400), European Union’s Horizon 2020 (732592) and the Cambridge NIHR Biomedical Research Centre

Systemic physiology augmented functional near-infrared spectroscopy: a powerful approach to study the embodied human brain.

In this Outlook paper, we explain why an accurate physiological interpretation of functional near-infrared spectroscopy (fNIRS) neuroimaging signals is facilitated when systemic physiological activity (e.g., cardiorespiratory and autonomic activity) is measured simultaneously by employing systemic physiology augmented functional near-infrared spectroscopy (SPA-fNIRS). The rationale for SPA-fNIRS is twofold: (i) SPA-fNIRS enables a more complete interpretation and understanding of the fNIRS signals measured at the head since they contain components originating from neurovascular coupling and from systemic physiological sources. The systemic physiology signals measured with SPA-fNIRS can be used for regressing out physiological confounding components in fNIRS signals. Misinterpretations can thus be minimized. (ii) SPA-fNIRS enables to study the embodied brain by linking the brain with the physiological state of the entire body, allowing novel insights into their complex interplay. We envisage the SPA-fNIRS approach will become increasingly important in the future

False positives and false negatives in functional near-infrared spectroscopy: issues, challenges, and the way forward

We highlight a significant problem that needs to be considered and addressed when performing functional near-infrared spectroscopy (fNIRS) studies, namely the possibility of inadvertently measuring fNIRS hemodynamic responses that are not due to neurovascular coupling. These can be misinterpreted as brain activity, i.e., "false positives" (errors caused by wrongly assigning a detected hemodynamic response to functional brain activity), or mask brain activity, i.e., "false negatives" (errors caused by wrongly assigning a not observed hemodynamic response in the presence of functional brain activity). Here, we summarize the possible physiological origins of these issues and suggest ways to avoid and remove them

Neuroimaging Biomarkers and Cognitive Function in Non-CNS Cancer and Its Treatment: Current Status and Recommendations for Future Research

Cognitive changes in patients undergoing treatment for non-central nervous system (CNS) cancers have been recognized for several decades, yet the underlying mechanisms are not well understood. Structural, functional and molecular neuroimaging has the potential to help clarify the neural bases of these cognitive abnormalities. Structural magnetic resonance imaging (MRI), functional MRI (fMRI), diffusion tensor imaging (DTI), MR spectroscopy (MRS), and positron emission tomography (PET) have all been employed in the study of cognitive effects of cancer treatment, with most studies focusing on breast cancer and changes thought to be induced by chemotherapy. Articles in this special issue of Brain Imaging and Behavior are devoted to neuroimaging studies of cognitive changes in patients with non-CNS cancer and include comprehensive critical reviews and novel research findings. The broad conclusions that can be drawn from past studies and the present body of new research is that there are structural and functional changes associated with cancer and various treatments, particularly systemic cytotoxic chemotherapy, although some cognitive and fMRI studies have identified changes at pre-treatment baseline. Recommendations to accelerate progress include well-powered multicenter neuroimaging studies, a better standardized definition of the cognitive phenotype and extension to other cancers. A systems biology framework incorporating multimodality neuroimaging, genetics and other biomarkers will be highly informative regarding individual differences in risk and protective factors and disease- and treatment-related mechanisms. Studies of interventions targeting cognitive changes are also needed. These next steps are expected to identify novel protective strategies and facilitate a more personalized medicine for cancer patients

Mid-term effects of carotid endarterectomy on cognition and white matter status evaluated by whole brain diffusion tensor imaging metrics: A preliminary analysis

Purpose: To analyze the mid-term (12 months) effects of carotid endarterectomy (CEA) on cognition and on the microstructural properties of the whole brain white matter in terms of derived diffusion Tensor imaging (DTI) metrics. Methods: We analyzed a population of 19 asymptomatic patients with extra-cranial internal carotid artery stenosis (eICA) eligible for CEA. All patients underwent cognitive evaluation with the Italian version of the Mini-Mental State Examination corrected for age and schooling, and with a Magnetic Resonance Imaging (MRI) investigation on a 1.5 Tesla MRI scanner, that included a 34-directions Diffusion Weighted Imaging (DWI) sequence for DTI metrics analysis. The global fractional anisotropy (gFA), global mean diffusivity (gMD), global radial diffusivity (gRD) and global axial diffusivity (gAD) were calculated for each patient. Both the cognitive and the imaging evaluation were performed at baseline (PRE-CEA) and 12 months after CEA (POST-CEA). Two-tailed Paerson's correlation test and paired samples t-test were used for evaluating the correlation between PRE-CEA and POST-CEA values, adopting a p-value of <0.05 as statistically significant. Results: A statistically significant increase of the MMSE scores (p < 0.0001), as well as for gFA (p < 0.0001), and a statistically significant reduction of gMD (p = 0.027) and gRD (p = 0.0005) was observed 12 months following uncomplicated CEA. Conclusions: These findings suggest that CEA is associated with a general improvement of the WM microstructure of the whole brain