The gut protist Tritrichomonas arnold restrains virus-mediated loss of oral tolerance by modulating dietary antigen-presenting dendritic cells.

Loss of oral tolerance (LOT) to gluten, driven by dendritic cell (DC) priming of gluten-specific T helper 1 (Th1) cell immune responses, is a hallmark of celiac disease (CeD) and can be triggered by enteric viral infections. Whether certain commensals can moderate virus-mediated LOT remains elusive. Here, using a mouse model of virus-mediated LOT, we discovered that the gut-colonizing protist Tritrichomonas (T.) arnold promotes oral tolerance and protects against reovirus- and murine norovirus-mediated LOT, independent of the microbiota. Protection was not attributable to antiviral host responses or T. arnold-mediated innate type 2 immunity. Mechanistically, T. arnold directly restrained the proinflammatory program in dietary antigen-presenting DCs, subsequently limiting Th1 and promoting regulatory T cell responses. Finally, analysis of fecal microbiomes showed that T. arnold-related Parabasalid strains are underrepresented in human CeD patients. Altogether, these findings will motivate further exploration of oral-tolerance-promoting protists in CeD and other immune-mediated food sensitivities.

Dietary tryptophan metabolite released by intratumoral Lactobacillus reuteri facilitates immune checkpoint inhibitor treatment.

The use of probiotics by cancer patients is increasing, including among those undergoing immune checkpoint inhibitor (ICI) treatment. Here, we elucidate a critical microbial-host crosstalk between probiotic-released aryl hydrocarbon receptor (AhR) agonist indole-3-aldehyde (I3A) and CD8 T cells within the tumor microenvironment that potently enhances antitumor immunity and facilitates ICI in preclinical melanoma. Our study reveals that probiotic Lactobacillus reuteri (Lr) translocates to, colonizes, and persists within melanoma, where via its released dietary tryptophan catabolite I3A, it locally promotes interferon-γ-producing CD8 T cells, thereby bolstering ICI. Moreover, Lr-secreted I3A was both necessary and sufficient to drive antitumor immunity, and loss of AhR signaling within CD8 T cells abrogated Lr's antitumor effects. Further, a tryptophan-enriched diet potentiated both Lr- and ICI-induced antitumor immunity, dependent on CD8 T cell AhR signaling. Finally, we provide evidence for a potential role of I3A in promoting ICI efficacy and survival in advanced melanoma patients.

Anaerobic digestion as a tool to manage eutrophication and associated greenhouse gas emission.

Eutrophicated inland water bodies are noticed to be one of the contributing factors to greenhouse gas (GHGs) emissions. Direct discharge of untreated or partially treated water is a major concern. Microalgae-based technology and management are regarded as one of the potential nature-based approaches to combat eutrophication. In turn, the microalgae facilitate the recovery of GHGs contributing compounds in the form of organic biomass. The recovered algal biomass can be harnessed for the production of biofuels and other bio-products, like biofertilizer, using anaerobic digestion. By virtue, circular bio-economy can be achieved alongside mitigating GHGs emissions. Before implementing, it is vital to thoroughly explore the links between the process and potential alternatives for wastewater treatment, waste valorization, biofuel production, and land usage. Thus, the present review discusses the impact of eutrophication on ecology and environment, current technologies for mitigating eutrophication and GHGs, and energy recovery through the anaerobic digestion of algal biomass. Further, the processes at the intercept of wastewater treatment and biogas production were reviewed to leverage the potential of anaerobic digestion for making a circular bioeconomy framework.

A real-time fMRI neurofeedback system for the clinical alleviation of depression with a subject-independent classification of brain states: A proof of principle study.

Most clinical neurofeedback studies based on functional magnetic resonance imaging use the patient's own neural activity as feedback. The objective of this study was to create a subject-independent brain state classifier as part of a real-time fMRI neurofeedback (rt-fMRI NF) system that can guide patients with depression in achieving a healthy brain state, and then to examine subsequent clinical changes. In a first step, a brain classifier based on a support vector machine (SVM) was trained from the neural information of happy autobiographical imagery and motor imagery blocks received from a healthy female participant during an MRI session. In the second step, 7 right-handed female patients with mild or moderate depressive symptoms were trained to match their own neural activity with the neural activity corresponding to the "happiness emotional brain state" of the healthy participant. The training (4 training sessions over 2 weeks) was carried out using the rt-fMRI NF system guided by the brain-state classifier we had created. Thus, the informative voxels previously obtained in the first step, using SVM classification and Effect Mapping, were used to classify the Blood-Oxygen-Level Dependent (BOLD) activity of the patients and converted into real-time visual feedback during the neurofeedback training runs. Improvements in the classifier accuracy toward the end of the training were observed in all the patients [Session 4-1 Median = 6.563%; Range = 4.10-27.34; Wilcoxon Test (0), 2-tailed p = 0.031]. Clinical improvement also was observed in a blind standardized clinical evaluation [HDRS CE2-1 Median = 7; Range 2 to 15; Wilcoxon Test (0), 2-tailed p = 0.016], and in self-report assessments [BDI-II CE2-1 Median = 8; Range 1-15; Wilcoxon Test (0), 2-tailed p = 0.031]. In addition, the clinical improvement was still present 10 days after the intervention [BDI-II CE3-2_Median = 0; Range -1 to 2; Wilcoxon Test (0), 2-tailed p = 0.50/ HDRS CE3-2 Median = 0; Range -1 to 2; Wilcoxon Test (0), 2-tailed p = 0.625]. Although the number of participants needs to be increased and a control group included to confirm these findings, the results suggest a novel option for neural modulation and clinical alleviation in depression using noninvasive stimulation technologies.

Tet2 deficiency drives liver microbiome dysbiosis triggering Tc1 cell autoimmune hepatitis.

The triggers that drive interferon-γ (IFNγ)-producing CD8 T cell (Tc1 cell)-mediated autoimmune hepatitis (AIH) remain obscure. Here, we show that lack of hematopoietic Tet methylcytosine dioxygenase 2 (Tet2), an epigenetic regulator associated with autoimmunity, results in the development of microbiota-dependent AIH-like pathology, accompanied by hepatic enrichment of aryl hydrocarbon receptor (AhR) ligand-producing pathobionts and rampant Tc1 cell immunity. We report that AIH-like disease development is dependent on both IFNγ and AhR signaling, as blocking either reverts ongoing AIH-like pathology. Illustrating the critical role of AhR-ligand-producing pathobionts in this condition, hepatic translocation of the AhR ligand indole-3-aldehyde (I3A)-releasing Lactobacillus reuteri is sufficient to trigger AIH-like pathology. Finally, we demonstrate that I3A is required for L. reuteri-induced Tc1 cell differentiation in vitro and AIH-like pathology in vivo, both of which are restrained by Tet2 within CD8 T cells. This AIH-disease model may contribute to the development of therapeutics to alleviate AIH.

Mixotrophic microalgal-biofilm reactor augmenting biomass and biofuel productivity.

The present work aimed to evaluate the mixotrophic growth of Chlorella pyrenoidosa in a microalgal-biofilm reactor (MBR) using waste glycerol as an organic carbon source. The biomass productivity of C. pyrenoidosa (10.14 g m-2 d-1) under the mixotrophic mode was remarkably higher than that observed during the phototrophic mode (4.16 g m-2 d-1), under similar incubation conditions. The hydraulic retention time (HRT) of 6 d was found optimal for the higher productivity of microalgae in the MBR. Notably, based on biofuel quality, mixotrophically grown microalgal biomass was noted to have better suitability for biomethane production compared to biodiesel. Besides, up to 98.09, 75.74, and 55.86% removal of phosphate, nitrate, and COD, respectively, was recorded within 6 d under mixotrophic growth. Overall, the present findings magnificently demonstrate the efficient recycling of waste glycerol for higher biomass production coupled with phycoremediation using mixotrophic MBR.

Non-Invasive Functional Evaluation of the Human Spinal Cord by Assessing the Peri-Spinal Neurovascular Network With Near Infrared Spectroscopy.

Current medical care lacks an effective functional evaluation for the spinal cord. Magnetic resonance imaging and computed tomography mainly provide structural information of the spinal cord, while spinal somatosensory evoked potentials are limited by a low signal to noise ratio. We developed a non-invasive approach based on near-infrared spectroscopy in dual-wavelength (760 and 850 nm for deoxy- or oxyhemoglobin respectively) to record the neurovascular response (NVR) of the peri-spinal vascular network at the 7th cervical and 10th thoracic vertebral levels of the spinal cord, triggered by unilateral median nerve electrical stimulation (square pulse, 5-10 mA, 5 ms, 1 pulse every 4 minutes) at the wrist. Amplitude, rise-time, and duration of NVR were characterized in 20 healthy participants. A single, painless stimulus was able to elicit a high signal-to-noise ratio and multi-segmental NVR (mainly from Oxyhemoglobin) with a fast rise time of 6.18 [4.4-10.4] seconds (median [Percentile 25-75]) followed by a slow decay phase for about 30 seconds toward the baseline. Cervical NVR was earlier and larger than thoracic and no left/right asymmetry was detected. Stimulus intensity/NVR amplitude fitted to a 2nd order function. The characterization and feasibility of the peri-spinal NVR strongly support the potential clinical applications for a functional assessment of spinal cord lesions.

Weighted neurofeedback facilitates greater self-regulation of functional connectivity between the primary motor area and cerebellum.

Objective.Brain-computer interface (BCI) is a tool that can be used to train brain self-regulation and influence specific activity patterns, including functional connectivity, through neurofeedback. The functional connectivity of the primary motor area (M1) and cerebellum play a critical role in motor recovery after a brain injury, such as stroke. The objective of this study was to determine the feasibility of achieving control of the functional connectivity between M1 and the cerebellum in healthy subjects. Additionally, we aimed to compare the brain self-regulation of two different feedback modalities and their effects on motor performance.Approach.Nine subjects were trained with a real-time functional magnetic resonance imaging BCI system. Two groups were conformed: equal feedback group (EFG), which received neurofeedback that weighted the contribution of both regions of interest (ROIs) equally, and weighted feedback group (WFG) that weighted each ROI differentially (30% cerebellum; 70% M1). The magnitude of the brain activity induced by self-regulation was evaluated with the blood-oxygen-level-dependent (BOLD) percent change (BPC). Functional connectivity was assessed using temporal correlations between the BOLD signal of both ROIs. A finger-tapping task was included to evaluate the effect of brain self-regulation on motor performance.Main results.A comparison between the feedback modalities showed that WFG achieved significantly higher BPC in M1 than EFG. The functional connectivity between ROIs during up-regulation in WFG was significantly higher than EFG. In general, both groups showed better tapping speed in the third session compared to the first. For WFG, there were significant correlations between functional connectivity and tapping speed.Significance.The results show that it is possible to train healthy individuals to control M1-cerebellum functional connectivity with rtfMRI-BCI. Besides, it is also possible to use a weighted feedback approach to facilitate a higher activity of one region over another.

Four methods of brain pattern analyses of fMRI signals associated with wrist extension versus wrist flexion studied for potential use in future motor learning BCI.

OBJECTIVE: In stroke survivors, a treatment-resistant problem is inability to volitionally differentiate upper limb wrist extension versus flexion. When one intends to extend the wrist, the opposite occurs, wrist flexion, rendering the limb non-functional. Conventional therapeutic approaches have had limited success in achieving functional recovery of patients with chronic and severe upper extremity impairments. Functional magnetic resonance imaging (fMRI) neurofeedback is an emerging strategy that has shown potential for stroke rehabilitation. There is a lack of information regarding unique blood-oxygenation-level dependent (BOLD) cortical activations uniquely controlling execution of wrist extension versus uniquely controlling wrist flexion. Therefore, a first step in providing accurate neural feedback and training to the stroke survivor is to determine the feasibility of classifying (or differentiating) brain activity uniquely associated with wrist extension from that of wrist flexion, first in healthy adults. APPROACH: We studied brain signal of 10 healthy adults, who performed wrist extension and wrist flexion during fMRI data acquisition. We selected four types of analyses to study the feasibility of differentiating brain signal driving wrist extension versus wrist flexion, as follows: 1) general linear model (GLM) analysis; 2) support vector machine (SVM) classification; 3) 'Winner Take All'; and 4) Relative Dominance. RESULTS: With these four methods and our data, we found that few voxels were uniquely active during either wrist extension or wrist flexion. SVM resulted in only minimal classification accuracies. There was no significant difference in activation magnitude between wrist extension versus flexion; however, clusters of voxels showed extension signal > flexion signal and other clusters vice versa. Spatial patterns of activation differed among subjects. SIGNIFICANCE: We encountered a number of obstacles to obtaining clear group results in healthy adults. These obstacles included the following: high variability across healthy adults in all measures studied; close proximity of uniquely active voxels to voxels that were common to both the extension and flexion movements; in general, higher magnitude of signal for the voxels common to both movements versus the magnitude of any given uniquely active voxel for one type of movement. Our results indicate that greater precision in imaging will be required to develop a truly effective method for differentiating wrist extension versus wrist flexion from fMRI data.

Enzymatic pretreatment of algal biomass has different optimal conditions for biogas and bioethanol routes.

Enzymatic pretreatment is emerging as an efficient tool for the extraction of biofuel precursors from algal biomass. However, yardsticks for end-use directed selection of optimal pretreatment conditions are not yet identified. The present study, for the first time, reveals different optimal conditions for algal biomass solubilization and sugar release. Algal biomass pretreatment optimization was carried out using the Taguchi method. Crude enzyme from Aspergillus fischeri was found effective for pretreatment of Chlorella pyrenoidosa. Maximum sugar yield (190 mg g-1 biomass) from algal biomass was observed at a substrate concentration of 4 g L-1, with a 5% enzyme load at temperature 60°C, pH 5.5, and shaking speed of 80 rpm. In contrast, maximum sCOD (1350 mg g-1 biomass) was obtained at 2 g L-1 substrate concentration with enzyme load of 20% v/v, at 60°C, pH 4, and shaking speed of 100 rpm. Hence, the first set of conditions would be more beneficial for bioethanol production. Whereas another set of conditions would improve the biofuel production that requires maximum solubilization of algal biomass, such as fermentative methane production. Overall, the present observations established that process conditions required for enzymatic pretreatment of algal biomass should be selected according to the desired biofuel type.

Pallidal Connectivity Profiling of Stimulation-Induced Dyskinesia in Parkinson's Disease.

OBJECTIVES: The aim of this study is to identify anatomical regions related to stimulation-induced dyskinesia (SID) after pallidal deep brain stimulation (DBS) in Parkinson's disease (PD) patients and to analyze connectivity associated with SID. METHODS: This retrospective study analyzed the clinical and imaging data of PD patients who experienced SID during the monopolar review after pallidal DBS. We analyzed structural and functional connectivity using normative connectivity data with the volume of tissue activated (VTA) modeling. Each contact was assigned to either that producing SID (SID VTA) or that without SID (non-SID VTA). Structural and functional connectivity was compared between SID and non-SID VTAs. "Optimized VTAs" were also estimated using the DBS settings at 6 months after implantation. RESULTS: Of the 68 consecutive PD patients who underwent pallidal implantation, 20 patients (29%) experienced SID. SID VTAs were located more dorsally and anteriorly compared with non-SID and optimized VTAs and were primarily in the dorsal globus pallidus internus (GPi) and dorsal globus pallidus externus (GPe). SID VTAs showed significantly higher structural connectivity than non-SID VTAs to the associative cortex and supplementary motor area/premotor cortex (P < 0.0001). Simultaneously, non-SID VTAs showed greater connectivity to the primary sensory cortex, cerebellum, subthalamic nucleus, and motor thalamus (all P < 0.0004). Functional connectivity analysis showed significant differences between SID and non-SID VTAs in multiple regions, including the primary motor, premotor, and prefrontal cortices and cerebellum. CONCLUSION: SID VTAs were primarily in the dorsal GPi/GPe. The connectivity difference between the motor-related cortices and subcortical regions may explain the presence and absence of SID. © 2020 International Parkinson and Movement Disorder Society.

New insights on improved growth and biogas production potential of Chlorella pyrenoidosa through intermittent iron oxide nanoparticle supplementation.

In the present work, the effect of α-Fe2O3-nanoparticles (IONPs) supplementation at varying doses (0, 10, 20 and, 30 mg L-1) at the intermittent stage (after 12th day of growth period) was studied on the growth and biogas production potential of Chlorella pyrenoidosa. Significant enhancements in microalgae growth were observed with all the tested IONPs doses, the highest (2.94 ± 0.01 g L-1) being at 20 mg L-1. Consequently, the composition of the biomass was also improved. Based on the precedent determinations, theoretical chemical oxygen demand (CODth) as well as theoretical and stoichiometric methane potential (TMP, and SMP) were also estimated. The CODth, TMP, SMP values indicated IONPs efficacy for improving biogas productivity. Further, the biochemical methane potential (BMP) test was done for IONPs supplemented biomass. The BMP test revealed up to a 25.14% rise in biogas yield (605 mL g-1 VSfed) with 22.4% enhanced methane content for 30 mg L-1 IONPs supplemented biomass over control. Overall, at 30 mg L-1 IONPs supplementation, the cumulative enhancements in biomass, biogas, and methane content proffered a net rise of 98.63% in biomethane potential (≈ 2.86 × 104 m3 ha-1 year-1) compared to control. These findings reveal the potential of IONPs in improving microalgal biogas production.

Use of Real-Time Functional Magnetic Resonance Imaging-Based Neurofeedback to Downregulate Insular Cortex in Nicotine-Addicted Smokers.

It has been more than a decade since the first functional magnetic resonance imaging (fMRI)-based neurofeedback approach was successfully implemented. Since then, various studies have demonstrated that participants can learn to voluntarily control a circumscribed brain region. Consequently, real-time fMRI (rtfMRI) provided a novel opportunity to study modifications of behavior due to manipulation of brain activity. Hence, reports of rtfMRI applications to train self-regulation of brain activity and the concomitant modifications in behavioral and clinical conditions such as neurological and psychiatric disorders [e.g., schizophrenia, obsessive compulsive Disorder (OCD), stroke] have rapidly increased. Neuroimaging studies in addiction research have shown that the anterior cingulate cortex, orbitofrontal cortex, and insular cortex are activated during the presentation of drug-associated cues. Also, activity in both left and right insular cortices have been shown to be highly correlated with drug urges when participants are exposed to craving-eliciting cues. Hence, the bilateral insula is of particular importance in researching drug urges and addiction due to its role in the representation of bodily (interoceptive) states. This study explores the use of rtfMRI neurofeedback for the reduction in blood oxygen-level dependent (BOLD) activity in bilateral insular cortices of nicotine-addicted participants. The study also tests if there are neurofeedback training-associated modifications in the implicit attitudes of participants towards nicotine-craving cues and explicit-craving behavior.

Author Correction: Closed-loop brain training: the science of neurofeedback.

In this article, the affiliation for Mohit Rana was incorrectly listed as the Institute for Biological and Medical Engineering, Department of Psychiatry, and Section of Neuroscience, Pontificia Universidad Católica de Chile, Vicuña Mackenna 4860 Hernán Briones, piso 2, Macul 782-0436, Santiago, Chile. The listed affiliation should have been the following: Departamento de Psiquiatría, Escuela de Medicina, Centro Interdisciplinario de Neurociencias, Pontificia Universidad Católica de Chile, Santiago, Chile; and the Laboratory for Brain-Machine Interfaces and Neuromodulation, Pontificia Universidad Católica de Chile, Santiago, Chile. An acknowledgement to Mohit Rana's funding source was also missing. The following sentence should have been included in the acknowledgments section: M.R. is supported by a Fondecyt postdoctoral fellowship (project no. 3100648).

Self-Regulation of the Fusiform Face Area in Autism Spectrum: A Feasibility Study With Real-Time fMRI Neurofeedback.

One of the most important and early impairments in autism spectrum disorder (ASD) is the abnormal visual processing of human faces. This deficit has been associated with hypoactivation of the fusiform face area (FFA), one of the main hubs of the face-processing network. Neurofeedback based on real-time fMRI (rtfMRI-NF) is a technique that allows the self-regulation of circumscribed brain regions, leading to specific neural modulation and behavioral changes. The aim of the present study was to train participants with ASD to achieve up-regulation of the FFA using rtfMRI-NF, to investigate the neural effects of FFA up-regulation in ASD. For this purpose, three groups of volunteers with normal I.Q. and fluent language were recruited to participate in a rtfMRI-NF protocol of eight training runs in 2 days. Five subjects with ASD participated as part of the experimental group and received contingent feedback to up-regulate bilateral FFA. Two control groups, each one with three participants with typical development (TD), underwent the same protocol: one group with contingent feedback and the other with sham feedback. Whole-brain and functional connectivity analysis using each fusiform gyrus as independent seeds were carried out. The results show that individuals with TD and ASD can achieve FFA up-regulation with contingent feedback. RtfMRI-NF in ASD produced more numerous and stronger short-range connections among brain areas of the ventral visual stream and an absence of the long-range connections to insula and inferior frontal gyrus, as observed in TD subjects. Recruitment of inferior frontal gyrus was observed in both groups during FAA up-regulation. However, insula and caudate nucleus were only recruited in subjects with TD. These results could be explained from a neurodevelopment perspective as a lack of the normal specialization of visual processing areas, and a compensatory mechanism to process visual information of faces. RtfMRI-NF emerges as a potential tool to study visual processing network in ASD, and to explore its clinical potential.

Role of oxidative stress, infection and inflammation in male infertility.

Oxidative stress (OS), defined as an overabundance of reactive oxygen species (ROS) or a deficiency of antioxidants, has been linked to sperm damage and male infertility. There are many sources of OS and inflammation including varicocele, tobacco usage, alcohol, obesity/metabolic syndrome, leukocytospermia, sexually transmitted disease (i.e., Neisseria gonorrhoeae, Chlamydia trachomatis, Treponema pallidum), bacterial prostatitis, microorganism mutations leading to more OS, and viral infections (i.e., human immunodeficiency virus, hepatitis). This review is focusing on infection and inflammation-mediated OS, the inflammatory markers underlying pathology, clinical significance in male infertility, and a brief description of the recommended treatment modalities.

Modelling studies for photocatalytic degradation of organic dyes using TiO2 nanofibers.

In this work, modelling of the photocatalytic degradation of para-nitrophenol (PNP) using synthesized electrospun TiO2 nanofibers under UV light illumination is reported. A dynamic model was developed in order to understand the behaviour of operating parameters, i.e. light intensity and catalyst loading on the photocatalytic activity. This model was simulated and analysed for both TiO2 solid nanofibers and TiO2 hollow nanofibers, applied as photocatalysts in the Langmuir-Hinshelwood kinetic framework. The entire photocatalytic degradation rate follows pseudo-first-order kinetics. The simulated results obtained from the developed model are in good agreement with the experimental results. At a catalyst loading of 1.0 mg mL-1, better respective degradation rates were achieved at UV light irradiance of 4 mW cm-2, for both the TiO2 solid and hollow nanofibers. However, it was also observed that TiO2 hollow nanofibers have a higher adsorption rate than that of TiO2 solid nanofibers resulting in a higher photocatalytic degradation rate of PNP.

Closed-loop brain training: the science of neurofeedback.

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.

Real-Time fMRI in Neuroscience Research and Its Use in Studying the Aging Brain.

Cognitive decline is a major concern in the aging population. It is normative to experience some deterioration in cognitive abilities with advanced age such as related to memory performance, attention distraction to interference, task switching, and processing speed. However, intact cognitive functioning in old age is important for leading an independent day-to-day life. Thus, studying ways to counteract or delay the onset of cognitive decline in aging is crucial. The literature offers various explanations for the decline in cognitive performance in aging; among those are age-related gray and white matter atrophy, synaptic degeneration, blood flow reduction, neurochemical alterations, and change in connectivity patterns with advanced age. An emerging literature on neurofeedback and Brain Computer Interface (BCI) reports exciting results supporting the benefits of volitional modulation of brain activity on cognition and behavior. Neurofeedback studies based on real-time functional magnetic resonance imaging (rtfMRI) have shown behavioral changes in schizophrenia and behavioral benefits in nicotine addiction. This article integrates research on cognitive and brain aging with evidence of brain and behavioral modification due to rtfMRI neurofeedback. We offer a state-of-the-art description of the rtfMRI technique with an eye towards its application in aging. We present preliminary results of a feasibility study exploring the possibility of using rtfMRI to train older adults to volitionally control brain activity. Based on these first findings, we discuss possible implementations of rtfMRI neurofeedback as a novel technique to study and alleviate cognitive decline in healthy and pathological aging.

Correction: Real-Time Subject-Independent Pattern Classification of Overt and Covert Movements from fNIRS Signals.

[This corrects the article DOI: 10.1371/journal.pone.0159959.].