Real-time Magnetic Resonance Imaging Research Articles

Sound source locations and their roles in Japanese voiceless "glottal" fricative production.

Although [h] is described as a glottal fricative, it has never been demonstrated whether [h] has its source exclusively at the glottis. In this study, sound source locations and their influence on sound amplitudes were investigated by conducting mechanical experiments and airflow simulations. Vocal tract data of [h] were obtained in three phonemic contexts from two native Japanese subjects using three-dimensional static magnetic resonance imaging (MRI). Acrylic vocal tract replicas were constructed, and the sound was reproduced by supplying airflow to the vocal tracts with adducted or abducted vocal folds. The sound source locations were estimated by solving the Navier-Stokes equations. The results showed that the amplitudes of sounds produced by the vocal tracts with an open glottis were in a similar range (±3 dB) to those with a glottal gap of 3 mm in some contexts. The sound sources in these cases were observed in the pharyngeal cavity or near the soft palate. Similar degrees of oral constrictions were observed in the real-time MRI, indicating that the sound traditionally described as [h] is produced, at least in some contexts, with sound sources of turbulent flow generated by a supralaryngeal constriction of the following vowel.

Online self-evaluation of fMRI-based neurofeedback performance.

This study explores the subjective evaluation of supplementary motor area (SMA) regulation performance in a real-time functional magnetic resonance imaging neurofeedback (fMRI-NF) task. In fMRI-NF, people learn how to self-regulate their brain activity by performing mental actions to achieve a certain target level (TL) of blood-oxygen-level-dependent (BOLD) activation. Here, we studied two types of self-evaluation: performance predictions and perceived confidence in the prediction judgement. Participants completed three sessions of SMA regulation in a 7 T fMRI scanner, performing a mental drawing task. During each trial, they modulated their imagery strategy to achieve one of two different levels of SMA activation and reported a performance prediction and their confidence in the prediction before receiving delayed BOLD-activation feedback. Results show that participants' performance predictions improved with learning throughout the three sessions, and that these improvements were not driven exclusively by their knowledge of previous performance. Confidence reports on the other hand showed no change throughout training and did not correlate with better and worse predictions. In addition to shedding light on mechanisms of internal self-evaluation during neurofeedback training, these results also point to a dissociation between predictions of performance and confidence reports in the presence of feedback. This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

Inducing representational change in the hippocampus through real-time neurofeedback.

When you perceive or remember something, other related things come to mind, affecting how these competing items are subsequently perceived and remembered. Such behavioural consequences are believed to result from changes in the overlap of neural representations of these items, especially in the hippocampus. According to multiple theories, hippocampal overlap should increase (integration) when there is high coactivation between cortical representations. However, prior studies used indirect proxies for coactivation by manipulating stimulus similarity or task demands. Here, we induce coactivation in visual cortex more directly using closed-loop neurofeedback from real-time functional magnetic resonance imaging (fMRI). While viewing one object, participants were rewarded for activating the representation of another object as strongly as possible. Across multiple real-time fMRI sessions, participants succeeded in using this neurofeedback to increase coactivation. Compared with a baseline of untrained objects, this protocol led to memory integration in behaviour and the brain: the trained objects became harder for participants to discriminate behaviourally in a categorical perception task and harder to discriminate neurally from patterns of fMRI activity in their hippocampus as a result of losing unique features. These findings demonstrate that neurofeedback can be used to alter and combine memories.This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

Regulation of craving for real-time fMRI neurofeedback based on individual classification.

In previous real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) studies on smoking craving, the focus has been on within-region activity or between-region connectivity, neglecting the potential predictive utility of broader network activity. Moreover, there is debate over the use and relative predictive power of individual-specific and group-level classifiers. This study aims to further advance rtfMRI-NF for substance use disorders by using whole-brain rtfMRI-NF to assess smoking craving-related brain patterns, evaluate the performance of group-level or individual-level classification (n = 31) and evaluate the performance of an optimized classifier across repeated NF runs. Using real-time individual-level classifiers derived from whole-brain support vector machines, we found that classification accuracy between crave and no-crave conditions and between repeated NF runs increased across repeated runs at both individual and group levels. In addition, individual-level accuracy was significantly greater than group-level accuracy, highlighting the potential increased utility of an individually trained whole-brain classifier for volitional control over brain patterns to regulate smoking craving. This study provides evidence supporting the feasibility of using whole-brain rtfMRI-NF to modulate smoking craving-related brain responses and the potential for learning individual strategies through optimization across repeated feedback runs. This article is part of the theme issue 'Neurofeedback: new territories and neurocognitive mechanisms of endogenous neuromodulation'.

An automatic tracking method to measure the mandibula movement during real time MRI

Mandibular movement is complex and individual due to variations in the temporomandibular joint (TMJ). Consequently, patient-centered dentistry should incorporate patients’ specific anatomy and condylar function in treatment planning. Real-time magnetic resonance imaging (rt-MRI) visualizes relevant structures and tracks mandibular movement. However, current assessments rely on qualitative observations or time-consuming manual tracking, lacking reliability. This study developed an automatic tracking algorithm for mandibular movement in rt-MRI using least mean square registration (LMS) and compared it to manual tracking (MT) during mouth opening. Ten participants with skeletal class I underwent rt-MRI (10 frames/s). The same operator tracked the condylar pathway for the two methods, setting 2000 landmarks (2 landmarks x100 frames x10 participants) for MT and 210 landmarks (3 landmarks x7 frames x10 participants) for LMS. Time required, superimposition error, and the distance between tracked condylar pathways were compared between methods. LMS tracking was 76% faster and showed significantly better superimposition (0.0289 ± 0.0058) than MT (0.059 ± 0.0145) (p = 0.002). During one-third of the movement, the pathways tracked by both methods were more than 1 mm and 1° apart. These findings highlight the benefits of automatic condylar movement tracking in rt-MRI, laying the groundwork for more objective and quantitative observation of TMJ function.

ZnO Nanoparticles-Induced MRI Alterations to the Rat Olfactory Epithelium and Olfactory Bulb after Intranasal Instillation.

Since zinc oxide (ZnO) nanoparticles (NPs) have been widely applied, the nano community and the general public have paid great attention to the toxicity of ZnO NPs. We detected 20-nm ZnO NPs biotoxicity following nasal exposure utilizing the non-invasive and real-time magnetic resonance imaging (MRI) technique. MR images were scanned in the rat olfactory epithelium (OE) and olfactory bulb (OB) on a 4.7 T scanner following the treatment (as early as 1 day and up to 21 days after), and the histological changes were evaluated. The influence of the size of the ZnO NPs and chemical components was also investigated. Our study revealed that 20-nm ZnO NPs induced obvious structural disruption and inflammation in the OE and OB at the acute stage. The results suggest that the real-time and non-invasive advantages of MRI allow it to observe and assess, directly and dynamically, the potential toxicity of long-term exposure to ZnO NPs in the olfactory system. These findings indicate the size-dependent toxicity of ZnO NPs with respect to the olfactory bulb. Further study is needed to reveal the mechanism behind ZnO NPs' toxicity.

Self-navigated subspace reconstruction for real-time MR imaging of the vocal tract

Purpose: Real-time MRI offers a continuous and dynamic view of the object being imaged. Researchers have applied real-time MRI to speech production, which allows for the visualization of the vocal tract during speech.Methods: This study proposed applying self-navigated subspace reconstruction for real-time vocal tract imaging. We performed experiments on a clinical 3 T MRI using standard RF coils and rapid acquisition. Additionally, 1000 frames were compressed during reconstruction to a few principal components, and iterative low-rank approximation was performed on compressed k-space, in conjunction with the orthogonal basis estimation for the subspace.Results: The simulation study involving a 32-time acceleration showed that the proposed method produced a reasonably small root mean square error (RMSE) of 0.159, compared to 0.278 for sliding window reconstruction, 0.2527 for SToRM and 0.294 for low-rank reconstruction. The study also presented in vivo images of a typical sagittal image with a temporal resolution of 7 ms/frame or 21 ms/frame for the three-slice scan.Conclusion: Our study presented a subspace reconstruction technique that does not require a navigator echo, which can be used for real-time MRI, particularly in speech imaging applications.

Neural mechanisms underlying placebo and nocebo effects in tonic muscle pain

Pain is a highly subjective and multidimensional experience, significantly influenced by various psychological factors. Placebo analgesia and nocebo hyperalgesia exemplify this influence, where inert treatments result in pain relief or exacerbation, respectively. While extensive research has elucidated the psychological and neural mechanisms behind these effects, most studies have focused on transient pain stimuli. To explore these mechanisms in the context of tonic pain, we conducted a study using a 15-minute tonic muscle pain induction procedure, where hypertonic saline was infused into the left masseter of healthy participants. We collected real-time Visual Analogue Scale (VAS) scores and functional magnetic resonance imaging (fMRI) data during the induction of placebo analgesia and nocebo hyperalgesia via conditioned learning. Our findings revealed that placebo analgesia was more pronounced and lasted longer than nocebo hyperalgesia. Real-time pain ratings correlated significantly with neural activity in several brain regions. Notably, the putamen was implicated in both effects, while the caudate and other regions were differentially involved in placebo and nocebo effects. These findings confirm that the tonic muscle pain paradigm can be used to investigate the mechanisms of placebo and nocebo effects and indicate that placebo analgesia and nocebo hyperalgesia may have more distinct than common neural bases.

Real-Time fMRI Neurofeedback Training of Selective Attention in Older Adults.

Selective attention declines with age, due to age-related functional changes in dorsal anterior cingulate cortex (dACC). Real-time functional magnetic resonance imaging (rtfMRI) neurofeedback has been used in young adults to train volitional control of brain activity, including in dACC. For the first time, this study used rtfMRI neurofeedback to train 19 young and 27 older adults in volitional up- or down-regulation of bilateral dACC during a selective attention task. Older participants in the up-regulation condition (experimental group) showed greater reward points and dACC BOLD signal across training sessions, reflective of neurofeedback training success; and faster reaction time and better response accuracy, suggesting behavioral benefits on selective attention. These effects were not observed for older participants in the down-regulation condition (inverse condition control group), supporting specificity of volitional dACC up-regulation training in older adults. These effects were, unexpectedly, also not observed for young participants in the up-regulation condition (age control group), perhaps due to a lack of motivation to continue the training. These findings provide promising first evidence of functional plasticity in dACC in late life via rtfMRI neurofeedback up-regulation training, enhancing selective attention, and demonstrate proof of concept of rtfMRI neurofeedback training in cognitive aging.

Regulating posttraumatic stress disorder symptoms with neurofeedback: Regaining control of the mind

Neurofeedback is emerging as a psychophysiological treatment where self-regulation is achieved through online feed-back of neural states. Novel personalized medicine approaches are particularly important for the treatment of posttrau-matic stress disorder (PTSD), as symptom presentation of the disorder, as well as responses to treatment, are highly het-erogeneous. Learning to achieve control of specific neural substrates through neurofeedback has been shown to display therapeutic evidence in patients with a wide variety of psychiatric disorders, including PTSD. This article outlines the neural mechanisms underlying neurofeedback and examines converging evidence for the efficacy of neurofeedback as an adjunctive treatment for PTSD via both electroencephalography (EEG) and real-time functional magnetic resonance imaging (fMRI) modalities. Further, implications for the treatment of PTSD via neurofeedback in the military mem-ber and Veteran population is examined.

Accuracy of 3D real-time MRI temperature mapping in gel phantoms during microwave heating

BackgroundInterventional magnetic resonance imaging (MRI) can provide a comprehensive setting for microwave ablation of tumors with real-time monitoring of the energy delivery using MRI-based temperature mapping. The purpose of this study was to quantify the accuracy of three-dimensional (3D) real-time MRI temperature mapping during microwave heating in vitro by comparing MRI thermometry data to reference data measured by fiber-optical thermometry.MethodsNine phantom experiments were evaluated in agar-based gel phantoms using an in-room MR-conditional microwave system and MRI thermometry. MRI measurements were performed for 700 s (25 slices; temporal resolution 2 s). The temperature was monitored with two fiber-optical temperature sensors approximately 5 mm and 10 mm distant from the microwave antenna. Temperature curves of the sensors were compared to MRI temperature data of single-voxel regions of interest (ROIs) at the sensor tips; the accuracy of MRI thermometry was assessed as the root-mean-squared (RMS)-averaged temperature difference. Eighteen neighboring voxels around the original ROI were also evaluated and the voxel with the smallest temperature difference was additionally selected for further evaluation.ResultsThe maximum temperature changes measured by the fiber-optical sensors ranged from 7.3 K to 50.7 K. The median RMS-averaged temperature differences in the originally selected voxels ranged from 1.4 K to 3.4 K. When evaluating the minimum-difference voxel from the neighborhood, the temperature differences ranged from 0.5 K to 0.9 K. The microwave antenna and the MRI-conditional in-room microwave generator did not induce relevant radiofrequency artifacts.ConclusionAccurate 3D real-time MRI temperature mapping during microwave heating with very low RMS-averaged temperature errors below 1 K is feasible in gel phantoms.Relevance statementAccurate MRI-based volumetric real-time monitoring of temperature distribution and thermal dose is highly relevant in clinical MRI-based interventions and can be expected to improve local tumor control, as well as procedural safety by extending the limits of thermal (e.g., microwave) ablation of tumors in the liver and in other organs.Key PointsInterventional MRI can provide a comprehensive setting for the microwave ablation of tumors.MRI can monitor the microwave ablation using real-time MRI-based temperature mapping.3D real-time MRI temperature mapping during microwave heating is feasible.Measured temperature errors were below 1 °C in gel phantoms.The active in-room microwave generator did not induce any relevant radiofrequency artifacts.Graphical

Self-Regulation of the Posterior-Frontal Brain Activity with Real-Time fMRI Neurofeedback to Influence Perceptual Discrimination.

The Global Neuronal Workspace (GNW) hypothesis states that the visual percept is available to conscious awareness only if recurrent long-distance interactions among distributed brain regions activate neural circuitry extending from the posterior areas to prefrontal regions above a certain excitation threshold. To directly test this hypothesis, we trained 14 human participants to increase blood oxygenation level-dependent (BOLD) signals with real-time functional magnetic resonance imaging (rtfMRI)-based neurofeedback simultaneously in four specific regions of the occipital, temporal, insular and prefrontal parts of the brain. Specifically, we hypothesized that the up-regulation of the mean BOLD activity in the posterior-frontal brain regions lowers the perceptual threshold for visual stimuli, while down-regulation raises the threshold. Our results showed that participants could perform up-regulation (Wilcoxon test, session 1: p = 0.022; session 4: p = 0.041) of the posterior-frontal brain activity, but not down-regulation. Furthermore, the up-regulation training led to a significant reduction in the visual perceptual threshold, but no substantial change in perceptual threshold was observed after the down-regulation training. These findings show that the up-regulation of the posterior-frontal regions improves the perceptual discrimination of the stimuli. However, further questions as to whether the posterior-frontal regions can be down-regulated at all, and whether down-regulation raises the perceptual threshold, remain unanswered.

Training deep learning based dynamic MR image reconstruction using open-source natural videos

To develop and assess a deep learning (DL) pipeline to learn dynamic MR image reconstruction from publicly available natural videos (Inter4K). Learning was performed for a range of DL architectures (VarNet, 3D UNet, FastDVDNet) and corresponding sampling patterns (Cartesian, radial, spiral) either from true multi-coil cardiac MR data (N = 692) or from synthetic MR data simulated from Inter4K natural videos (N = 588). Real-time undersampled dynamic MR images were reconstructed using DL networks trained with cardiac data and natural videos, and compressed sensing (CS). Differences were assessed in simulations (N = 104 datasets) in terms of MSE, PSNR, and SSIM and prospectively for cardiac cine (short axis, four chambers, N = 20) and speech cine (N = 10) data in terms of subjective image quality ranking, SNR and Edge sharpness. Friedman Chi Square tests with post-hoc Nemenyi analysis were performed to assess statistical significance. In simulated data, DL networks trained with cardiac data outperformed DL networks trained with natural videos, both of which outperformed CS (p < 0.05). However, in prospective experiments DL reconstructions using both training datasets were ranked similarly (and higher than CS) and presented no statistical differences in SNR and Edge Sharpness for most conditions.The developed pipeline enabled learning dynamic MR reconstruction from natural videos preserving DL reconstruction advantages such as high quality fast and ultra-fast reconstructions while overcoming some limitations (data scarcity or sharing). The natural video dataset, code and pre-trained networks are made readily available on github.

Exercise MR of Skeletal Muscles, the Heart, and the Brain.

Magnetic resonance (MR) imaging (MRI) is routinely used to evaluate organ morphology and pathology in the human body at rest or in combination with pharmacological stress as an exercise surrogate. With MR during actual physical exercise, we can assess functional characteristics of tissues and organs under real-life stress conditions. This is particularly relevant in patients with limited exercise capacity or exercise intolerance, and where complaints typically present only during physical activity, such as in neuromuscular disorders, inherited metabolic diseases, and heart failure. This review describes practical and physiological aspects of exercise MR of skeletal muscles, the heart, and the brain. The acute effects of physical exercise on these organs are addressed in the light of various dynamic quantitative MR readouts, including phosphorus-31 MR spectroscopy (31P-MRS) of tissue energy metabolism, phase-contrast MRI of blood flow and muscle contraction, real-time cine MRI of cardiac performance, and arterial spin labeling MRI of muscle and brain perfusion. Exercise MR will help advancing our understanding of underlying mechanisms that contribute to exercise intolerance, which often proceed structural and anatomical changes in disease. Its potential to detect disease-driven alterations in organ function, perfusion, and metabolism under physiological stress renders exercise MR stress testing a powerful noninvasive imaging modality to aid in disease diagnosis and risk stratification. Although not yet integrated in most clinical workflows, and while some applications still require thorough validation, exercise MR has established itself as a comprehensive and versatile modality for characterizing physiology in health and disease in a noninvasive and quantitative way. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 1.

As fast as an X-ray: real-time magnetic resonance imaging for diagnosis of idiopathic scoliosis in children and adolescents

BackgroundIdiopathic scoliosis is common in adolescence. Due to the rapid growth of the spine, it must be monitored closely with radiographs to ensure timely intervention when therapy is needed. As these radiographs continue into young adulthood, patients are repeatedly exposed to ionizing radiation.ObjectiveThis study aimed to investigate whether real-time magnetic resonance imaging (MRI) is equivalent to conventional radiography in juvenile idiopathic scoliosis for determining curvature, rotation and the Risser stage. Additionally, the time requirement should be quantified.Materials and methodsChildren with idiopathic scoliosis who had postero-anterior whole-spine radiography for clinical indications were included in this prospective study. A real-time spine MRI was performed at 3 tesla in the supine position, capturing images in both the coronal and sagittal planes. The scoliosis was assessed using Cobb angle, rotation was evaluated based on Nash and Moe criteria, and the Risser stage was determined for each modality. The correlations between modalities and a correction factor for the Cobb angle between the standing and supine position were calculated.ResultsA total of 33 children (aged 5–17 years), who met the inclusion criteria, were recruited. The Cobb angle (R2 = 0.972; P < 0.01) was positively correlated with a correction factor of 1.07 between modalities. Additionally, the degree of rotation (R2 = 0.92; P < 0.01) and the Risser stage (R2 = 0.93; P < 0.01) demonstrated a strong correlation.ConclusionReal-time MRI is equivalent to conventional radiography in determining baseline parameters. Furthermore, it is radiation-free and less time-consuming.Graphical abstract

Improved Magnetic Resonance Image Reconstruction using Compressed Sensing and Adaptive Multi Extreme Particle Swarm Optimization Algorithm

One powerful technique that can offer a thorough examination of the body's internal structure is magnetic resonance imaging (MRI). MRI's lengthy acquisition times, however, may restrict its clinical usefulness, particularly in situations where time is of the essence. Compressed sensing (CS) has emerged as a potentially useful method for cutting down on MRI acquisition times; nevertheless, the effectiveness of CS-MRI is dependent on the selection of the sparsity-promoting algorithm and sampling scheme. This research paper presents a novel method based on adaptive multi-extreme particle swarm optimization (AMEPSO) and dual tree complex wavelet transform (DTCWT) for fast image acquisition in magnetic resonance. The method uses AMEPSO in order to maximize the sampling pattern and minimize reconstruction error, while also exploiting the sparsity of MR images in the DTCWT domain to improve directional selectivity and shift invariance. MATLAB software was used for simulation of the proposed method. In comparison with the particle swarm optimized-DTCWT (PSODTCWT) and DTCWT algorithms, respectively, the results demonstrated an improvement in the peak signal-to-noise ratio of 8.92% and 15.92% and a higher structural similarity index measure of 3.69% and 7.5%. Based on these improvements, the proposed method could potentially make high-quality, real-time MRI imaging possible, which might improve detection and treatment of medical conditions and increase the throughput of MRI machines.

MR-based navigation for robot-assisted endovascular procedures

AbstractThere is increasing interests in robotic and computer technologies to accurately perform endovascular intervention. One major limitation of current endovascular intervention—either manual or robot-assisted is the surgical navigation which still relies on 2D fluoroscopy. Recent research efforts are towards MRI-guided interventions to reduce ionizing radiation exposure, and to improve diagnosis, planning, navigation, and execution of endovascular interventions. We propose an MR-based navigation framework for robot-assisted endovascular procedures. The framework allows the acquisition of real-time MR images; segmentation of the vasculature and tracking of vascular instruments; and generation of MR-based guidance, both visual and haptic. The instrument tracking accuracy—a key aspect of the navigation framework—was assessed via 4 dedicated experiments with different acquisition settings, framerate, and time. The experiments showed clinically acceptable tracking accuracy in the range of 1.30–3.80 mm RMSE. We believe that this work represents a valuable first step towards MR-guided robot-assisted intervention.

Assessing osteoporosis in postmenopausal women: preliminary results using a novel lumbar spine phantom-based MRI scoring method.

To develop a novel magnetic resonance imaging (MRI) phantom for producing F-score (for fat) and W-score (for water) and to evaluate the performance of these scores in assessing osteoporosis and related vertebral fractures. First, a real-time phantom consisting of oil and water tubes was manufactured. Then, 30 female volunteers (age: 62.3 ± 6.3years) underwent lumbar spine examination with MRI (using a novel phantom) and dual-energy X-ray absorptiometry (DXA), following ethical approval. MRI phantom-based F-score and W-score were defined by normalizing the vertebral signal intensities (SIs) by the oil and water SIs of the phantom on T1- and T2-weighted images, respectively. The diagnostic performances of the new scores for assessing osteoporosis and vertebral fractures were examined using receiver operating characteristic analysis and compared with DXA-measured areal bone mineral density (DXA-aBMD). The F-score and W-score were greater in the osteoporotic patients (3.93 and 2.29) than the non-osteoporotic subjects (3.05 and 1.79) and achieved AUC values of 0.85 and 0.74 (p < 0.05), respectively, when detecting osteoporosis. Similarly, F-score and W-score had greater values for the fracture patients (3.94 and 2.53) than the non-fracture subjects (3.14 and 1.69) and produced better AUC values (0.90 for W-score and 0.79 for F-score) compared to DXA-aBMD (AUC: 0.27, p < 0.05). In addition,the F-score and W-score had a strong correlation (r = 0.77; p < 0.001). A novel real-time lumber spine MRI phantom was developed, based upon which newly defined F-score and W-score were able to detect osteoporosis and demonstrated an improved ability over DXA-aBMD in differentiating patients with vertebral fractures.

Articulatory and acoustic differences between lyric and dramatic singing in Western classical music.

Within the realm of voice classification, singers could be sub-categorized by the weight of their repertoire, the so-called "singer's Fach." However, the opposite pole terms "lyric" and "dramatic" singing are not yet well defined by their acoustic and articulatory characteristics. Nine professional singers of different singers' Fach were asked to sing a diatonic scale on the vowel /a/, first in what the singers considered as lyric and second in what they considered as dramatic. Image recording was performed using real time magnetic resonance imaging (MRI) with 25 frames/s, and the audio signal was recorded via an optical microphone system. Analysis was performed with regard to sound pressure level (SPL), vibrato amplitude, and frequency and resonance frequencies as well as articulatory settings of the vocal tract. The analysis revealed three primary differences between dramatic and lyric singing: Dramatic singing was associated with greater SPL and greater vibrato amplitude and frequency as well as lower resonance frequencies. The higher SPL is an indication of voice source changes, and the lower resonance frequencies are probably caused by the lower larynx position. However, all these strategies showed a considerable individual variability. The singers' Fach might contribute to perceptual differences even for the same singer with regard to the respective repertoire.

Functional and structural connectivity success predictors of real-time fMRI neurofeedback targeting DLPFC: Contributions from central executive, salience, and default mode networks.

Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback (NF), a training method for the self-regulation of brain activity, has shown promising results as a neurorehabilitation tool, depending on the ability of the patient to succeed in neuromodulation. This study explores connectivity-based structural and functional success predictors in an NF n-back working memory paradigm targeting the dorsolateral prefrontal cortex (DLPFC). We established as the NF success metric the linear trend on the ability to modulate the target region during NF runs and performed a linear regression model considering structural and functional connectivity (intrinsic and seed-based) metrics. We found a positive correlation between NF success and the default mode network (DMN) intrinsic functional connectivity and a negative correlation with the DLPFC-precuneus connectivity during the 2-back condition, indicating that success is associated with larger uncoupling between DMN and the executive network. Regarding structural connectivity, the salience network emerges as the main contributor to success. Both functional and structural classification models showed good performance with 77% and 86% accuracy, respectively. Dynamic switching between DMN, salience network and central executive network seems to be the key for neurofeedback success, independently indicated by functional connectivity on the localizer run and structural connectivity data.