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 ( = 31) and evaluate the performance of an optimized classifier across repeated NF runs.

Electronic Cigarette Vaping Did Not Enhance the Neural Process of Working Memory for Regular Cigarette Smokers.

Background: Electronic cigarettes (e-cigs) as substitute devices for regular tobacco cigarettes (r-cigs) have been increasing in recent times. We investigated neuronal substrates of vaping e-cigs and smoking r-cigs from r-cig smokers.

Methods: Twenty-two r-cig smokers made two visits following overnight smoking cessation.

Predictors of real-time fMRI neurofeedback performance and improvement - A machine learning mega-analysis.

Real-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signals, which can lead to improvements in behavior in healthy participants as well as to improvements of clinical symptoms in patient populations. However, a considerably large ratio of participants undergoing neurofeedback training do not learn to control their own brain signals and, consequently, do not benefit from neurofeedback interventions, which limits clinical efficacy of neurofeedback interventions. As neurofeedback success varies between studies and participants, it is important to identify factors that might influence neurofeedback success.

Cigarette craving modulation is more feasible than resistance modulation for heavy cigarette smokers: empirical evidence from functional MRI data.

Background: Modulation of cigarette craving and neuronal activations from nicotine-dependent cigarette smokers using real-time functional MRI (rtfMRI)-based neurofeedback (rtfMRI-NF) has been previously reported.

Objectives: The aim of this study was to evaluate the efficacy of rtfMRI-NF training in reducing cigarette cravings using fMRI data acquired before and after training.

Methods: Treatment-seeking male heavy cigarette smokers (N = 14) were enrolled and randomly assigned to two conditions related to rtfMRI-NF training aiming at resisting the urge to smoke.

Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success.

Functional magnetic resonance imaging multivoxel pattern analysis reveals neuronal substrates for collaboration and competition with myopic and predictive strategic reasoning.

Competition and collaboration are strategies that can be used to optimize the outcomes of social interactions. Research into the neuronal substrates underlying these aspects of social behavior has been limited due to the difficulty in distinguishing complex activation via univariate analysis. Therefore, we employed multivoxel pattern analysis of functional magnetic resonance imaging to reveal the neuronal activations underlying competitive and collaborative processes when the collaborator/opponent used myopic/predictive reasoning.

Mediation analysis of triple networks revealed functional feature of mindfulness from real-time fMRI neurofeedback.

The triple networks, namely the default-mode network (DMN), the central executive network (CEN), and the salience network (SN), play crucial roles in disorders of the brain, as well as in basic neuroscientific processes such as mindfulness. However, currently, there is no consensus on the underlying functional features of the triple networks associated with mindfulness. In this study, we tested the hypothesis that (a) the partial regression coefficient (i.

The inclusion of functional connectivity information into fMRI-based neurofeedback improves its efficacy in the reduction of cigarette cravings.

Real-time fMRI (rtfMRI) neurofeedback (NF) facilitates volitional control over brain activity and the modulation of associated mental functions. The NF signals of traditional rtfMRI-NF studies predominantly reflect neuronal activity within ROIs. In this study, we describe a novel rtfMRI-NF approach that includes a functional connectivity (FC) component in the NF signal (FC-added rtfMRI-NF).

Mesocorticolimbic hyperactivity of deprived smokers and brain imaging.

We determined the association of neuronal circuitry with the desire to smoke by acquiring and analyzing functional MRI data. The data were acquired in both abstained and subsequently satiated (by 'natural' cigarette smoking) heavy smokers and also in demographically and intellectually matched nonsmokers. During the acquisition, participants were viewing alternating smoking and nonsmoking images that were interleaved by fixation images.

Are posterior default-mode networks more robust than anterior default-mode networks? Evidence from resting-state fMRI data analysis.

Intrinsic brain activity known as default-mode networks (DMNs) has been observed predominantly within the medial/superior frontal areas, anterior/posterior cingulate gyri, and precuneus using blood-oxygenation-level-dependent (BOLD) functional MRI (fMRI). Despite anecdotal evidence of distinct spatial patterns reflecting neuropsychiatric conditions in these DMNs, rigorous analysis of the characteristic traits of DMNs has been limited in previous studies. In this letter, the reproducibility and potential variability of the anterior and posterior DMNs were evaluated based on individual-level variations in effect sizes, activated areas, and causal interactions.