Real‐time fMRI neurofeedback of the mediodorsal and anterior thalamus enhances correlation between thalamic BOLD activity and alpha EEG rhythm

Real‐time fMRI neurofeedback (rtfMRI‐nf) with simultaneous EEG allows volitional modulation of BOLD activity of target brain regions and investigation of related electrophysiological activity. We applied this approach to study correlations between thalamic BOLD activity and alpha EEG rhythm. Healthy volunteers in the experimental group (EG, n = 15) learned to upregulate BOLD activity of the target region consisting of the mediodorsal (MD) and anterior (AN) thalamic nuclei using rtfMRI‐nf during retrieval of happy autobiographical memories. Healthy subjects in the control group (CG, n = 14) were provided with a sham feedback. The EG participants were able to significantly increase BOLD activities of the MD and AN. Functional connectivity between the MD and the inferior precuneus was significantly enhanced during the rtfMRI‐nf task. Average individual changes in the occipital alpha EEG power significantly correlated with the average MD BOLD activity levels for the EG. Temporal correlations between the occipital alpha EEG power and BOLD activities of the MD and AN were significantly enhanced, during the rtfMRI‐nf task, for the EG compared to the CG. Temporal correlations with the alpha power were also significantly enhanced for the posterior nodes of the default mode network, including the precuneus/posterior cingulate, and for the dorsal striatum. Our findings suggest that the temporal correlation between the MD BOLD activity and posterior alpha EEG power is modulated by the interaction between the MD and the inferior precuneus, reflected in their functional connectivity. Our results demonstrate the potential of the rtfMRI‐nf with simultaneous EEG for noninvasive neuromodulation studies of human brain function.     

Reorganization of functional brain networks mediates the improvement of cognitive performance following real‐time neurofeedback training of working memory

Working memory (WM) is essential for individuals' cognitive functions. Neuroimaging studies indicated that WM fundamentally relied on a frontoparietal working memory network (WMN) and a cinguloparietal default mode network (DMN). Behavioral training studies demonstrated that the two networks can be modulated by WM training. Different from the behavioral training, our recent study used a real‐time functional MRI (rtfMRI)‐based neurofeedback method to conduct WM training, demonstrating that WM performance can be significantly improved after successfully upregulating the activity of the target region of interest (ROI) in the left dorsolateral prefrontal cortex (Zhang et al., [2013]: PloS One 8:e73735); however, the neural substrate of rtfMRI‐based WM training remains unclear. In this work, we assessed the intranetwork and internetwork connectivity changes of WMN and DMN during the training, and their correlations with the change of brain activity in the target ROI as well as with the improvement of post‐training behavior. Our analysis revealed an “ROI‐network‐behavior” correlation relationship underlying the rtfMRI training. Further mediation analysis indicated that the reorganization of functional brain networks mediated the effect of self‐regulation of the target brain activity on the improvement of cognitive performance following the neurofeedback training. The results of this study enhance our understanding of the neural basis of real‐time neurofeedback and suggest a new direction to improve WM performance by regulating the functional connectivity in the WM related networks. Hum Brain Mapp 36:1705–1715, 2015. © 2014 Wiley Periodicals, Inc.     

Amygdala real‐time functional magnetic resonance imaging neurofeedback for major depressive disorder: A review

Advances in imaging technologies have allowed for the analysis of functional magnetic resonance imaging data in real‐time (rtfMRI), leading to the development of neurofeedback (nf) training. This rtfMRI‐nf training utilizes functional magnetic resonance imaging (fMRI) tomographic localization capacity to allow a person to see and regulate the localized hemodynamic signal from his or her own brain. In this review, we summarize the results of several studies that have developed and applied neurofeedback training to healthy and depressed individuals with the amygdala as the neurofeedback target and the goal to increase the hemodynamic response during positive autobiographical memory recall. We review these studies and highlight some of the challenges and advances in developing an rtfMRI‐nf paradigm for broader use in psychiatric populations. The work described focuses on our line of research aiming to develop the rtfMRI‐nf into an intervention, and includes a discussion of the selection of a region of interest for feedback, selecting a control condition, behavioral and cognitive effects of training, and predicting which participants are most likely to respond well to training. While the results of these studies are encouraging and suggest the clinical potential of amygdala rtfMRI‐nf in alleviating symptoms of major depressive disorder, larger studies are warranted to confirm its efficacy.     

Real‐time fMRI neurofeedback in adolescents with attention deficit hyperactivity disorder

Attention Deficit Hyperactivity Disorder (ADHD) is associated with poor self‐control, underpinned by inferior fronto‐striatal deficits. Real‐time functional magnetic resonance neurofeedback (rtfMRI‐NF) allows participants to gain self‐control over dysregulated brain regions. Despite evidence for beneficial effects of electrophysiological‐NF on ADHD symptoms, no study has applied the spatially superior rtfMRI‐NF neurotherapy to ADHD. A randomized controlled trial tested the efficacy of rtfMRI‐NF of right inferior prefrontal cortex (rIFG), a key region that is compromised in ADHD and upregulated with psychostimulants, on improvement of ADHD symptoms, cognition, and inhibitory fMRI activation. To control for region‐specificity, an active control group received rtfMRI‐NF of the left parahippocampal gyrus (lPHG). Thirty‐one ADHD boys were randomly allocated and had to learn to upregulate their target brain region in an average of 11 rtfMRI‐NF runs over 2 weeks. Feedback was provided through a video‐clip of a rocket that had to be moved up into space. A transfer session without feedback tested learning retention as a proximal measure of transfer to everyday life. Both NF groups showed significant linear activation increases with increasing number of runs in their respective target regions and significant reduction in ADHD symptoms after neurotherapy and at 11‐month follow‐up. Only the group targeting rIFG, however, showed a transfer effect, which correlated with ADHD symptom reductions, improved at trend level in sustained attention, and showed increased IFG activation during an inhibitory fMRI task. This proof‐of‐concept study demonstrates for the first time feasibility, safety, and shorter‐ and longer‐term efficacy of rtfMRI‐NF of rIFG in adolescents with ADHD. Hum Brain Mapp 38:3190–3209, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.     

Quality and denoising in real‐time functional magnetic resonance imaging neurofeedback: A methods review

Neurofeedback training using real‐time functional magnetic resonance imaging (rtfMRI‐NF) allows subjects voluntary control of localised and distributed brain activity. It has sparked increased interest as a promising non‐invasive treatment option in neuropsychiatric and neurocognitive disorders, although its efficacy and clinical significance are yet to be determined. In this work, we present the first extensive review of acquisition, processing and quality control methods available to improve the quality of the neurofeedback signal. Furthermore, we investigate the state of denoising and quality control practices in 128 recently published rtfMRI‐NF studies. We found: (a) that less than a third of the studies reported implementing standard real‐time fMRI denoising steps, (b) significant room for improvement with regards to methods reporting and (c) the need for methodological studies quantifying and comparing the contribution of denoising steps to the neurofeedback signal quality. Advances in rtfMRI‐NF research depend on reproducibility of methods and results. Notably, a systematic effort is needed to build up evidence that disentangles the various mechanisms influencing neurofeedback effects. To this end, we recommend that future rtfMRI‐NF studies: (a) report implementation of a set of standard real‐time fMRI denoising steps according to a proposed COBIDAS‐style checklist ( https://osf.io/kjwhf/ ), (b) ensure the quality of the neurofeedback signal by calculating and reporting community‐informed quality metrics and applying offline control checks and (c) strive to adopt transparent principles in the form of methods and data sharing and support of open‐source rtfMRI‐NF software. Code and data for reproducibility, as well as an interactive environment to explore the study data, can be accessed at https://github.com/jsheunis/quality‐and‐denoising‐in‐rtfmri‐nf.     

The neurobiology of emotion regulation in posttraumatic stress disorder: Amygdala downregulation via real‐time fMRI neurofeedback

Amygdala dysregulation has been shown to be central to the pathophysiology of posttraumatic stress disorder (PTSD) representing a critical treatment target. Here, amygdala downregulation was targeted using real‐time fMRI neurofeedback (rt‐fMRI‐nf) in patients with PTSD, allowing us to examine further the regulation of emotional states during symptom provocation. Patients (n = 10) completed three sessions of rt‐fMRI‐nf with the instruction to downregulate activation in the amygdala, while viewing personalized trauma words. Amygdala downregulation was assessed by contrasting (a) regulate trials, with (b) viewing trauma words and not attempting to regulate. Training was followed by one transfer run not involving neurofeedback. Generalized psychophysiological interaction (gPPI) and dynamic causal modeling (DCM) analyses were also computed to explore task‐based functional connectivity and causal structure, respectively. It was found that PTSD patients were able to successfully downregulate both right and left amygdala activation, showing sustained effects within the transfer run. Increased activation in the dorsolateral and ventrolateral prefrontal cortex (PFC), regions related to emotion regulation, was observed during regulate as compared with view conditions. Importantly, activation in the PFC, rostral anterior cingulate cortex, and the insula, were negatively correlated to PTSD dissociative symptoms in the transfer run. Increased functional connectivity between the amygdala‐ and both the dorsolateral and dorsomedial PFC was found during regulate, as compared with view conditions during neurofeedback training. Finally, our DCM analysis exploring directional structure suggested that amygdala downregulation involves both top‐down and bottom‐up information flow with regard to observed PFC‐amygdala connectivity. This is the first demonstration of successful downregulation of the amygdala using rt‐fMRI‐nf in PTSD, which was critically sustained in a subsequent transfer run without neurofeedback, and corresponded to increased connectivity with prefrontal regions involved in emotion regulation during the intervention. Hum Brain Mapp 38:541–560, 2017. © 2016 Wiley Periodicals, Inc.     

Reduced functional coupling in the default‐mode network during self‐referential processing

Activity within the default‐mode network (DMN) is thought to be related to self‐referential processing, such as thinking about one's preferences or personality traits. Although the DMN is generally considered to function as a network, evidence is starting to accumulate that suggests that areas of the DMN are each specialized for different subfunctions of self‐referential processing. Here, we address the issue of functional specialization by investigating changes in coupling between areas of the DMN during self‐referential processing. To this aim, brain activity was assessed during a task in which subjects had to indicate whether a trait adjective described their own personality (self‐referential, Self condition), that of another person (other‐referential, Other condition), or whether the trait was socially desirable (nonreferential, Control condition). To exclude confounding effects of cardiorespiratory processes on activity and functional coupling, we corrected the fMRI signal for these effects. Activity within areas of the DMN was found to be modulated by self‐referential processing. More specifically, during the Self condition compared to the Other and Control condition, activity within the dorsal medial prefrontal cortex, ventral medial prefrontal cortex, and posterior cingulate cortex was increased. Moreover, coupling between areas of the DMN was reduced during the Self condition compared to the Other and Control condition, while coupling between regions of the DMN and regions outside the network was increased. As such, these results provide an indication for functional specialization within the DMN and support the notion that each area of the DMN is involved in different subfunctions of self‐referential processing. Hum Brain Mapp, 2010. © 2010 Wiley‐Liss, Inc.     

How feedback,motor imagery,and reward influence brain self‐regulation using real‐time fMRI

The learning process involved in achieving brain self‐regulation is presumed to be related to several factors, such as type of feedback, reward, mental imagery, duration of training, among others. Explicitly instructing participants to use mental imagery and monetary reward are common practices in real‐time fMRI (rtfMRI) neurofeedback (NF), under the assumption that they will enhance and accelerate the learning process. However, it is still not clear what the optimal strategy is for improving volitional control. We investigated the differential effect of feedback, explicit instructions and monetary reward while training healthy individuals to up‐regulate the blood‐oxygen‐level dependent (BOLD) signal in the supplementary motor area (SMA). Four groups were trained in a two‐day rtfMRI‐NF protocol: G_F with NF only, G_F,I with NF + explicit instructions (motor imagery), G_F,R with NF + monetary reward, and G_F,I,R with NF + explicit instructions (motor imagery) + monetary reward. Our results showed that G_F increased significantly their BOLD self‐regulation from day‐1 to day‐2 and G_F,R showed the highest BOLD signal amplitude in SMA during the training. The two groups who were instructed to use motor imagery did not show a significant learning effect over the 2 days. The additional factors, namely motor imagery and reward, tended to increase the intersubject variability in the SMA during the course of training. Whole brain univariate and functional connectivity analyses showed common as well as distinct patterns in the four groups, representing the varied influences of feedback, reward, and instructions on the brain. Hum Brain Mapp 37:3153–3171, 2016. © 2016 Wiley Periodicals, Inc .     

Acquired self‐control of insula cortex modulates emotion recognition and brain network connectivity in schizophrenia

Real‐time functional magnetic resonance imaging (rtfMRI) is a novel technique that has allowed subjects to achieve self‐regulation of circumscribed brain regions. Despite its anticipated therapeutic benefits, there is no report on successful application of this technique in psychiatric populations. The objectives of the present study were to train schizophrenia patients to achieve volitional control of bilateral anterior insula cortex on multiple days, and to explore the effect of learned self‐regulation on face emotion recognition (an extensively studied deficit in schizophrenia) and on brain network connectivity. Nine patients with schizophrenia were trained to regulate the hemodynamic response in bilateral anterior insula with contingent rtfMRI neurofeedback, through a 2‐weeks training. At the end of the training stage, patients performed a face emotion recognition task to explore behavioral effects of learned self‐regulation. A learning effect in self‐regulation was found for bilateral anterior insula, which persisted through the training. Following successful self‐regulation, patients recognized disgust faces more accurately and happy faces less accurately. Improvements in disgust recognition were correlated with levels of self‐activation of right insula. RtfMRI training led to an increase in the number of the incoming and outgoing effective connections of the anterior insula. This study shows for the first time that patients with schizophrenia can learn volitional brain regulation by rtfMRI feedback training leading to changes in the perception of emotions and modulations of the brain network connectivity. These findings open the door for further studies of rtfMRI in severely ill psychiatric populations, and possible therapeutic applications. Hum Brain Mapp, 2013. © 2011 Wiley Periodicals, Inc.     

Angular default mode network connectivity across working memory load

Initially identified during no‐task, baseline conditions, it has now been suggested that the default mode network (DMN) engages during a variety of working memory paradigms through its flexible interactions with other large‐scale brain networks. Nevertheless, its contribution to whole‐brain connectivity dynamics across increasing working memory load has not been explicitly assessed. The aim of our study was to determine which DMN hubs relate to working memory task performance during an fMRI‐based n‐back paradigm with parametric increases in difficulty. Using a voxel‐wise metric, termed the intrinsic connectivity contrast (ICC), we found that the bilateral angular gyri (core DMN hubs) displayed the greatest change in global connectivity across three levels of n‐back task load. Subsequent seed‐based functional connectivity analysis revealed that the angular DMN regions robustly interact with other large‐scale brain networks, suggesting a potential involvement in the global integration of information. Further support for this hypothesis comes from the significant correlations we found between angular gyri connectivity and reaction times to correct responses. The implication from our study is that the DMN is actively involved during the n‐back task and thus plays an important role related to working memory, with its core angular regions contributing to the changes in global brain connectivity in response to increasing environmental demands. Hum Brain Mapp 38:41–52, 2017. © 2016 Wiley Periodicals, Inc.     

Insight and psychosis: Functional and anatomical brain connectivity and self‐reflection in Schizophrenia

Impaired insight into illness, associated with worse treatment outcome, is common in schizophrenia. Insight has been related to the self‐reflective processing, centred on the medial frontal cortex. We hypothesized that anatomical and functional routes to and from the ventromedial prefrontal cortex (vmPFC) would differ in patients according to their degree of impaired insight. Forty‐five schizophrenia patients and 19 healthy subjects performed a self‐reflection task during fMRI, and underwent diffusion tensor imaging. Using dynamic causal modelling we observed increased effective connectivity from the posterior cingulate cortex (PCC), inferior parietal lobule (IPL), and dorsal mPFC (dmPFC) towards the vmPFC with poorer insight and decrease from vmPFC to the IPL. Stronger connectivity from the PCC to vmPFC during judgment of traits related to self was associated with poorer insight. We found small‐scale significant changes in white matter integrity associated with clinical insight. Self‐reflection may be influenced by synaptic changes that lead to the observed alterations in functional connectivity accompanied by the small‐scale but measurable alterations in anatomical connections. Our findings may point to a neural compensatory response to an impairment of connectivity between self‐processing regions. Similarly, the observed hyper‐connectivity might be a primary deficit linked to inefficiency in the component cognitive processes that lead to impaired insight. We suggest that the stronger cognitive demands placed on patients with poor insight is reflected in increased effective connectivity during the task in this study. Hum Brain Mapp 36:4859–4868, 2015. © 2015 Wiley Periodicals, Inc .     

Individualized real-time fMRI neurofeedback to attenuate craving in nicotine-dependent smokers

BackgroundCue-induced craving plays an important role in relapse, and the neural correlates of cue-induced craving have been elucidated using fMRI. This study examined the utility of real-time fMRI (rtfMRI) neurofeedback to strengthen self-regulation of craving-related neural activation and cue-reactivity in cigarette smokers.MethodsNicotine-dependent smokers were randomized to rtfMRI neurofeedback or to a no-feedback control group. Participants completed 3 neuroimaging visits. Within each visit, an initial run during which smoking-related cues were used to provoke craving, an individualized craving-related region of interest (ROI) in the prefrontal cortex or anterior cingulate cortex was identified. In the rtfMRI group, activity from the ROI was fed back via a visual display during 3 subsequent runs while participants were instructed to reduce craving during cue exposure. The control group had an identical experience with no feedback provided.ResultsForty-four nicotine-dependent smokers were recruited to participate in our study; data from the 33 participants who completed a 1-week follow-up visit were included in the analysis. Subjective craving ratings and cue-induced brain activation were lower in the rtfMRI group than in the control group.LimitationsAs participants were not seeking treatment, clinical outcomes are lacking.ConclusionNicotine-dependent smokers receiving rtfMRI feedback from an individualized ROI attenuated smoking cue–elicited neural activation and craving, relative to a control group. Further studies are needed in treatment-seeking smokers to determine if this intervention can translate into a clinically meaningful treatment modality.     

Prevent breaking bad: A proof of concept study of rebalancing the brain's rumination circuit with real‐time fMRI functional connectivity neurofeedback

Rumination, repetitively thinking about the causes, consequences, and one''s negative affect, has been considered as an important factor of depression. The intrusion of ruminative thoughts is not easily controlled, and it may be useful to visualize one''s neural activity related to rumination and to use that information to facilitate one''s self‐control. Real‐time fMRI neurofeedback (rtfMRI‐nf) enables one to see and regulate the fMRI signal from their own brain. This proof‐of concept study utilized connectivity‐based rtfMRI‐nf (cnf) to normalize brain functional connectivity (FC) associated with rumination. Healthy participants were instructed to brake or decrease FC between the precuneus and the right temporoparietal junction (rTPJ), associated with high levels of rumination, while engaging in a self‐referential task. The cnf group (n = 14) showed a linear decrease in the precuneus‐rTPJ FC across neurofeedback training (trend [112] = −0.180, 95% confidence interval [CI] −0.330 to −0.031, while the sham group (n = 14) showed a linear increase in the target FC (trend [112] = 0.151, 95% CI 0.017 to 0.299). Although the cnf group showed a greater reduction in state‐rumination compared to the sham group after neurofeedback training (p < .05), decoupled precuneus‐rTPJ FC did not predict attenuated state‐rumination. We did not find any significant aversive effects of rtfMRI‐nf in all study participants. These results suggest that cnf has the capacity to influence FC among precuneus and rTPJ of a ruminative brain circuit. This approach can be applied to mood and anxiety patients to determine the clinical benefits of reduction in maladaptive rumination.     

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. Thus, here we employed a meta‐analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no‐feedback runs (i.e., self‐regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain‐based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.     

Wavelet‐based regularity analysis reveals recurrent spatiotemporal behavior in resting‐state fMRI

One of the major findings from multimodal neuroimaging studies in the past decade is that the human brain is anatomically and functionally organized into large‐scale networks. In resting state fMRI (rs‐fMRI), spatial patterns emerge when temporal correlations between various brain regions are tallied, evidencing networks of ongoing intercortical cooperation. However, the dynamic structure governing the brain's spontaneous activity is far less understood due to the short and noisy nature of the rs‐fMRI signal. Here, we develop a wavelet‐based regularity analysis based on noise estimation capabilities of the wavelet transform to measure recurrent temporal pattern stability within the rs‐fMRI signal across multiple temporal scales. The method consists of performing a stationary wavelet transform to preserve signal structure, followed by construction of “lagged” subsequences to adjust for correlated features, and finally the calculation of sample entropy across wavelet scales based on an “objective” estimate of noise level at each scale. We found that the brain's default mode network (DMN) areas manifest a higher level of irregularity in rs‐fMRI time series than rest of the brain. In 25 aged subjects with mild cognitive impairment and 25 matched healthy controls, wavelet‐based regularity analysis showed improved sensitivity in detecting changes in the regularity of rs‐fMRI signals between the two groups within the DMN and executive control networks, compared with standard multiscale entropy analysis. Wavelet‐based regularity analysis based on noise estimation capabilities of the wavelet transform is a promising technique to characterize the dynamic structure of rs‐fMRI as well as other biological signals. Hum Brain Mapp 36:3603–3620, 2015. © 2015 Wiley Periodicals, Inc.     

Cognitive and default‐mode resting state networks: Do male and female brains “rest” differently?

Variability in human behavior related to sex is supported by neuroimaging studies showing differences in brain activation patterns during cognitive task performance. An emerging field is examining the human connectome, including networks of brain regions that are not only temporally‐correlated during different task conditions, but also networks that show highly correlated spontaneous activity during a task‐free state. Both task‐related and task‐free network activity has been associated with individual task performance and behavior under certain conditions. Therefore, our aim was to determine whether sex differences exist during a task‐free resting state for two networks associated with cognitive task performance (executive control network (ECN), salience network (SN)) and the default mode network (DMN). Forty‐nine healthy subjects (26 females, 23 males) underwent a 5‐min task‐free fMRI scan in a 3T MRI. An independent components analysis (ICA) was performed to identify the best‐fit IC for each network based on specific spatial nodes defined in previous studies. To determine the consistency of these networks across subjects we performed self‐organizing group‐level ICA analyses. There were no significant differences between sexes in the functional connectivity of the brain areas within the ECN, SN, or the DMN. These important findings highlight the robustness of intrinsic connectivity of these resting state networks and their similarity between sexes. Furthermore, our findings suggest that resting state fMRI studies do not need to be controlled for sex. Hum Brain Mapp, 2010. © 2010 Wiley‐Liss, Inc.     

Dysregulation of working memory and default‐mode networks in schizophrenia using independent component analysis,an fBIRN and MCIC study

Deficits in working memory (WM) are a consistent neurocognitive marker for schizophrenia. Previous studies have suggested that WM is the product of coordinated activity in distributed functionally connected brain regions. Independent component analysis (ICA) is a data‐driven approach that can identify temporally coherent networks that underlie fMRI activity. We applied ICA to an fMRI dataset for 115 patients with chronic schizophrenia and 130 healthy controls by performing the Sternberg Item Recognition Paradigm. Here, we describe the first results using ICA to identify differences in the function of WM networks in schizophrenia compared to controls. ICA revealed six networks that showed significant differences between patients with schizophrenia and healthy controls. Four of these networks were negatively task‐correlated and showed deactivation across the posterior cingulate, precuneus, medial prefrontal cortex, anterior cingulate, inferior parietal lobules, and parahippocampus. These networks comprise brain regions known as the default‐mode network (DMN), a well‐characterized set of regions shown to be active during internal modes of cognition and implicated in schizophrenia. Two networks were positively task‐correlated, with one network engaging WM regions such as bilateral DLPFC and inferior parietal lobules while the other network engaged primarily the cerebellum. Our results suggest that DLPFC dysfunction in schizophrenia might be lateralized to the left and intrinsically tied to other regions such as the inferior parietal lobule and cingulate gyrus. Furthermore, we found that DMN dysfunction in schizophrenia exists across multiple subnetworks of the DMN and that these subnetworks are individually relevant to the pathophysiology of schizophrenia. In summary, this large multsite study identified multiple temporally coherent networks, which are aberrant in schizophrenia versus healthy controls and suggests that both task‐correlated and task‐anticorrelated networks may serve as potential biomarkers. Hum Brain Mapp, 2009. © 2009 Wiley‐Liss, Inc.     

Social reinforcement can regulate localized brain activity

Social learning is essential for adaptive behavior in humans. Neurofeedback based on functional magnetic resonance imaging (fMRI) trains control over localized brain activity. It can disentangle learning processes at the neural level and thus investigate the mechanisms of operant conditioning with explicit social reinforcers. In a pilot study, a computer-generated face provided a positive feedback (smiling) when activity in the anterior cingulate cortex (ACC) increased and gradually returned to a neutral expression when the activity dropped. One female volunteer without previous experience in fMRI underwent training based on a social reinforcer. Directly before and after the neurofeedback runs, neural responses to a cognitive interference task (Simon task) were recorded. We observed a significant increase in activity within ACC during the neurofeedback blocks, correspondent with the a-priori defined anatomical region of interest. In the course of the neurofeedback training, the subject learned to regulate ACC activity and could maintain the control even without direct feedback. Moreover, ACC was activated significantly stronger during Simon task after the neurofeedback training when compared to before. Localized brain activity can be controlled by social reward. The increased ACC activity transferred to a cognitive task with the potential to reduce cognitive interference. Systematic studies are required to explore long-term effects on social behavior and clinical applications.

     

Test‐retest reliability of the default mode network in a multi‐centric fMRI study of healthy elderly: Effects of data‐driven physiological noise correction techniques

Understanding how to reduce the influence of physiological noise in resting state fMRI data is important for the interpretation of functional brain connectivity. Limited data is currently available to assess the performance of physiological noise correction techniques, in particular when evaluating longitudinal changes in the default mode network (DMN) of healthy elderly participants. In this 3T harmonized multisite fMRI study, we investigated how different retrospective physiological noise correction (rPNC) methods influence the within‐site test‐retest reliability and the across‐site reproducibility consistency of DMN‐derived measurements across 13 MRI sites. Elderly participants were scanned twice at least a week apart (five participants per site). The rPNC methods were: none (NPC), Tissue‐based regression, PESTICA and FSL‐FIX. The DMN at the single subject level was robustly identified using ICA methods in all rPNC conditions. The methods significantly affected the mean z‐scores and, albeit less markedly, the cluster‐size in the DMN; in particular, FSL‐FIX tended to increase the DMN z‐scores compared to others. Within‐site test‐retest reliability was consistent across sites, with no differences across rPNC methods. The absolute percent errors were in the range of 5–11% for DMN z‐scores and cluster‐size reliability. DMN pattern overlap was in the range 60–65%. In particular, no rPNC method showed a significant reliability improvement relative to NPC. However, FSL‐FIX and Tissue‐based physiological correction methods showed both similar and significant improvements of reproducibility consistency across the consortium (ICC = 0.67) for the DMN z‐scores relative to NPC. Overall these findings support the use of rPNC methods like tissue‐based or FSL‐FIX to characterize multisite longitudinal changes of intrinsic functional connectivity. Hum Brain Mapp 37:2114–2132, 2016. © 2016 Wiley Periodicals, Inc.     

The role of the ventromedial prefrontal cortex in automatic formation of impression and reflected impression

Previous neuroimaging studies demonstrated that ventromedial prefrontal cortex (vmPFC) activity reflects how much an individual positively views each person (impression). Here, we investigated whether the degree to which individuals think others positively view them (reflected impression) is similarly tracked by activity in the vmPFC by using fMRI and speed‐dating events. We also examined whether activity of the vmPFC in response to the faces of others would predict the impression formed through direct interactions with them. The task consisted of three sessions: pre‐speed‐dating fMRI, speed‐dating events, and post‐speed‐dating fMRI (not reported here). During the pre‐speed‐dating fMRI, each participant passively viewed the faces of others whom they would meet in the subsequent speed‐dating events. After the fMRI, they rated the impression and reflected impression of each face. During the speed‐dating events, the participants had 3‐min conversations with partners whose faces were presented during the fMRI task, and they were asked to choose the partners whom they preferred at the end of the events. The results revealed that the value of both the impression and reflected impression were automatically represented in the vmPFC. However, the impression fully mediated the link between the reflected impression and vmPFC activity. These results highlight a close link between reflected appraisal and impression formation and provide important insights into neural and psychological models of how the reflected impression is formed in the human brain.