Placebo hampers ability to self-regulate brain activity: A double-blind sham-controlled neurofeedback study

Manipulating cybersickness in virtual reality-based neurofeedback and its effects on training performance

Objective. Virtual reality (VR) serves as a modern and powerful tool to enrich neurofeedback (NF) and brain-computer interface (BCI) applications as well as to achieve higher user motivation and adherence to training. However, between 20%-80% of all the users develop symptoms of cybersickness (CS), namely nausea, oculomotor problems or disorientation during VR interaction, which influence user performance and behavior in VR. Hence, we investigated whether CS-inducing VR paradigms influence the success of a NF training task.Approach. We tested 39 healthy participants (20 female) in a single-session VR-based NF study. One half of the participants was presented with a high CS-inducing VR-environment where movement speed, field of view and camera angle were varied in a CS-inducing fashion throughout the session and the other half underwent NF training in a less CS-inducing VR environment, where those parameters were held constant. The NF training consisted of 6 runs of 3 min each, in which participants should increase their sensorimotor rhythm (SMR, 12-15 Hz) while keeping artifact control frequencies constant (Theta 4-7 Hz, Beta 16-30 Hz). Heart rate and subjectively experienced CS were also assessed.Main results. The high CS-inducing condition tended to lead to more subjectively experienced CS nausea symptoms than the low CS-inducing condition. Further, women experienced more CS, a higher heart rate and showed a worse NF performance compared to men. However, the SMR activity during the NF training was comparable between both the high and low CS-inducing groups. Both groups were able to increase their SMR across feedback runs, although, there was a tendency of higher SMR power for male participants in the low CS group.Significance. Hence, sickness symptoms in VR do not necessarily impair NF/BCI training success. This takes us one step further in evaluating the practicability of VR in BCI and NF applications. Nevertheless, inter-individual differences in CS susceptibility should be taken into account for VR-based NF applications.

Whole-brain mechanism of neurofeedback therapy: predictive modeling of neurofeedback outcomes on repetitive negative thinking in depression

Real-time fMRI neurofeedback (rtfMRI-NF) has emerged as a promising intervention for psychiatric disorders, yet its clinical efficacy remains underexplored due to an incomplete mechanistic understanding. This study aimed to delineate the whole-brain mechanisms underpinning the effects of rtfMRI-NF on repetitive negative thinking in depression. In a double-blind randomized controlled trial, forty-three depressed individuals underwent NF training targeting the functional connectivity (FC) between the posterior cingulate cortex and the right temporoparietal junction, linked to rumination severity. Participants were randomly assigned to active or sham groups, with the sham group receiving synthesized feedback mimicking real NF signal patterns. The active group demonstrated a significant reduction in brooding rumination scores (d = -1.52, p < 0.001), whereas the sham group did not (d = -0.23, p = 0.503). While the target FC did not show discernible training effects or group differences, connectome-based predictive modeling (CPM) analysis revealed that the interaction between brain activity during regulation and brain response to the feedback signal was the critical factor in explaining treatment outcomes. The model incorporating this interaction successfully predicted rumination changes across both groups. The FCs significantly contributing to the prediction were distributed across brain regions, notably the frontal control, salience network, and subcortical reward processing areas. These results underscore the importance of considering the interplay between brain regulation activities and brain response to the feedback signal in understanding the therapeutic mechanisms of rtfMRI-NF. The study affirms rtfMRI-NF's potential as a therapeutic intervention for repetitive negative thinking and highlights the need for a nuanced understanding of the whole-brain mechanisms contributing to its efficacy.

EEG decoding with spatiotemporal convolutional neural network for visualization and closed-loop control of sensorimotor activities: A simultaneous EEG-fMRI study

Closed-loop neurofeedback training utilizes neural signals such as scalp electroencephalograms (EEG) to manipulate specific neural activities and the associated behavioral performance. A spatiotemporal filter for high-density whole-head scalp EEG using a convolutional neural network can overcome the ambiguity of the signaling source because each EEG signal includes information on the remote regions. We simultaneously acquired EEG and functional magnetic resonance images in humans during the brain-computer interface (BCI) based neurofeedback training and compared the reconstructed and modeled hemodynamic responses of the sensorimotor network. Filters constructed with a convolutional neural network captured activities in the targeted network with spatial precision and specificity superior to those of the EEG signals preprocessed with standard pipelines used in BCI-based neurofeedback paradigms. The middle layers of the trained model were examined to characterize the neuronal oscillatory features that contributed to the reconstruction. Analysis of the layers for spatial convolution revealed the contribution of distributed cortical circuitries to reconstruction, including the frontoparietal and sensorimotor areas, and those of temporal convolution layers that successfully reconstructed the hemodynamic response function. Employing a spatiotemporal filter and leveraging the electrophysiological signatures of the sensorimotor excitability identified in our middle layer analysis would contribute to the development of a further effective neurofeedback intervention.

Multimodal and hemispheric graph-theoretical brain network predictors of learning efficacy for frontal alpha asymmetry neurofeedback

EEG neurofeedback using frontal alpha asymmetry (FAA) has been widely used for emotion regulation, but its effectiveness is controversial. Studies indicated that individual differences in neurofeedback training can be traced to neuroanatomical and neurofunctional features. However, they only focused on regional brain structure or function and overlooked possible neural correlates of the brain network. Besides, no neuroimaging predictors for FAA neurofeedback protocol have been reported so far. We designed a single-blind pseudo-controlled FAA neurofeedback experiment and collected multimodal neuroimaging data from healthy participants before training. We assessed the learning performance for evoked EEG modulations during training (L1) and at rest (L2), and investigated performance-related predictors based on a combined analysis of multimodal brain networks and graph-theoretical features. The main findings of this study are described below. First, both real and sham groups could increase their FAA during training, but only the real group showed a significant increase in FAA at rest. Second, the predictors during training blocks and at rests were different: L1 was correlated with the graph-theoretical metrics (clustering coefficient and local efficiency) of the right hemispheric gray matter and functional networks, while L2 was correlated with the graph-theoretical metrics (local and global efficiency) of the whole-brain and left the hemispheric functional network. Therefore, the individual differences in FAA neurofeedback learning could be explained by individual variations in structural/functional architecture, and the correlated graph-theoretical metrics of learning performance indices showed different laterality of hemispheric networks. These results provided insight into the neural correlates of inter-individual differences in neurofeedback learning.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-023-09939-x.

Post-stroke aphasia rehabilitation using an adapted visual P300 brain-computer interface training: improvement over time, but specificity remains undetermined

Introduction

This study aimed to evaluate the efficacy of visual P300 brain-computer interface use to support rehabilitation of chronic language production deficits commonly experienced by individuals with a left-sided stroke resulting in post-stroke aphasia.

Methods

The study involved twelve participants, but five dropped out. Additionally, data points were missing for three participants in the remaining sample of seven participants. The participants underwent four assessments-a baseline, pre-assessment, post-assessment, and follow-up assessment. Between the pre-and post-assessment, the participants underwent at least 14 sessions of visual spelling using a brain-computer interface. The study aimed to investigate the impact of this intervention on attention, language production, and language comprehension and to determine whether there were any potential effects on quality of life and well-being.

Results

None of the participants showed a consistent improvement in attention. All participants showed an improvement in spontaneous speech production, and three participants experienced a reduction in aphasia severity. We found an improvement in subjective quality of life and daily functioning. However, we cannot rule out the possibility of unspecific effects causing or at least contributing to these results.

Conclusion

Due to challenges in assessing the patient population, resulting in a small sample size and missing data points, the results of using visual P300 brain-computer interfaces for chronic post-stroke aphasia rehabilitation are preliminary. Thus, we cannot decisively judge the potential of this approach.

Who Wants to Enhance Their Cognitive Abilities? Potential Predictors of the Acceptance of Cognitive Enhancement

With advances in new technologies, the topic of cognitive enhancement has been at the center of public debate in recent years. Various enhancement methods (e.g., brain stimulation, smart drugs, or working memory training) promise improvements in one's cognitive abilities such as intelligence and memory. Although these methods have been rather ineffective so far, they are largely available to the general public and can be applied individually. As applying enhancement might be accompanied by certain risks, it is important to understand which individuals seek to enhance themselves. For instance, individuals' intelligence, personality, and interests might predict their willingness to get enhanced. Thus, in a preregistered study, we asked 257 participants about their acceptance of various enhancement methods and tested predictors thereof, such as participants' psychometrically measured and self-estimated intelligence. While both measured and self-estimated intelligence as well as participants' implicit beliefs about intelligence, did not predict participants' acceptance of enhancement; a younger age, higher interest in science-fiction, and (partially) higher openness as well as lower conscientiousness did. Thus, certain interests and personality traits might contribute to the willingness to enhance one's cognition. Finally, we discuss the need for replication and argue for testing other potential predictors of the acceptance of cognitive enhancement.

Assessment of the capacity to modulate brain signals in a home-based SMR neurofeedback training setting

Electroencephalogram (EEG)-based neurofeedback (NF) is mainly used in clinical settings as a therapeutic intervention or to optimize performance in healthy individuals. Home-based NF systems are available and might facilitate general access to NF training, especially when repeated training sessions are necessary. However, it remains an open question whether NF training at home is possible without remote monitoring. In the present study, we assessed the capacity of healthy individuals to modulate their own EEG activity when using a home-based NF training system in a comparable manner as if participants had purchased a commercially available NF system. Participants' face-to-face contact with experimenters was reduced to a minimum, and instructions were provided only in the form of written information or videos. Initially, 38 participants performed 9 sessions of sensorimotor rhythm (SMR) (12-15 Hz) based NF training (three generalization sessions, six training sessions). An active control group (n = 19) received feedback on random EEG frequencies. Because of technical problems, bad EEG data quality, or non-compliance, 21 participants had to be excluded from the final data analysis, providing first evidence for the difficulties of non-supervised home-based NF training. In this study, participants were not able to modulate their own brain activity in a desired direction during NF training. Our results indicate that personal interaction with a NF expert might be of relevance and that remote supervision of the training data and more direct communication with the NF users are necessary to enable successful NF training performance. We provide suggestions for the development and implementation of home-based NF systems.

Thirty-minute motor imagery exercise aided by EEG sensorimotor rhythm neurofeedback enhances morphing of sensorimotor cortices: a double-blind sham-controlled study

Neurofeedback training using electroencephalogram (EEG)-based brain-computer interfaces (BCIs) combined with mental rehearsals of motor behavior has demonstrated successful self-regulation of motor cortical excitability. However, it remains unclear whether the acquisition of skills to voluntarily control neural excitability is accompanied by structural plasticity boosted by neurofeedback. Here, we sought short-term changes in cortical structures induced by 30 min of BCI-based neurofeedback training, which aimed at the regulation of sensorimotor rhythm (SMR) in scalp EEG. When participants performed kinesthetic motor imagery of right finger movement with online feedback of either event-related desynchronisation (ERD) of SMR magnitude from the contralateral sensorimotor cortex (SM1) or those from other participants (i.e. placebo), the learning rate of SMR-ERD control was significantly different. Although overlapped structural changes in gray matter volumes were found in both groups, significant differences revealed by group-by-group comparison were spatially different; whereas the veritable neurofeedback group exhibited sensorimotor area-specific changes, the placebo exhibited spatially distributed changes. The white matter change indicated a significant decrease in the corpus callosum in the verum group. Furthermore, the learning rate of SMR regulation was correlated with the volume changes in the ipsilateral SM1, suggesting the involvement of interhemispheric motor control circuitries in BCI control tasks.

Effects of virtual reality-based feedback on neurofeedback training performance—A sham-controlled study

Electroencephalography-neurofeedback (EEG-NF) has become a valuable tool in the field of psychology, e.g., to improve cognitive function. Nevertheless, a large percentage of NF users seem to be unable to control their own brain activation. Therefore, the aim of this study was to examine whether a different kind of visual feedback could positively influence NF performance after one training session. Virtual reality (VR) seems to have beneficial training effects and has already been reported to increase motivational training aspects. In the present study, we tested 61 young healthy adults (mean age: 23.48 years; 28 female) to investigate, whether 3D VR-based NF training has a more beneficial effect on the sensorimotor rhythm (SMR, 12–15 Hz) power increase than a mere 2D conventional NF paradigm. In the 3D group, participants had to roll a ball along a predefined path in an immersive virtual environment, whereas the 2D group had to increase the height of a bar. Both paradigms were presented using VR goggles. Participants completed one baseline and six feedback runs with 3 min each, in which they should try to increase SMR power over Cz. Half of the participants received real feedback whereas the other half received sham feedback. Participants receiving 3D VR-based feedback showed a linear increase in SMR power over the feedback runs within one training session. This was the case for the real as well as for the sham 3D feedback group and might be related to more general VR-related effects. The 2D group receiving the conventional bar feedback showed no changes in SMR power over the feedback runs. The present study underlines that the visual feedback modality has differential effects on the NF training performance and that 3D VR-based feedback has advantages over conventional 2D feedback.

Spatially bivariate EEG-neurofeedback can manipulate interhemispheric inhibition

Human behavior requires inter-regional crosstalk to employ the sensorimotor processes in the brain. Although external neuromodulation techniques have been used to manipulate interhemispheric sensorimotor activity, a central controversy concerns whether this activity can be volitionally controlled. Experimental tools lack the power to up- or down-regulate the state of the targeted hemisphere over a large dynamic range and, therefore, cannot evaluate the possible volitional control of the activity. We addressed this difficulty by using the recently developed method of spatially bivariate electroencephalography (EEG)-neurofeedback to systematically enable the participants to modulate their bilateral sensorimotor activities. Here, we report that participants learn to up- and down-regulate the ipsilateral excitability to the imagined hand while maintaining constant contralateral excitability; this modulates the magnitude of interhemispheric inhibition (IHI) assessed by the paired-pulse transcranial magnetic stimulation (TMS) paradigm. Further physiological analyses revealed that the manipulation capability of IHI magnitude reflected interhemispheric connectivity in EEG and TMS, which was accompanied by intrinsic bilateral cortical oscillatory activities. Our results show an interesting approach for neuromodulation, which might identify new treatment opportunities, e.g., in patients suffering from a stroke.

The Role of Expectation and Beliefs on the Effects of Non-Invasive Brain Stimulation

Non-invasive brain stimulation (NIBS) techniques are used in clinical and cognitive neuroscience to induce a mild magnetic or electric field in the brain to modulate behavior and cortical activation. Despite the great body of literature demonstrating promising results, unexpected or even paradoxical outcomes are sometimes observed. This might be due either to technical and methodological issues (e.g., stimulation parameters, stimulated brain area), or to participants’ expectations and beliefs before and during the stimulation sessions. In this narrative review, we present some studies showing that placebo and nocebo effects, associated with positive and negative expectations, respectively, could be present in NIBS trials, both in experimental and in clinical settings. The lack of systematic evaluation of subjective expectations and beliefs before and after stimulation could represent a caveat that overshadows the potential contribution of placebo and nocebo effects in the outcome of NIBS trials.

Believing is achieving - On the role of treatment expectation in neurofeedback applications

In neurofeedback applications, neural activity is recorded, processed in real-time and fed back to the user in order to facilitate self-regulation of the putative neural mechanisms that underlie cognition and behavior. Numerous studies suggest that neurofeedback interventions are an efficacious treatment particularly for patients with attention-deficit/hyperactivity disorder (ADHD). In recent years, however, findings of several well-controlled studies raised doubts concerning the proposed mechanism of action behind the behavioral effect of neurofeedback. This study investigated the impact of expectation on the efficacy of a sensorimotor rhythm (SMR) training. In a within-subjects design 30 blinded volunteers with ADHD symptoms received a standard SMR training session after inducing no (no-expectancy condition), positive (placebo condition), and negative (nocebo condition) expectations regarding the effectiveness of neurofeedback (by telling them that they would train a specific frequency band that was previously shown to be either unrelated to attention, should improve attention, or interfere with attentional processes). After each training, participants were presented with a cognitive test and subsequently requested to rate their performance on it. We could show that participants were able to successfully modify their EEG signal during training. Further, we found an effect over trainings on objective attentional performance. Most importantly, we found that the expectancy of positive or negative treatment effects considerably changed participants' perception of neurofeedback's efficacy even in the absence of any objective evidence. This study presents strong first evidence for a substantial effect of self-confirming response expectancies as one factor underlying the efficacy of neurofeedback. Future research has to carefully consider the impact of such psychosocial mechanisms when evaluating the (specific) efficacy of neuromodulatory treatments.

Impact of placebo-related instruction on HEG biofeedback outcomes in children with ADHD

Studies to date have not revealed any differences between biofeedback (BFB) methods vs. placebo treatment in reducing ADHD symptoms. The purpose of this randomized controlled study was to assess the impact of placebo expectations on gain in hemoencephalographic (HEG) BFB. The final cohort consisted of 33 children with ADHD aged 9-14. Individuals were assigned to one of two groups (with standard active training instruction vs. placebo-related instruction) and were subjected to five HEG BFB sessions. Children with standard instruction exhibited higher growth of regional cerebral blood oxygenation during the HEG BFB session as well as better results in cognitive tests (vigilance and visual search) at the end of the experiment compared to children with placebo-related instruction. The data obtained indicate the difficulty in designing studies assessing BFB efficacy. Placebo expectation may adversely affect HEG BFB outcomes in children with ADHD.

Scalp electroencephalograms over ipsilateral sensorimotor cortex reflect contraction patterns of unilateral finger muscles

A variety of neural substrates are implicated in the initiation, coordination, and stabilization of voluntary movements underpinned by adaptive contraction and relaxation of agonist and antagonist muscles. To achieve such flexible and purposeful control of the human body, brain systems exhibit extensive modulation during the transition from resting state to motor execution and to maintain proper joint impedance. However, the neural structures contributing to such sensorimotor control under unconstrained and naturalistic conditions are not fully characterized. To elucidate which brain regions are implicated in generating and coordinating voluntary movements, we employed a physiologically inspired, two-stage method to decode relaxation and three patterns of contraction in unilateral finger muscles (i.e., extension, flexion, and co-contraction) from high-density scalp electroencephalograms (EEG). The decoder consisted of two parts employed in series. The first discriminated between relaxation and contraction. If the EEG data were discriminated as contraction, the second stage then discriminated among the three contraction patterns. Despite the difficulty in dissociating detailed contraction patterns of muscles within a limb from scalp EEG signals, the decoder performance was higher than chance-level by 2-fold in the four-class classification. Moreover, weighted features in the trained decoders revealed EEG features differentially contributing to decoding performance. During the first stage, consistent with previous reports, weighted features were localized around sensorimotor cortex (SM1) contralateral to the activated fingers, while those during the second stage were localized around ipsilateral SM1. The loci of these weighted features suggested that the coordination of unilateral finger muscles induced different signaling patterns in ipsilateral SM1 contributing to motor control. Weighted EEG features enabled a deeper understanding of human sensorimotor processing as well as of a more naturalistic control of brain-computer interfaces.

Individual variation in alpha neurofeedback training efficacy predicts pain modulation

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Sensorimotor alpha neurofeedback training effect on pain perception was assessed.

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Neurofeedback training decreased the sensory-discriminative aspect of pain.

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Neurofeedback training increased the affective-motivational aspect of pain.

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Pain modulation by neurofeedback training was dependent upon the training efficacy.

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Neurofeedback training efficacy predicted sensory-discriminative pain modulation.

Studies have shown an association between sensorimotor α-oscillation and pain perception. It suggests the potential use of neurofeedback (NFB) training for pain modulation through modifying sensorimotor α-oscillation. Here, a single-session NFB training protocol targeted on increasing sensorimotor α-oscillations was applied to forty-five healthy participants. Pain thresholds to nociceptive laser stimulations and pain ratings (intensity and unpleasantness) to identical laser painful stimulations were assessed immediately before and after NFB training. Participants had larger pain thresholds, but rated the identical painful laser stimulation as more unpleasant after NFB training. These pain measurements were further compared between participants with high or low NFB training efficacy that was quantified as the regression slope of α-oscillation throughout the ten training blocks. A significant increase in pain thresholds was observed among participants with high-efficacy; whereas a significant increase in pain ratings was observed among participants with low-efficacy. These results suggested that NFB training decreased the sensory-discriminative aspect of pain, but increased the affective-motivational aspect of pain, whereas both pain modulations were dependent upon the NFB training efficacy. Importantly, correlation analysis across all participants revealed that a greater NFB training efficacy predicted a greater increase in pain thresholds particularly at hand contralateral to NFB target site, but no significant correlation was observed between NFB training efficacy and modulation on pain ratings. It thus provided causal evidence for a link between sensorimotor α-oscillation and the sensory-discriminative aspect of pain, and highlighted the need for personalized neurofeedback for the benefits on pain modulation at the individual level. Future studies can adopt a double-blind sham-controlled protocol to validate NFB training induced pain modulation.

Neurofeedback of scalp bi-hemispheric EEG sensorimotor rhythm guides hemispheric activation of sensorimotor cortex in the targeted hemisphere

Oscillatory electroencephalographic (EEG) activity is associated with the excitability of cortical regions. Visual feedback of EEG-oscillations may promote sensorimotor cortical activation, but its spatial specificity is not truly guaranteed due to signal interaction among interhemispheric brain regions. Guiding spatially specific activation is important for facilitating neural rehabilitation processes. Here, we tested whether users could explicitly guide sensorimotor cortical activity to the contralateral or ipsilateral hemisphere using a spatially bivariate EEG-based neurofeedback that monitors bi-hemispheric sensorimotor cortical activities for healthy participants. Two different motor imageries (shoulder and hand MIs) were selected to see how differences in intrinsic corticomuscular projection patterns might influence activity lateralization. We showed sensorimotor cortical activities during shoulder, but not hand MI, can be brought under ipsilateral control with guided EEG-based neurofeedback. These results are compatible with neuroanatomy; shoulder muscles are innervated bihemispherically, whereas hand muscles are mostly innervated contralaterally. We demonstrate the neuroanatomically-inspired approach enables us to investigate potent neural remodeling functions that underlie EEG-based neurofeedback via a BCI.

How Much Do Strategy Reports Tell About the Outcomes of Neurofeedback Training? A Study on the Voluntary Up-Regulation of the Sensorimotor Rhythm

The core learning mechanisms of neurofeedback (NF) training are associative, implicit, and, consequently, largely impervious to consciousness. Many other aspects of training that determine training outcomes, however, are accessible to conscious processing. The outcomes of sensorimotor rhythm (SMR) up-regulation training are related to the strategies reported by participants. The classification methods of individual strategies employed hitherto were possibly under influence of the idiosyncratic interpretation of the rater. To measure and possibly overcome this limitation, we employed independent raters to analyze strategies reported during SMR up-regulation training. Sixty-two healthy young participants took part in a single session of SMR up-regulation training. After completing six blocks of training, in which they received either simple visual feedback or a gamified version thereof, participants were required to report the strategies employed. Their individual learning outcomes were computed as well. Results point out that individual strategies as well as NF learning outcomes were not particularly sensitive to the presence of gamified elements in training the SMR up-regulation. A high degree of consistency across independent raters classifying strategy reports was observed. Some strategies were more typical of responders while other ones were more common among non-responders. In summary, we demonstrate a more objective and transparent way to analyze individual mental strategies to shed more light on the differences between NF responders and non-responders.

Yes, I can - maybe … Effects of placebo-related instructions on neuroregulation in children with ADHD

Neurofeedback training (NFT) provides strategies for children with ADHD to achieve changes on the neurophysiological and behavioral level to attenuate ADHD symptoms. We assume self-efficacy (an "active attitude"), a core variable in successful NFT. In a randomized, double-blind controlled study, we investigated the impact of a "placebo instruction" on the EEG-regulation performance during two sessions of Theta-Beta-NFT in children with ADHD (age 8-12 years). Children receiving the information "this might be a placebo-training" showed inferior neuroregulation (n = 10) compared to children receiving a standard instruction (n = 12). Results of our pilot study are discussed in view of factors necessary for a valid training (ensuring maximal self-efficacy in the participants) and the fidelity of placebo-controlled trials in NFT-research.

Alpha down-regulation neurofeedback training effects on implicit motor learning and consolidation

OBJECTIVE

Implicit motor learning, which is a non-conscious form of learning characterized by motor performance improvement with practice, plays an essential role in various daily activities. Earlier study using neurofeedback training (NFT), a type of brain-computer interaction that enables the user to learn self-regulating his/her own brain activity, demonstrated that down-regulating alpha over primary motor cortex by NFT could immediately facilitate the implicit motor learning in a relatively simple motor task. However, detailed effects on EEG and implicit motor learning due to NFT especially in a more complex motor task are still unclear.

APPROACH

We designed a single-blind sham-controlled between-subject study to examine whether alpha down-regulation NFT could facilitate implicit motor learning and also its consolidation in a more difficult and motor predominant task. At left primary motor cortex (C3) in two days, the alpha NFT group received alpha down-regulation training through auditory feedback while the sham-control group received random beta NFT. At the end of NFT, all participants performed the continuous tracking task with their dominant (right) hand to evaluate the implicit motor learning immediately. Finally, the continuous tracking task was performed again on the next day to assess consolidation effects.

MAIN RESULTS

The alpha NFT group successfully decreased alpha amplitude during NFT, whereas the sham-control group maintained alpha at a relatively stable level. There was unfortunately no statistical evidence proving that the alpha NFT group significantly enhanced the implicit motor learning at the end of NFT and the consolidation on the next day compared to the sham-control group. Nevertheless, a significant correlation was found between the alpha change trend during NFT and the implicit motor learning for all participants, suggesting that faster alpha down-regulation was associated with better implicit motor learning.

SIGNIFICANCE

The findings suggested a close link between implicit motor learning and alpha change induced by NFT.

Real-Time Functional Connectivity-Informed Neurofeedback of Amygdala-Frontal Pathways Reduces Anxiety

BACKGROUND

Deficient emotion regulation and exaggerated anxiety represent a major transdiagnostic psychopathological marker. On the neural level these deficits have been closely linked to impaired, yet treatment-sensitive, prefrontal regulatory control over the amygdala. Gaining direct control over these pathways could therefore provide an innovative and promising intervention to regulate exaggerated anxiety. To this end the current proof-of-concept study evaluated the feasibility, functional relevance and maintenance of a novel connectivity-informed real-time fMRI neurofeedback training.

METHODS

In a randomized crossover sham-controlled design, 26 healthy subjects with high anxiety underwent real-time fMRI-guided neurofeedback training to enhance connectivity between the ventrolateral prefrontal cortex (vlPFC) and the amygdala (target pathway) during threat exposure. Maintenance of regulatory control was assessed after 3 days and in the absence of feedback. Training-induced changes in functional connectivity of the target pathway and anxiety ratings served as primary outcomes.

RESULTS

Training of the target, yet not the sham control, pathway significantly increased amygdala-vlPFC connectivity and decreased levels of anxiety. Stronger connectivity increases were significantly associated with higher anxiety reduction on the group level. At the follow-up, volitional control over the target pathway was maintained in the absence of feedback.

CONCLUSIONS

The present results demonstrate for the first time that successful self-regulation of amygdala-prefrontal top-down regulatory circuits may represent a novel intervention to control anxiety. As such, the present findings underscore both the critical contribution of amygdala-prefrontal circuits to emotion regulation and the therapeutic potential of connectivity-informed real-time neurofeedback.

Sham tDCS: A hidden source of variability? Reflections for further blinded, controlled trials

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation technique increasingly used to modulate neural activity in the living brain. In order to establish the neurophysiological, cognitive or clinical effects of tDCS, most studies compare the effects of active tDCS to those observed with a sham tDCS intervention. In most cases, sham tDCS consists in delivering an active stimulation for a few seconds to mimic the sensations observed with active tDCS and keep participants blind to the intervention. However, to date, sham-controlled tDCS studies yield inconsistent results, which might arise in part from sham inconsistencies. Indeed, a multiplicity of sham stimulation protocols is being used in the tDCS research field and might have different biological effects beyond the intended transient sensations. Here, we seek to enlighten the scientific community to this possible confounding factor in order to increase reproducibility of neurophysiological, cognitive and clinical tDCS studies.