Visual hallucinations originating in the retinofugal pathway under clinical and psychedelic conditions

Psychedelics like LSD (Lysergic acid diethylamide) and psilocybin are known to modulate perceptual modalities due to the activation of mostly serotonin receptors in specific cortical (e.g., visual cortex) and subcortical (e.g., thalamus) regions of the brain. In the visual domain, these psychedelic modulations often result in peculiar disturbances of viewed objects and light and sometimes even in hallucinations of non-existent environments, objects, and creatures. Although the underlying processes are poorly understood, research conducted over the past twenty years on the subjective experience of psychedelics details theories that attempt to explain these perceptual alterations due to a disruption of communication between cortical and subcortical regions. However, rare medical conditions in the visual system like Charles Bonnet syndrome that cause perceptual distortions may shed new light on the additional importance of the retinofugal pathway in psychedelic subjective experiences. Interneurons in the retina called amacrine cells could be the first site of visual psychedelic modulation and aid in disrupting the hierarchical structure of how humans perceive visual information. This paper presents an understanding of how the retinofugal pathway communicates and modulates visual information in psychedelic and clinical conditions. Therefore, we elucidate a new theory of psychedelic modulation in the retinofugal pathway.

Acoustic-electric trigeminal-nerve stimulation enhances functional connectivity in patients with disorders of consciousness

AIM

Disruption of functional brain connectivity is thought to underlie disorders of consciousness (DOC) and recovery of impaired connectivity is suggested as an indicator of consciousness restoration. We recently found that rhythmic acoustic-electric trigeminal-nerve stimulation (i.e., musical stimulation synchronized to electrical stimulation of the trigeminal nerve) in the gamma band can improve consciousness in patients with DOC. Here, we investigated whether these beneficial stimulation effects are mediated by alterations in functional connectivity.

METHODS

Sixty-three patients with DOC underwent 5 days of gamma, beta, or sham acoustic-electric trigeminal-nerve stimulation. Resting-state electroencephalography was measured before and after the stimulation and functional connectivity was assessed using phase-lag index (PLI).

RESULTS

We found that gamma stimulation induces an increase in gamma-band PLI. Further characterization revealed that the enhancing effect is (i) specific to the gamma band (as we observed no comparable change in beta-band PLI and no effect of beta-band acoustic-electric stimulation or sham stimulation), (ii) widely spread across the cortex, and (iii) accompanied by improvements in patients' auditory abilities.

CONCLUSION

These findings show that gamma acoustic-electric trigeminal-nerve stimulation can improve resting-state functional connectivity in the gamma band, which in turn may be linked to auditory abilities and/or consciousness restoration in DOC patients.

It takes two (seconds): decreasing encoding time for two-choice functional near-infrared spectroscopy brain-computer interface communication

Significance

Brain-computer interfaces (BCIs) can provide severely motor-impaired patients with a motor-independent communication channel. Functional near-infrared spectroscopy (fNIRS) constitutes a promising BCI-input modality given its high mobility, safety, user comfort, cost-efficiency, and relatively low motion sensitivity.

Aim

The present study aimed at developing an efficient and convenient two-choice fNIRS communication BCI by implementing a relatively short encoding time (2 s), considerably increasing communication speed, and decreasing the cognitive load of BCI users.

Approach

To encode binary answers to 10 biographical questions, 10 healthy adults repeatedly performed a combined motor-speech imagery task within 2 different time windows guided by auditory instructions. Each answer-encoding run consisted of 10 trials. Answers were decoded during the ongoing experiment from the time course of the individually identified most-informative fNIRS channel-by-chromophore combination.

Results

The answers of participants were decoded online with an accuracy of 85.8% (run-based group mean). Post-hoc analysis yielded an average single-trial accuracy of 68.1%. Analysis of the effect of number of trial repetitions showed that the best information-transfer rate could be obtained by combining four encoding trials.

Conclusions

The study demonstrates that an encoding time as short as 2 s can enable immediate, efficient, and convenient fNIRS-BCI communication.

Talking with hands and feet: Selective somatosensory attention and fMRI enable robust and convenient brain-based communication

In brain-based communication, voluntarily modulated brain signals (instead of motor output) are utilized to interact with the outside world. The possibility to circumvent the motor system constitutes an important alternative option for severely paralyzed. Most communication brain-computer interface (BCI) paradigms require intact visual capabilities and impose a high cognitive load, but for some patients, these requirements are not given. In these situations, a better-suited, less cognitively demanding information-encoding approach may exploit auditorily-cued selective somatosensory attention to vibrotactile stimulation. Here, we propose, validate and optimize a novel communication-BCI paradigm using differential fMRI activation patterns evoked by selective somatosensory attention to tactile stimulation of the right hand or left foot. Using cytoarchitectonic probability maps and multi-voxel pattern analysis (MVPA), we show that the locus of selective somatosensory attention can be decoded from fMRI-signal patterns in (especially primary) somatosensory cortex with high accuracy and reliability, with the highest classification accuracy (85.93%) achieved when using Brodmann area 2 (SI-BA2) at a probability level of 0.2. Based on this outcome, we developed and validated a novel somatosensory attention-based yes/no communication procedure and demonstrated its high effectiveness even when using only a limited amount of (MVPA) training data. For the BCI user, the paradigm is straightforward, eye-independent, and requires only limited cognitive functioning. In addition, it is BCI-operator friendly given its objective and expertise-independent procedure. For these reasons, our novel communication paradigm has high potential for clinical applications.

Magnetic resonance imaging at 9.4 T: the Maastricht journey

The 9.4 T scanner in Maastricht is a whole-body magnet with head gradients and parallel RF transmit capability. At the time of the design, it was conceptualized to be one of the best fMRI scanners in the world, but it has also been used for anatomical and diffusion imaging. 9.4 T offers increases in sensitivity and contrast, but the technical ultra-high field (UHF) challenges, such as field inhomogeneities and constraints set by RF power deposition, are exacerbated compared to 7 T. This article reviews some of the 9.4 T work done in Maastricht. Functional imaging experiments included blood oxygenation level-dependent (BOLD) and blood-volume weighted (VASO) fMRI using different readouts. BOLD benefits from shorter T₂* at 9.4 T while VASO from longer T₁. We show examples of both ex vivo and in vivo anatomical imaging. For many applications, pTx and optimized coils are essential to harness the full potential of 9.4 T. Our experience shows that, while considerable effort was required compared to our 7 T scanner, we could obtain high-quality anatomical and functional data, which illustrates the potential of MR acquisitions at even higher field strengths. The practical challenges of working with a relatively unique system are also discussed.

Rhythmic musical-electrical trigeminal nerve stimulation improves impaired consciousness

Accumulating evidence shows that consciousness is linked to neural oscillations in the thalamocortical system, suggesting that deficits in these oscillations may underlie disorders of consciousness (DOC). However, patient-friendly non-invasive treatments targeting this functional anomaly are still missing and the therapeutic value of oscillation restoration has remained unclear. We propose a novel approach that aims to restore DOC patients' thalamocortical oscillations by combining rhythmic trigeminal-nerve stimulation with comodulated musical stimulation ("musical-electrical TNS"). In a double-blind, placebo-controlled, parallel-group study, we recruited 63 patients with DOC and randomly assigned them to groups receiving gamma, beta, or sham musical-electrical TNS. The stimulation was applied for 40 min on five consecutive days. We measured patients' consciousness before and after the stimulation using behavioral indicators and neural responses to rhythmic auditory speech. We further assessed their outcomes one year later. We found that musical-electrical TNS reliably lead to improvements in consciousness and oscillatory brain activity at the stimulation frequency: 43.5 % of patients in the gamma group and 25 % of patients in the beta group showed an improvement of their diagnosis after being treated with the stimulation. This group of benefitting patients still showed more positive outcomes one year later. Moreover, patients with stronger behavioral benefits showed stronger improvements in oscillatory brain activity. These findings suggest that brain oscillations contribute to consciousness and that musical-electrical TNS may serve as a promising approach to improve consciousness and predict long-term outcomes in patients with DOC.

See, Hear, or Feel - to Speak: A Versatile Multiple-Choice Functional Near-Infrared Spectroscopy-Brain-Computer Interface Feasible With Visual, Auditory, or Tactile Instructions

Severely motor-disabled patients, such as those suffering from the so-called "locked-in" syndrome, cannot communicate naturally. They may benefit from brain-computer interfaces (BCIs) exploiting brain signals for communication and therewith circumventing the muscular system. One BCI technique that has gained attention recently is functional near-infrared spectroscopy (fNIRS). Typically, fNIRS-based BCIs allow for brain-based communication via voluntarily modulation of brain activity through mental task performance guided by visual or auditory instructions. While the development of fNIRS-BCIs has made great progress, the reliability of fNIRS-BCIs across time and environments has rarely been assessed. In the present fNIRS-BCI study, we tested six healthy participants across three consecutive days using a straightforward four-choice fNIRS-BCI communication paradigm that allows answer encoding based on instructions using various sensory modalities. To encode an answer, participants performed a motor imagery task (mental drawing) in one out of four time periods. Answer encoding was guided by either the visual, auditory, or tactile sensory modality. Two participants were tested outside the laboratory in a cafeteria. Answers were decoded from the time course of the most-informative fNIRS channel-by-chromophore combination. Across the three testing days, we obtained mean single- and multi-trial (joint analysis of four consecutive trials) accuracies of 62.5 and 85.19%, respectively. Obtained multi-trial accuracies were 86.11% for visual, 80.56% for auditory, and 88.89% for tactile sensory encoding. The two participants that used the fNIRS-BCI in a cafeteria obtained the best single- (72.22 and 77.78%) and multi-trial accuracies (100 and 94.44%). Communication was reliable over the three recording sessions with multi-trial accuracies of 86.11% on day 1, 86.11% on day 2, and 83.33% on day 3. To gauge the trade-off between number of optodes and decoding accuracy, averaging across two and three promising fNIRS channels was compared to the one-channel approach. Multi-trial accuracy increased from 85.19% (one-channel approach) to 91.67% (two-/three-channel approach). In sum, the presented fNIRS-BCI yielded robust decoding results using three alternative sensory encoding modalities. Further, fNIRS-BCI communication was stable over the course of three consecutive days, even in a natural (social) environment. Therewith, the developed fNIRS-BCI demonstrated high flexibility, reliability and robustness, crucial requirements for future clinical applicability.

Selective auditory attention within naturalistic scenes modulates reactivity to speech sounds

Rapid recognition and categorization of sounds are essential for humans and animals alike, both for understanding and reacting to our surroundings and for daily communication and social interaction. For humans, perception of speech sounds is of crucial importance. In real life, this task is complicated by the presence of a multitude of meaningful non‐speech sounds. The present behavioural, magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) study was set out to address how attention to speech versus attention to natural non‐speech sounds within complex auditory scenes influences cortical processing. The stimuli were superimpositions of spoken words and environmental sounds, with parametric variation of the speech‐to‐environmental sound intensity ratio. The participants' task was to detect a repetition in either the speech or the environmental sound. We found that specifically when participants attended to speech within the superimposed stimuli, higher speech‐to‐environmental sound ratios resulted in shorter sustained MEG responses and stronger BOLD fMRI signals especially in the left supratemporal auditory cortex and in improved behavioural performance. No such effects of speech‐to‐environmental sound ratio were observed when participants attended to the environmental sound part within the exact same stimuli. These findings suggest stronger saliency of speech compared with other meaningful sounds during processing of natural auditory scenes, likely linked to speech‐specific top‐down and bottom‐up mechanisms activated during speech perception that are needed for tracking speech in real‐life‐like auditory environments.

Holistic processing only? The role of the right fusiform face area in radiological expertise

Radiologists can visually detect abnormalities on radiographs within 2s, a process that resembles holistic visual processing of faces. Interestingly, there is empirical evidence using functional magnetic resonance imaging (fMRI) for the involvement of the right fusiform face area (FFA) in visual-expertise tasks such as radiological image interpretation. The speed by which stimuli (e.g., faces, abnormalities) are recognized is an important characteristic of holistic processing. However, evidence for the involvement of the right FFA in holistic processing in radiology comes mostly from short or artificial tasks in which the quick, ‘holistic’ mode of diagnostic processing is not contrasted with the slower ‘search-to-find’ mode. In our fMRI study, we hypothesized that the right FFA responds selectively to the ‘holistic’ mode of diagnostic processing and less so to the ‘search-to-find’ mode. Eleven laypeople and 17 radiologists in training diagnosed 66 radiographs in 2s each (holistic mode) and subsequently checked their diagnosis in an extended (10-s) period (search-to-find mode). During data analysis, we first identified individual regions of interest (ROIs) for the right FFA using a localizer task. Then we employed ROI-based ANOVAs and obtained tentative support for the hypothesis that the right FFA shows more activation for radiologists in training versus laypeople, in particular in the holistic mode (i.e., during 2s trials), and less so in the search-to-find mode (i.e., during 10-s trials). No significant correlation was found between diagnostic performance (diagnostic accuracy) and brain-activation level within the right FFA for both, short-presentation and long-presentation diagnostic trials. Our results provide tentative evidence from a diagnostic-reasoning task that the FFA supports the holistic processing of visual stimuli in participants’ expertise domain.

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. Here, for the first time, we employed a big data machine learning approach to investigate the influence of 20 different design-specific (e.g. activity vs. connectivity feedback), region of interest-specific (e.g. cortical vs. subcortical) and subject-specific factors (e.g. age) on neurofeedback performance and improvement in 608 participants from 28 independent experiments. With a classification accuracy of 60% (considerably different from chance level), we identified two factors that significantly influenced neurofeedback performance: Both the inclusion of a pre-training no-feedback run before neurofeedback training and neurofeedback training of patients as compared to healthy participants were associated with better neurofeedback performance. The positive effect of pre-training no-feedback runs on neurofeedback performance might be due to the familiarization of participants with the neurofeedback setup and the mental imagery task before neurofeedback training runs. Better performance of patients as compared to healthy participants might be driven by higher motivation of patients, higher ranges for the regulation of dysfunctional brain signals, or a more extensive piloting of clinical experimental paradigms. Due to the large heterogeneity of our dataset, these findings likely generalize across neurofeedback studies, thus providing guidance for designing more efficient neurofeedback studies specifically for improving clinical neurofeedback-based interventions. To facilitate the development of data-driven recommendations for specific design details and subpopulations the field would benefit from stronger engagement in open science research practices and data sharing.

Guiding functional near-infrared spectroscopy optode-layout design using individual (f)MRI data: effects on signal strength

Significance: Designing optode layouts is an essential step for functional near-infrared spectroscopy (fNIRS) experiments as the quality of the measured signal and the sensitivity to cortical regions-of-interest depend on how optodes are arranged on the scalp. This becomes particularly relevant for fNIRS-based brain-computer interfaces (BCIs), where developing robust systems with few optodes is crucial for clinical applications. Aim: Available resources often dictate the approach researchers use for optode-layout design. We investigated whether guiding optode layout design using different amounts of subject-specific magnetic resonance imaging (MRI) data affects the fNIRS signal quality and sensitivity to brain activation when healthy participants perform mental-imagery tasks typically used in fNIRS-BCI experiments. Approach: We compared four approaches that incrementally incorporated subject-specific MRI information while participants performed mental-calculation, mental-rotation, and inner-speech tasks. The literature-based approach (LIT) used a literature review to guide the optode layout design. The probabilistic approach (PROB) employed individual anatomical data and probabilistic maps of functional MRI (fMRI)-activation from an independent dataset. The individual fMRI (iFMRI) approach used individual anatomical and fMRI data, and the fourth approach used individual anatomical, functional, and vascular information of the same subject (fVASC). Results: The four approaches resulted in different optode layouts and the more informed approaches outperformed the minimally informed approach (LIT) in terms of signal quality and sensitivity. Further, PROB, iFMRI, and fVASC approaches resulted in a similar outcome. Conclusions: We conclude that additional individual MRI data lead to a better outcome, but that not all the modalities tested here are required to achieve a robust setup. Finally, we give preliminary advice to efficiently using resources for developing robust optode layouts for BCI and neurofeedback applications.

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.

The Potential of Functional Near-Infrared Spectroscopy-Based Neurofeedback-A Systematic Review and Recommendations for Best Practice

Background: The effects of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI)-neurofeedback on brain activation and behaviors have been studied extensively in the past. More recently, researchers have begun to investigate the effects of functional near-infrared spectroscopy-based neurofeedback (fNIRS-neurofeedback). FNIRS is a functional neuroimaging technique based on brain hemodynamics, which is easy to use, portable, inexpensive, and has reduced sensitivity to movement artifacts.

Method: We provide the first systematic review and database of fNIRS-neurofeedback studies, synthesizing findings from 22 peer-reviewed studies (including a total of N = 441 participants; 337 healthy, 104 patients). We (1) give a comprehensive overview of how fNIRS-neurofeedback training protocols were implemented, (2) review the online signal-processing methods used, (3) evaluate the quality of studies using pre-set methodological and reporting quality criteria and also present statistical sensitivity/power analyses, (4) investigate the effectiveness of fNIRS-neurofeedback in modulating brain activation, and (5) review its effectiveness in changing behavior in healthy and pathological populations.

Results and discussion: (1–2) Published studies are heterogeneous (e.g., neurofeedback targets, investigated populations, applied training protocols, and methods). (3) Large randomized controlled trials are still lacking. In view of the novelty of the field, the quality of the published studies is moderate. We identified room for improvement in reporting important information and statistical power to detect realistic effects. (4) Several studies show that people can regulate hemodynamic signals from cortical brain regions with fNIRS-neurofeedback and (5) these studies indicate the feasibility of modulating motor control and prefrontal brain functioning in healthy participants and ameliorating symptoms in clinical populations (stroke, ADHD, autism, and social anxiety). However, valid conclusions about specificity or potential clinical utility are premature.

Conclusion: Due to the advantages of practicability and relatively low cost, fNIRS-neurofeedback might provide a suitable and powerful alternative to EEG and fMRI neurofeedback and has great potential for clinical translation of neurofeedback. Together with more rigorous research and reporting practices, further methodological improvements may lead to a more solid understanding of fNIRS-neurofeedback. Future research will benefit from exploiting the advantages of fNIRS, which offers unique opportunities for neurofeedback research.

Consensus on the reporting and experimental design of clinical and cognitive-behavioural neurofeedback studies (CRED-nf checklist)

Neurofeedback has begun to attract the attention and scrutiny of the scientific and medical mainstream. Here, neurofeedback researchers present a consensus-derived checklist that aims to improve the reporting and experimental design standards in the field.

An Augmented-Reality fNIRS-Based Brain-Computer Interface: A Proof-of-Concept Study

Augmented reality (AR) enhances the user's environment by projecting virtual objects into the real world in real-time. Brain-computer interfaces (BCIs) are systems that enable users to control external devices with their brain signals. BCIs can exploit AR technology to interact with the physical and virtual world and to explore new ways of displaying feedback. This is important for users to perceive and regulate their brain activity or shape their communication intentions while operating in the physical world. In this study, twelve healthy participants were introduced to and asked to choose between two motor-imagery tasks: mental drawing and interacting with a virtual cube. Participants first performed a functional localizer run, which was used to select a single fNIRS channel for decoding their intentions in eight subsequent choice-encoding runs. In each run participants were asked to select one choice of a six-item list. A rotating AR cube was displayed on a computer screen as the main stimulus, where each face of the cube was presented for 6 s and represented one choice of the six-item list. For five consecutive trials, participants were instructed to perform the motor-imagery task when the face of the cube that represented their choice was facing them (therewith temporally encoding the selected choice). In the end of each run, participants were provided with the decoded choice based on a joint analysis of all five trials. If the decoded choice was incorrect, an active error-correction procedure was applied by the participant. The choice list provided in each run was based on the decoded choice of the previous run. The experimental design allowed participants to navigate twice through a virtual menu that consisted of four levels if all choices were correctly decoded. Here we demonstrate for the first time that by using AR feedback and flexible choice encoding in form of search trees, we can increase the degrees of freedom of a BCI system. We also show that participants can successfully navigate through a nested menu and achieve a mean accuracy of 74% using a single motor-imagery task and a single fNIRS channel.

Brain-Based Binary Communication Using Spatiotemporal Features of fNIRS Responses

“Locked-in” patients lose their ability to communicate naturally due to motor system dysfunction. Brain-computer interfacing offers a solution for their inability to communicate by enabling motor-independent communication. Straightforward and convenient in-session communication is essential in clinical environments. The present study introduces a functional near-infrared spectroscopy (fNIRS)-based binary communication paradigm that requires limited preparation time and merely nine optodes. Eighteen healthy participants performed two mental imagery tasks, mental drawing and spatial navigation, to answer yes/no questions during one of two auditorily cued time windows. Each of the six questions was answered five times, resulting in five trials per answer. This communication paradigm thus combines both spatial (two different mental imagery tasks, here mental drawing for “yes” and spatial navigation for “no”) and temporal (distinct time windows for encoding a “yes” and “no” answer) fNIRS signal features for information encoding. Participants’ answers were decoded in simulated real-time using general linear model analysis. Joint analysis of all five encoding trials resulted in an average accuracy of 66.67 and 58.33% using the oxygenated (HbO) and deoxygenated (HbR) hemoglobin signal respectively. For half of the participants, an accuracy of 83.33% or higher was reached using either the HbO signal or the HbR signal. For four participants, effective communication with 100% accuracy was achieved using either the HbO or HbR signal. An explorative analysis investigated the differentiability of the two mental tasks based solely on spatial fNIRS signal features. Using multivariate pattern analysis (MVPA) group single-trial accuracies of 58.33% (using 20 training trials per task) and 60.56% (using 40 training trials per task) could be obtained. Combining the five trials per run using a majority voting approach heightened these MVPA accuracies to 62.04 and 75%. Additionally, an fNIRS suitability questionnaire capturing participants’ physical features was administered to explore its predictive value for evaluating general data quality. Obtained questionnaire scores correlated significantly (r = -0.499) with the signal-to-noise of the raw light intensities. While more work is needed to further increase decoding accuracy, this study shows the potential of answer encoding using spatiotemporal fNIRS signal features or spatial fNIRS signal features only.

Real-time fMRI for brain-computer interfacing

Brain-computer interfaces (BCIs) based on functional magnetic resonance imaging (fMRI) provide an important complement to other noninvasive BCIs. While fMRI has several disadvantages (being nonportable, methodologically challenging, costly, and noisy), it is the only method providing high spatial resolution whole-brain coverage of brain activation. These properties allow relating mental activities to specific brain regions and networks providing a transparent scheme for BCI users to encode information and for real-time fMRI BCI systems to decode the intents of the user. Various mental activities have been used successfully in fMRI BCIs so far that can be classified into the four categories: (a) higher-order cognitive tasks (e.g., mental calculation), (b) covert language-related tasks (e.g., mental speech and mental singing), (c) imagery tasks (motor, visual, auditory, tactile, and emotion imagery), and (d) selective attention tasks (visual, auditory, and tactile attention). While the ultimate spatial and temporal resolution of fMRI BCIs is limited by the physiologic properties of the hemodynamic response, technical and analytical advances will likely lead to substantially improved fMRI BCIs in the future using, for example, decoding of imagined letter shapes at 7T as the basis for more "natural" communication BCIs.

Topographic Somatosensory Imagery for Real-Time fMRI Brain-Computer Interfacing

Real-time functional magnetic resonance imaging (fMRI) is a promising non-invasive method for brain-computer interfaces (BCIs). BCIs translate brain activity into signals that allow communication with the outside world. Visual and motor imagery are often used as information-encoding strategies, but can be challenging if not grounded in recent experience in these modalities, e.g., in patients with locked-in-syndrome (LIS). In contrast, somatosensory imagery might constitute a more suitable information-encoding strategy as the somatosensory function is often very robust. Somatosensory imagery has been shown to activate the somatotopic cortex, but it has been unclear so far whether it can be reliably detected on a single-trial level and successfully classified according to specific somatosensory imagery content. Using ultra-high field 7-T fMRI, we show reliable and high-accuracy single-trial decoding of left-foot (LF) vs. right-hand (RH) somatosensory imagery. Correspondingly, higher decoding accuracies were associated with greater spatial separation of hand and foot decoding-weight patterns in the primary somatosensory cortex (S1). Exploiting these novel neuroscientific insights, we developed-and provide a proof of concept for-basic BCI communication by showing that binary (yes/no) answers encoded by somatosensory imagery can be decoded with high accuracy in simulated real-time (in 7 subjects) as well as in real-time (1 subject). This study demonstrates that body part-specific somatosensory imagery differentially activates somatosensory cortex in a topographically specific manner; evidence which was surprisingly still lacking in the literature. It also offers proof of concept for a novel somatosensory imagery-based fMRI-BCI control strategy, with particularly high potential for visually and motor-impaired patients. The strategy could also be transferred to lower MRI field strengths and to mobile functional near-infrared spectroscopy. Finally, given that communication BCIs provide the BCI user with a form of feedback based on their brain signals and can thus be considered as a specific form of neurofeedback, and that repeated use of a BCI has been shown to enhance underlying representations, we expect that the current BCI could also offer an interesting new approach for somatosensory rehabilitation training in the context of stroke and phantom limb pain.

Success and failure of controlling the real-time functional magnetic resonance imaging neurofeedback signal are reflected in the striatum

INTRODUCTION

Over the last decades, neurofeedback has been applied in variety of research contexts and therapeutic interventions. Despite this extensive use, its neural mechanisms are still under debate. Several scientific advances have suggested that different networks become jointly active during neurofeedback, including regions generally involved in self-regulation, regions related to the specific mental task driving the neurofeedback and regions generally involved in feedback learning (Sitaram et al., 2017, Nature Reviews Neuroscience, 18, 86).

METHODS

To investigate the neural mechanisms specific to neurofeedback but independent from general effects of self-regulation, we compared brain activation as measured with functional magnetic resonance imaging (fMRI) across different mental tasks involving gradual self-regulation with and without providing neurofeedback. Ten participants freely chose one self-regulation task and underwent two training sessions during fMRI scanning, one with and one without receiving neurofeedback. During neurofeedback sessions, feedback signals were provided in real-time based on activity in task-related, individually defined target regions. In both sessions, participants aimed at reaching and holding low, medium, or high brain-activation levels in the target region.

RESULTS

During gradual self-regulation with neurofeedback, a network of cortical control regions as well as regions implicated in reward and feedback processing were activated. Self-regulation with feedback was accompanied by stronger activation within the striatum across different mental tasks. Additional time-resolved single-trial analysis revealed that neurofeedback performance was positively correlated with a delayed brain response in the striatum that reflected the accuracy of self-regulation.

CONCLUSION

Overall, these findings support that neurofeedback contributes to self-regulation through task-general regions involved in feedback and reward processing.

Control freaks: Towards optimal selection of control conditions for fMRI neurofeedback studies

fMRI Neurofeedback research employs many different control conditions. Currently, there is no consensus as to which control condition is best, and the answer depends on what aspects of the neurofeedback-training design one is trying to control for. These aspects can range from determining whether participants can learn to control brain activity via neurofeedback to determining whether there are clinically significant effects of the neurofeedback intervention. Lack of consensus over criteria for control conditions has hampered the design and interpretation of studies employing neurofeedback protocols. This paper presents an overview of the most commonly employed control conditions currently used in neurofeedback studies and discusses their advantages and disadvantages. Control conditions covered include no control, treatment-as-usual, bidirectional-regulation control, feedback of an alternative brain signal, sham feedback, and mental-rehearsal control. We conclude that the selection of the control condition(s) should be determined by the specific research goal of the study and best procedures that effectively control for relevant confounding factors.

The prestimulus default mode network state predicts cognitive task performance levels on a mental rotation task

BACKGROUND

Linking individual task performance to preceding, regional brain activation is an ongoing goal of neuroscientific research. Recently, it could be shown that the activation and connectivity within large-scale brain networks prior to task onset influence performance levels. More specifically, prestimulus default mode network (DMN) effects have been linked to performance levels in sensory near-threshold tasks, as well as cognitive tasks. However, it still remains uncertain how the DMN state preceding cognitive tasks affects performance levels when the period between task trials is long and flexible, allowing participants to engage in different cognitive states.

METHODS

We here investigated whether the prestimulus activation and within-network connectivity of the DMN are predictive of the correctness and speed of task performance levels on a cognitive (match-to-sample) mental rotation task, employing a sparse event-related functional magnetic resonance imaging (fMRI) design.

RESULTS

We found that prestimulus activation in the DMN predicted the speed of correct trials, with a lower amplitude preceding correct fast response trials compared to correct slow response trials. Moreover, we found higher connectivity within the DMN before incorrect trials compared to correct trials.

CONCLUSION

These results indicate that pre-existing activation and connectivity states within the DMN influence task performance on cognitive tasks, both effecting the correctness and speed of task execution. The findings support existing theories and empirical work on relating mind-wandering and cognitive task performance to the DMN and expand these by establishing a relationship between the prestimulus DMN state and the speed of cognitive task performance.

The Neural Implementation of Surgical Expertise Within the Mirror-Neuron System: An fMRI Study

Motor expertise is an important aspect of high-level performance in professional tasks such as surgery. While recently it has been shown that brain activation as measured by functional magnetic resonance imaging (fMRI) within the mirror-neuron system (MNS) is modulated by expertise in sports and music, little is known about the neural underpinnings of professional, e.g., surgical expertise. Here, we investigated whether and (if so) how surgical expertise is implemented in the MNS in medical professionals across three levels of surgical qualification. In order to answer the more specific research question, namely, if the neural implementation of motor expertise develops in a linear or non-linear fashion, the study compares not only brain activation within the MNS related to action observation of novices and experts, but also intermediates. Ten novices (medical students), ten intermediates (residents in orthopedic surgery) and ten experts (orthopedic surgeons) watched 60 video clips (5 s each) of daily-life activities and surgical procedures each while their brain activation was measured using a 3-T fMRI scanner. An established localization procedure was followed to functionally define the MNS for each participant individually. A 2 (video type: daily-life activities, surgical procedures) × 3 (expertise level: novice, intermediate, expert) ANOVA yielded a non-significant interaction. Furthermore, separate analyses of the precentral and parietal part of the MNS also yielded non-significant interactions. However, post hoc comparisons showed that intermediates displayed marginally significantly lower brain activation in response to surgery-related videos within the MNS than novices. No other significant differences were found. We did not find evidence for the hypothesis that the brain-activation level in the MNS evoked by observing surgical videos reflects the level of surgical expertise in the professional task of (orthopedic) surgery. However, the results suggest a potential non-linear relationship between expertise level and MNS-activation level.

Do Patients Thought to Lack Consciousness Retain the Capacity for Internal as Well as External Awareness?

It is well established that some patients, who are deemed to have disorders of consciousness, remain entirely behaviorally non-responsive and are diagnosed as being in a vegetative state, yet can nevertheless demonstrate covert awareness of their external environment by modulating their brain activity, a phenomenon known as cognitive-motor dissociation. However, the extent to which these patients retain internal awareness remains unknown. To investigate the potential for internal and external awareness in patients with chronic disorders of consciousness (DoC), we asked whether the pattern of juxtaposition between the functional time-courses of the default mode (DMN) and fronto-parietal networks, shown in healthy individuals to mediate the naturally occurring dominance switching between internal and external aspects of consciousness, was present in these patients. We used a highly engaging movie by Alfred Hitchcock to drive the recruitment of the fronto-parietal networks, including the dorsal attention (DAN) and executive control (ECN) networks, and their maximal juxtaposition to the DMN in response to the complex stimulus, relative to rest and a scrambled, meaningless movie baseline condition. We tested a control group of healthy participants (N = 13/12) and two groups of patients with disorders of consciousness, one comprised of patients who demonstrated independent, neuroimaging-based evidence of covert external awareness (N = 8), and the other of those who did not (N = 8). Similarly to the healthy controls, only the group of patients with overt and, critically, covert external awareness showed significantly heightened differentiation between the DMN and the DAN in response to movie viewing relative to their resting state time-courses, which was driven by the movie's narrative. This result suggested the presence of functional integrity in the DMN and fronto-parietal networks and their relationship to one another in patients with covert external awareness. Similar to the effect in healthy controls, these networks became more strongly juxtaposed to one another in response to movie viewing relative to the baseline conditions, suggesting the potential for internal and external awareness during complex stimulus processing. Furthermore, our results suggest that naturalistic paradigms can dissociate between groups of DoC patients with and without covert awareness based on the functional integrity of brain networks.

Frequency-Selective Attention in Auditory Scenes Recruits Frequency Representations Throughout Human Superior Temporal Cortex

A sound of interest may be tracked amid other salient sounds by focusing attention on its characteristic features including its frequency. Functional magnetic resonance imaging findings have indicated that frequency representations in human primary auditory cortex (AC) contribute to this feat. However, attentional modulations were examined at relatively low spatial and spectral resolutions, and frequency-selective contributions outside the primary AC could not be established. To address these issues, we compared blood oxygenation level-dependent (BOLD) responses in the superior temporal cortex of human listeners while they identified single frequencies versus listened selectively for various frequencies within a multifrequency scene. Using best-frequency mapping, we observed that the detailed spatial layout of attention-induced BOLD response enhancements in primary AC follows the tonotopy of stimulus-driven frequency representations-analogous to the "spotlight" of attention enhancing visuospatial representations in retinotopic visual cortex. Moreover, using an algorithm trained to discriminate stimulus-driven frequency representations, we could successfully decode the focus of frequency-selective attention from listeners' BOLD response patterns in nonprimary AC. Our results indicate that the human brain facilitates selective listening to a frequency of interest in a scene by reinforcing the fine-grained activity pattern throughout the entire superior temporal cortex that would be evoked if that frequency was present alone.

Neural Entrainment to Speech Modulates Speech Intelligibility

Speech is crucial for communication in everyday life. Speech-brain entrainment, the alignment of neural activity to the slow temporal fluctuations (envelope) of acoustic speech input, is a ubiquitous element of current theories of speech processing. Associations between speech-brain entrainment and acoustic speech signal, listening task, and speech intelligibility have been observed repeatedly. However, a methodological bottleneck has prevented so far clarifying whether speech-brain entrainment contributes functionally to (i.e., causes) speech intelligibility or is merely an epiphenomenon of it. To address this long-standing issue, we experimentally manipulated speech-brain entrainment without concomitant acoustic and task-related variations, using a brain stimulation approach that enables modulating listeners' neural activity with transcranial currents carrying speech-envelope information. Results from two experiments involving a cocktail-party-like scenario and a listening situation devoid of aural speech-amplitude envelope input reveal consistent effects on listeners' speech-recognition performance, demonstrating a causal role of speech-brain entrainment in speech intelligibility. Our findings imply that speech-brain entrainment is critical for auditory speech comprehension and suggest that transcranial stimulation with speech-envelope-shaped currents can be utilized to modulate speech comprehension in impaired listening conditions.

Quantitative representations of an exaggerated anxiety response in the brain of female spider phobics-a parametric fMRI study

We employed a novel parametric spider picture set in the context of a parametric fMRI anxiety provocation study, designed to tease apart brain regions involved in threat monitoring from regions representing an exaggerated anxiety response in spider phobics. For the stimulus set, we systematically manipulated perceived proximity of threat by varying a depicted spider's context, size, and posture. All stimuli were validated in a behavioral rating study (phobics n = 20; controls n = 20; all female). An independent group participated in a subsequent fMRI anxiety provocation study (phobics n = 7; controls n = 7; all female), in which we compared a whole-brain categorical to a whole-brain parametric analysis. Results demonstrated that the parametric analysis provided a richer characterization of the functional role of the involved brain networks. In three brain regions-the mid insula, the dorsal anterior cingulate, and the ventrolateral prefrontal cortex-activation was linearly modulated by perceived proximity specifically in the spider phobia group, indicating a quantitative representation of an exaggerated anxiety response. In other regions (e.g., the amygdala), activation was linearly modulated in both groups, suggesting a functional role in threat monitoring. Prefrontal regions, such as dorsolateral prefrontal cortex, were activated during anxiety provocation but did not show a stimulus-dependent linear modulation in either group. The results confirm that brain regions involved in anxiety processing hold a quantitative representation of a pathological anxiety response and more generally suggest that parametric fMRI designs may be a very powerful tool for clinical research in the future, particularly when developing novel brain-based interventions (e.g., neurofeedback training). Hum Brain Mapp 38:3025-3038, 2017. © 2017 Wiley Periodicals, Inc.

fMRI Neurofeedback Training for Increasing Anterior Cingulate Cortex Activation in Adult Attention Deficit Hyperactivity Disorder. An Exploratory Randomized, Single-Blinded Study

Attention Deficit Hyperactivity Disorder (ADHD) is characterized by poor cognitive control/attention and hypofunctioning of the dorsal anterior cingulate cortex (dACC). In the current study, we investigated for the first time whether real-time fMRI neurofeedback (rt-fMRI) training targeted at increasing activation levels within dACC in adults with ADHD leads to a reduction of clinical symptoms and improved cognitive functioning. An exploratory randomized controlled treatment study with blinding of the participants was conducted. Participants with ADHD (n = 7 in the neurofeedback group, and n = 6 in the control group) attended four weekly MRI training sessions (60-min training time/session), during which they performed a mental calculation task at varying levels of difficulty, in order to learn how to up-regulate dACC activation. Only neurofeedback participants received continuous feedback information on actual brain activation levels within dACC. Before and after the training, ADHD symptoms and relevant cognitive functioning was assessed. Results showed that both groups achieved a significant increase in dACC activation levels over sessions. While there was no significant difference between the neurofeedback and control group in clinical outcome, neurofeedback participants showed stronger improvement on cognitive functioning. The current study demonstrates the general feasibility of the suggested rt-fMRI neurofeedback training approach as a potential novel treatment option for ADHD patients. Due to the study’s small sample size, potential clinical benefits need to be further investigated in future studies.

Trial Registration: ISRCTN12390961

Automated selection of brain regions for real-time fMRI brain-computer interfaces

OBJECTIVE

Brain-computer interfaces (BCIs) implemented with real-time functional magnetic resonance imaging (rt-fMRI) use fMRI time-courses from predefined regions of interest (ROIs). To reach best performances, localizer experiments and on-site expert supervision are required for ROI definition. To automate this step, we developed two unsupervised computational techniques based on the general linear model (GLM) and independent component analysis (ICA) of rt-fMRI data, and compared their performances on a communication BCI. Approach. 3 T fMRI data of six volunteers were re-analyzed in simulated real-time. During a localizer run, participants performed three mental tasks following visual cues. During two communication runs, a letter-spelling display guided the subjects to freely encode letters by performing one of the mental tasks with a specific timing. GLM- and ICA-based procedures were used to decode each letter, respectively using compact ROIs and whole-brain distributed spatio-temporal patterns of fMRI activity, automatically defined from subject-specific or group-level maps.

MAIN RESULTS

Letter-decoding performances were comparable to supervised methods. In combination with a similarity-based criterion, GLM- and ICA-based approaches successfully decoded more than 80% (average) of the letters. Subject-specific maps yielded optimal performances. Significance. Automated solutions for ROI selection may help accelerating the translation of rt-fMRI BCIs from research to clinical applications.

When the Brain Takes 'BOLD' Steps: Real-Time fMRI Neurofeedback Can Further Enhance the Ability to Gradually Self-regulate Regional Brain Activation

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Humans are able to gradually self-regulate regional brain activation by applying cognitive strategies.

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Providing rtfMRI neurofeedback can enhance the gradual self-regulation ability.

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Findings are generalizable to various mental tasks and clinical MR field strengths.

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Novel parametric activation paradigm enriches spectrum of rtfMRI-neurofeedback and BCI methodology.

Brain-computer interfaces (BCIs) based on real-time functional magnetic resonance imaging (rtfMRI) are currently explored in the context of developing alternative (motor-independent) communication and control means for the severely disabled. In such BCI systems, the user encodes a particular intention (e.g., an answer to a question or an intended action) by evoking specific mental activity resulting in a distinct brain state that can be decoded from fMRI activation. One goal in this context is to increase the degrees of freedom in encoding different intentions, i.e., to allow the BCI user to choose from as many options as possible. Recently, the ability to voluntarily modulate spatial and/or temporal blood oxygenation level-dependent (BOLD)-signal features has been explored implementing different mental tasks and/or different encoding time intervals, respectively. Our two-session fMRI feasibility study systematically investigated for the first time the possibility of using magnitudinal BOLD-signal features for intention encoding. Particularly, in our novel paradigm, participants (n = 10) were asked to alternately self-regulate their regional brain-activation level to 30%, 60% or 90% of their maximal capacity by applying a selected activation strategy (i.e., performing a mental task, e.g., inner speech) and modulation strategies (e.g., using different speech rates) suggested by the experimenters. In a second step, we tested the hypothesis that the additional availability of feedback information on the current BOLD-signal level within a region of interest improves the gradual-self regulation performance. Therefore, participants were provided with neurofeedback in one of the two fMRI sessions. Our results show that the majority of the participants were able to gradually self-regulate regional brain activation to at least two different target levels even in the absence of neurofeedback. When provided with continuous feedback on their current BOLD-signal level, most participants further enhanced their gradual self-regulation ability. Our findings were observed across a wide variety of mental tasks and across clinical MR field strengths (i.e., at 1.5 T and 3 T), indicating that these findings are robust and can be generalized across mental tasks and scanner types. The suggested novel parametric activation paradigm enriches the spectrum of current rtfMRI-neurofeedback and BCI methodology and has considerable potential for fundamental and clinical neuroscience applications.

Evidence for normal letter-sound integration, but altered language pathways in a case of recovered Landau-Kleffner Syndrome

Landau-Kleffner Syndrome (LKS) is a rare form of acquired aphasia in children, characterized by epileptic discharges, which occur mostly during sleep. After normal speech and language development, aphasia develops between the ages of 3-7 years in a period ranging from days to months. The epileptic discharges usually disappear after reaching adulthood, but language outcomes are usually poor if no treatment focused on restoration of (non-) verbal communication is given. Patients often appear deaf-mute, but sign language, as part of the treatment, may lead to recovery of communication. The neural mechanisms underlying poor language outcomes in LKS are not yet understood. In this detailed functional MRI study of a recovered LKS patient - that is, a patient no longer suffering from epileptic discharges, audiovisual multi-sensory processing was investigated, since LKS patients are often proficient in reading, but not in speech perception. In the recovered LKS patient a large difference in the neural activation to auditory stimuli was found in the left versus the right auditory cortex, which cannot be attributed to hearing loss. Compared to healthy proficient readers investigated earlier with the same fMRI experiment, the patient demonstrated normal letter-sound integration in the superior temporal gyrus as demonstrated by the multi-sensory interaction index, indicating intact STG function. Diffusion Tensor Imaging (DTI) based fiber tracking in the LKS patient showed fibers originating from Heschl's gyrus that seem to be left-right inverted with respect to HG fiber pattern described in the literature for healthy controls. In the patient, in both hemispheres we found arcuate fibers projecting from (homologues of) Broca's to Wernicke's areas, and a lack of fibers from arcuate left inferior parietal and sylvian areas reported in healthy subjects. We observed short arcuate segments in the right hemisphere. Although speculative, our results suggest intact temporal lobe processing but an altered temporal to frontal connectivity. The altered connectivity might explain observed short-term verbal memory problems, disturbed (speech) sound-motor interaction and online feedback of speech and might be one of the neuronal factors underlying LKS.

fMRI neurofeedback facilitates anxiety regulation in females with spider phobia

Background: Spider phobics show an exaggerated fear response when encountering spiders. This fear response is aggravated by negative and irrational beliefs about the feared object. Cognitive reappraisal can target these beliefs, and therefore has a fear regulating effect. The presented study investigated if neurofeedback derived from functional magnetic resonance imaging (fMRI) would facilitate anxiety regulation by cognitive reappraisal, using spider phobia as a model of anxiety disorders. Feedback was provided based on activation in left dorsolateral prefrontal cortex and right insula, as indicators of engagement and regulation success, respectively.

Methods: Eighteen female spider phobics participated in a randomized, controlled, single-blinded study. All participants completed a training session in the MRI scanner. Participants assigned to the neurofeedback condition were instructed to shape their regulatory strategy based on the provided feedback. Participants assigned to the control condition were asked to adapt their strategy intuitively.

Results: Neurofeedback participants exhibited lower anxiety levels than the control group at the end of the training. In addition, only neurofeedback participants achieved down-regulation of insula activation levels by cognitive reappraisal. Group differences became more pronounced over time, supporting learning as a mechanism behind this effect. Importantly, within the neurofeedback group, achieved changes in insula activation levels during training predicted long-term anxiety reduction.

Conclusions: The conducted study provides first evidence that fMRI neurofeedback has a facilitating effect on anxiety regulation in spider phobia.

Windowed correlation: a suitable tool for providing dynamic fMRI-based functional connectivity neurofeedback on task difficulty

The goal of neurofeedback training is to provide participants with relevant information on their ongoing brain processes in order to enable them to change these processes in a meaningful way. Under the assumption of an intrinsic brain-behavior link, neurofeedback can be a tool to guide a participant towards a desired behavioral state, such as a healthier state in the case of patients. Current research in clinical neuroscience regarding the most robust indicators of pathological brain processes in psychiatric and neurological disorders indicates that fMRI-based functional connectivity measures may be among the most important biomarkers of disease. The present study therefore investigated the general potential of providing fMRI neurofeedback based on functional correlations, computed from short-window time course data at the level of single task periods. The ability to detect subtle changes in task performance with block-wise functional connectivity measures was evaluated based on imaging data from healthy participants performing a simple motor task, which was systematically varied along two task dimensions representing two different aspects of task difficulty. The results demonstrate that fMRI-based functional connectivity measures may provide a better indicator for an increase in overall (motor) task difficulty than activation level-based measures. Windowed functional correlations thus seem to provide relevant and unique information regarding ongoing brain processes, which is not captured equally well by standard activation level-based neurofeedback measures. Functional connectivity markers, therefore, may indeed provide a valuable tool to enhance and monitor learning within an fMRI neurofeedback setup.

Pattern classification of valence in depression

Neuroimaging biomarkers of depression have potential to aid diagnosis, identify individuals at risk and predict treatment response or course of illness. Nevertheless none have been identified so far, potentially because no single brain parameter captures the complexity of the pathophysiology of depression. Multi-voxel pattern analysis (MVPA) may overcome this issue as it can identify patterns of voxels that are spatially distributed across the brain. Here we present the results of an MVPA to investigate the neuronal patterns underlying passive viewing of positive, negative and neutral pictures in depressed patients. A linear support vector machine (SVM) was trained to discriminate different valence conditions based on the functional magnetic resonance imaging (fMRI) data of nine unipolar depressed patients. A similar dataset obtained in nine healthy individuals was included to conduct a group classification analysis via linear discriminant analysis (LDA). Accuracy scores of 86% or higher were obtained for each valence contrast via patterns that included limbic areas such as the amygdala and frontal areas such as the ventrolateral prefrontal cortex. The LDA identified two areas (the dorsomedial prefrontal cortex and caudate nucleus) that allowed group classification with 72.2% accuracy. Our preliminary findings suggest that MVPA can identify stable valence patterns, with more sensitivity than univariate analysis, in depressed participants and that it may be possible to discriminate between healthy and depressed individuals based on differences in the brain's response to emotional cues.

Real-time self-regulation of emotion networks in patients with depression

Many patients show no or incomplete responses to current pharmacological or psychological therapies for depression. Here we explored the feasibility of a new brain self-regulation technique that integrates psychological and neurobiological approaches through neurofeedback with functional magnetic resonance imaging (fMRI). In a proof-of-concept study, eight patients with depression learned to upregulate brain areas involved in the generation of positive emotions (such as the ventrolateral prefrontal cortex (VLPFC) and insula) during four neurofeedback sessions. Their clinical symptoms, as assessed with the 17-item Hamilton Rating Scale for Depression (HDRS), improved significantly. A control group that underwent a training procedure with the same cognitive strategies but without neurofeedback did not improve clinically. Randomised blinded clinical trials are now needed to exclude possible placebo effects and to determine whether fMRI-based neurofeedback might become a useful adjunct to current therapies for depression.