Neurofeedback-dependent influence of the ventral striatum using a working memory paradigm targeting the dorsolateral prefrontal cortex
2023 | Frontiers in Behavioral Neuroscience | LINK
Daniela Pereira, Alexandre Sayal, João Pereira, Sofia Morais, António Macedo, Bruno Direito, Miguel Castelo-Branco
Abstract
Executive functions and motivation have been established as key aspects for neurofeedback success. However, task-specific influence of cognitive strategies is scarcely explored. In this study, we test the ability to modulate the dorsolateral prefrontal cortex, a strong candidate for clinical application of neurofeedback in several disorders with dysexecutive syndrome, and investigate how feedback contributes to better performance in a single session. Participants of both neurofeedback (n = 17) and sham-control (n = 10) groups were able to modulate DLPFC in most runs (with or without feedback) while performing a working memory imagery task. However, activity in the target area was higher and more sustained in the active group when receiving feedback. Furthermore, we found increased activity in the nucleus accumbens in the active group, compared with a predominantly negative response along the block in participants receiving sham feedback. Moreover, they acknowledged the non-contingency between imagery and feedback, reflecting the impact on motivation. This study reinforces DLPFC as a robust target for neurofeedback clinical implementations and enhances the critical influence of the ventral striatum, both poised to achieve success in the self-regulation of brain activity.
Assessing MR-compatibility of somatosensory stimulation devices: A systematic review on testing methodologies
2023 | Frontiers in Neuroscience | LINK
Carolina Travassos, Alexandre Sayal, Bruno Direito, João Pereira, Teresa Sousa, Miguel Castelo-Branco
Abstract
Functional magnetic resonance imaging (fMRI) has been extensively used as a tool to map the brain processes related to somatosensory stimulation. This mapping includes the localization of task-related brain activation and the characterization of brain activity dynamics and neural circuitries related to the processing of somatosensory information. However, the magnetic resonance (MR) environment presents unique challenges regarding participant and equipment safety and compatibility. This study aims to systematically review and analyze the state-of-the-art methodologies to assess the safety and compatibility of somatosensory stimulation devices in the MR environment. A literature search, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement guidelines, was performed in PubMed, Scopus, and Web of Science to find original research on the development and testing of devices for somatosensory stimulation in the MR environment. Nineteen records that complied with the inclusion and eligibility criteria were considered. The findings are discussed in the context of the existing international standards available for the safety and compatibility assessment of devices intended to be used in the MR environment. In sum, the results provided evidence for a lack of uniformity in the applied testing methodologies, as well as an in-depth presentation of the testing methodologies and results. Lastly, we suggest an assessment methodology (safety, compatibility, performance, and user acceptability) that can be applied to devices intended to be used in the MR environment.
Training the social brain - clinical and neural effects of an 8-week real-time functional Magnetic Resonance Imaging neurofeedback Phase IIa Clinical Trial in Autism
2021 | Autism: International Journal of Research and Practice | LINK
Bruno Direito, Susana Mouga, Alexandre Sayal, Marco Simões, Hugo Quental, Inês Bernardino, Rebecca Playle, Rachel McNamara, David EJ Linden, Guiomar Oliveira, Miguel Castelo-Branco
Abstract
Autism spectrum disorder is characterized by abnormal function in core social brain regions. Here, we demonstrate the feasibility of real-time functional magnetic resonance imaging volitional neurofeedback. Following up the demonstration of neuromodulation in healthy participants, in this repeated-measure design clinical trial, 15 autism spectrum disorder patients were enrolled in a 5-session training program of real-time functional magnetic resonance imaging neurofeedback targeting facial emotion expressions processing, using the posterior superior temporal sulcus as region-of-interest. Participants were able to modulate brain activity in this region-of-interest, over multiple sessions. Moreover, we identified the relevant clinical and neural effects, as documented by whole-brain neuroimaging results and neuropsychological measures, including emotion recognition of fear, immediately after the intervention and persisting after 6 months. Neuromodulation profiles demonstrated subject-specificity for happy, sad, and neutral facial expressions, an unsurprising variable pattern in autism spectrum disorder. Modulation occurred in negative or positive directions, even for neutral faces, in line with their often-perceived ambiguity in autism spectrum disorder. Striatal regions (associated with success/failure of neuromodulation), saliency (insula/anterior cingulate cortex), and emotional control (medial prefrontal cortex) networks were recruited during neuromodulation. Recruitment of the operant learning network is consistent with participants’ engagement. Compliance, immediate intervention benefits, and their persistence after 6 months pave the way for a future Phase IIb/III, randomized controlled clinical trial, with a larger sample that will allow to conclude on clinical benefits from neurofeedback training in autism spectrum disorder (NCT02440451).
Directly Exploring the Neural Correlates of Feedback-Related Reward Saliency and Valence During Real-Time fMRI-Based Neurofeedback
2021 | Frontiers in Human Neuroscience | LINK
Bruno Direito, Manuel Ramos, João Pereira, Alexandre Sayal, Teresa Sousa, Miguel Castelo-Branco
Abstract
Introduction: The potential therapeutic efficacy of real-time fMRI Neurofeedback has received increasing attention in a variety of psychological and neurological disorders and as a tool to probe cognition. Despite its growing popularity, the success rate varies significantly, and the underlying neural mechanisms are still a matter of debate. The question whether an individually tailored framework positively influences neurofeedback success remains largely unexplored. Methods: To address this question, participants were trained to modulate the activity of a target brain region, the visual motion area hMT+/V5, based on the performance of three imagery tasks with increasing complexity: imagery of a static dot, imagery of a moving dot with two and with four opposite directions. Participants received auditory feedback in the form of vocalizations with either negative, neutral or positive valence. The modulation thresholds were defined for each participant according to the maximum BOLD signal change of their target region during the localizer run. Results: We found that 4 out of 10 participants were able to modulate brain activity in this region-of-interest during neurofeedback training. This rate of success (40%) is consistent with the neurofeedback literature. Whole-brain analysis revealed the recruitment of specific cortical regions involved in cognitive control, reward monitoring, and feedback processing during neurofeedback training. Individually tailored feedback thresholds did not correlate with the success level. We found region-dependent neuromodulation profiles associated with task complexity and feedback valence. Discussion: Findings support the strategic role of task complexity and feedback valence on the modulation of the network nodes involved in monitoring and feedback control, key variables in neurofeedback frameworks optimization. Considering the elaborate design, the small sample size here tested (N = 10) impairs external validity in comparison to our previous studies. Future work will address this limitation. Ultimately, our results contribute to the discussion of individually tailored solutions, and justify further investigation concerning volitional control over brain activity.
Identification of competing neural mechanisms underlying positive and negative perceptual hysteresis in the human visual system
2020 | NeuroImage | LINK
Alexandre Sayal, Teresa Sousa, João V. Duarte, Gabriel N. Costa, Ricardo Martins, Miguel Castelo-Branco
Abstract
Hysteresis is a well-known phenomenon in physics that relates changes in a system with its prior history. It is also part of human visual experience (perceptual hysteresis), and two different neural mechanisms might explain it: persistence (a cause of positive hysteresis), which forces to keep a current percept for longer, and adaptation (a cause of negative hysteresis), which in turn favors the switch to a competing percept early on. In this study, we explore the neural correlates underlying these mechanisms and the hypothesis of their competitive balance, by combining behavioral assessment with fMRI. We used machine learning on the behavioral data to distinguish between positive and negative hysteresis, and discovered a neural correlate of persistence at a core region of the ventral attention network, the anterior insula. Our results add to the understanding of perceptual multistability and reveal a possible mechanistic explanation for the regulation of different forms of perceptual hysteresis.
Volitional Modulation of the Left DLPFC Neural Activity Based on a Pain Empathy Paradigm—A Potential Novel Therapeutic Target for Pain
2020 | Frontiers in Neurology | LINK
Carolina Travassos, Alexandre Sayal, Bruno Direito, João Castelhano, Miguel Castelo-Branco
Abstract
The ability to perceive and feel another person' pain as if it were one's own pain, e.g., pain empathy, is related to brain activity in the “pain-matrix” network. A non-core region of this network in Dorsolateral Prefrontal Cortex (DLPFC) has been suggested as a modulator of the attentional-cognitive dimensions of pain processing in the context of pain empathy. We conducted a neurofeedback experiment using real-time functional magnetic resonance imaging (rt-fMRI-NF) to investigate the association between activity in the left DLPFC (our neurofeedback target area) and the perspective assumed by the participant (“first-person”/“Self” or “third-person”/“Other” perspective of a pain-inducing stimulus), based on a customized pain empathy task. Our main goals were to assess the participants' ability to volitionally modulate activity in their own DLPFC through an imagery task of pain empathy and to investigate into which extent this ability depends on feedback. Our results demonstrate participants' ability to significantly modulate brain activity of the neurofeedback target area for the “first-person”/”Self” and “third-person”/”Other” perspectives. Results of both perspectives show that the participants were able to modulate (with statistical significance) the activity already in the first run of the session, in spite of being naïve to the task and even in the absence of feedback information. Moreover, they improved modulation throughout the session, particularly in the “Self” perspective. These results provide new insights on the role of DLPFC in pain and pain empathy mechanisms and validate the proposed protocol, paving the way for future interventional studies in clinical populations with empathic deficits.
The boundaries of state-space Granger causality analysis applied to BOLD simulated data: A comparative modelling and simulation approach
2020 | Journal of Neuroscience Methods | LINK
Tiago T. Fernandes, Bruno Direito, Alexandre Sayal, João Pereira, Alexandre Andrade, Miguel Castelo-Branco
Abstract
The analysis of connectivity has become a fundamental tool in human neuroscience. Granger Causality Mapping is a data-driven method that uses Granger Causality (GC) to assess the existence and direction of influence between signals, based on temporal precedence of information. More recently, a theory of Granger causality has been developed for state-space (SS-GC) processes, but little is known about its statistical validation and application on functional magnetic resonance imaging (fMRI) data. We explored different multivariate computational frameworks to define the optimal combination for GC estimation. We hypothesized a new heuristic, combining SS-GC with a distinct statistical validation technique, Time Reversed Testing, validating it on synthetic data. We test its performance with a number of experimental parameters, including block structure, sampling frequency, noise and system mean pairwise correlation, using a statistical framework of binary classification. We found that SS-GC with time reversed testing outperforms other frameworks. The results validate the application of SS-GC to generative models. When estimating reliable causal relations, SS-GC returns promising results, especially when considering synthetic data with a high impact of noise and sampling rate. In this study, we empirically explored the boundaries of SS-GC with time reversed testing, a data-driven causality analysis framework with potential applicability to fMRI data.
How much of the BOLD-fMRI signal can be approximated from simultaneous EEG data: relevance for the transfer and dissemination of neurofeedback interventions
2020 | Journal of Neural Engineering | LINK
Marco Simões, Rodolfo Abreu, Bruno Direito, Alexandre Sayal, João Castelhano, Paulo Carvalho, Miguel Castelo-Branco
Abstract
fMRI-based neurofeedback (NF) interventions represent the method of choice for the neuromodulation of localized brain areas. Although we have already validated an fMRI-NF protocol targeting the facial expressions processing network (FEPN), its dissemination is hampered by the economical and logistical constraints of fMRI-NF interventions, which may be however surpassed by transferring it to EEG setups, due to their low cost and portability. One of the major challenges of this procedure is then to reconstruct the BOLD-fMRI signal measured at the FEPN using only EEG signals. Because these types of approaches have been poorly explored so far, here we systematically investigated the extent at which the BOLD-fMRI signal recorded from the FEPN during a fMRI-NF protocol could be reconstructed from the simultaneously recorded EEG signal. Several features from both scalp and source spaces (the latter estimated using continuous EEG source imaging) were extracted and used as predictors in a regression problem using random forests. Furthermore, three different approaches to deal with the hemodynamic delay of the BOLD signal were tested. The resulting models were compared with the only approach already proposed in the literature that uses spectral features and considers different time delays. The combination of linear and non-linear features (particularly the largest Lyapunov exponent and entropy measures) projected into the source space, spatially filtered by independent component analysis (ICA) and convolved with multiple HRF functions peaking at different latencies, increases significantly the reconstruction accuracy (defined as the correlation between the measured and approximated BOLD signal) from 20% (direct comparison with the method used in the current literature) to 56%. With this pipeline, a more accurate reconstruction of the BOLD signal can be obtained, which will positively impact the transfer of fMRI-based neurofeedback interventions to EEG setups, and more importantly, their dissemination and efficacy in modulating the activity of the desired brain areas.
Targeting dynamic facial processing mechanisms in superior temporal sulcus using a novel fMRI neurofeedback target
2019 | Journal of Neuroscience | LINK
Bruno Direito, João Lima, Marco Simões, Alexandre Sayal, Teresa Sousa, Michael Lurhs, Carlos Ferreira, Miguel Castelo-Branco
Abstract
The superior temporal sulcus (STS) encompasses a complex set of regions involved in a wide range of cognitive functions. To understand its functional properties, neuromodulation approaches such brain stimulation or neurofeedback can be used. We investigated whether the posterior STS (pSTS), a core region in the face perception and imagery network, could be specifically identified based on the presence of dynamic facial expressions (and not just on simple motion or static face signals), and probed with neurofeedback. Recognition of facial expressions is critically impaired in autism spectrum disorder, making this region a relevant target for future clinical neurofeedback studies. We used a stringent localizer approach based on the contrast of dynamic facial expressions against static neutral faces plus moving dots. The target region had to be specifically responsive to dynamic facial expressions instead of mere motion and/or the presence of a static face. The localizer was successful in selecting this region across subjects. Neurofeedback was then performed, using this region as a target, with two novel feedback rules (mean or derivative-based, using visual or auditory interfaces). Our results provide evidence that a facial expression-selective cluster in pSTS can be identified and may represent a suitable target for neurofeedback approaches, aiming at social and emotional cognition. These findings highlight the presence of a highly selective region in STS encoding dynamic aspects of facial expressions. Future studies should elucidate its role as a mechanistic target for neurofeedback strategies in clinical disorders of social cognition such as autism.
Evidence for distinct levels of neural adaptation to both coherent and incoherently moving visual surfaces in visual area hMT+
2019 | NeuroImage | LINK
Teresa Sousa, Alexandre Sayal, JOão V. Duarte, Gabriel N. Costa,Ricardo Martins, Miguel Castelo-Branco
Abstract
Visual adaptation describes the processes by which the visual system alters its operating properties in response to changes in the environment. It is one of the mechanisms controlling visual perceptual bistability – when two perceptual solutions are available – by controlling the duration of each percept. Moving plaids are an example of such ambiguity. They can be perceived as two surfaces sliding incoherently over each other or as a single coherent surface. Here, we investigated, using fMRI, whether activity in the human motion complex (hMT+), a region tightly related to the perceptual integration of visual motion, is modulated by distinct forms of visual adaptation to coherent or incoherent perception of moving plaids. Our hypothesis is that exposure to global coherent or incoherent moving stimuli leads to different levels of measurable adaptation, reflected in hMT+ activity. We found that the strength of the measured visual adaptation effect depended on whether subjects integrated (coherent percept) or segregated (incoherent percept) surface motion signals. Visual motion adaptation was significant both for coherent motion and globally incoherent surface motion. Although not as strong as to the coherent percept, visual adaptation due to the incoherent percept also affects hMT+. This shows that adaptation can contribute to regulate percept duration during visual bistability, with distinct weights, depending on the type of percept. Our findings suggest a link between bistability and adaptation mechanisms, both due to coherent and incoherent motion percepts, but in an asymmetric manner. These asymmetric adaptation weights have strong implications in models of perceptual decision and may explain asymmetry of perceptual interpretation periods.