Publications

In this page I provide a list of the publications I worked on. Feel free to check my Google Scholar page or CiênciaVitae for the full list.

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.