Hydrogels in Cutaneous Wound Healing: Insights into Characterization, Properties, Formulation and Therapeutic Potential.

Hydrogels are polymeric materials that possess a set of characteristics meeting various requirements of an ideal wound dressing, making them promising for wound care. These features include, among others, the ability to absorb and retain large amounts of water and the capacity to closely mimic native structures, such as the extracellular matrix, facilitating various cellular processes like proliferation and differentiation. The polymers used in hydrogel formulations exhibit a broad spectrum of properties, allowing them to be classified into two main categories: natural polymers like collagen and chitosan, and synthetic polymers such as polyurethane and polyethylene glycol. This review offers a comprehensive overview and critical analysis of the key polymers that can constitute hydrogels, beginning with a brief contextualization of the polymers. It delves into their function, origin, and chemical structure, highlighting key sources of extraction and obtaining. Additionally, this review encompasses the main intrinsic properties of these polymers and their roles in the wound healing process, accompanied, whenever available, by explanations of the underlying mechanisms of action. It also addresses limitations and describes some studies on the effectiveness of isolated polymers in promoting skin regeneration and wound healing. Subsequently, we briefly discuss some application strategies of hydrogels derived from their intrinsic potential to promote the wound healing process. This can be achieved due to their role in the stimulation of angiogenesis, for example, or through the incorporation of substances like growth factors or drugs, such as antimicrobials, imparting new properties to the hydrogels. In addition to substance incorporation, the potential of hydrogels is also related to their ability to serve as a three-dimensional matrix for cell culture, whether it involves loading cells into the hydrogel or recruiting cells to the wound site, where they proliferate on the scaffold to form new tissue. The latter strategy presupposes the incorporation of biosensors into the hydrogel for real-time monitoring of wound conditions, such as temperature and pH. Future prospects are then ultimately addressed. As far as we are aware, this manuscript represents the first comprehensive approach that brings together and critically analyzes fundamental aspects of both natural and synthetic polymers constituting hydrogels in the context of cutaneous wound healing. It will serve as a foundational point for future studies, aiming to contribute to the development of an effective and environmentally friendly dressing for wounds.

EEG as a potential ground truth for the assessment of cognitive state in software development activities: A multimodal imaging study.

Cognitive human error and recent cognitive taxonomy on human error causes of software defects support the intuitive idea that, for instance, mental overload, attention slips, and working memory overload are important human causes for software bugs. In this paper, we approach the EEG as a reliable surrogate to MRI-based reference of the programmer's cognitive state to be used in situations where heavy imaging techniques are infeasible. The idea is to use EEG biomarkers to validate other less intrusive physiological measures, that can be easily recorded by wearable devices and useful in the assessment of the developer's cognitive state during software development tasks. Herein, our EEG study, with the support of fMRI, presents an extensive and systematic analysis by inspecting metrics and extracting relevant information about the most robust features, best EEG channels and the best hemodynamic time delay in the context of software development tasks. From the EEG-fMRI similarity analysis performed, we found significant correlations between a subset of EEG features and the Insula region of the brain, which has been reported as a region highly related to high cognitive tasks, such as software development tasks. We concluded that despite a clear inter-subject variability of the best EEG features and hemodynamic time delay used, the most robust and predominant EEG features, across all the subjects, are related to the Hjorth parameter Activity and Total Power features, from the EEG channels F4, FC4 and C4, and considering in most of the cases a hemodynamic time delay of 4 seconds used on the hemodynamic response function. These findings should be taken into account in future EEG-fMRI studies in the context of software debugging.

Assessment of distance to primary percutaneous coronary intervention centres in ST-segment elevation myocardial infarction: Overcoming inequalities with process mining tools.

Objectives: In ST-segment elevation myocardial infarction (STEMI), time delay between symptom onset and treatment is critical to improve outcome. The expected transport delay between patient location and percutaneous coronary intervention (PCI) centre is paramount for choosing the adequate reperfusion therapy. The "Centro" region of Portugal has heterogeneity in PCI assess due to geographical reasons. We aimed to explore time delays between regions using process mining tools. Methods: Retrospective observational analysis of patients with STEMI from the Portuguese Registry of Acute Coronary Syndromes. We collected information on geographical area of symptom onset, reperfusion option, and in-hospital mortality. We built a national and a regional patient's flow models by using a process mining methodology based on parallel activity-based log inference algorithm. Results: Totally, 8956 patients (75% male, 48% from 51 to 70 years) were included in the national model. Most patients (73%) had primary PCI, with the median time between admission and treatment <120 minutes in every region; "Centro" had the longest delay. In the regional model corresponding to the "Centro" region of Portugal divided by districts, only 61% had primary PCI, with "Guarda" (05:04) and "Castelo Branco" (06:50) showing longer delays between diagnosis and reperfusion than "Coimbra" (01:19). For both models, in-hospital mortality was higher for those without reperfusion therapy compared to PCI and fibrinolysis. Conclusion: Process mining tools help to understand referencing networks visually, easily highlighting its inefficiencies and potential needs for improvement. A new PCI centre in the "Centro" region is critical to offer timely first-line treatment to their population.

A neurophysiological signature of dynamic emotion recognition associated with social communication skills and cortical gamma-aminobutyric acid levels in children.

Introduction: Emotion recognition is a core feature of social perception. In particular, perception of dynamic facial emotional expressions is a major feature of the third visual pathway. However, the classical N170 visual evoked signal does not provide a pure correlate of such processing. Indeed, independent component analysis has demonstrated that the N170 component is already active at the time of the P100, and is therefore distorted by early components. Here we implemented, a dynamic face emotional paradigm to isolate a more pure face expression selective N170. We searched for a neural correlate of perception of dynamic facial emotional expressions, by starting with a face baseline from which a facial expression evolved. This allowed for a specific facial expression contrast signal which we aimed to relate with social communication abilities and cortical gamma-aminobutyric acid (GABA) levels. Methods: We recorded event-related potentials (ERPs) and Magnetic Resonance (MRS) measures in 35 typically developing (TD) children, (10-16 years) sex-matched, during emotion recognition of an avatar morphing/unmorphing from neutral to happy/sad expressions. This task allowed for the elimination of the contribution low-level visual components, in particular the P100, by morphing baseline isoluminant neutral faces into specific expressions, isolating dynamic emotion recognition. Therefore, it was possible to isolate a dynamic face sensitive N170 devoid of interactions with earlier components. Results: We found delayed N170 and P300, with a hysteresis type of dependence on stimulus trajectory (morphing/unmorphing), with hemispheric lateralization. The delayed N170 is generated by an extrastriate source, which can be related to the third visual pathway specialized in biological motion processing. GABA levels in visual cortex were related with N170 amplitude and latency and predictive of worse social communication performance (SCQ scores). N170 latencies reflected delayed processing speed of emotional expressions and related to worse social communication scores. Discussion: In sum, we found a specific N170 electrophysiological signature of dynamic face processing related to social communication abilities and cortical GABA levels. These findings have potential clinical significance supporting the hypothesis of a spectrum of social communication abilities and the identification of a specific face-expression sensitive N170 which can potentially be used in the development of diagnostic and intervention tools.

Real-Time PCR Protocol for Detection and Quantification of Three Pathogenic Members of the Vibrionaceae Family.

Vibriosis, an often-fatal disease induced by pathogenic members of the Vibrionaceae family, causes severe economic losses in aquacultures. To mitigate/avoid vibriosis outbursts, it is vital to detect and quantify these pathogens as early as possible. However, standard microbiological methods are time-consuming and often underestimate cell counts, which calls for the development of valid alternatives. In this study, real-time polymerase chain reaction (qPCR) was employed to detect the pathogenic species Vibrio alginolyticus, Listonella anguillara, and Vibrio harveyi using a new primer pair targeting the groEL gene. In addition, the DNA extraction efficiency of three methods, two commercial kits and the boiling method, was compared. The most efficient method was the DNeasy Blood and Tissue kit, with a detection limit ranging between 154 and 600 CFU mL-1 in the case of V. alginolyticus and L. anguillara, and 48 CFU mL-1 for V. harveyi. Thus, this study presents the development and evaluation of a method for the early quantification of all three species in saline suspensions. However, the results obtained by spiking a microalgae sample with V. harveyi emphasize the importance of adjusting the DNA control's standard curve to the relevant extraction matrices, as it affects the DNA extraction efficiency and may hamper an accurate quantification with qPCR.

Modulatory effect of Gracilaria gracilis on European seabass gut microbiota community and its functionality.

Seaweeds are an important source of nutrients and bioactive compounds and have a high potential as health boosters in aquaculture. This study evaluated the effect of dietary inclusion of Gracilaria gracilis biomass or its extract on the European seabass (Dicentrarchus labrax) gut microbial community. Juvenile fish were fed a commercial-like diet with 2.5% or 5% seaweed biomass or 0.35% seaweed extract for 47 days. The gut microbiome was assessed by 16S rRNA amplicon sequencing, and its diversity was not altered by the seaweed supplementation. However, a reduction in Proteobacteria abundance was observed. Random forest analysis highlighted the genera Photobacterium, Staphylococcus, Acinetobacter, Micrococcus and Sphingomonas, and their abundances were reduced when fish were fed diets with algae. SparCC correlation network analysis suggested several mutualistic and other antagonistic relationships that could be related to the predicted altered functions. These pathways were mainly related to the metabolism and biosynthesis of protective compounds such as ectoine and were upregulated in fish fed diets supplemented with algae. This study shows the beneficial potential of Gracilaria as a functional ingredient through the modulation of the complex microbial network towards fish health improvement.

How Reliable Are Ultra-Short-Term HRV Measurements during Cognitively Demanding Tasks?

Ultra-short-term HRV features assess minor autonomous nervous system variations such as variations resulting from cognitive stress peaks during demanding tasks. Several studies compare ultra-short-term and short-term HRV measurements to investigate their reliability. However, existing experiments are conducted in low cognitively demanding environments. In this paper, we propose to evaluate these measurements' reliability under cognitively demanding tasks using a near real-life setting. For this purpose, we selected 31 HRV features, extracted from data collected from 21 programmers performing code comprehension, and compared them across 18 different time frames, ranging from 3 min to 10 s. Statistical significance and correlation tests were performed between the features extracted using the larger window (3 min) and the same features extracted with the other 17 time frames. We paired these analyses with Bland-Altman plots to inspect how the extraction window size affects the HRV features. The main results show 13 features that presented at least 50% correlation when using 60-second windows. The HF and mNN features achieved around 50% correlation using a 30-second window. The 30-second window was the smallest time frame considered to have reliable measurements. Furthermore, the mNN feature proved to be quite robust to the shortening of the time resolution.

A Bayesian-optimized design for an interpretable convolutional neural network to decode and analyze the P300 response in autism.

Objective.P300 can be analyzed in autism spectrum disorder (ASD) to derive biomarkers and can be decoded in brain-computer interfaces to reinforce ASD impaired skills. Convolutional neural networks (CNNs) have been proposed for P300 decoding, outperforming traditional algorithms but they (a) do not investigate optimal designs in different training conditions; (b) lack in interpretability. To overcome these limitations, an interpretable CNN (ICNN), that we recently proposed for motor decoding, has been modified and adopted here, with its optimal design searched via Bayesian optimization.Approach.The ICNN provides a straightforward interpretation of spectral and spatial features learned to decode P300. The Bayesian-optimized (BO) ICNN design was investigated separately for different training strategies (within-subject, within-session, and cross-subject) and BO models were used for the subsequent analyses. Specifically, transfer learning (TL) potentialities were investigated by assessing how pretrained cross-subject BO models performed on a new subject vs. random-initialized models. Furthermore, within-subject BO-derived models were combined with an explanation technique (ICNN + ET) to analyze P300 spectral and spatial features.Main results.The ICNN resulted comparable or even outperformed existing CNNs, at the same time being lighter. BO ICNN designs differed depending on the training strategy, needing more capacity as the training set variability increased. Furthermore, TL provided higher performance than networks trained from scratch. The ICNN + ET analysis suggested the frequency range [2, 5.8] Hz as the most relevant, and spatial features showed a right-hemispheric parietal asymmetry. The ICNN + ET-derived features, but not ERP-derived features, resulted significantly and highly correlated to autism diagnostic observation schedule clinical scores.Significance.This study substantiates the idea that a CNN can be designed both accurate and interpretable for P300 decoding, with an optimized design depending on the training condition. The novel ICNN-based analysis tool was able to better capture ASD neural signatures than traditional event-related potential analysis, possibly paving the way for identifying novel biomarkers.

Detection of mcr-1 Gene in Undefined Vibrio Species Isolated from Clams.

The increase of antimicrobial resistant strains is leading to an emerging threat to public health. Pathogenic Vibrio are responsible for human and animal illness. The Enterobacteriaceae family includes microorganisms that affect humans, causing several infections. One of the main causes of human infection is related to the ingestion of undercooked seafood. Due to their filter-feeding habit, marine invertebrates, such as clams, are known to be a natural reservoir of specific microbial communities. In the present study, Vibrionaceae and coliforms microorganisms were isolated from clams. A microbial susceptibility test was performed using the disk diffusion method. From 43 presumptive Vibrio spp. and 17 coliforms, three Vibrio spp. with MICs to colistin >512 mg L-1 were found. From the 23 antimicrobial resistance genes investigated, only the three isolates that showed phenotypic resistance to colistin contained the mcr-1 gene. Genotypic analysis for virulence genes in EB07V indicated chiA gene presence. The results from the plasmid cure and transformation showed that the resistance is chromosomally mediated. Biochemical analysis and MLSA, on the basis of four protein-coding gene sequences (recA, rpoB, groEL and dnaJ), grouped the isolates into the genus Vibrio but distinguished them as different from any known Vibrio spp.

Short-Term Immune Responses of Gilthead Seabream (Sparus aurata) Juveniles against Photobacterium damselae subsp. piscicida.

Photobacteriosis is a septicaemic bacterial disease affecting several marine species around the globe, resulting in significant economic losses. Although many studies have been performed related to the pathogen virulence and resistance factors, information regarding the host defence mechanisms activated once an infection takes place is still scarce. The present study was designed to understand innate immune responses of farmed juvenile gilthead seabream (Sparus aurata) after Photobacterium damselae subsp. piscicida (Phdp) infection. Therefore, two groups of seabream juveniles were intraperitoneally injected with 100 µL of PBS (placebo) or 100 µL of exponentially growing Phdp (1 × 106 CFU/mL; infected). The blood, plasma, liver, and head kidney of six fish from each treatment were sampled immediately before infection and 3, 6, 9, 24 and 48 h after infection for the broad screening of fish immune and oxidative stress responses. Infected animals presented marked anaemia, neutrophilia and monocytosis, conditions that are correlated with an increased expression of genes related to inflammation and phagocytic activity. Similar studies with different fish species and bacteria can be useful for the definition of health biomarkers that might help fish farmers to prevent the occurrence of such diseases.

Assessing Arousal Through Multimodal Biosignals: A Preliminary Approach.

The increase in Autism Spectrum Disorder (ASD) prevalence estimates over the last decades has driven a quest to develop new forms of rehabilitation that can be accessible to a larger part of this population. These rehabilitation approaches often take the form of computer games that are blind to the user's emotional state, which compromises their efficacy. In this study, a set of physiological signals were acquired in simultaneous with functional Magnetic Resonance Imaging (fMRI) with the future prospect of combining both kinds of data to create models capable of assessing the true emotional state of their users based on physiological response as a measure of autonomic nervous system, having as ground truth the activity of targeted brain regions. This paper describes an initial approach, focusing on the information contained on the physiological signals alone. A total of 35 features were extracted from biosignals' segments and subsequently used for automatic classification of arousal state (High Arousal vs. Low Arousal). The suboptimal results, although some extracted features present statistically significant differences, underline the challenging nature of our proposal and the added obstacles of recording physiological signals in the magnetic resonance environment. Further exploration of the measured signals is needed to gather a bigger number of discriminative features that can improve classification outcomes.

Parametric fMRI analysis of videos of variable arousal levels reveals different dorsal vs ventral activation preferences between autism and controls.

Atypical sensory processing is now considered a ubiquitous feature of autism spectrum disorder (ASD) and is responsible for the atypical sensory-based behaviours seen in these individuals. Specifically, emotional arousal is a critical ASD target since it comprises emotion regulation and sensory processing, two core aspects of autism. So, in this project, we used task-based fMRI and a well-catalogued dataset of videos with variable arousal levels to characterize the sensory processing of emotional arousal content in ASD and typically developed controls. Our analysis revealed a difference in the secondary attention network where ASD individuals showed a clear yet lateralized preference to the dorsal attention network, whereas the neurotypical individuals preferred the ventral attention network.

Potential use of macroalgae Gracilaria gracilis in diets for European seabass (Dicentrarchus labrax): Health benefits from a sustainable source.

Seaweeds still possess a large undisclosed potential, mainly due to their constituent's richness, which may have several uses for society. In aquaculture, they may play a role as an ecological sustainable aquafeed supplement to increase overall health and fight pathogenic outbreaks. This study aimed to evaluate the general health modulation that the inclusion of Gracilaria gracilis could accomplish in the diet of Dicentrarchus labrax. Dried algae at 2.5% and 5% and algal extract at 0.35% inclusion levels were supplemented to seabass diet to evaluate possible growth, haematological, immunological, antioxidant, metabolic, and intestinal morphological modulations. The supplementations did not impact growth or feed utilization, and barely affected the haematological profile and some metabolic parameters. Nevertheless, it caused a marked outcome on lysozyme, some oxidative stress biomarkers, and intestine morphology, suggesting beneficial consequences from the algal inclusion. Dried algae powder, with a 2.5% inclusion, boosted immune response, with higher plasmatic lysozyme and intestinal acid goblet cells and protected against oxidative damages by improved enzymatic and non-enzymatic responses. Thus, we provide evidence that dietary seaweed application may be a path towards a more sustainable aquaculture industry.

Effects of anodal multichannel transcranial direct current stimulation (tDCS) on social-cognitive performance in healthy subjects: A randomized sham-controlled crossover pilot study.

Recent studies suggest that temporoparietal junction (TPJ) modulation can influence attention and social cognition performance. Nevertheless, no studies have used multichannel transcranial direct current stimulation (tDCS) over bilateral TPJ to estimate the effects on these neuropsychological functions. The project STIPED is using optimized multichannel stimulation as an innovative treatment approach for chronic pediatric neurodevelopmental disorders, namely in children/adolescents with Autism Spectrum Disorder (ASD). In this pilot study, we aim to explore whether anodal multichannel tDCS coupled with a Joint Attention Task (JAT) influences social-cognitive task performance relative to sham stimulation, both in an Emotion Recognition Task (ERT) and in a Mooney Faces Detection Task (MFDT), as well as to evaluate this technique's safety and tolerability. Twenty healthy adults were enrolled in a randomized, single-blinded, sham-controlled, crossover study. During two sessions, participants completed the ERT and the MFDT before and after 20min of sham or anodal tDCS over bilateral TPJ. No significant differences on performance accuracy and reaction time were found between stimulation conditions for all tasks, including the JAT. A significant main time effect for overall accuracy and reaction time was found for the MFDT. Itching was the most common side effect and stimulation conditions detection was at chance level. Results suggest that multichannel tDCS over bilateral TPJ does not affect performance of low-level emotional recognition tasks in healthy adults. Although preliminary safety and tolerability are demonstrated, further studies over longer periods will be pursued to investigate the clinical efficacy in children/adolescents with ASD, where social cognition impairments are preponderant.

Disclosing the potential of eleganolone for Parkinson's disease therapeutics: Neuroprotective and anti-inflammatory activities.

The treatment of Parkinson´s disease (PD) has benefited from significant advances resulting from the increasing research efforts focused on new therapeutics. However, the current treatments for PD are mostly symptomatic, alleviating disease symptoms without reversing or retarding disease progression. Thus, it is critical to find new molecules that can result in more effective treatments. Within this framework, this study aims to evaluate the neuroprotective and anti-inflammatory effects of three compounds (eleganolone, eleganonal and fucosterol) isolated from the brown seaweed Bifurcaria bifurcata. In vitro neuroprotective effects were evaluated on a PD cellular model induced by the neurotoxin 6-hydroxydopamine (6-OHDA) on SH-SY5Y human cells, while lipopolysaccharide (LPS) - stimulated RAW 264.7 macrophages were used to evaluate the anti-inflammatory potential. Additionally, the underlying mechanisms of action were also investigated. Compounds were isolated by preparative chromatographic methods and their structural elucidation attained by NMR spectroscopy. Among the tested compounds, eleganolone (0.1-1 µM; 24 h) reverted the neurotoxicity induced by 6-OHDA in about 20%. The neuroprotective effects were mediated by mitochondrial protection, reduction of oxidative stress, inflammation and apoptosis, and inhibition of NF-kB pathway. The results suggest that eleganolone may provide advantages in the treatment of neurodegenerative conditions and, therefore, should be considered for future preclinical studies.

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.

LAY ABSTRACT: Neurofeedback is an emerging therapeutic approach in neuropsychiatric disorders. Its potential application in autism spectrum disorder remains to be tested. Here, we demonstrate the feasibility of real-time functional magnetic resonance imaging volitional neurofeedback in targeting social brain regions in autism spectrum disorder. In this clinical trial, autism spectrum disorder patients were enrolled in a program with five training sessions of neurofeedback. Participants were able to control their own brain activity in this social brain region, with positive clinical and neural effects. Larger, controlled, and blinded clinical studies will be required to confirm the benefits.

Loliolide, a New Therapeutic Option for Neurological Diseases? In Vitro Neuroprotective and Anti-Inflammatory Activities of a Monoterpenoid Lactone Isolated from Codium tomentosum.

Parkinsons Disease (PD) is the second most common neurodegenerative disease worldwide, and is characterized by a progressive degeneration of dopaminergic neurons. Without an effective treatment, it is crucial to find new therapeutic options to fight the neurodegenerative process, which may arise from marine resources. Accordingly, the goal of the present work was to evaluate the ability of the monoterpenoid lactone Loliolide, isolated from the green seaweed Codium tomentosum, to prevent neurological cell death mediated by the neurotoxin 6-hydroxydopamine (6-OHDA) on SH-SY5Y cells and their anti-inflammatory effects in RAW 264.7 macrophages. Loliolide was obtained from the diethyl ether extract, purified through column chromatography and identified by NMR spectroscopy. The neuroprotective effects were evaluated by the MTT method. Cells' exposure to 6-OHDA in the presence of Loliolide led to an increase of cells' viability in 40%, and this effect was mediated by mitochondrial protection, reduction of oxidative stress condition and apoptosis, and inhibition of the NF-kB pathway. Additionally, Loliolide also suppressed nitric oxide production and inhibited the production of TNF-α and IL-6 pro-inflammatory cytokines. The results suggest that Loliolide can inspire the development of new neuroprotective therapeutic agents and thus, more detailed studies should be considered to validate its pharmacological potential.

BCIAUT-P300: A Multi-Session and Multi-Subject Benchmark Dataset on Autism for P300-Based Brain-Computer-Interfaces.

There is a lack of multi-session P300 datasets for Brain-Computer Interfaces (BCI). Publicly available datasets are usually limited by small number of participants with few BCI sessions. In this sense, the lack of large, comprehensive datasets with various individuals and multiple sessions has limited advances in the development of more effective data processing and analysis methods for BCI systems. This is particularly evident to explore the feasibility of deep learning methods that require large datasets. Here we present the BCIAUT-P300 dataset, containing 15 autism spectrum disorder individuals undergoing 7 sessions of P300-based BCI joint-attention training, for a total of 105 sessions. The dataset was used for the 2019 IFMBE Scientific Challenge organized during MEDICON 2019 where, in two phases, teams from all over the world tried to achieve the best possible object-detection accuracy based on the P300 signals. This paper presents the characteristics of the dataset and the approaches followed by the 9 finalist teams during the competition. The winner obtained an average accuracy of 92.3% with a convolutional neural network based on EEGNet. The dataset is now publicly released and stands as a benchmark for future P300-based BCI algorithms based on multiple session data.

The conscious experience of color constancy and neural responses to subliminal deviations - A behavioral and EEG/ERP oddball study.

INTRODUCTION: Color constancy, a property of conscious color experience, maintains object color appearance across illuminant changes. We investigated the neural correlates of subliminal vs. conscious stimulus deviations of color constancy manipulations. METHODS: Behavioral and Oddball EEG/ERP experiments were conducted (n = 20). Psychophysical illuminant variation discrimination thresholds were first estimated, to establish individual perceptual awareness ranges, allowing for simulation of natural daylight spectral and spatial variations on colored surfaces, at different ambiguity levels. RESULTS: Behavioral results validated illuminant choice. ERPs showed a significant modulation of posterior P1 component specifically for the subliminal global uniform deviation condition, respecting color constancy. Neural correlates of conscious percepts were identified at posterior N2-P3 latencies, parietal (P3b) and frontal regions. CONCLUSIONS: We identified an early subliminal correlate of low-level illuminant change, which reflects automatic unconscious detection of global color constancy deviations. Its suppression under conscious perception is probably due to top-down suppression according to prediction error models.

How much of the BOLD-fMRI signal can be approximated from simultaneous EEG data: relevance for the transfer and dissemination of neurofeedback interventions.

OBJECTIVE: 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. APPROACH: 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. MAIN RESULTS: 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%. SIGNIFICANCE: 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.