Noninvasive transcranial brain stimulation in central post-stroke pain: A systematic review.

BACKGROUND: The aim of this systematic review is to analyze the efficacy of noninvasive brain stimulation (NBS) in the treatment of central post-stroke pain (CPSP). METHODS: We included randomized controlled trials testing the efficacy of transcranial magnetic stimulation (TMS) or transcranial direct current stimulation versus placebo or other usual therapy in patients with CPSP. Articles in English, Portuguese, Spanish, Italian, and French were included. A bibliographic search was independently conducted on June 1, 2022, by two authors, using the databases MEDLINE (PubMed), Embase (Elsevier), Cochrane Central Register of Controlled Trials (CENTRAL), Scopus, and Web of Science Core Collection. The risk of bias was assessed using the second version of the Cochrane risk of bias (RoB 2) tool and the certainty of the evidence was evaluated through Grading of Recommendations Assessment, Development and Evaluation. RESULTS: A total of 2,674 records were identified after removing duplicates, of which 5 eligible studies were included, involving a total of 119 patients. All five studies evaluated repetitive TMS, four of which stimulated the primary motor cortex (M1) and one stimulated the premotor/dorsolateral prefrontal cortex. Only the former one reported a significant pain reduction in the short term, while the latter one was interrupted due to a consistent lack of analgesic effect. CONCLUSION: NBS in the M1 area seems to be effective in reducing short-term pain; however, more high-quality homogeneous studies, with long-term follow-up, are required to determine the efficacy of this treatment in CSPS.

Predicting conversion from mild cognitive impairment to Alzheimer's disease: a multimodal approach.

Successively predicting whether mild cognitive impairment patients will progress to Alzheimer's disease is of significant clinical relevance. This ability may provide information that can be leveraged by emerging intervention approaches and thus mitigate some of the negative effects of the disease. Neuroimaging biomarkers have gained some attention in recent years and may be useful in predicting the conversion of mild cognitive impairment to Alzheimer's disease. We implemented a novel multi-modal approach that allowed us to evaluate the potential of different imaging modalities, both alone and in different degrees of combinations, in predicting the conversion to Alzheimer's disease of mild cognitive impairment patients. We applied this approach to the imaging data from the Alzheimer's Disease Neuroimaging Initiative that is a multi-modal imaging dataset comprised of MRI, Fluorodeoxyglucose PET, Florbetapir PET and diffusion tensor imaging. We included a total of 480 mild cognitive impairment patients that were split into two groups: converted and stable. Imaging data were segmented into atlas-based regions of interest, from which relevant features were extracted for the different imaging modalities and used to construct machine-learning models to classify mild cognitive impairment patients into converted or stable, using each of the different imaging modalities independently. The models were then combined, using a simple weight fusion ensemble strategy, to evaluate the complementarity of different imaging modalities and their contribution to the prediction accuracy of the models. The single-modality findings revealed that the model, utilizing features extracted from Florbetapir PET, demonstrated the highest performance with a balanced accuracy of 83.51%. Concerning multi-modality models, not all combinations enhanced mild cognitive impairment conversion prediction. Notably, the combination of MRI with Fluorodeoxyglucose PET emerged as the most promising, exhibiting an overall improvement in predictive capabilities, achieving a balanced accuracy of 78.43%. This indicates synergy and complementarity between the two imaging modalities in predicting mild cognitive impairment conversion. These findings suggest that ß-amyloid accumulation provides robust predictive capabilities, while the combination of multiple imaging modalities has the potential to surpass certain single-modality approaches. Exploring modality-specific biomarkers, we identified the brainstem as a sensitive biomarker for both MRI and Fluorodeoxyglucose PET modalities, implicating its involvement in early Alzheimer's pathology. Notably, the corpus callosum and adjacent cortical regions emerged as potential biomarkers, warranting further study into their role in the early stages of Alzheimer's disease.

Rapid effects of tryptamine psychedelics on perceptual distortions and early visual cortical population receptive fields.

N, N-dimethyltryptamine (DMT) is a psychedelic tryptamine acting on 5-HT2A serotonin receptors, which is associated with intense visual hallucinatory phenomena and perceptual changes such as distortions in visual space. The neural underpinnings of these effects remain unknown. We hypothesised that changes in population receptive field (pRF) properties in the primary visual cortex (V1) might underlie visual perceptual experience. We tested this hypothesis using magnetic resonance imaging (MRI) in a within-subject design. We used a technique called pRF mapping, which measures neural population visual response properties and retinotopic maps in early visual areas. We show that in the presence of visual effects, as documented by the Hallucinogen Rating Scale (HRS), the mean pRF sizes in V1 significantly increase in the peripheral visual field for active condition (inhaled DMT) compared to the control. Eye and head movement differences were absent across conditions. This evidence for short-term effects of DMT in pRF may explain perceptual distortions induced by psychedelics such as field blurring, tunnel vision (peripheral vision becoming blurred while central vision remains sharp) and the enlargement of nearby visual space, particularly at the visual locations surrounding the fovea. Our findings are also consistent with a mechanistic framework whereby gain control of ongoing and evoked activity in the visual cortex is controlled by activation of 5-HT2A receptors.

Neural underpinnings of ethical decisions in life and death dilemmas in naïve and expert firefighters.

When a single choice impacts on life outcomes, faculties to make ethical judgments come into play. Here we studied decisions in a real-life setting involving life-and-death outcomes that affect others and the decision-maker as well. We chose a genuine situation where prior training and expertise play a role: firefighting in life-threatening situations. By studying the neural correlates of dilemmas involving life-saving decisions, using realistic firefighting situations, allowed us to go beyond previously used hypothetical dilemmas, while addressing the role of expertise and the use of coping strategies (n = 47). We asked the question whether the neural underpinnings of deontologically based decisions are affected by expertise. These realistic life-saving dilemmas activate the same core reward and affective processing network, in particular the ventromedial prefrontal cortex, nucleus accumbens and amygdala, irrespective of prior expertise, thereby supporting general domain theories of ethical decision-making. We found that brain activity in the hippocampus and insula parametrically increased as the risk increased. Connectivity analysis showed a larger directed influence of the insula on circuits related to action selection in non-experts, which were slower than experts in non rescuing decisions. Relative neural activity related to the decision to rescue or not, in the caudate nucleus, insula and anterior cingulate cortex was negatively associated with coping strategies, in experts (firefighters) suggesting practice-based learning. This shows an association between activity and expert-related usage of coping strategies. Expertise enables salience network activation as a function of behavioural coping dimensions, with a distinct connectivity profile when facing life-rescuing dilemmas.

European Autism GEnomics Registry (EAGER): protocol for a multicentre cohort study and registry.

INTRODUCTION: Autism is a common neurodevelopmental condition with a complex genetic aetiology that includes contributions from monogenic and polygenic factors. Many autistic people have unmet healthcare needs that could be served by genomics-informed research and clinical trials. The primary aim of the European Autism GEnomics Registry (EAGER) is to establish a registry of participants with a diagnosis of autism or an associated rare genetic condition who have undergone whole-genome sequencing. The registry can facilitate recruitment for future clinical trials and research studies, based on genetic, clinical and phenotypic profiles, as well as participant preferences. The secondary aim of EAGER is to investigate the association between mental and physical health characteristics and participants' genetic profiles. METHODS AND ANALYSIS: EAGER is a European multisite cohort study and registry and is part of the AIMS-2-TRIALS consortium. EAGER was developed with input from the AIMS-2-TRIALS Autism Representatives and representatives from the rare genetic conditions community. 1500 participants with a diagnosis of autism or an associated rare genetic condition will be recruited at 13 sites across 8 countries. Participants will be given a blood or saliva sample for whole-genome sequencing and answer a series of online questionnaires. Participants may also consent to the study to access pre-existing clinical data. Participants will be added to the EAGER registry and data will be shared externally through established AIMS-2-TRIALS mechanisms. ETHICS AND DISSEMINATION: To date, EAGER has received full ethical approval for 11 out of the 13 sites in the UK (REC 23/SC/0022), Germany (S-375/2023), Portugal (CE-085/2023), Spain (HCB/2023/0038, PIC-164-22), Sweden (Dnr 2023-06737-01), Ireland (230907) and Italy (CET_62/2023, CEL-IRCCS OASI/24-01-2024/EM01, EM 2024-13/1032 EAGER). Findings will be disseminated via scientific publications and conferences but also beyond to participants and the wider community (eg, the AIMS-2-TRIALS website, stakeholder meetings, newsletters).

Dynamically predicting comprehension difficulties through physiological data and intelligent wearables.

Comprehending digital content written in natural language online is vital for many aspects of life, including learning, professional tasks, and decision-making. However, facing comprehension difficulties can have negative consequences for learning outcomes, critical thinking skills, decision-making, error rate, and productivity. This paper introduces an innovative approach to predict comprehension difficulties at the local content level (e.g., paragraphs). Using affordable wearable devices, we acquire physiological responses non-intrusively from the autonomous nervous system, specifically pulse rate variability, and electrodermal activity. Additionally, we integrate data from a cost-effective eye-tracker. Our machine learning algorithms identify 'hotspots' within the content and regions corresponding to a high cognitive load. These hotspots represent real-time predictors of comprehension difficulties. By integrating physiological data with contextual information (such as the levels of experience of individuals), our approach achieves an accuracy of 72.11% ± 2.21, a precision of 0.77, a recall of 0.70, and an f1 score of 0.73. This study opens possibilities for developing intelligent, cognitive-aware interfaces. Such interfaces can provide immediate contextual support, mitigating comprehension challenges within content. Whether through translation, content generation, or content summarization using available Large Language Models, this approach has the potential to enhance language comprehension.

Executive function in schizophrenia and autism in adults shares common components separating high and low performance groups.

The profile of executive function (EF) in adults with Schizophrenia (SCZ) and autism spectrum disorder (ASD) remains unclear. This study aims to ascertain if distinct EF patterns can be identified between each clinical condition by comparing the neuropsychological profile of adults with SCZ and ASD, for whom the differential diagnosis is still highly challenging. Forty-five individuals (15 SCZ, 15 ASD, 15 controls) matched for age, sex, education level, and handedness underwent intelligence evaluation and neuropsychological testing for working memory, inhibition, planning and set-shifting, and verbal fluency subdomains. Principal component analysis (2D-PCA) using variables representing 4 domains was employed to identify patterns in neuropsychological profiles. The ASD group had lower scores on the Digits Forward subtest compared to the SCZ group (7.2 ± 2.1 vs. 9.3 ± 1.9, p = 0.003; Cohen's d: 1.05). ASD also performed significantly worse on the Stroop Word Test compared to the control group (77.7± 17.9 vs. 98.0 ± 12.7, p = 0.009; Cohen's d: 1.31). No significant differences were observed between ASD and SCZ on other EF measures. The larger contributors for the dimensions in 2D-PCA were the Digits Forward subtest and Stroop Word Test. Still, there was substantial overlap between the clinical groups. This study suggests a high degree of similarity of EF between SCZ and ASD. Through four EF measures, the discrimination of low and high-functioning EF groups spanning both diagnostic categories may help to identify the individuals who could better benefit from cognitive rehabilitation strategies.

Corrigendum: A conceptual view of cognitive intervention in older adults with and without cognitive decline-a systemic review.

[This corrects the article DOI: 10.3389/fragi.2022.844725.].

Corrigendum: Assessing MR-compatibility of somatosensory stimulation devices: a systematic review on testing methodologies.

[This corrects the article DOI: 10.3389/fnins.2023.1071749.].

Corrigendum: Normative mice retinal thickness: 16-month longitudinal characterization of wild-type mice and changes in a model of Alzheimer's disease.

[This corrects the article DOI: 10.3389/fnagi.2023.1161847.].

Quality of life and performance status after cardiopulmonary resuscitation: A study in Cova da Beira University Hospital Center's intensive care unit.

INTRODUCTION AND OBJECTIVES: Cardiac arrest (CA) is associated with high morbidity and mortality. Many studies focus on survival, but few explore the outcomes. The aim of this study is to analyze the survival curve, independence, quality of life, and performance status after CA. METHODS: This retrospective study included adults admitted to the intensive care unit of Cova da Beira University Hospital Center after CA between 2015 and 2019. We analyzed patient records and applied a questionnaire including EuroQoL's EQ-5D-3L and ECOG performance status. RESULTS: Ninety-seven patients were included (mean age 75.74 years). Thirty-one patients (32.0%) survived to hospital discharge. There was a significant loss of independence for activities of daily living, with 50.0% of those previously independent becoming dependent and 47.5% of those previously at home being institutionalized. Diabetes, female gender, and length of hospital stay were especially impactful on these findings. One year after CA, only 20.6% were alive and only 13.4% (65% of the one-year survivors) were independent. Nine patients answered our questionnaire. Mean EQ-5D quality of life index (0.528±0.297) and the most affected domains ('Pain/discomfort' and 'Anxiety/depression') were similar to the Portuguese population aged >30 years. However, 66.6% reported a decline in their quality of life. Lastly, seven respondents had a good performance status (ECOG 0-1). CONCLUSIONS: There was a significant loss of independence after CA. Moreover, despite the acceptable performance status and the quality of life results being similar to the general population, there was a perceived deterioration post-CA. Ultimately, we emphasize the need to improve care for these patients.

Exposure to DEP Modifies the Human Umbilical Artery Vascular Resistance Contributing to Hypertension in Pregnancy.

Hypertensive disorders in pregnancy (HDP) are the most prevalent diseases during pregnancy. In addition to the already identified risk factors, exposure to environmental contaminants has been also considered a new one. Phthalates, which are classified as priority environmental pollutants due to their ubiquitousness and endocrine disrupting properties, have been implicated in HDP in some epidemiological studies. Nevertheless, phthalates' vascular impacts still need to be clarified. Thus, we aimed to understand the connection between phthalates exposure and the occurrence of gestational hypertension, as well as the pathway involved in the pathological vascular effects. We investigated diethyl phthalate's (DEP) effect on the vascular reactivity of the human umbilical arteries (HUAs) from normotensive and hypertensive pregnant women. Both DEP's nongenomic (within minutes effect) and genomic (24 h exposure to DEP) actions were evaluated, as well as the contribution of cyclic guanosine monophosphate and Ca2+ channel pathways. The results show that short-term exposure to DEP interferes with serotonin and histamine receptors, while after prolonged exposure, DEP seems to share the same vasorelaxant mechanism as estrogens, through the NO/sGC/cGMP/PKG signaling pathway, and to interfere with the L-type Ca2+ channels. Thus, the vascular effect induced by DEP is similar to that observed in HUA from hypertensive pregnancies, demonstrating that the development of HDP may be a consequence of DEP exposure.

Polyphenols: immunonutrients tipping the balance of immunometabolism in chronic diseases.

Mounting evidence progressively appreciates the vital interplay between immunity and metabolism in a wide array of immunometabolic chronic disorders, both autoimmune and non-autoimmune mediated. The immune system regulates the functioning of cellular metabolism within organs like the brain, pancreas and/or adipose tissue by sensing and adapting to fluctuations in the microenvironment's nutrients, thereby reshaping metabolic pathways that greatly impact a pro- or anti-inflammatory immunophenotype. While it is agreed that the immune system relies on an adequate nutritional status to function properly, we are only just starting to understand how the supply of single or combined nutrients, all of them termed immunonutrients, can steer immune cells towards a less inflamed, tolerogenic immunophenotype. Polyphenols, a class of secondary metabolites abundant in Mediterranean foods, are pharmacologically active natural products with outstanding immunomodulatory actions. Upon binding to a range of receptors highly expressed in immune cells (e.g. AhR, RAR, RLR), they act in immunometabolic pathways through a mitochondria-centered multi-modal approach. First, polyphenols activate nutrient sensing via stress-response pathways, essential for immune responses. Second, they regulate mammalian target of rapamycin (mTOR)/AMP-activated protein kinase (AMPK) balance in immune cells and are well-tolerated caloric restriction mimetics. Third, polyphenols interfere with the assembly of NLR family pyrin domain containing 3 (NLRP3) in endoplasmic reticulum-mitochondria contact sites, inhibiting its activation while improving mitochondrial biogenesis and autophagosome-lysosome fusion. Finally, polyphenols impact chromatin remodeling and coordinates both epigenetic and metabolic reprogramming. This work moves beyond the well-documented antioxidant properties of polyphenols, offering new insights into the multifaceted nature of these compounds. It proposes a mechanistical appraisal on the regulatory pathways through which polyphenols modulate the immune response, thereby alleviating chronic low-grade inflammation. Furthermore, it draws parallels between pharmacological interventions and polyphenol-based immunonutrition in their modes of immunomodulation across a wide spectrum of socioeconomically impactful immunometabolic diseases such as Multiple Sclerosis, Diabetes (type 1 and 2) or even Alzheimer's disease. Lastly, it discusses the existing challenges that thwart the translation of polyphenols-based immunonutritional interventions into long-term clinical studies. Overcoming these limitations will undoubtedly pave the way for improving precision nutrition protocols and provide personalized guidance on tailored polyphenol-based immunonutrition plans.

Improved Chemical and Radiochemical Synthesis of Neuropeptide Y Y2 Receptor Antagonist N-Methyl-JNJ-31020028 and Preclinical Positron Emission Tomography Studies.

Neuropeptide Y (NPY) is one of the most abundant peptides in the central nervous system of mammals and is involved in several physiological processes through NPY Y1, Y2, Y4 and Y5 receptors. Of those, the Y2 receptor has particular relevance for its autoreceptor role in inhibiting the release of NPY and other neurotransmitters and for its involvement in relevant mechanisms such as feeding behaviour, cognitive processes, emotion regulation, circadian rhythms and disorders such as epilepsy and cancer. PET imaging of the Y2 receptor can provide a valuable platform to understand this receptor's functional role and evaluate its potential as a therapeutic target. In this work, we set out to refine the chemical and radiochemical synthesis of the Y2 receptor antagonist N-[11C]Me-JNJ31020028 for in vivo PET imaging studies. The non-radioactive reference compound, N-Me-JNJ-31020028, was synthesised through batch synthesis and continuous flow methodology, with 43% and 92% yields, respectively. N-[11C]Me-JNJ-31020028 was obtained with a radiochemical purity > 99%, RCY of 31% and molar activity of 156 GBq/µmol. PET imaging clearly showed the tracer's biodistribution in several areas of the mouse brain and gut where Y2 receptors are known to be expressed.

Irreversible atrophy in memory brain regions over 7 years is predicted by glycemic control in type 2 diabetes without mild cognitive impairment.

Memory-related impairments in type 2 diabetes may be mediated by insulin resistance and hyperglycemia. Previous cross-sectional studies have controversially suggested a relationship between metabolic control and a decrease in hippocampal volumes, but only longitudinal studies can test this hypothesis directly. We performed a longitudinal morphometric study to provide a direct test of a possible role of higher levels of glycated hemoglobin with long term brain structural integrity in key regions of the memory system - hippocampus, parahippocampal gyrus and fusiform gyrus. Grey matter volume was measured at two different times - baseline and after ~7 years. We found an association between higher initial levels of HbA1C and grey matter volume loss in all three core memory regions, even in the absence of mild cognitive impairment. Importantly, these neural effects persisted in spite of the fact that patients had significantly improved their glycemic control. This suggests that early high levels of HbA1c might be irreversibly associated with subsequent long-term atrophy in the medial temporal cortex and that early intensive management is critical.

Functional and structural connectivity success predictors of real-time fMRI neurofeedback targeting DLPFC: Contributions from central executive, salience, and default mode networks.

Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback (NF), a training method for the self-regulation of brain activity, has shown promising results as a neurorehabilitation tool, depending on the ability of the patient to succeed in neuromodulation. This study explores connectivity-based structural and functional success predictors in an NF n-back working memory paradigm targeting the dorsolateral prefrontal cortex (DLPFC). We established as the NF success metric the linear trend on the ability to modulate the target region during NF runs and performed a linear regression model considering structural and functional connectivity (intrinsic and seed-based) metrics. We found a positive correlation between NF success and the default mode network (DMN) intrinsic functional connectivity and a negative correlation with the DLPFC-precuneus connectivity during the 2-back condition, indicating that success is associated with larger uncoupling between DMN and the executive network. Regarding structural connectivity, the salience network emerges as the main contributor to success. Both functional and structural classification models showed good performance with 77% and 86% accuracy, respectively. Dynamic switching between DMN, salience network and central executive network seems to be the key for neurofeedback success, independently indicated by functional connectivity on the localizer run and structural connectivity data.

Neurofeedback training of executive function in autism spectrum disorder: distinct effects on brain activity levels and compensatory connectivity changes.

BACKGROUND: Deficits in executive function (EF) are consistently reported in autism spectrum disorders (ASD). Tailored cognitive training tools, such as neurofeedback, focused on executive function enhancement might have a significant impact on the daily life functioning of individuals with ASD. We report the first real-time fMRI neurofeedback (rt-fMRI NF) study targeting the left dorsolateral prefrontal cortex (DLPFC) in ASD. METHODS: Thirteen individuals with autism without intellectual disability and seventeen neurotypical individuals completed a rt-fMRI working memory NF paradigm, consisting of subvocal backward recitation of self-generated numeric sequences. We performed a region-of-interest analysis of the DLPFC, whole-brain comparisons between groups and, DLPFC-based functional connectivity. RESULTS: The ASD and control groups were able to modulate DLPFC activity in 84% and 98% of the runs. Activity in the target region was persistently lower in the ASD group, particularly in runs without neurofeedback. Moreover, the ASD group showed lower activity in premotor/motor areas during pre-neurofeedback run than controls, but not in transfer runs, where it was seemingly balanced by higher connectivity between the DLPFC and the motor cortex. Group comparison in the transfer run also showed significant differences in DLPFC-based connectivity between groups, including higher connectivity with areas integrated into the multidemand network (MDN) and the visual cortex. CONCLUSIONS: Neurofeedback seems to induce a higher between-group similarity of the whole-brain activity levels (including the target ROI) which might be promoted by changes in connectivity between the DLPFC and both high and low-level areas, including motor, visual and MDN regions.

Portuguese observational cross-sectional clinical imaging study protocol to investigate central dopaminergic mechanisms of successful weight loss through bariatric surgery.

INTRODUCTION: Bariatric surgery (BS) is the treatment of choice for refractory obesity. Although weight loss (WL) reduces the prevalence of obesity-related comorbidities, not all patients maintain it. It has been suggested that central mechanisms involving dopamine receptors may play a role in successful WL. This protocol describes an observational cross-sectional study to test if the binding of central dopamine receptors is similar in individuals who responded successfully to BS and age- and gender-matched normal-weight healthy individuals (controls). As secondary goals, the protocol will investigate if this binding correlates with key parameters such as age, hormonal status, anthropometric metrics and neurobehavioural scores. Finally, as exploratory goals, we will include a cohort of individuals with obesity before and after BS to explore whether obesity and type of BS (sleeve gastrectomy and Roux-en-Y gastric bypass) yield distinct binding values and track central dopaminergic changes resulting from BS. METHODS AND ANALYSIS: To address the major research question of this observational study, positron emission tomography (PET) with [11C]raclopride will be used to map brain dopamine type 2 and 3 receptors (D2/3R) non-displaceable binding potential (BPND) of individuals who have successfully responded to BS. Mean regional D2/3R BPND values will be compared with control individuals by two one-sided test approaches. The sample size (23 per group) was estimated to demonstrate the equivalence between two independent group means. In addition, these binding values will be correlated with key parameters to address secondary goals. Finally, for exploratory analysis, these values will be compared within the same individuals (before and after BS) and between individuals with obesity and controls and types of BS. ETHICS AND DISSEMINATION: The project and informed consent received ethical approval from the Faculty of Medicine and the Coimbra University Hospital ethics committees. Results will be disseminated in international peer-reviewed journals and conferences.

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.