Search

Callous unemotional (CU) traits refer to specific deficits in affective experience and interpersonal style, characterized by absence of guilt, constrictive display of emotion and failure to show empathy, callous use of others for one’s own gain. The Inventory of Callous-Unemotional Traits (ICU) was developed to measure CU traits in children and adolescents. The aim of this study was to analyze the factorial structure of the Portuguese version of teacher-report ICU for children in school age and examine psychometric properties such as internal consistency and convergent validity in a community sample. Thirty-six teachers provided behavioral ratings of 100 and 78 children of elementary school, 88 boys and 90 girls, aged between 6 and 10 years old. Confirmatory factor analyses provided further support to a 2-factor structure, comprising the following dimensions: callous and uncaring. This study showed that the ICU seems a reliable an accessible tool that can be used in the Portuguese educational context to evaluate CU traits with low time consumption.

Oxytocin (OT) is a key modulator of human social cognition, popular in behavioral neuroscience. To adequately design and interpret intranasal OT (IN-OT) research, it is crucial to know for how long it affects human brain function once administered. However, this has been mostly deduced from peripheral body fluids studies, or uncommonly used dosages. We aimed to characterize IN-OT’s effects on human brain function using resting-state EEG microstates across a typical experimental session duration. Nineteen healthy males participated in a double-blind, placebo-controlled, within-subject, cross-over design of 24 IU of IN-OT in 12-min windows 15 min-to-1 h 42min after administration. We observed IN-OT effects on all microstates, across the observation span. During eyes-closed, IN-OT increased duration and contribution of A and contribution and occurrence of D, decreased duration and contribution of B and C; and increased transition probability C-to-B and C-to-D. In eyes-open, it increased A-to-C and A-to-D. As microstates A and D have been related to phonological auditory and attentional networks, respectively, we posit IN-OT may tune the brain for reception of external stimuli, particularly of social nature—tentatively supporting current neurocognitive hypotheses of OT. Moreover, we contrast our overall results against a comprehensive literature review of IN-OT time-course effects in the brain, highlighting comparability issues.

Electroencephalogram microstates are recurrent scalp potential configurations that remain stable for around 90 ms. The dynamics of two of the four canonical classes of microstates, commonly labeled as C and D, have been suggested as a potential endophenotype for schizophrenia. For endophenotypes, unaffected relatives of patients must show abnormalities compared to controls. Here, we examined microstate dynamics in resting-state recordings of unaffected siblings of patients with schizophrenia, patients with schizophrenia, healthy controls, and patients with first episodes of psychosis (FEP). Patients with schizophrenia and their siblings showed increased presence of microstate class C and decreased presence of microstate class D compared to controls. No difference was found between FEP and chronic patients. Our findings suggest that the dynamics of microstate classes C and D are a candidate endophenotype for schizophrenia., EEG microstate abnormalities have been reported in patients with schizophrenia. Here the authors demonstrate that patients and their siblings show similar microstate abnormalities compared to healthy controls.

Introduction. Diabetic neuropathy (DN) is one of the most devastating complications of diabetes mellitus; however, in contrast to other countries, there are no scientific studies in Portugal evaluating the impact of demographic and clinical characteristics of this pathological entity. The aim of this study was to evaluate the impact of gender, metabolic control, age of diabetic patients, as well as time of disease progression, the appearance of complaints related to neuropathic pain. Material and methods. A multicentre study with a non-probabilistic, convenience sample of 359 patients was performed employing the quantitative method, using the Statistical Package for Social Science 24 software. The p-value of p < 0.05 was defined to consider a result statistically significant. The Spearman correlation coefficient (r) was determined to determine the relationship between categorical variables. Results. There was no statistically significant difference in the prevalence of DN between genders (p = 0.633 and r = 0.025). There was a statistically significant relationship between the value of HbA1c and DN, with p = 0.010 and r = 0.136. There is a relationship between age and complaints of neuropathic pain, with p = 0.034 and r = 0.112. The variable, time of disease progression, is also correlated with the appearance of complaints of neuropathic pain with p = 0.020 and r = 0.112. Conclusion. The prevalence of neuropathic pain in subjects with diabetes is not negligible and is associated with modifiable risk factors that can be identified, possibly modified and prevented. The correct approach for these patients, which involves screening and early treatment, is decisive improving functionality and quality of life.

Visual backward masking (VBM) deficits are candidate endophenotypes of schizophrenia indexing genetic liability of the disorder. In VBM, a target is followed by a mask that deteriorates target perception. Schizophrenia patients and, to a lesser extent, their unaffected relatives show strong and reproducible VBM deficits. In patients, VBM deficits are associated with strongly decreased amplitudes in the evoked-related potentials (ERPs). Here, to unveil the neural mechanisms of VBM in schizophrenia, circumventing illness-specific confounds, we investigated the electroencephalogram correlates of VBM in unaffected siblings of schizophrenia patients. We tested 110 schizophrenia patients, 60 siblings, and 83 healthy controls. As in previous studies, patients showed strong behavioral deficits and decreased ERP amplitudes compared to controls. Surprisingly, the ERP amplitudes of siblings were even higher than the ones of controls, while their performances were similar. ERP amplitudes in siblings were found to correlate with performance. These results suggest that VBM is deteriorated in patients and siblings. However, siblings, unlike patients, can partially compensate for the deficits by over-activating a network of brain regions.

Social dominance, the main organizing principle of social hierarchies, facilitates priority access to resources by dominant individuals. Throughout taxa, individuals are more likely to become dominant if they act first in social situations and acting fast may provide evolutionary advantage; yet whether fast decision-making is a behavioral predisposition of dominant persons outside of social contexts is not known. Following characterization of participants for social dominance motivation, we found that, indeed, men high in social dominance respond faster–without loss of accuracy–than those low in dominance across a variety of decision-making tasks. Both groups did not differ in a simple reaction task. Then, we selected a decision-making task and applied high-density electroencephalography (EEG) to assess temporal dynamics of brain activation through event related potentials. We found that promptness to respond in the choice task in dominant individuals is related to a strikingly amplified brain signal at approximately 240 ms post-stimulus presentation. Source imaging analyses identified higher activity in the left insula and in the cingulate, right inferior temporal and right angular gyri in high than in low dominance participants. Our findings suggest that promptness to respond in choice situations, regardless of social context, is a biomarker for social disposition.

© 2020 The Authors. European Journal of Immunology published by Wiley‐VCH GmbH. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited., SARS-CoV-2 has emerged as a human pathogen, causing clinical signs, from fever to pneumonia-COVID-19-but may remain mild or asymptomatic. To understand the continuing spread of the virus, to detect those who are and were infected, and to follow the immune response longitudinally, reliable and robust assays for SARS-CoV-2 detection and immunological monitoring are needed. We quantified IgM, IgG, and IgA antibodies recognizing the SARS-CoV-2 receptor-binding domain (RBD) or the Spike (S) protein over a period of 6 months following COVID-19 onset. We report the detailed setup to monitor the humoral immune response from over 300 COVID-19 hospital patients and healthcare workers, 2500 University staff, and 198 post-COVID-19 volunteers. Anti-SARS-CoV-2 antibody responses follow a classic pattern with a rapid increase within the first three weeks after symptoms. Although titres reduce subsequently, the ability to detect anti-SARS-CoV-2 IgG antibodies remained robust with confirmed neutralization activity for up to 6 months in a large proportion of previously virus-positive screened subjects. Our work provides detailed information for the assays used, facilitating further and longitudinal analysis of protective immunity to SARS-CoV-2. Importantly, it highlights a continued level of circulating neutralising antibodies in most people with confirmed SARS-CoV-2., We like to acknowledge the funding from the European Union H2020 ERA project (No 667824 – EXCELLtoINNOV) and the Fundação para a Ciência e a Tecnologia (FCT) to P.F‐C. (SFRH/BD/131605/2017), PTDC/MED‐IMU/28003/2017, and research4COVID19 (no. 231_596873172, Generating SARS‐CoV2 seroconversion assay and no. 729, High‐throughput SARS‐CoV2 neutralizing antibodies assessment), with additional support by Sociedade Francisco Manuel dos Santos.

BackgroundMining activities have environmental impacts due to sediment movement and contamination of areas and may also pose risks to people’s food security. In Brazil, the majority of coal mining activities are in the south, in the Santa Catarina carboniferous region. In this region, previously mined areas contaminated with heavy metals frequently occur nearby inhabited zones. Mining is part of the daily lives of local communities, and its environmental impacts are visible in the landscape; however, plants with medicinal and food use from these areas can be still consumed. Heavy metals are contaminants that do not have odor, color, or taste, and are therefore difficult to detect. We aimed to verify whether people use plants from contaminated mine areas, and understand which factors can influence the use of these resources, even from areas visibly impacted.MethodsWe conducted 195 semi-structured interviews with residents from 14 areas nearby abandoned mines in the main municipalities of the Santa Catarina carboniferous region. We asked each interviewee about the length of time they lived in the region, their perception of the quality of the environment, and what plant species were used and for what purpose. We constructed generalized multivariate linear models to verify which variables can affect the group of species mentioned and generalized linear models to verify which variables can affect the total number of citations. We estimated the frequency of citing species collected using the Smith index.ResultsFrom all interviewees, 127 (65%) reported collecting plants for medicinal and food use, directly from contaminated mine areas. Long-term residents, as well as those who noticed more environmental changes (positive and negative), cited more plants used and had more detailed knowledge of plant use in their communities. When asked if they were aware of the possible contamination of mined areas, 85% said they knew about it. However, only 10% associated negative health effects with the use of plant species collected in contaminated mined areas.ConclusionsOur study demonstrates that people living nearby contaminated areas use and consume locally sourced plants, e.g., people know little about the danger of this contamination in their food and the risk of these contaminants to their health. These results also reveal a lack of information about contamination, as well as a lack of actions that include local communities in contaminated area restoration strategies. This situation poses a risk to the food security of the people living nearby former coal mining areas.

Objective With the advent of high-density EEG and studies of large numbers of participants, yielding increasingly greater amounts of data, supervised methods for artifact rejection have become excessively time consuming. Here, we propose a novel automatic pipeline (APP) for pre-processing and artifact rejection of EEG data, which innovates relative to existing methods by not only following state-of-the-art guidelines but also further employing robust statistics. Methods APP was tested on event-related potential (ERP) data from healthy participants and schizophrenia patients, and resting-state (RS) data from healthy participants. Its performance was compared with that of existing automatic methods (FASTER for ERP data, TAPEEG and Prep pipeline for RS data) and supervised pre-processing by experts. Results APP rejected fewer bad channels and bad epochs than the other methods. In the ERP study, it produced significantly higher amplitudes than FASTER, which were consistent with the supervised scheme. In the RS study, it produced spectral measures that correlated well with the automatic alternatives and the supervised scheme. Conclusion APP effectively removed EEG artifacts, performing similarly to the supervised scheme and outperforming existing automatic alternatives. Significance The proposed automatic pipeline provides a reliable and efficient tool for pre-processing large datasets of both evoked and resting-state EEG.

External stimuli and tasks often elicit negative BOLD responses in various brain regions, and growing experimental evidence supports that these phenomena are functionally meaningful. In this work, the high sensitivity available at 7T was explored to map and characterize both positive (PBRs) and negative BOLD responses (NBRs) to visual checkerboard stimulation, occurring in various brain regions within and beyond the visual cortex. Recently-proposed accelerated fMRI techniques were employed for data acquisition, and procedures for exclusion of large draining vein contributions, together with ICA-assisted denoising, were included in the analysis to improve response estimation. Besides the visual cortex, significant PBRs were found in the lateral geniculate nucleus and superior colliculus, as well as the pre-central sulcus; in these regions, response durations increased monotonically with stimulus duration, in tight covariation with the visual PBR duration. Significant NBRs were found in the visual cortex, auditory cortex, default-mode network (DMN) and superior parietal lobule; NBR durations also tended to increase with stimulus duration, but were significantly less sustained than the visual PBR, especially for the DMN and superior parietal lobule. Responses in visual and auditory cortex were further studied for checkerboard contrast dependence, and their amplitudes were found to increase monotonically with contrast, linearly correlated with the visual PBR amplitude. Overall, these findings suggest the presence of dynamic neuronal interactions across multiple brain regions, sensitive to stimulus intensity and duration, and demonstrate the richness of information obtainable when jointly mapping positive and negative BOLD responses at a whole-brain scale, with ultra-high field fMRI.

Tissue-resident memory T (T

Electroencephalography (EEG) neurofeedback (NF) training has been shown to produce long-lasting effects on the improvement of cognitive function as well as the normalization of aberrant brain activity in disease. However, the impact of the sensory modality used as the NF reinforcement signal on training effectiveness has not been systematically investigated. In this work, an EEG-based NF-training system was developed targeting the individual upper-alpha (UA) band and using either a visual or an auditory reinforcement signal, so as to compare the effects of the two sensory modalities. Sixteen healthy volunteers were randomly assigned to the Visual or Auditory group, where a radius-varying sphere or a volume-varying sound, respectively, reflected the relative amplitude of UA measured at EEG electrode Cz. Each participant underwent a total of four NF sessions, of approximately 40 min each, on consecutive days. Both groups showed significant increases in UA at Cz within sessions, and also across sessions. Effects subsequent to NF training were also found beyond the target frequency UA and scalp location Cz, namely in the lower-alpha and theta bands and in posterior brain regions, respectively. Only small differences were found on the EEG between the Visual and Auditory groups, suggesting that auditory reinforcement signals may be as effective as the more commonly used visual signals. The use of auditory NF may potentiate training protocols conducted under mobile conditions, which are now possible due to the increasing availability of wireless EEG systems.

Over the last decade, we have witnessed consistent advances in risk assessment procedures, namely the validation of those used with juveniles who have committed sexual offenses. The adaptation of these instruments into other languages requires research examining the conceptual and metric equivalence of the instruments, not just translation equivalence. Informed by data from 141 boys, aged 13 to 18, the psychometric properties of the Portuguese version of the Juvenile Sex Offender Assessment Protocol–II (J-SOAP-II), regarding reliability and construct validation, are presented and discussed. Factor structure, internal consistency, and interrater reliability were examined, and a reliable factorial structure that was consistent with the original validation of the J-SOAP was found. Scales 2 and 3 had good internal consistency, and Scale 1 had acceptable internal consistency. Results regarding concurrent validity revealed mostly statistically significant correlations. The implications of this research for juvenile sex offender risk assessments are discussed., The author(s) received no financial support for the research, authorship, and/or publication of this article.

Cerebrovascular reactivity (CVR) reflects the capacity of blood vessels to adjust their caliber in order to maintain a steady supply of brain perfusion, and it may provide a sensitive disease biomarker. Measurement of the blood oxygen level dependent (BOLD) response to a hypercapnia-inducing breath-hold (BH) task has been frequently used to map CVR noninvasively using functional magnetic resonance imaging (fMRI). However, the best modeling approach for the accurate quantification of CVR maps remains an open issue. Here, we compare and optimize Fourier models of the BOLD response to a BH task with a preparatory inspiration, and assess the test-retest reproducibility of the associated CVR measurements, in a group of 10 healthy volunteers studied over two fMRI sessions. Linear combinations of sine-cosine pairs at the BH task frequency and its successive harmonics were added sequentially in a nested models approach, and were compared in terms of the adjusted coefficient of determination and corresponding variance explained (VE) of the BOLD signal, as well as the number of voxels exhibiting significant BOLD responses, the estimated CVR values, and their test-retest reproducibility. The brain average VE increased significantly with the Fourier model order, up to the 3rd order. However, the number of responsive voxels increased significantly only up to the 2nd order, and started to decrease from the 3rd order onwards. Moreover, no significant relative underestimation of CVR values was observed beyond the 2nd order. Hence, the 2nd order model was concluded to be the optimal choice for the studied paradigm. This model also yielded the best test-retest reproducibility results, with intra-subject coefficients of variation of 12 and 16% and an intra-class correlation coefficient of 0.74. In conclusion, our results indicate that a Fourier series set consisting of a sine-cosine pair at the BH task frequency and its two harmonics is a suitable model for BOLD-fMRI CVR measurements based on a BH task with preparatory inspiration, yielding robust estimates of this important physiological parameter.

Background Independent Component Analysis (ICA) is commonly used for the identification of sources of interest in electroencephalographic (EEG) data, but the selection of the relevant components remains an open issue depending on the specific application. New Method We propose a novel approach for the objective selection of epilepsy-related independent components (ICs) from EEG data collected during functional Magnetic Resonance Imaging (fMRI) acquisitions, called PROJection onto Independent Components (PROJIC). Inter-ictal epileptiform discharges (IEDs) are identified on a reference EEG dataset collected outside the MRI scanner by an expert neurophysiologist, and the resulting average IED is projected onto the IC space of the EEG data collected simultaneously with fMRI. The power of the IED projection is then used to inform a k-means clustering algorithm of the ICs, allowing for the classification of epilepsy-related ICs. Comparison with existing methods The performance of PROJIC was compared with two methods previously proposed for the objective selection of EEG ICs of interest, which are based on the explicit similarity of the ICs with spatio-temporal templates of the events of interest, instead of the projection power. Results The proposed PROJIC method outperformed the others for both artificial and real data (19 datasets collected from 6 patients with drug-refractory focal epilepsy), with an average accuracy of 98.6%. Conclusions The ability of our method to accurately and objectively select epilepsy-related ICs makes it an important contribution for simultaneous EEG–fMRI epilepsy studies, with potential applications in the analysis of event-related EEG activity more generally, and also in EEG artefact correction.

The enhanced functional sensitivity offered by ultra-high field imaging may significantly benefit simultaneous EEG-fMRI studies, but the concurrent increases in artifact contamination can strongly compromise EEG data quality. In the present study, we focus on EEG artifacts created by head motion in the static B0 field. A novel approach for motion artifact detection is proposed, based on a simple modification of a commercial EEG cap, in which four electrodes are non-permanently adapted to record only magnetic induction effects. Simultaneous EEG-fMRI data were acquired with this setup, at 7 T, from healthy volunteers undergoing a reversing-checkerboard visual stimulation paradigm. Data analysis assisted by the motion sensors revealed that, after gradient artifact correction, EEG signal variance was largely dominated by pulse artifacts (81-93%), but contributions from spontaneous motion (4-13%) were still comparable to or even larger than those of actual neuronal activity (3-9%). Multiple approaches were tested to determine the most effective procedure for denoising EEG data incorporating motion sensor information. Optimal results were obtained by applying an initial pulse artifact correction step (AAS-based), followed by motion artifact correction (based on the motion sensors) and ICA denoising. On average, motion artifact correction (after AAS) yielded a 61% reduction in signal power and a 62% increase in VEP trial-by-trial consistency. Combined with ICA, these improvements rose to a 74% power reduction and an 86% increase in trial consistency. Overall, the improvements achieved were well appreciable at single-subject and single-trial levels, and set an encouraging quality mark for simultaneous EEG-fMRI at ultra-high field.

Depression and schizophrenia are two psychiatric diseases with high co-morbidity. For this reason, it is important to find sensitive endophenotypes, which may disentangle the two disorders. The Shine-Through paradigm, a visual backward masking task, is a potential endophenotype for schizophrenia. Masking is strongly deteriorated in schizophrenia patients, which is reflected in reduced EEG amplitudes. Here, we tested whether masking deficits and associated EEG changes are also found in patients with major depressive disorder. First, we replicated previous findings showing that depressive patients exhibit, at most, only weak masking deficits. Second, we found that the EEG amplitudes of depressive patients were reduced compared to controls and slightly increased compared to schizophrenia patients. As a secondary analysis, we compared the performance in the masking paradigm with three cognitive tasks, namely: the Wisconsin card sorting test, a verbal fluency test and a degraded continuous performance test. Performance in all but the verbal fluency test could discriminate schizophrenia from depression.

Congestive heart failure (CHF) occurs when the heart can no longer maintain the baseline metabolic demand triggered by physiological venous pressure. In the pediatric population, it corresponds to a complex entity with multiple etiologies, depending on the age group assessed, being mainly associated with congenital structural malformations, cardiomyopathies, or secondary to arrhythmogenic, infectious, ischemic, toxic or infiltrative events1. The incidence of CHF in children also varies according to the underlying condition, ranging from 15% to 25% in patients with congenital heart defects. In structurally normal hearts, cardiomyopathy is the major factor associated with CHF, with a 40% incidence of CHF reported in those patients1. Isolated noncompaction cardiomyopathy is a rare disease, whose incidence in the general population ranges from 0.014% to 1.3%. It might result from a failure in compaction of the ventricular myocardium between weeks 5 and 8 of the embryonic life, leading to the persistence of myocardial trabeculations and deep recesses, which communicate with the ventricular cavity, generating myocardial thickening in two distinct layers (compacted and noncompacted). Initially reported in the pediatric population or with a congenital cardiopathy, it also affects adults with no other heart disease2,3. This failure in the regression of embryonic sinusoids is postulated to be due to the extremely high pressures that the ventricles undergo in that developmental period. However, the literature has reported a genetic aspect emphasizing the relationship of the disease with different genes, such as the mutation of gene G4.5 in families with severe infantile noncompaction cardiomyopathy, mutations P121L, CYPHER/ZASP, E101K, and a locus containing the disease gene in chromosome 11p153. The major complications of patients with noncompaction cardiomyopathy are pulmonary thromboembolism, arrhythmias and CHF3. In addition to the usual treatment of CHF, new classes of drugs, such as the phosphodiesterase type 5 (PDE-5) inhibitors, have been studied4. They are currently used for the treatment of erectile dysfunction and pulmonary arterial hypertension, and began to be studied for the treatment of CHF after the demonstration of higher PDE-5 expression in myocytes and vascular muscle cells, as well as of markers of oxidative stress in patients with CHF5. We report, for the first time, the clinical and laboratory findings of a patient with noncompaction cardiomyopathy after the addition of sildenafil (PDE-5 inhibitor) to the usual treatment.

Segmented three-dimensional echo planar imaging (3D-EPI) provides higher image signal-to-noise ratio (SNR) than standard single-shot two-dimensional echo planar imaging (2D-EPI), but is more sensitive to physiological noise. The aim of this study was to compare physiological noise removal efficiency in single-shot 2D-EPI and segmented 3D-EPI acquired at 7 Tesla. Two approaches were investigated based either on physiological regressors (PR) derived from cardiac and respiratory phases, or on principal component analysis (PCA) using additional resting-state data. Results show that, prior to physiological noise removal, 2D-EPI data had higher temporal SNR (tSNR), while spatial SNR was higher in 3D-EPI. Blood oxygen level dependent (BOLD) sensitivity was similar for both methods. The PR-based approach allowed characterization of relative contributions from different noise sources, confirming significant increases in physiological noise from 2D to 3D prior to correction. Both physiological noise removal approaches produced significant increases in tSNR and BOLD sensitivity, and these increases were larger for 3D-EPI, resulting in higher BOLD sensitivity in the 3D-EPI than in the 2D-EPI data. The PCA-based approach was the most effective correction method, yielding higher tSNR values for 3D-EPI than for 2D-EPI postcorrection.

Dyslipidemia is one of the main risk factors associated with cardiovascular diseases. Few data on the impacts of congenital heart diseases are available with regard to the prevalence of dyslipidemia in children. Our study evaluated the lipid profile in children with congenital heart disease at a referral center. From January 2011 to July 2012, 52 pediatric patients had their lipid, metabolic and clinical profiles traced. The mean age was 10.4 ± 2.8 years and male/female rate of 1.38:1. Our population had 53.8% patients with high levels of total cholesterol and 13.4% (CI 95 %, from 6.6 to 25.2%) of them also presenting LDL levels ≥ 130 mg/dL, which characterizes dyslipidemia. The group of dyslipidemic patients presented only two obese individuals. Our data show that the presence of congenital heart disease does not lead to higher risk associated with the prevalence of dyslipidemia. Therefore, the screening of this specific population should follow the regular pediatric guidelines, which are also independent of the nutritional status of the children tested.

Purpose To study arterial spin labeling (ASL) MRI techniques and to investigate various problematic issues that still hinder the accurate and robust quantitative analysis of ASL data. Materials and Methods A pulsed-ASL (PASL) sequence was implemented on a 3-T imaging system and a protocol was developed for the measurement of perfusion based on fitting to a standard kinetic model. Both numerical simulations and multi-inversion time MRI data were analyzed. The effect of fitting a kinetic curve to a large region of interest (ROI) with a distribution of arterial transit times was compared to a pixel-by-pixel (PBP) method. Results It was found that a significant underestimation of perfusion of approximately 17 ± 6% (P < 0.001) occurs in gray matter, when comparing an ROI with a PBP analysis over a group of 12 healthy subjects. Conclusion Analysis of ASL data based on a large ROI may suffer from inaccuracies arising from a distribution of transit times, implying that averaging of ASL kinetic data over such regions should therefore be avoided. When possible, a PBP fit should be performed. J. Magn. Reson. Imaging 2005;21:676–682. © 2005 Wiley-Liss, Inc.

Several strategies have been proposed to model and remove physiological noise from resting-state fMRI (rs-fMRI) data, particularly at ultrahigh fields (7 Tesla), including contributions from respiratory volume (RV) and heart rate (HR) signal fluctuations. Recent studies suggest that these contributions are highly variable across subjects and that physiological noise correction may thus benefit from optimization at the subject or even voxel level. Here, we systematically investigated the impact of the degree of spatial specificity (group, subject, newly proposed cluster, and voxel levels) on the optimization of RV and HR models. For each degree of spatial specificity, we measured the fMRI signal variance explained (VE) by each model, as well as the functional connectivity underlying three well-known resting-state networks (RSNs) obtained from the fMRI data after removal of RV+HR contributions. Whole-brain, high-resolution rs-fMRI data were acquired from twelve healthy volunteers at 7 Tesla, while simultaneously recording their cardiac and respiratory signals. Although VE increased with spatial specificity up to the voxel level, the accuracy of functional connectivity measurements improved only up to the cluster level, and subsequently decreased at the voxel level. This suggests that voxelwise modeling over-fits to local fluctuations with no physiological meaning. In conclusion, our results indicate that 7 Tesla rs-fMRI connectivity measurements improve if a cluster-based physiological noise correction approach is employed in order to take into account the individual spatial variability in the HR and RV contributions.

The study of spontaneous brain activity based on BOLD-fMRI may be seriously compromised by the presence of signal fluctuations of non-neuronal origin, most prominently due to cardiac and respiratory mechanisms. Methods used for modeling and correction of the so-called physiological noise usually rely on the concurrent measurement of cardiac and respiratory signals. In simultaneous EEG-fMRI recordings, which are primarily aimed at the study of spontaneous brain activity, the electrocardiogram (ECG) is typically measured as part of the EEG setup but respiratory data are not generally available. Here, we propose to use the ECG-derived respiratory (EDR) signal estimated by Empirical Mode Decomposition (EMD) as a surrogate of the respiratory signal, for retrospective physiological noise correction of typical simultaneous EEG-fMRI data. A physiological noise model based on these physiological signals (P-PNM) complemented with fMRI-derived noise regressors was generated, and evaluated, for 17 simultaneous EEG-fMRI datasets acquired from a group of seven epilepsy patients imaged at 3T. The respiratory components of P-PNM were found to explain BOLD variance significantly in addition to the cardiac components, suggesting that the EDR signal was successfully extracted from the ECG, and P-PNM outperformed an image-based model (I-PNM) in terms of total BOLD variance explained. Further, the impact of the correction using P-PNM on fMRI mapping of patient-specific epileptic networks and the resting-state default mode network (DMN) was assessed in terms of sensitivity and specificity and, when compared with an ICA-based procedure and a standard pre-processing pipeline, P-PNM achieved the best performance. Overall, our results support the feasibility and utility of extracting physiological noise models of the BOLD signal resorting to ECG data exclusively, with substantial impact on the simultaneous EEG-fMRI mapping of resting-state networks, and, most importantly, epileptic networks where sensitivity and specificity are still limited.

Simultaneous EEG–fMRI offers the possibility of non-invasively studying the spatiotemporal dynamics of epileptic activity propagation from the focus towards an extended brain network, through the identification of the haemodynamic correlates of ictal electrical discharges. In epilepsy associated with hypothalamic hamartomas (HH), seizures are known to originate in the HH but different propagation pathways have been proposed. Here, Dynamic Causal Modelling (DCM) was employed to estimate the seizure propagation pathway from fMRI data recorded in a HH patient, by testing a set of clinically plausible network connectivity models of discharge propagation. The model consistent with early propagation from the HH to the temporal–occipital lobe followed by the frontal lobe was selected as the most likely model to explain the data. Our results demonstrate the applicability of DCM to investigate patient-specific effective connectivity in epileptic networks identified with EEG–fMRI. In this way, it is possible to study the propagation pathway of seizure activity, which has potentially great impact in the decision of the surgical approach for epilepsy treatment., Highlights ► Seizure EEG–fMRI data of a hypothalamic hamartoma epileptic patient was analysed. ► Two competing hypotheses for seizure propagation pathways were tested. ► DCM was used to estimate all plausible connectivity models of seizure propagation. ► Bayesian model selection yielded a model consistent with previous evidence. ► This study provides the first application of DCM to EEG–fMRI data of human seizures.

The ballistocardiogram (BCG) artifact is currently one of the most challenging in the EEG acquired concurrently with fMRI, with correction invariably yielding residual artifacts and/or deterioration of the physiological signals of interest. In this paper, we propose a family of methods whereby the EEG is decomposed using Independent Component Analysis (ICA) and a novel approach for the selection of BCG-related independent components (ICs) is used (PROJection onto Independent Components, PROJIC). Three ICA-based strategies for BCG artifact correction are then explored: 1) BCG-related ICs are removed from the back-reconstruction of the EEG (PROJIC); and 2-3) BCG-related ICs are corrected for the artifact occurrences using an Optimal Basis Set (OBS) or Average Artifact Subtraction (AAS) framework, before back-projecting all ICs onto EEG space (PROJIC-OBS and PROJIC-AAS, respectively). A novel evaluation pipeline is also proposed to assess the methods performance, which takes into account not only artifact but also physiological signal removal, allowing for a flexible weighting of the importance given to physiological signal preservation. This evaluation is used for the group-level parameter optimization of each algorithm on simultaneous EEG-fMRI data acquired using two different setups at 3T and 7T. Comparison with state-of-the-art BCG correction methods showed that PROJIC-OBS and PROJIC-AAS outperformed the others when priority was given to artifact removal or physiological signal preservation, respectively, while both PROJIC-AAS and AAS were in general the best choices for intermediate trade-offs. The impact of the BCG correction on the quality of event-related potentials (ERPs) of interest was assessed in terms of the relative reduction of the standard error (SE) across trials: 26/66%, 32/62% and 18/61% were achieved by, respectively, PROJIC, PROJIC-OBS and PROJIC-AAS, for data collected at 3T/7T. Although more significant improvements were achieved at 7T, the results were qualitatively comparable for both setups, which indicate the wide applicability of the proposed methodologies and recommendations.

The simultaneous recording of scalp electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) can provide unique insights into the dynamics of human brain function, and the increased functional sensitivity offered by ultra-high field fMRI opens exciting perspectives for the future of this multimodal approach. However, simultaneous recordings are susceptible to various types of artifacts, many of which scale with magnetic field strength and can seriously compromise both EEG and fMRI data quality in recordings above 3T. The aim of the present study was to implement and characterize an optimized setup for simultaneous EEG-fMRI in humans at 7 T. The effects of EEG cable length and geometry for signal transmission between the cap and amplifiers were assessed in a phantom model, with specific attention to noise contributions from the MR scanner coldheads. Cable shortening (down to 12 cm from cap to amplifiers) and bundling effectively reduced environment noise by up to 84% in average power and 91% in inter-channel power variability. Subject safety was assessed and confirmed via numerical simulations of RF power distribution and temperature measurements on a phantom model, building on the limited existing literature at ultra-high field. MRI data degradation effects due to the EEG system were characterized via B0 and B1(+) field mapping on a human volunteer, demonstrating important, although not prohibitive, B1 disruption effects. With the optimized setup, simultaneous EEG-fMRI acquisitions were performed on 5 healthy volunteers undergoing two visual paradigms: an eyes-open/eyes-closed task, and a visual evoked potential (VEP) paradigm using reversing-checkerboard stimulation. EEG data exhibited clear occipital alpha modulation and average VEPs, respectively, with concomitant BOLD signal changes. On a single-trial level, alpha power variations could be observed with relative confidence on all trials; VEP detection was more limited, although statistically significant responses could be detected in more than 50% of trials for every subject. Overall, we conclude that the proposed setup is well suited for simultaneous EEG-fMRI at 7 T.

The study aimed to analyze the available evidence in the literature on nursing care in the hospital post-cardiac surgery. Data were collected from electronic databases LILACS, SciELO, MEDLINE, via DeCS thoracic surgery, hospital, nursing care, in the period 2001 to 2011. Ten articles were selected that showed the need to develop a plan of nursing discharge focusing on prevention of complications and coping with physical limitations resulting from heart surgery. Thus, the discharge should be considered from the time of admission, with carefully planned actions involving patient and family. O estudo objetivou analisar evidências disponíveis na literatura sobre a assistência de enfermagem na alta hospitalar em pós-operatório de cirurgia cardíaca. Os dados foram coletados das bases eletrônicas LILACS, SciELO, MEDLINE, através dos DeCS cirurgia torácica, alta hospitalar, cuidados de enfermagem, no período de 2001 a 2011. Foram selecionados dez artigos que revelaram a necessidade de desenvolver um plano de alta de enfermagem com foco na prevenção das complicações e no enfrentamento das limitações físicas decorrentes da cirurgia cardíaca. Destarte, a alta hospitalar deve ser pensada desde o momento da admissão, com ações de cuidado planejadas envolvendo paciente e familiar.

It has recently been proposed that hypocapnic cerebrovascular reactivity (CVR) can be assessed by measuring the blood oxygenation level dependent (BOLD) response to paced deep breathing (PDB) tasks inducing mild hypocapnia and vasoconstriction. In this work, we aim to assess the test–retest reproducibility and inter-subject variability of BOLD CVR measurements obtained using a PDB task and different methods to analyse the associated BOLD signal. The respiratory protocol consisted of alternating 40 s of PDB with normal free breathing; expired CO 2 pressure levels (P ET CO 2 ) were continuously monitored. CVR was quantified using either a timecourse curve analysis (TCA) approach, where the magnitude of response peaks is emphasized, or general linear modelling (GLM) including optimisation of the BOLD response latencies. The GLM fit was carried out using two types of response regressors: one that was computed as the convolution of P ET CO 2 traces with a gamma function and another that consisted of the convolution of PDB paradigm blocks with a physiological model of the respiratory response. Haemodynamic response latencies were optimised either on a voxel basis or for the whole imaging region. We found that the GLM method based on PDB task or P ET CO 2 traces and voxelwise optimisation of response latencies provided the most reproducible measures of CVR. For the average grey matter CVR, the inter-subject coefficient of variation (CV inter ) / intra-subject coefficient of variation (CV intra ) / intra-class correlation coefficient (ICC) were 20%/8%/0.8 and 27%/8%/0.9, using the task and P ET CO 2 timecourses, respectively. In terms of the spatial reproducibility, the group mean (± standard deviation) of the spatial ICC (ICC spatial ) was 1.04 ± 0.23 and 1.02 ± 0.26, for the task and P ET CO 2 timecourses, respectively. These results indicate generally good reproducibility of the hypocapnic CVR maps obtained using the proposed PDB task and analysis methodology. This suggests that such protocol may therefore offer a promising alternative to conventional vasoactive challenges, which avoids their discomfort and difficulty.

To evaluate the reproducibility of estimation of cerebral blood flow (CBF), bolus arrival time (BAT), and arterial blood volume (aBV) from arterial spin labeling (ASL) data acquired at multiple postlabeling delays (PLDs).CBF, BAT, and aBV parameters were estimated from flow-suppressed and nonflow-suppressed multiple-PDL PICORE-Q2TIPS ASL using model-based Bayesian and least-squares fitting frameworks, and aBV was also obtained from a model-free approach. Reproducibility of these parameters was assessed by computing the within- and between-subject coefficients of variability (CVw and CVb).CVw and CVb were comparable across model-based approaches, but were greater for the aBV from the model-free approach. Overall, the Bayesian model estimation procedure was found to provide the best compromise between reliability and reproducibility, yielding CVw/CVb values of 21/21, 3/4, and 24/26% for CBF, BAT, and aBV, respectively. Although a CBF range of 45 mL/100g/min to 59 mL/100g/min was found on average and a BAT of 0.7-1.0 seconds across methods, the corresponding maps were comparable in terms of the parameters' spatial distributions, and in particular in the identification of macrovascular locations, as assessed through comparison with time-of-flight images.Reproducible estimates of CBF, BAT, and aBV values can be obtained from non-macroflow-suppressed ASL using both least-squares and Bayesian model-based methods.

The nature of visual impairments in Alzheimer's disease (AD) and their relation with other cognitive deficits remains highly debated. We asked whether independent visual deficits are present in AD and amnestic forms of mild cognitive impairment (MCI) in the absence of other comorbidities by performing a hierarchical analysis of low-level and high-level visual function in MCI and AD. Since parietal structures are a frequent pathophysiological target in AD and subserve 3D vision driven by motion cues, we hypothesized that the parietal visual dorsal stream function is predominantly affected in these conditions. We used a novel 3D task combining three critical variables to challenge parietal function: 3D motion coherence of objects of unknown orientation, with constrained temporal integration of these cues. Groups of amnestic MCI (n = 20), AD (n = 19), and matched controls (n = 20) were studied. Low-level visual function was assessed using psychophysical contrast sensitivity tests probing the magnocellular, parvocellular, and koniocellular pathways. We probed visual ventral stream function using the Benton Face Recognition task. We have found hierarchical visual impairment in AD, independently of neuropsychological deficits, in particular in the novel parietal 3D task, which was selectively affected in MCI. Integration of local motion cues into 3D objects was specifically and most strongly impaired in AD and MCI, especially when 3D motion was unpredictable, with variable orientation and short-lived in space and time. In sum, specific early dorsal stream visual impairment occurs independently of ventral stream, low-level visual and neuropsychological deficits, in amnestic types of MCI and AD.

The importance of music in our daily life has given rise to an increased number of studies addressing the brain regions involved in its appreciation. Some of these studies controlled only for the familiarity of the stimuli, while others relied on pleasantness ratings, and others still on musical preferences. With a listening test and a functional magnetic resonance imaging (fMRI) experiment, we wished to clarify the role of familiarity in the brain correlates of music appreciation by controlling, in the same study, for both familiarity and musical preferences. First, we conducted a listening test, in which participants rated the familiarity and liking of song excerpts from the pop/rock repertoire, allowing us to select a personalized set of stimuli per subject. Then, we used a passive listening paradigm in fMRI to study music appreciation in a naturalistic condition with increased ecological value. Brain activation data revealed that broad emotion-related limbic and paralimbic regions as well as the reward circuitry were significantly more active for familiar relative to unfamiliar music. Smaller regions in the cingulate cortex and frontal lobe, including the motor cortex and Broca's area, were found to be more active in response to liked music when compared to disliked one. Hence, familiarity seems to be a crucial factor in making the listeners emotionally engaged with music, as revealed by fMRI data.

Pulsed arterial spin labeling (PASL) techniques potentially allow the absolute, noninvasive quantification of brain perfusion using MRI. This can be achieved by fitting a kinetic model to the data acquired at a number of sampling times. However, the intrinsically low signal-to-noise ratio of PASL measurements usually requires substantial signal averaging, which may result in undesirably long scanning times. A judicious choice of the sampling points is, therefore, crucial in order to minimize scanning time, while optimizing estimation accuracy. On the other hand, a priori information regarding the model parameters may improve estimation performance. Here, we propose a Bayesian framework to determine an optimal sampling strategy and estimation method for the measurement of brain perfusion and arterial transit time (ATT). A Bayesian Fisher information criterion is used to determine the optimal sampling points and a MAP criterion is employed for the estimation of the model parameters, both taking into account the uncertainty in the model parameters as well as the amount of noise in the data. By Monte Carlo simulations, we show that using optimal compared to uniform sampling strategies, as well as the Bayesian estimator relative to a standard least squares approach, improves the accuracy of perfusion and ATT measurements. Moreover, we also demonstrate the applicability of the proposed approach to real data, with the advantage of reduced intersubject variability relative to conventional sampling and estimation approaches.

The new clinically available arterial spin labeling (ASL) perfusion imaging sequences present some advantages relatively to the commonly used blood oxygen level‐dependent (BOLD) method for functional brain studies using magnetic resonance imaging (MRI). In particular, regional cerebral blood flow (CBF) changes are thought to be more directly related with neuronal activation. In this study, we aimed to investigate the accuracy of the functional localization of the hand motor area obtained by simultaneous CBF and BOLD contrasts provided by ASL functional MRI (fMRI) and compare it with a standard BOLD fMRI protocol. For this purpose, we measured the distance between the center of gravity of the activation clusters obtained with each contrast (CBF, BOLD(ASL), and Standard BOLD) and 11 positions defined on a well‐established anatomical landmark of the hand motor area (the omega in the axial plane of the precentral gyrus). We found that CBF measurements were significantly closer to the anatomical landmark than the ones obtained using either simultaneous BOLD(ASL) or standard BOLD contrasts. Moreover, we also observed reduced intersubject variability of the functional localization, as well as percent signal change, for CBF relative to both BOLD contrast measurements. In conclusion, our results add further evidence in support to the notion that CBF provides a more accurate localization of motor activation than BOLD contrast, indicating that ASL may be an appropriate technique for clinical fMRI studies. Hum Brain Mapp, 2013. © 2011 Wiley Periodicals, Inc.

Report of three cases of chylothorax and one case of chylous ascites in children who had undergone cardiac surgery with no response to routine clinical treatment, based on fasting and long-term parenteral nutrition. Treatment with octreotide at an initial dose of 1.0 mcg/kg/h was chosen, with a gradual increase of 1.0 mcg/kg/hr/day until a maximum dose of 4.0 mcg/kg/h. All cases had a favorable response, with gradual reduction of drainage output until prognosis improvement with no significant side effects.

BOLD contrast is the most commonly used functional MRI method for studies of brain activity. However, the underlying physiological processes giving rise to measured BOLD signal changes (which include contribution from changes in cerebral blood flow (CBF), cerebral blood volume (CBV) and cerebral metabolic rate of oxygen consumption (CMRO2)) vary substantially between sessions and subjects. To determine whether direct CBF measurement is a more reliable technique, we compared the localisation of activation and reproducibility of relative signal change measured by optimised BOLD versus CBF measured using the arterial spin labelling (ASL) technique. Data were collected within the primary sensorimotor cortex in normal healthy controls performing a simple finger-tapping task over three imaging sessions (two on same day and one on a different day). The displacement between the foci of BOLD and CBF activation was less than the linear dimension of one voxel (2.4 mm), however, BOLD activation was significantly closer to the nearest draining vein compared to CBF activation (PÂ =Â 0.030). For the relative signal change measurement, we found that CBF has a lower inter-subject variation than BOLD (PÂ

OBJECTIVE: To report short and midtem follow-up results of balloon aortic valvuloplasty to treat congenital aortic stenosis. METHODS: Seventy-five patients (median age: 8 years) underwent the procedure through the retrograde femoral or carotid route. RESULTS: The procedure was completed in 74 patients (98.6%). The peak-to-peak systolic gradient dropped from 79.6±27.7 to 22.3±17.8 mmHg (P

Visual backward masking is strongly impaired in patients with schizophrenia. Masking deficits have been proposed as potential endophenotypes of schizophrenia. Masking performance deficits manifest as strongly reduced amplitudes in the electroencephalogram (EEG). In order to fulfill the criteria of an endophenotype, masking deficits should not vary substantially across time and should be present at the first psychotic event. To verify whether these conditions are met for visual backward masking, we tested patients with first episode psychosis (n = 21) in a longitudinal study. Patients were tested with visual backward masking and EEG three times every six months over a period of one year. We found that the EEG amplitudes of patients with first episode psychosis were higher as compared to those of patients with schizophrenia but lower as compared to those of unaffected controls. More interestingly, we found that the EEG amplitudes of patients with first episode psychosis remained stable over the course of one year. Since chronic schizophrenia patients have strongly reduced amplitudes, we speculate that the neural correlates of masking deficits (EEG amplitudes) continue to decrease as the disease progresses.

Summary Purpose: We investigated functional reorganization mechanisms of the human medial temporal lobe (MTL) for episodic memory, in patients suffering from medial temporal lobe epilepsy (MTLE) with hippocampal sclerosis (HS). Methods: We used functional magnetic resonance imaging (fMRI) to measure brain activity changes during matched episodic encoding tasks of abstract words (Verbal) and line drawings (Visual), in patients with unilateral right MTLE undergoing presurgical evaluation and healthy controls. Results: As expected, a significant interaction between material type and the side of MTL activity was present in the control group, with preferential involvement of the left hippocampus in verbal encoding and the right parahippocampal region in visual encoding. When compared with controls, right MTLE patients with intact performance activated a region in the left hippocampus more during visual encoding, which resulted in an interaction between group and hemisphere. Importantly, an effect of memory performance on visual encoding activity was observed in the patients, with greater engagement of the left MTL being associated with higher recognition scores. Interestingly, activity in the left MTL also depended on the epileptic seizure frequency, suggesting a role for this clinical parameter in the recruitment of contralateral regions. Discussion: Taken together, these results indicate functional reorganization of the MTLs in right HS, through transfer of function from the right to the left hemisphere, and strongly suggest an adaptive role for such reorganization mechanism in supporting preserved visual memory.