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Statistical learning refers to the ability to extract the statistical relations embedded in a sequence, and it plays a crucial role in the development of communicative and social skills that are impacted in the Autism Spectrum Disorder (ASD). Here, we investigated the relationship between infants' SL ability and autistic traits in their parents. Using a visual habituation task, we tested infant offspring of adults (non-diagnosed) who show high (HAT infants) versus low (LAT infants) autistic traits. Results demonstrated that LAT infants learned the statistical structure embedded in a visual sequence, while HAT infants failed. Moreover, infants' SL ability was related to autistic traits in their parents, further suggesting that early dysfunctions in SL might contribute to variabilities in ASD symptoms.

The capacity of the Child Behavior Checklist 1½-5 (CBCL 1½-5) to identify children with autism spectrum disorder (ASD) at 18 months was tested on 37 children clinically referred for ASD and 46 children at elevated likelihood of developing ASD due to having an affected brother/sister. At 30 months the clinically referred children all received a confirmatory diagnosis, and 10 out of 46 siblings received a diagnosis of ASD. CBCL 1½-5 profiles were compared with a group of matched children with typical development (effect of cognitive level controlled for). The capacity of the CBCL 1½-5 DSM Oriented-Pervasive Developmental Problems scale to differentiate correctly between children diagnosed with ASD and children with typical development appeared dependent on group ascertainment methodology.

Abstract Background It has been more than 20 years since the malaria epidemiologic shift to school-aged children was noted. In the meantime, school-aged children (5–15 years) have become increasingly more vulnerable with asymptomatic malaria prevalence reaching up to 70%, making them reservoirs for subsequent transmission of malaria in the endemic communities. Intermittent Preventive Treatment of malaria in schoolchildren (IPTsc) has proven to be an effective tool to shrink this reservoir. As of 3rd June 2022, the World Health Organization recommends IPTsc in moderate and high endemic areas. Even so, for decision-makers, the adoption of scientific research recommendations has been stifled by real-world implementation challenges. This study presents methodology, challenges faced, and mitigations used in the evaluation of the implementation of IPTsc using dihydroartemisinin-piperaquine (DP) in three councils (Handeni District Council (DC), Handeni Town Council (TC) and Kilindi DC) of Tanga Region, Tanzania so as to understand the operational feasibility and effectiveness of IPTsc on malaria parasitaemia and clinical malaria incidence. Methods The study deployed an effectiveness-implementation hybrid design to assess feasibility and effectiveness of IPTsc using DP, the interventional drug, against standard of care (control). Wards in the three study councils were the randomization unit (clusters). Each ward was randomized to implement IPTsc or not (control). In all wards in the IPTsc arm, DP was given to schoolchildren three times a year in four-month intervals. In each council, 24 randomly selected wards (12 per study arm, one school per ward) were chosen as representatives for intervention impact evaluation. Mixed design methods were used to assess the feasibility and acceptability of implementing IPTsc as part of a more comprehensive health package for schoolchildren. The study reimagined an existing school health programme for Neglected Tropical Diseases (NTD) control include IPTsc implementation. Results The study shows IPTsc can feasibly be implemented by integrating it into existing school health and education systems, paving the way for sustainable programme adoption in a cost-effective manner. Conclusions Through this article other interested countries may realise a feasible plan for IPTsc implementation. Mitigation to any challenge can be customized based on local circumstances without jeopardising the gains expected from an IPTsc programme. Trial registration clinicaltrials.gov, NCT04245033. Registered 28 January 2020, https://clinicaltrials.gov/ct2/show/NCT04245033

Abstract Background To develop a pipeline for automatic extraction of quantitative metrics and radiomic features from lung computed tomography (CT) and develop artificial intelligence (AI) models supporting differential diagnosis between coronavirus disease 2019 (COVID-19) and other viral pneumonia (non-COVID-19). Methods Chest CT of 1,031 patients (811 for model building; 220 as independent validation set (IVS) with positive swab for severe acute respiratory syndrome coronavirus-2 (647 COVID-19) or other respiratory viruses (384 non-COVID-19) were segmented automatically. A Gaussian model, based on the HU histogram distribution describing well-aerated and ill portions, was optimised to calculate quantitative metrics (QM, n = 20) in both lungs (2L) and four geometrical subdivisions (GS) (upper front, lower front, upper dorsal, lower dorsal; n = 80). Radiomic features (RF) of first (RF1, n = 18) and second (RF2, n = 120) order were extracted from 2L using PyRadiomics tool. Extracted metrics were used to develop four multilayer-perceptron classifiers, built with different combinations of QM and RF: Model1 (RF1-2L); Model2 (QM-2L, QM-GS); Model3 (RF1-2L, RF2-2L); Model4 (RF1-2L, QM-2L, GS-2L, RF2-2L). Results The classifiers showed accuracy from 0.71 to 0.80 and area under the receiving operating characteristic curve (AUC) from 0.77 to 0.87 in differentiating COVID-19 versus non-COVID-19 pneumonia. Best results were associated with Model3 (AUC 0.867 ± 0.008) and Model4 (AUC 0.870 ± 0.011. For the IVS, the AUC values were 0.834 ± 0.008 for Model3 and 0.828 ± 0.011 for Model4. Conclusions Four AI-based models for classifying patients as COVID-19 or non-COVID-19 viral pneumonia showed good diagnostic performances that could support clinical decisions.

The recovery of motor functions after stroke is fostered by the functional integration of large-scale brain networks, including the motor network (MN) and high-order cognitive controls networks, such as the default mode (DMN) and executive control (ECN) networks. In this paper, electroencephalography signals are used to investigate interactions among these three resting state networks (RSNs) in subacute stroke patients after motor rehabilitation. A novel metric, the O-information rate (OIR), is used to quantify the balance between redundancy and synergy in the complex high-order interactions among RSNs, as well as its causal decomposition to identify the direction of information flow. The paper also employs conditional spectral Granger causality to assess pairwise directed functional connectivity between RSNs. After rehabilitation, a synergy increase among these RSNs is found, especially driven by MN. From the pairwise description, a reduced directed functional connectivity towards MN is enhanced after treatment. Besides, inter-network connectivity changes are associated with motor recovery, for which the mediation role of ECN seems to play a relevant role, both from pairwise and high-order interactions perspective.

Objective: The aim of the present study is to explore whether a single session of transcutaneous Vagus Nerve Stimulation (tVNS) can enhance the ipsilesional, and contralesional upper limb motor functions as well as cognitive functions in stroke patients. The effects of the stimulation were evaluated through two different tasks: the box and blocks test (BB), indexing manual dexterity, and the Go/No-go task, a visuomotor paradigm used to assess both motor readiness and response inhibition. Tests were administered without tVNS, during tVNS and during sham tVNS. Results: The BB showed a statistical difference for both contralesional side (p = 0.05) between Basal-Real condition (p = 0.042) and ipsilesional side (p = 0.001) between Basal-Real (p = 0.008) and for Real-Sham (p = 0.005). Any statistical difference was found for the mean latencies in the three conditions of the Go/No-go test. Conclusion: A single session of tVNS seems to improve upper limb motor functions but not cognitive functions in post-stroke patients, despite a positive trend was detected.

Objective: Human figure drawings are widely used in clinical practice as a qualitative indication of Body Representations (BRs) alterations in stroke patients. The objective of this study is to present and validate the use of a new app called QDraw for the quantitative analysis of drawings and to investigate whether this analysis can reveal distortions of BRs in chronic stroke patients. Results: QDraw has proven to generate reliable data as compared to manual scoring and in terms of inter-rater reliability, as shown by the high correlation coefficients. Moreover, human figure drawings from chronic stroke patients demonstrated a distortion of upper limb perception, as shown by a significantly higher arm length asymmetry compared to legs, whereas no difference was found in healthy controls. Conclusions: The present study supports the use of quantitative, digital methods (the QDraw app) to analyze human figure drawings as a tool to evaluate BRs distortions in stroke patients.

Abstract Background Malaria rapid diagnostic tests (RDTs) based on the detection of the Plasmodium falciparum histidine-rich protein 2 (HRP2) antigen are widely used for detection of active infection with this parasite and are the only practical malaria diagnostic test in some endemic settings. External validation of RDT results from field surveys can confirm appropriate RDT performance. Methods A community-based cross-sectional survey was conducted between July and November 2017 enrolling participants of all ages in households from 15 villages in four border regions of Tanzania: Geita, Kigoma, Mtwara and Ruvuma. All participants had an RDT performed in the field and provided a blood sample for later laboratory multiplex antigen detection of HRP2. In assessing the continuous HRP2 levels in participant blood versus RDT result, dose–response logistic regression provided quantitative estimates for HRP2 limit of detection (LOD). Results From the 15 study villages, 6941 persons were enrolled that had a RDT at time of enrollment and provided a DBS for later laboratory antigen detection. RDT positive prevalence for the HRP2 band by village ranged from 20.0 to 43.6%, but the magnitude of this prevalence did not have an effect on the estimated LOD of RDTs utilized in different villages. Overall, HRP2 single-target tests had a lower LOD at the 95% probability of positive RDT (4.3 ng/mL; 95% CI 3.4–5.4) when compared to pLDH/HRP2 dual target tests (5.4 ng/mL; 4.5–6.3), though this difference was not significant. With the exception of one village, all other 14 villages (93.3%) showed RDT LOD estimates at 90% probability of positive RDT between 0.5 and 12.0 ng/mL. Conclusions Both HRP2-only and pLDH/HRP2 combo RDTs utilized in a 2017 Tanzania cross-sectional survey of border regions generally performed well, and reliably detected HRP2 antigen in the low ng/mL range. Though single target tests had lower levels of HRP2 detection, both tests were within similar ranges among the 15 villages. Comparison of quantitative HRP2 detection limits among study sites can help interpret RDT testing results when generating population prevalence estimates for malaria infection.

Since chlorohydrazones are planar molecules, it is in principle possible to distinguish between their E and Z stereoisomers. Chlorohydrazones are known to preferentially assume the Z configuration around the C=N double bond, and their (E, Z) isomerization is almost suppressed at room temperature. The lack, or rather the difficulty, of such an isomerization has been conveniently addressed by the in-depth theoretical study of seven C-methoxycarbonyl-N-aryl chlorohydrazones (aryl = phenyl, 4-chlorophenyl, 4-bromophenyl, 4-iodophenyl, 2-chlorophenyl, 2-bromophenyl, and 2-iodophenyl). DFT ωB97M-D4/cc-pVTZ calculations of these C-methoxycarbonyl-N-aryl chlorohydrazones, supported by the XRD determination of the molecular structure, provided a complete picture of the isomerization processes in the studied compounds. The analysis of the energetics, molecular geometry, and electronic structure (the latter in the framework of the Quantum Theory of Atoms In Molecules) showed that the Z isomers are thermodynamically favored because, within the low-energy planar isomers with extensive π conjugation, the electrostatic interactions between the dipoles of the C–O, C–Cl, and N–H bonds overcome the stabilization induced by the N–H ··· O bond present in the E isomers. We confirmed that the (E, Z) isomerization occurs by the umklapp mechanism, in which the –NHAr moiety rotates in the molecular plane towards a linear C=N–N configuration and then proceeds to the other isomer. The (E, Z) isomerization is very slow at room temperature because the umklapp interconversion has high barriers (≈110 kJ/mol) despite the extended π electron delocalization present in the transition state.

Abstract This study was designed to investigate the feasibility and the potential effects on walking performance of a short gait training with a novel impairment-specific hip assistance (iHA) through a bilateral active pelvis orthosis (APO) in patients with acquired brain injury (ABI). Fourteen subjects capable of independent gait and exhibiting mild-to-moderate gait deficits, due to an ABI, were enrolled. Subjects presenting deficit in hip flexion and/or extension were included and divided into two groups based on the presence (group A, n = 6) or absence (group B, n = 8) of knee hyperextension during stance phase of walking. Two iHA-based profiles were developed for the groups. The protocol included two overground gait training sessions using APO, and two evaluation sessions, pre and post training. Primary outcomes were pre vs. post-training walking distance and steady-state speed in the 6-min walking test. Secondary outcomes were self-selected speed, joint kinematics and kinetics, gait symmetry and forward propulsion, assessed through 3D gait analysis. Following the training, study participants significantly increased the walked distance and average steady-state speed in the 6-min walking tests, both when walking with and without the APO. The increased walked distance surpassed the minimal clinically important difference for groups A and B, (respectively, 42 and 57 m > 34 m). In group A, five out of six subjects had decreased knee hyperextension at the post-training session (on average the peak of the knee extension angle was reduced by 36%). Knee flexion during swing phase increased, by 16% and 31%, for A and B groups respectively. Two-day gait training with APO providing iHA was effective and safe in improving walking performance and knee kinematics in ABI survivors. These preliminary findings suggest that this strategy may be viable for subject-specific post-ABI gait rehabilitation.

Abstract Background Current efforts to estimate the spatially diverse malaria burden in malaria-endemic countries largely involve the use of epidemiological modelling methods for describing temporal and spatial heterogeneity using sparse interpolated prevalence data from periodic cross-sectional surveys. However, more malaria-endemic countries are beginning to consider local routine data for this purpose. Nevertheless, routine information from health facilities (HFs) remains widely under-utilized despite improved data quality, including increased access to diagnostic testing and the adoption of the electronic District Health Information System (DHIS2). This paper describes the process undertaken in mainland Tanzania using routine data to develop a high-resolution, micro-stratification risk map to guide future malaria control efforts. Methods Combinations of various routine malariometric indicators collected from 7098 HFs were assembled across 3065 wards of mainland Tanzania for the period 2017–2019. The reported council-level prevalence classification in school children aged 5–16 years (PfPR5–16) was used as a benchmark to define four malaria risk groups. These groups were subsequently used to derive cut-offs for the routine indicators by minimizing misclassifications and maximizing overall agreement. The derived-cutoffs were converted into numbered scores and summed across the three indicators to allocate wards into their overall risk stratum. Results Of 3065 wards, 353 were assigned to the very low strata (10.5% of the total ward population), 717 to the low strata (28.6% of the population), 525 to the moderate strata (16.2% of the population), and 1470 to the high strata (39.8% of the population). The resulting micro-stratification revealed malaria risk heterogeneity within 80 councils and identified wards that would benefit from community-level focal interventions, such as community-case management, indoor residual spraying and larviciding. Conclusion The micro-stratification approach employed is simple and pragmatic, with potential to be easily adopted by the malaria programme in Tanzania. It makes use of available routine data that are rich in spatial resolution and that can be readily accessed allowing for a stratification of malaria risk below the council level. Such a framework is optimal for supporting evidence-based, decentralized malaria control planning, thereby improving the effectiveness and allocation efficiency of malaria control interventions.

Growing evidence suggests that artificial intelligence tools could help radiologists in differentiating COVID-19 pneumonia from other types of viral (non-COVID-19) pneumonia. To test this hypothesis, an R-AI classifier capable of discriminating between COVID-19 and non-COVID-19 pneumonia was developed using CT chest scans of 1031 patients with positive swab for SARS-CoV-2 (n = 647) and other respiratory viruses (n = 384). The model was trained with 811 CT scans, while 220 CT scans (n = 151 COVID-19; n = 69 non-COVID-19) were used for independent validation. Four readers were enrolled to blindly evaluate the validation dataset using the CO-RADS score. A pandemic-like high suspicion scenario (CO-RADS 3 considered as COVID-19) and a low suspicion scenario (CO-RADS 3 considered as non-COVID-19) were simulated. Inter-reader agreement and performance metrics were calculated for human readers and R-AI classifier. The readers showed good agreement in assigning CO-RADS score (Gwet’s AC2 = 0.71, p < 0.001). Considering human performance, accuracy = 78% and accuracy = 74% were obtained in the high and low suspicion scenarios, respectively, while the AI classifier achieved accuracy = 79% in distinguishing COVID-19 from non-COVID-19 pneumonia on the independent validation dataset. The R-AI classifier performance was equivalent or superior to human readers in all comparisons. Therefore, a R-AI classifier may support human readers in the difficult task of distinguishing COVID-19 from other types of viral pneumonia on CT imaging.

Introduction Oral cavity squamous cell carcinoma (OCSCC) is the most common malignancy in the oral cavity. Two types of mandibular resections have been described: the segmental mandibulectomy and the marginal mandibulectomy. Both may have a different impact over the quality of life, oncological prognosis, and functional or aesthetic result.

Summary: Background: Cognitive impairment has been reported after many types of infection, including SARS-CoV-2. Whether deficits following SARS-CoV-2 improve over time is unclear. Studies to date have focused on hospitalised individuals with up to a year follow-up. The presence, magnitude, persistence and correlations of effects in community-based cases remain relatively unexplored. Methods: Cognitive performance (working memory, attention, reasoning, motor control) was assessed in a prospective cohort study of participants from the United Kingdom COVID Symptom Study Biobank between July 12, 2021 and August 27, 2021 (Round 1), and between April 28, 2022 and June 21, 2022 (Round 2). Participants, recruited from the COVID Symptom Study smartphone app, comprised individuals with and without SARS-CoV-2 infection and varying symptom duration. Effects of COVID-19 exposures on cognitive accuracy and reaction time scores were estimated using multivariable ordinary least squares linear regression models weighted for inverse probability of participation, adjusting for potential confounders and mediators. The role of ongoing symptoms after COVID-19 infection was examined stratifying for self-perceived recovery. Longitudinal analysis assessed change in cognitive performance between rounds. Findings: 3335 individuals completed Round 1, of whom 1768 also completed Round 2. At Round 1, individuals with previous positive SARS-CoV-2 tests had lower cognitive accuracy (N = 1737, β = −0.14 standard deviations, SDs, 95% confidence intervals, CI: −0.21, −0.07) than negative controls. Deficits were largest for positive individuals with ≥12 weeks of symptoms (N = 495, β = −0.22 SDs, 95% CI: −0.35, −0.09). Effects were comparable to hospital presentation during illness (N = 281, β = −0.31 SDs, 95% CI: −0.44, −0.18), and 10 years age difference (60–70 years vs. 50–60 years, β = −0.21 SDs, 95% CI: −0.30, −0.13) in the whole study population. Stratification by self-reported recovery revealed that deficits were only detectable in SARS-CoV-2 positive individuals who did not feel recovered from COVID-19, whereas individuals who reported full recovery showed no deficits. Longitudinal analysis showed no evidence of cognitive change over time, suggesting that cognitive deficits for affected individuals persisted at almost 2 years since initial infection. Interpretation: Cognitive deficits following SARS-CoV-2 infection were detectable nearly two years post infection, and largest for individuals with longer symptom durations, ongoing symptoms, and/or more severe infection. However, no such deficits were detected in individuals who reported full recovery from COVID-19. Further work is needed to monitor and develop understanding of recovery mechanisms for those with ongoing symptoms. Funding: Chronic Disease Research Foundation, Wellcome Trust, National Institute for Health and Care Research, Medical Research Council, British Heart Foundation, Alzheimer's Society, European Union, COVID-19 Driver Relief Fund, French National Research Agency.

Scientific and industrial reasons dictate the study of the solid state of imepitoin, a highly safe and tolerable anticonvulsant drug used in the therapy of epileptic dogs that was approved in the Europe Union in 2013. Our investigations allowed us to discover the existence of a new polymorph of imepitoin, which finds itself in a monotropic relationship with the crystalline form (polymorph I) already known and present on the market. This form (polymorph II), obtained by crystallization from xylene, remains metastable under ambient conditions for at least 1 year. Both solid forms were characterized by thermal (DSC and TGA), spectroscopic (FT-IR and Raman), microscopic (SEM and HSM), and diffractometric techniques. The thermodynamic relationship between the two polymorphs (monotropic) is such that it is not possible to study the melting of polymorph II, not even by adopting appropriate experimental strategies. Our measurements highlighted that the melting peak of imepitoin actually also includes an onset of melt decomposition. The ab initio structure solution, obtained from synchrotron X-ray powder diffraction data collected at room temperature, allowed us to determine the crystal structure of the new polymorph (II). It crystallizes in the monoclinic crystal structure, P21/c space group (#14), with a = 14.8687(6) Å, b = 7.2434(2) Å, c = 12.5592(4) Å, β = 107.5586(8)°, V = 1289.61(8) Å3, and Z = 4.

Botulinum toxin type-A (BoNT-A) has emerged as a key therapeutic agent for the management of spasticity. This paper presents a comprehensive bibliometric and visual analysis of research concerning BoNT-A treatment of spasticity to elucidate current trends and future directions in this research area. A search was conducted in the Web of Science database for articles focused on the use of BoNT-A in spasticity published between 2000 and 2022. We extracted various metrics, including counts of publications and contributions from different countries, institutions, authors, and journals. Analytical methods in CiteSpace were employed for the examination of co-citations, collaborations, and the co-occurrence of keywords. Our search yielded 1489 publications. Analysis revealed a consistent annual increase in research output. The United States, United Kingdom, and Italy were the leading contributors. The top institution in this research was Assistance Publique Hopitaux, Paris. The journal containing the highest number of relevant publications was Toxins. Key frequently occurring keywords were ‘stroke’, ‘cerebral palsy’, ‘adult spasticity’, and ‘upper extremity’. This study identified 12 clusters of keywords and 15 clusters of co-cited references, indicating the main focus areas and emerging themes in this field. This study comprehensively analyzed and summarized trends in BoNT-A research in the field of spasticity over the past 22 years.

Cardiovascular disease (CVD) is common in people with HIV (PWH), and has great impact in terms of morbidity and mortality. Several intertwined mechanisms are believed to play a role in determining the increased risk of CVD, including the effect of certain antiretrovirals; among these, the role of integrase strand-transfer inhibitors (INSTIs) is yet to be fully elucidated. We conducted a multicenter, observational study comprising 4984 PWH evaluating the antiretroviral therapy (ART)-related nature of CVD in real life settings, both in naïve vs. treatment-experienced people. A comparison was conducted between INSTIs vs. either protease inhibitors (PIs) or non-nucleoside reverse transcriptase inhibitors (NNRTIs) considering demographic, baseline clinical characteristics, incidence of CVD in both 2-year and complete follow-up periods. Among 2357 PWH exposed to INSTIs, 24 people experienced CVD; the corresponding figure was 12 cases out of 2599 PWH exposed to other ART classes. At univariate and multivariate analysis, a tendency towards an increased risk of CVD was observed in the 2-year follow-up period in PWH exposed to INSTIs in the absence, however, of statistical significance. These findings leave open the hypothesis that INSTIs may play a role, albeit minimal, in determining an increased risk of CVD in PWH.

Cenobamate (CNB) is a new anti-seizure medication (ASM) recently introduced in clinical practice after approval by the FDA and EMA for the add-on treatment of focal onset seizures in adult patients. Although its mechanism of action has not been fully understood, CNB showed promising clinical efficacy in patients treated with concomitant ASMs. The accessibility of CNB could pave a way for the treatment of refractory or drug-resistant epilepsies, which still affect at least one-third of the patients under pharmacological treatment. In this context, therapeutic drug monitoring (TDM) offers a massive opportunity for better management of epileptic patients, especially those undergoing combined therapy. Here, we describe the first fully validated ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC–MS/MS) method for the quantification of CNB and concomitant ASMs in human plasma, with samples extracted either manually or by means of a liquid handler. Our method was validated according to the most recent ICH International Guideline M10 for Bioanalytical Method Validation and Study Sample Analysis. The method proved to be selective for CNB and displayed a linear range from 0.8 to 80 mg/L; no matrix effect was found (98.2 ± 4.1%), while intra-day and inter-day accuracy and precision were within the acceptance range. Also, CNB short- and long-term stability in plasma under different conditions was assessed. Leftover human plasma samples were employed as study samples for method validation. Our method proved to be highly sensitive and selective to quantify CNB and concomitant ASMs in human plasma; therefore, this method can be employed for a routinely TDM-based approach to support physicians in the management of an epileptic patient.

Although anatomical brain hemispheric asymmetries have been clearly documented in the infant brain, findings concerning functional hemispheric specialization have been inconsistent. The present report aims to assess whether bilaterally symmetric synchronous activity between the two hemispheres is a characteristic of the infant brain. To asses cortical bilateral synchronicity, we used decomposition by independent component analysis (ICA) of high-density electroencephalographic (EEG) data collected in an auditory passive oddball paradigm. Decompositions of concatenated 64-channel EEG data epochs from each of 34 typically developing 6-month-old infants and from 18 healthy young adults participating in the same passive auditory oddball protocol were compared to characterize differences in functional brain organization between early life and adulthood. Our results show that infant EEG decompositions comprised a larger number of independent component (IC) effective source processes compatible with a cortical origin and having bilaterally near-symmetric scalp projections (13.8% of the infant data ICs presented a bilateral pattern vs. 4.3% of the adult data ICs). These IC projections could be modeled as the sum of potentials volume-conducted to the scalp from synchronous locally coherent field activities in corresponding left and right cortical source areas. To conclude, in this paradigm, source-resolved infant brain EEG exhibited more bilateral synchronicity than EEG produced by the adult brain, supporting the hypothesis that more strongly unilateral and likely more functionally specialized unihemispheric cortical field activities are concomitants of brain maturation.