Showing papers in "Brain Sciences in 2021"

Long-Lasting Cognitive Abnormalities after COVID-19.

Abstract: Considering the mechanisms capable of causing brain alterations in COVID-19, we aimed to study the occurrence of cognitive abnormalities in the months following hospital discharge. We recruited 38 (aged 22-74 years; 27 males) patients hospitalized for complications of SARS-CoV-2 infection in nonintensive COVID units. Participants underwent neuropsychological testing about 5 months after hospital discharge. Of all patients, 42.1% had processing speed deficits, while 26.3% showed delayed verbal recall deficits. Twenty-one percent presented with deficits in both processing speed and verbal memory. Bivariate analysis revealed a positive correlation between the lowest arterial oxygen partial pressure (PaO2) to fractional inspired oxygen (FiO2) (P/F) ratio during hospitalization and verbal memory consolidation performance (SRT-LTS score, r = 0.404, p = 0.027), as well as a positive correlation between SpO2 levels upon hospital arrival and delayed verbal recall performance (SRT-D score, rs = 0.373, p = 0.042). Acute respiratory distress syndrome (ARDS) during hospitalization was associated with worse verbal memory performance (ARDS vs. no ARDS: SRT-LTS mean score = 30.63 ± 13.33 vs. 44.50 ± 13.16, p = 0.007; SRT-D mean score = 5.95 ± 2.56 vs. 8.10 ± 2.62, p = 0.029). Cognitive abnormalities can frequently be found in COVID-19 patients 5 months after hospital discharge. Increased fatigability, deficits of concentration and memory, and overall decreased cognitive speed months after hospital discharge can interfere with work and daily activities.

Prevalence of Anxiety, Depression, and Stress among Teachers during the COVID-19 Pandemic: A Rapid Systematic Review with Meta-Analysis.

Abstract: Background: Since the beginning of the COVID-19 pandemic, teachers have been accumulating adverse psychological symptoms due to the closure of educational centers and the need to adapt to different teaching modalities. Methods: Medline and PubMed were searched for studies on the prevalence of depression, anxiety, stress, and burn-out in teachers, published from 1 December 2019 to 15 June 2021. Results: In total, eight studies were included in this study. The results show that teachers report levels of anxiety (17%), depression (19%), and stress (30%). In Asia, there has been more anxiety compared to other continents. Overall, anxiety has been higher among teachers in schools compared to universities. However, stress levels have been higher among teachers in universities compared to schools. Statistically, there were no significant differences regarding gender and age in any of the symptoms. Conclusions: The results suggest that teachers at different educational levels are experiencing adverse psychological symptomatology during the COVID-19 pandemic, and that anxiety levels vary between different countries. However, more international studies are needed to fully understand the impact of the pandemic on teachers’ mental health.

Summary of over Fifty Years with Brain-Computer Interfaces-A Review.

Abstract: Over the last few decades, the Brain-Computer Interfaces have been gradually making their way to the epicenter of scientific interest. Many scientists from all around the world have contributed to the state of the art in this scientific domain by developing numerous tools and methods for brain signal acquisition and processing. Such a spectacular progress would not be achievable without accompanying technological development to equip the researchers with the proper devices providing what is absolutely necessary for any kind of discovery as the core of every analysis: the data reflecting the brain activity. The common effort has resulted in pushing the whole domain to the point where the communication between a human being and the external world through BCI interfaces is no longer science fiction but nowadays reality. In this work we present the most relevant aspects of the BCIs and all the milestones that have been made over nearly 50-year history of this research domain. We mention people who were pioneers in this area as well as we highlight all the technological and methodological advances that have transformed something available and understandable by a very few into something that has a potential to be a breathtaking change for so many. Aiming to fully understand how the human brain works is a very ambitious goal and it will surely take time to succeed. However, even that fraction of what has already been determined is sufficient e.g., to allow impaired people to regain control on their lives and significantly improve its quality. The more is discovered in this domain, the more benefit for all of us this can potentially bring.

Differential Deep Convolutional Neural Network Model for Brain Tumor Classification.

Abstract: The classification of brain tumors is a difficult task in the field of medical image analysis. Improving algorithms and machine learning technology helps radiologists to easily diagnose the tumor without surgical intervention. In recent years, deep learning techniques have made excellent progress in the field of medical image processing and analysis. However, there are many difficulties in classifying brain tumors using magnetic resonance imaging; first, the difficulty of brain structure and the intertwining of tissues in it; and secondly, the difficulty of classifying brain tumors due to the high density nature of the brain. We propose a differential deep convolutional neural network model (differential deep-CNN) to classify different types of brain tumor, including abnormal and normal magnetic resonance (MR) images. Using differential operators in the differential deep-CNN architecture, we derived the additional differential feature maps in the original CNN feature maps. The derivation process led to an improvement in the performance of the proposed approach in accordance with the results of the evaluation parameters used. The advantage of the differential deep-CNN model is an analysis of a pixel directional pattern of images using contrast calculations and its high ability to classify a large database of images with high accuracy and without technical problems. Therefore, the proposed approach gives an excellent overall performance. To test and train the performance of this model, we used a dataset consisting of 25,000 brain magnetic resonance imaging (MRI) images, which includes abnormal and normal images. The experimental results showed that the proposed model achieved an accuracy of 99.25%. This study demonstrates that the proposed differential deep-CNN model can be used to facilitate the automatic classification of brain tumors.

COVID-19 and Alzheimer's Disease.

Abstract: The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a neurotropic virus with a high neuroinvasive potential. Indeed, more than one-third of patients develop neurological symptoms, including confusion, headache, and hypogeusia/ageusia. However, long-term neurological consequences have received little interest compared to respiratory, cardiovascular, and renal manifestations. Several mechanisms have been proposed to explain the potential SARS-CoV-2 neurological injury that could lead to the development of neurodegenerative diseases, including Alzheimer’s Disease (AD). A mutualistic relationship between AD and COVID-19 seems to exist. On the one hand, COVID-19 patients seem to be more prone to developing AD. On the other hand, AD patients could be more susceptible to severe COVID-19. In this review, we sought to provide an overview on the relationship between AD and COVID-19, focusing on the potential role of biomarkers, which could represent precious tool for early identification of COVID-19 patients at high risk of developing AD.

Quantitative Evaluation of Task-Induced Neurological Outcome after Stroke.

Abstract: Electroencephalography (EEG) can access ischemic stroke-derived cortical impairment and is believed to be a prospective predictive method for acute stroke prognostics, neurological outcome, and post-stroke rehabilitation management. This study aims to quantify EEG features to understand task-induced neurological declines due to stroke and evaluate the biomarkers to distinguish the ischemic stroke group and the healthy adult group. We investigated forty-eight stroke patients (average age 72.2 years, 62% male) admitted to the rehabilitation center and seventy-five healthy adults (average age 77 years, 31% male) with no history of known neurological diseases. EEG was recorded through frontal, central, temporal, and occipital cortical electrodes (Fz, C1, C2, T7, T8, Oz) using wireless EEG devices and a newly developed data acquisition platform within three months after the appearance of symptoms of ischemic stroke (clinically confirmed). Continuous EEG data were recorded during the consecutive resting, motor (walking and working activities), and cognitive reading tasks. The statistical results showed that alpha, theta, and delta activities are biomarkers classifying the stroke patients and the healthy adults in the motor and cognitive states. DAR and DTR of the stroke group differed significantly from those of the healthy control group during the resting, motor, and cognitive tasks. Using the machine-learning approach, the C5.0 model showed 78% accuracy for the resting state, 89% accuracy in the functional motor walking condition, 84% accuracy in the working condition, and 85% accuracy in the cognitive reading state for classification the stroke group and the control group. This study is expected to be helpful for post-stroke treatment and post-stroke recovery.

Post-Acute COVID-19 Symptoms, a Potential Link with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A 6-Month Survey in a Mexican Cohort

Abstract: The aim of this study was to describe the clinical evolution during 6 months of follow-up of adults recovered from COVID-19. We tried to determine how many met the definition of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). A total of 130 patients (51.0 ± 14 years, 34.6% female) were enrolled. Symptoms were common, participants reported a median number of 9 (IQR 5-14) symptoms. Fatigue was the most common symptom (61/130; 46.9%). Patients with fatigue were older 53.9 ± 13.5 years compared with 48.5 ± 13.3 years in those without fatigue (p = 0.02) and had a longer length of hospital stay, 17 ± 14 days vs. 13 ± 10 days (p = 0.04). There was no difference in other comorbidities between patients with fatigue and those without it, and no association between COVID-19 severity and fatigue. After multivariate adjustment of all baseline clinical features, only age 40 to 50 years old was positively associated with fatigue, OR 2.5 (95% CI 1.05-6.05) p = 0.03. In our survey, only 17 (13%) patients met the Institute of Medicine's criteria for "systemic exertion intolerance disease," the new name of ME/CFS. In conclusion, in some patients, the features of post-acute COVID-19 syndrome overlap with the clinical features of ME/CFS.

HPA Axis in the Pathomechanism of Depression and Schizophrenia: New Therapeutic Strategies Based on Its Participation.

Abstract: The hypothalamic-pituitary-adrenal (HPA) axis is involved in the pathophysiology of many neuropsychiatric disorders. Increased HPA axis activity can be observed during chronic stress, which plays a key role in the pathophysiology of depression. Overactivity of the HPA axis occurs in major depressive disorder (MDD), leading to cognitive dysfunction and reduced mood. There is also a correlation between the HPA axis activation and gut microbiota, which has a significant impact on the development of MDD. It is believed that the gut microbiota can influence the HPA axis function through the activity of cytokines, prostaglandins, or bacterial antigens of various microbial species. The activity of the HPA axis in schizophrenia varies and depends mainly on the severity of the disease. This review summarizes the involvement of the HPA axis in the pathogenesis of neuropsychiatric disorders, focusing on major depression and schizophrenia, and highlights a possible correlation between these conditions. Although many effective antidepressants are available, a large proportion of patients do not respond to initial treatment. This review also discusses new therapeutic strategies that affect the HPA axis, such as glucocorticoid receptor (GR) antagonists, vasopressin V1B receptor antagonists and non-psychoactive CB1 receptor agonists in depression and/or schizophrenia.

Neural Decoding of EEG Signals with Machine Learning: A Systematic Review.

Abstract: Electroencephalography (EEG) is a non-invasive technique used to record the brain’s evoked and induced electrical activity from the scalp. Artificial intelligence, particularly machine learning (ML) and deep learning (DL) algorithms, are increasingly being applied to EEG data for pattern analysis, group membership classification, and brain-computer interface purposes. This study aimed to systematically review recent advances in ML and DL supervised models for decoding and classifying EEG signals. Moreover, this article provides a comprehensive review of the state-of-the-art techniques used for EEG signal preprocessing and feature extraction. To this end, several academic databases were searched to explore relevant studies from the year 2000 to the present. Our results showed that the application of ML and DL in both mental workload and motor imagery tasks has received substantial attention in recent years. A total of 75% of DL studies applied convolutional neural networks with various learning algorithms, and 36% of ML studies achieved competitive accuracy by using a support vector machine algorithm. Wavelet transform was found to be the most common feature extraction method used for all types of tasks. We further examined the specific feature extraction methods and end classifier recommendations discovered in this systematic review.

Systemic Inflammatory Response Index and Futile Recanalization in Patients with Ischemic Stroke Undergoing Endovascular Treatment

Abstract: Futile recanalization remains a significant challenge for endovascular treatment (EVT) of acute ischemic stroke (AIS). The inflammatory response that occurs after cerebral infarct plays a central role in stroke pathobiology that can influence the outcome of a recanalization procedure. The aim of this study was to evaluate the relationship between the systemic inflammatory response index (SIRI) and futile recanalization in patients with AIS. We retrospectively identified consecutive patients with ischemic stroke due to proximal arterial occlusion in the anterior circulation, who were treated with EVT and achieved near-complete or complete recanalization. Absolute neutrophil count (ANC), absolute monocyte count (AMC), and absolute lymphocyte count (ALC) were collected from admission blood work to calculate SIRI as ANC × AMC/ALC. The study outcome was futile recanalization, defined as poor functional status [modified Rankin scale (mRS) score ≥ 3] at 3 months despite complete or near-complete recanalization. A total of 184 patients were included. Futile recanalization was observed in 110 (59.8%) patients. Older patients (odds ratio (OR) = 1.07, 95% confidence interval (CI): 1.04–1.10, p < 0.001), higher admission National Institutes of Health stroke scale score (OR = 1.10, 95% CI: 1.02–1.19, p = 0.013), and higher admission SIRI (OR = 1.08, 95% CI: 1.01–1.17, p = 0.028) increased the risk of the poor outcome at 3 months despite complete or near-complete recanalization.

Mothers' Experiences and Challenges Raising a Child with Autism Spectrum Disorder: A Qualitative Study.

Abstract: Although the study of autism is burgeoning with important implications both for public health and society, there is little research exploring the experiences of raising a child with autism spectrum disorder (ASD) from the maternal perspective. The aim of this study was to investigate the lived experiences of mothers of children with ASD in Greece. Nine mothers of children with ASD were recruited and engaged in semistructured interviews. Transcripts of the interviews were analyzed using interpretative phenomenological analysis. Three interconnected themes were identified in the analysis: (a) emotional burden, (b) family burden, and (c) social burden. A key finding in the themes was the sense of burden, distress, and vulnerability experienced by the mothers. The findings provide valuable understanding of the experiences of mothers raising children with ASD in one of Europe’s medium-income countries. Further, results can be used by researchers, clinicians, mental health providers, and policy makers to address the unique needs of families caring for and supporting children with ASD.

Cerebrospinal Fluid Biomarkers of Alzheimer's Disease: Current Evidence and Future Perspectives.

Abstract: Alzheimer's disease is a progressive, clinically heterogeneous, and particularly complex neurodegenerative disease characterized by a decline in cognition. Over the last two decades, there has been significant growth in the investigation of cerebrospinal fluid (CSF) biomarkers for Alzheimer's disease. This review presents current evidence from many clinical neurochemical studies, with findings that attest to the efficacy of existing core CSF biomarkers such as total tau, phosphorylated tau, and amyloid-β (Aβ42), which diagnose Alzheimer's disease in the early and dementia stages of the disorder. The heterogeneity of the pathophysiology of the late-onset disease warrants the growth of the Alzheimer's disease CSF biomarker toolbox; more biomarkers showing other aspects of the disease mechanism are needed. This review focuses on new biomarkers that track Alzheimer's disease pathology, such as those that assess neuronal injury (VILIP-1 and neurofilament light), neuroinflammation (sTREM2, YKL-40, osteopontin, GFAP, progranulin, and MCP-1), synaptic dysfunction (SNAP-25 and GAP-43), vascular dysregulation (hFABP), as well as CSF α-synuclein levels and TDP-43 pathology. Some of these biomarkers are promising candidates as they are specific and predict future rates of cognitive decline. Findings from the combinations of subclasses of new Alzheimer's disease biomarkers that improve their diagnostic efficacy in detecting associated pathological changes are also presented.

Congenital Disorders of Glycosylation from a Neurological Perspective.

Abstract: Most plasma proteins, cell membrane proteins and other proteins are glycoproteins with sugar chains attached to the polypeptide-glycans. Glycosylation is the main element of the post-translational transformation of most human proteins. Since glycosylation processes are necessary for many different biological processes, patients present a diverse spectrum of phenotypes and severity of symptoms. The most frequently observed neurological symptoms in congenital disorders of glycosylation (CDG) are: epilepsy, intellectual disability, myopathies, neuropathies and stroke-like episodes. Epilepsy is seen in many CDG subtypes and particularly present in the case of mutations in the following genes: ALG13, DOLK, DPAGT1, SLC35A2, ST3GAL3, PIGA, PIGW, ST3GAL5. On brain neuroimaging, atrophic changes of the cerebellum and cerebrum are frequently seen. Brain malformations particularly in the group of dystroglycanopathies are reported. Despite the growing number of CDG patients in the world and often neurological symptoms dominating in the clinical picture, the number of performed screening tests eg transferrin isoforms is systematically decreasing as broadened genetic testing is recently more favored. The aim of the review is the summary of selected neurological symptoms in CDG described in the literature in one paper. It is especially important for pediatric neurologists not experienced in the field of metabolic medicine. It may help to facilitate the diagnosis of this expanding group of disorders. Biochemically, this paper focuses on protein glycosylation abnormalities.

Therapeutic Potentials of Ketamine and Esketamine in Obsessive–Compulsive Disorder (OCD), Substance Use Disorders (SUD) and Eating Disorders (ED): A Review of the Current Literature

Abstract: The obsessive–compulsive spectrum refers to disorders drawn from several diagnostic categories that share core features related to obsessive–compulsive disorder (OCD), such as obsessive thoughts, compulsive behaviors and anxiety. Disorders that include these features can be grouped according to the focus of the symptoms, e.g., bodily preoccupation (i.e., eating disorders, ED) or impulse control (i.e., substance use disorders, SUD), and they exhibit intriguing similarities in phenomenology, etiology, pathophysiology, patient characteristics and clinical outcomes. The non-competitive N-methyl-D-aspartate receptor (NMDAr) antagonist ketamine has been indicated to produce remarkable results in patients with treatment-resistant depression, post-traumatic stress disorder and OCD in dozens of small studies accrued over the past decade, and it appears to be promising in the treatment of SUD and ED. However, despite many small studies, solid evidence for the benefits of its use in the treatment of OCD spectrum and addiction is still lacking. Thus, the aim of this perspective article is to examine the potential for ketamine and esketamine in treating OCD, ED and SUD, which all involve recurring and intrusive thoughts and generate associated compulsive behavior. A comprehensive and updated overview of the literature regarding the pharmacological mechanisms of action of both ketamine and esketamine, as well as their therapeutic advantages over current treatments, are provided in this paper. An electronic search was performed, including all papers published up to April 2021, using the following keywords (“ketamine” or “esketamine”) AND (“obsessive” OR “compulsive” OR “OCD” OR “SUD” OR “substance use disorder” OR “addiction” OR “craving” OR “eating” OR “anorexia”) NOT review NOT animal NOT “in vitro”, on the PubMed, Cochrane Library and Web of Science online databases. The review was conducted in accordance with preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. The use and efficacy of ketamine in SUD, ED and OCD is supported by glutamatergic neurotransmission dysregulation, which plays an important role in these conditions. Ketamine’s use is increasing, and preliminary data are optimistic. Further studies are needed in order to better clarify the many unknowns related to the use of both ketamine and esketamine in SUD, ED and OCD, and to understand their long-term effectiveness.

Biological Functions of Rat Ultrasonic Vocalizations, Arousal Mechanisms, and Call Initiation.

Abstract: This review summarizes all reported and suspected functions of ultrasonic vocalizations in infant and adult rats. The review leads to the conclusion that all types of ultrasonic vocalizations subserving all functions are vocal expressions of emotional arousal initiated by the activity of the reticular core of the brainstem. The emotional arousal is dichotomic in nature and is initiated by two opposite-in-function ascending reticular systems that are separate from the cognitive reticular activating system. The mesolimbic cholinergic system initiates the aversive state of anxiety with concomitant emission of 22 kHz calls, while the mesolimbic dopaminergic system initiates the appetitive state of hedonia with concomitant emission of 50 kHz vocalizations. These two mutually exclusive arousal systems prepare the animal for two different behavioral outcomes. The transition from broadband infant isolation calls to the well-structured adult types of vocalizations is explained, and the social importance of adult rat vocal communication is emphasized. The association of 22 kHz and 50 kHz vocalizations with aversive and appetitive states, respectively, was utilized in numerous quantitatively measured preclinical models of physiological, psychological, neurological, neuropsychiatric, and neurodevelopmental investigations. The present review should help in understanding and the interpretation of these models in biomedical research.

Neutrophil-to-Lymphocyte, Platelet-to-Lymphocyte and Monocyte-to-Lymphocyte Ratio in Bipolar Disorder

Abstract: Background: Several inflammatory hypotheses have been suggested to explain the etiopathogenesis of bipolar disorder (BD) and its different phases. Neutrophil-to-lymphocyte (NLR), platelet-to-lymphocyte (PLR), and monocyte-to-lymphocyte (MLR) ratios have been proposed as potential peripheral biomarkers of mood episodes. Methods: We recruited 294 patients affected by BD, of which 143 were experiencing a (hypo)manic episode and 151 were in a depressive phase. A blood sample was drawn to perform a complete blood count. NLR, PLR, and MLR were subsequently calculated. A t-test was performed to evaluate differences in blood cell counts between depressed and (hypo)manic patients and a regression model was then computed. Results: Mean values of neutrophils, platelets, mean platelet volume, NLR, PLR, and MLR were significantly higher in (hypo)manic than depressed individuals. Logistic regression showed that PLR may represent an independent predictor of (hypo)mania. Conclusions: Altered inflammatory indexes, particularly PLR, may explain the onset and recurrence of (hypo)manic episodes in patients with BD. As inflammatory ratios represent economical and accessible markers of inflammation, further studies should be implemented to better elucidate their role as peripheral biomarkers of BD mood episodes.

Hybrid Deep Learning (hDL)-Based Brain-Computer Interface (BCI) Systems: A Systematic Review.

Abstract: Background: Brain-Computer Interface (BCI) is becoming more reliable, thanks to the advantages of Artificial Intelligence (AI). Recently, hybrid Deep Learning (hDL), which combines different DL algorithms, has gained momentum over the past five years. In this work, we proposed a review on hDL-based BCI starting from the seminal studies in 2015. Objectives: We have reviewed 47 papers that apply hDL to the BCI system published between 2015 and 2020 extracting trends and highlighting relevant aspects to the topic. Methods: We have queried four scientific search engines (Google Scholar, PubMed, IEEE Xplore and Elsevier Science Direct) and different data items were extracted from each paper such as the database used, kind of application, online/offline training, tasks used for the BCI, pre-processing methodology adopted, type of normalization used, which kind of features were extracted, type of DL architecture used, number of layers implemented and which optimization approach were used as well. All these items were then investigated one by one to uncover trends. Results: Our investigation reveals that Electroencephalography (EEG) has been the most used technique. Interestingly, despite the lower Signal-to-Noise Ratio (SNR) of the EEG data that makes pre-processing of that data mandatory, we have found that the pre-processing has only been used in 21.28% of the cases by showing that hDL seems to be able to overcome this intrinsic drawback of the EEG data. Temporal-features seem to be the most effective with 93.94% accuracy, while spatial-temporal features are the most used with 33.33% of the cases investigated. The most used architecture has been Convolutional Neural Network-Recurrent Neural Network CNN-RNN with 47% of the cases. Moreover, half of the studies have used a low number of layers to achieve a good compromise between the complexity of the network and computational efficiency. Significance: To give useful information to the scientific community, we make our summary table of hDL-based BCI papers available and invite the community to published work to contribute to it directly. We have indicated a list of open challenges, emphasizing the need to use neuroimaging techniques other than EEG, such as functional Near-Infrared Spectroscopy (fNIRS), deeper investigate the advantages and disadvantages of using pre-processing and the relationship with the accuracy obtained. To implement new combinations of architectures, such as RNN-based and Deep Belief Network DBN-based, it is necessary to better explore the frequency and temporal-frequency features of the data at hand.

The Differential Impact of COVID-19 Lockdown on Sleep Quality, Insomnia, Depression, Stress, and Anxiety among Late Adolescents and Elderly in Italy.

Abstract: The restraining measures due to the COVID-19 outbreak deeply affected the general population’s sleep health and psychological status. The current literature proposes young and older people as two particularly at-risk groups. However, the differential impact of the lockdown period in these specific age categories needs to be disentangled. Through a web-based survey adopting validated questionnaires, we evaluated and compared sleep quality/habits, insomnia, perceived stress, depression, and anxiety symptoms of Italian late adolescents (n = 670; mean age ± SD, 19.38 ± 0.74, 18–20 years) and elderly (n = 253; 68.18 ± 2.79, 65–75 years). Young respondents reported more severe insomnia symptoms, worse subjective sleep quality, longer sleep latency, higher daytime dysfunction, and a more prevalent disruption of sleep habits (bedtime, get-up time, nap) than the elderly. On the other hand, older participants showed shorter sleep duration, lower habitual sleep efficiency, and greater use of sleep medications. Finally, the younger population displayed higher levels of depression and perceived stress. Our findings indicate that the lockdown period had more pervasive repercussions on sleep and the mental health of late adolescents. The implementation of supportive strategies is encouraged for this vulnerable population group.

Early Right Motor Cortex Response to Happy and Fearful Facial Expressions: A TMS Motor-Evoked Potential Study

Abstract: The ability to rapidly process others' emotional signals is crucial for adaptive social interactions. However, to date it is still unclear how observing emotional facial expressions affects the reactivity of the human motor cortex. To provide insights on this issue, we employed single-pulse transcranial magnetic stimulation (TMS) to investigate corticospinal motor excitability. Healthy participants observed happy, fearful and neutral pictures of facial expressions while receiving TMS over the left or right motor cortex at 150 and 300 ms after picture onset. In the early phase (150 ms), we observed an enhancement of corticospinal excitability for the observation of happy and fearful emotional faces compared to neutral expressions specifically in the right hemisphere. Interindividual differences in the disposition to experience aversive feelings (personal distress) in interpersonal emotional contexts predicted the early increase in corticospinal excitability for emotional faces. No differences in corticospinal excitability were observed at the later time (300 ms) or in the left M1. These findings support the notion that emotion perception primes the body for action and highlights the role of the right hemisphere in implementing a rapid and transient facilitatory response to emotional arousing stimuli, such as emotional facial expressions.

Psychological and Emotional Effects of Digital Technology on Children in COVID-19 Pandemic.

Abstract: COVID-19 has caused obstacles in continuing normal life almost everywhere in the world by causing the implementation of social distancing and eventually imposing the lockdown. This has become the reason for the increase in technology usage in daily life for professional work as well as for entertainment purposes. There has been an increased prevalence of technology usage in adolescents and children during lockdown leaving its impact on their lives either in a positive or negative aspect. The overall documented percentage increase of technology usage in children was about 15%, of which smartphone usage has 61.7% of prevalence. Disturbance in brain functioning is suggested to be originated by compromise of neuroplasticity of the nerves. The radiofrequency (RF) radiations emitting from the smartphone are of doubtful concern as a brain tumor risk factor in children. The increased usage can have effects on brain functioning that will compromise sleep and cognitive abilities and develop risk for certain mental illnesses including, but not limited to, depression, anxiety, Alzheimer’s disease, and attention-deficit/hyperactive disorder (ADHD). Despite being a threat for developing mental illness, video games are proven to reduce depression and anxiety, and increase creativity, skills, and cognition in children. The increased usage of technology can have a positive and negative impact on the mental development of adolescents and children depending on the trends in the usage. However, parents should be monitoring their children’s mental health and behavior in these difficult times of pandemic.

Psychological impact of covid-19 outbreak on families of children with autism spectrum disorder and typically developing peers: An online survey

Abstract: Background: When COVID-19 was declared as a pandemic, many countries imposed severe lockdowns that changed families’ routines and negatively impacted on parents’ and children’s mental health. Several studies on families with children with autism spectrum disorder (ASD) revealed that lockdown increased the difficulties faced by individuals with ASD, as well as parental distress. No studies have analyzed the interplay between parental distress, children’s emotional responses, and adaptive behaviors in children with ASD considering the period of the mandatory lockdown. Furthermore, we compared families with children on the spectrum and families with typically developing (TD) children in terms of their distress, children’s emotional responses, and behavioral adaptation. Methods: In this study, 120 parents of children aged 5–10 years (53 with ASD) participated. Results: In the four tested models, children’s positive and negative emotional responses mediated the impact of parental distress on children’s playing activities. In the ASD group, parents reported that their children expressed more positive emotions, but fewer playing activities, than TD children. Families with children on the spectrum reported greater behavioral problems during the lockdown and more parental distress. Conclusions: Our findings inform the interventions designed for parents to reduce distress and to develop coping strategies to better manage the caregiver–child relationship.

Comparison of Brain Activation Patterns during Olfactory Stimuli between Recovered COVID-19 Patients and Healthy Controls: A Functional Near-Infrared Spectroscopy (fNIRS) Study

Abstract: Impaired sense of smell occurs in a fraction of patients with COVID-19 infection, but its effect on cerebral activity is unknown. Thus, this case report investigated the effect of COVID-19 infection on frontotemporal cortex activity during olfactory stimuli. In this preliminary study, patients who recovered from COVID-19 infection (n = 6) and healthy controls who never contracted COVID-19 (n = 6) were recruited. Relative changes in frontotemporal cortex oxy-hemoglobin during olfactory stimuli was acquired using functional near-infrared spectroscopy (fNIRS). The area under curve (AUC) of oxy-hemoglobin for the time interval 5 s before and 15 s after olfactory stimuli was derived. In addition, olfactory function was assessed using the Sniffin' Sticks 12-identification test (SIT-12). Patients had lower SIT-12 scores than healthy controls (p = 0.026), but there were no differences in oxy-hemoglobin AUC between healthy controls and patients (p > 0.05). This suggests that past COVID-19 infection may not affect frontotemporal cortex function, and these preliminary results need to be verified in larger samples.

Musical Training and Brain Volume in Older Adults.

Abstract: Musical practice, including musical training and musical performance, has been found to benefit cognitive function in older adults. Less is known about the role of musical experiences on brain structure in older adults. The present study examined the role of different types of musical behaviors on brain structure in older adults. We administered the Goldsmiths Musical Sophistication Index, a questionnaire that includes questions about a variety of musical behaviors, including performance on an instrument, musical practice, allocation of time to music, musical listening expertise, and emotional responses to music. We demonstrated that musical training, defined as the extent of musical training, musical practice, and musicianship, was positively and significantly associated with the volume of the inferior frontal cortex and parahippocampus. In addition, musical training was positively associated with volume of the posterior cingulate cortex, insula, and medial orbitofrontal cortex. Together, the present study suggests that musical behaviors relate to a circuit of brain regions involved in executive function, memory, language, and emotion. As gray matter often declines with age, our study has promising implications for the positive role of musical practice on aging brain health.

Developmental Language Disorder: Early Predictors, Age for the Diagnosis, and Diagnostic Tools. A Scoping Review.

Abstract: Background. Developmental Language Disorder (DLD) is frequent in childhood and may have long-term sequelae. By employing an evidence-based approach, this scoping review aims at identifying (a) early predictors of DLD; (b) the optimal age range for the use of screening and diagnostic tools; (c) effective diagnostic tools in preschool children. Methods. We considered systematic reviews, meta-analyses, and primary observational studies with control groups on predictive, sensitivity and specificity values of screening and diagnostic tools and psycholinguistic measures for the assessment of DLD in preschool children. We identified 37 studies, consisting of 10 systematic reviews and 27 primary studies. Results. Delay in gesture production, receptive and/or expressive vocabulary, syntactic comprehension, or word combination up to 30 months emerged as early predictors of DLD, a family history of DLD appeared to be a major risk factor, and low socioeconomic status and environmental input were reported as risk factors with lower predictive power. Optimal time for screening is suggested between age 2 and 3, for diagnosis around age 4. Because of the high variability of sensitivity and specificity values, joint use of standardized and psycholinguistic measures is suggested to increase diagnostic accuracy. Conclusions. Monitoring risk situations and employing caregivers’ reports, clinical assessment and multiple linguistic measures are fundamental for an early identification of DLD and timely interventions.

The Use and Impact of Cognitive Enhancers among University Students: A Systematic Review.

Abstract: Introduction: Cognitive enhancers (CEs), also known as “smart drugs”, “study aids” or “nootropics” are a cause of concern. Recent research studies investigated the use of CEs being taken as study aids by university students. This manuscript provides an overview of popular CEs, focusing on a range of drugs/substances (e.g., prescription CEs including amphetamine salt mixtures, methylphenidate, modafinil and piracetam; and non-prescription CEs including caffeine, cobalamin (vitamin B12), guarana, pyridoxine (vitamin B6) and vinpocetine) that have emerged as being misused. The diverted non-prescription use of these molecules and the related potential for dependence and/or addiction is being reported. It has been demonstrated that healthy students (i.e., those without any diagnosed mental disorders) are increasingly using drugs such as methylphenidate, a mixture of dextroamphetamine/amphetamine, and modafinil, for the purpose of increasing their alertness, concentration or memory. Aim: To investigate the level of knowledge, perception and impact of the use of a range of CEs within Higher Education Institutions. Methodology: A systematic review was conducted in adherence with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Whilst 1400 studies were identified within this study through a variety of electronic databases (e.g., 520 through PubMed, 490 through Science Direct and 390 through Scopus), 48 papers were deemed relevant and were included in this review. Results: The most popular molecules identified here included the stimulant CEs, e.g., methylphenidate, modafinil, amphetamine salt mixtures and caffeine-related compounds; stimulant CEs’ intake was more prevalent among males than females; drugs were largely obtained from friends and family, as well as via the Internet. It is therefore suggested that CEs are increasingly being used among healthy individuals, mainly students without any diagnosed cognitive disorders, to increase their alertness, concentration, or memory, in the belief that these CEs will improve their performance during examinations or when studying. The impact of stimulant CEs may include tolerance, dependence and/or somatic (e.g., cardiovascular; neurological) complications. Discussion: The availability of CEs for non-medical indications in different countries is influenced by a range of factors including legal, social and ethical factors. Considering the risk factors and motivations that encourage university students to use CE drugs, it is essential to raise awareness about CE-related harms, counteract myths regarding “safe” CE use and address cognitive enhancement in an early stage during education as a preventative public health measure.

Virtual Reality for Neurorehabilitation and Cognitive Enhancement.

Abstract: Our access to computer-generated worlds changes the way we feel, how we think, and how we solve problems In this review, we explore the utility of different types of virtual reality, immersive or non-immersive, for providing controllable, safe environments that enable individual training, neurorehabilitation, or even replacement of lost functions The neurobiological effects of virtual reality on neuronal plasticity have been shown to result in increased cortical gray matter volumes, higher concentration of electroencephalographic beta-waves, and enhanced cognitive performance Clinical application of virtual reality is aided by innovative brain-computer interfaces, which allow direct tapping into the electric activity generated by different brain cortical areas for precise voluntary control of connected robotic devices Virtual reality is also valuable to healthy individuals as a narrative medium for redesigning their individual stories in an integrative process of self-improvement and personal development Future upgrades of virtual reality-based technologies promise to help humans transcend the limitations of their biological bodies and augment their capacity to mold physical reality to better meet the needs of a globalized world

Gait Recovery with an Overground Powered Exoskeleton: A Randomized Controlled Trial on Subacute Stroke Subjects

Abstract: Background: Overground Robot-Assisted Gait Training (o-RAGT) provides intensive gait rehabilitation. This study investigated the efficacy of o-RAGT in subacute stroke subjects, compared to conventional gait training. Methods: A multicenter randomized controlled trial was conducted on 75 subacute stroke subjects (38 in the Experimental Group (EG) and 37 in the Control Group (CG)). Both groups received 15 sessions of gait training (5 sessions/week for 60 min) and daily conventional rehabilitation. The subjects were assessed at the beginning (T1) and end (T2) of the training period with the primary outcome of a 6 Minutes Walking Test (6MWT), the Modified Ashworth Scale of the Affected lower Limb (MAS-AL), the Motricity Index of the Affected lower Limb (MI-AL), the Trunk Control Test (TCT), Functional Ambulation Classification (FAC), a 10 Meters Walking Test (10MWT), the modified Barthel Index (mBI), and the Walking Handicap Scale (WHS). Results: The 6MWT increased in both groups, which was confirmed by both frequentist and Bayesian analyses. Similar outcomes were registered in the MI-AL, 10MWT, mBI, and MAS-AL. The FAC and WHS showed a significant number of subjects improving in functional and community ambulation in both groups at T2. Conclusions: The clinical effects of o-RAGT were similar to conventional gait training in subacute stroke subjects. The results obtained in this study are encouraging and suggest future clinical trials on the topic.

Peritumoral Microenvironment in High-Grade Gliomas: From FLAIRectomy to Microglia–Glioma Cross-Talk

Abstract: Cellular composition and molecular signatures of the glioma core compared with infiltrative margins are different, and it is well known that the tumor edge is enriched in microglia In this review of the literature, we summarize the role of the peritumoral area in high-grade gliomas (HGGs) from surgical and biological points of view There is evidence on the dual role of microglia in HGGs—a scavenger-tumoricidal role when microglia are activated in an M1 phenotype and a role favoring tumor growth and infiltration/migration when microglia are activated in an M2 phenotype Microglia polarization is mediated by complex pathways involving cross-talk with glioma cells In this scenario, extracellular vesicles and their miRNA cargo seem to play a central role The switch to a specific phenotype correlates with prognosis and the pathological assessment of a specific microglial setting can predict a patient’s outcome Some authors have designed an engineered microglial cell as a biologically active vehicle for the delivery of intraoperative near-infrared fluorescent dye with the aim of helping surgeons detect peritumoral infiltrated areas during resection Furthermore, the pharmacological modulation of microglia-glioma cross-talk paves the way to more effective therapies

Long-Term Brain Disorders in Post Covid-19 Neurological Syndrome (PCNS) Patient

Abstract: In the recent pandemic disease, called COVID-19, the role of neurologists and neurobiologists represents a chance to study key features of brain infection and deepen neurological manifestations of COVID-19 and other coronavirus infections In fact, many studies suggest brain damage during infection and persistent neurological symptoms after COVID-19 infection Reverse transcription PCR test, antibody tests, Computed Tomography (CT) of the lung, and Magnetic Resonance (MR) of the brain of the patient were periodically performed during this case report for eight months after infection The aim of this article is to describe the prolonged neurological clinical consequences related to COVID-19 We believe it is clinically clear that we can define a post-acute COVID-19 neurological syndrome Therefore, in patients after a severe clinical condition of COVID-19, a deepening of persistent neurological signs is necessary

Behavior Testing in Rodents: Highlighting Potential Confounds Affecting Variability and Reproducibility

Abstract: Rodent models of brain disorders including neurodevelopmental, neuropsychiatric, and neurodegenerative diseases are essential for increasing our understanding of underlying pathology and for preclinical testing of potential treatments. Some of the most important outcome measures in such studies are behavioral. Unfortunately, reports from different labs are often conflicting, and preclinical studies in rodent models are not often corroborated in human trials. There are many well-established tests for assessing various behavioral readouts, but subtle aspects can influence measurements. Features such as housing conditions, conditions of testing, and the sex and strain of the animals can all have effects on tests of behavior. In the conduct of behavior testing, it is important to keep these features in mind to ensure the reliability and reproducibility of results. In this review, we highlight factors that we and others have encountered that can influence behavioral measures. Our goal is to increase awareness of factors that can affect behavior in rodents and to emphasize the need for detailed reporting of methods.