Editor’s Choice Articles

Objective: The coronavirus belongs to the family of Coronaviridae, which are not branched single-stranded RNA viruses. COVID-19 creates respiratory problems and infections ranging from mild to severe. The virus features mechanisms that serve to delay the cellular immune response. The host’s response is responsible for the pathological process that leads to tissue destruction. Temporomandibular disorders are manifested by painful jaw musculature and jaw joint areas, clicks, or creaks when opening or closing the mouth. All these symptoms can be disabling and occur during chewing and when the patient yawns or even speaks. The pandemic situation has exacerbated anxieties and amplified the vulnerability of individuals. Therefore, from this mechanism, how the COVID-19 pandemic may have increased the incidence of temporomandibular disorders is perceived. The purpose of this review is to evaluate whether COVID-19-related anxiety has caused an increase in temporomandibular dysfunction symptoms in adults to children. Methods: PubMed, Web of Science, Lilacs, and Scopus were systematically searched, until 30 July 2022, to identify studies presenting: the connection between COVID-19 with temporomandibular disorders. Results: From 198 papers, 4 studies were included. Literature studies have shown that the state of uncertainty and anxiety has led to an increase in the incidence of this type of disorder, although not all studies agree. Seventy-three studies were identified after viewing all four search engines; at the end of the screening phase, only four were considered that met the PECO, the planned inclusion, and the exclusion criteria. All studies showed a statistically significant correlation between temporomandibular disorders and COVID-19 with a p < 0.05. Conclusions: All studies agreed that there is an association between COVID-19 and increased incidence of temporomandibular disorders. Full article

In the recent years, growing attention has been paid to the use of camouflaging strategies by adult populations suffering from autism spectrum disorder (ASD) with milder manifestations and without intellectual impairment, which may lead to a delay in diagnosis or even a misdiagnosis. In fact, high-functioning ASD individuals were reported to be more aware of their communication difficulties and were more likely make considerable efforts to adjust their behavior to conventional rules of non-autistic individuals, learning to imitate other non-ASD individuals. Moreover, females reported a higher frequency of camouflaging strategies, suggesting a role of camouflaging in the gender gap of the ASD diagnosis. Although camouflaging strategies can sometimes grant a better level of adjustment, even resulting in a hyper-adaptive behavior, they are also often correlated with negative mental health consequences due to the long-term stress associated with continuous attempts to adapt in day-to-day life. In this framework, the aim of the present work was to review the available studies that assessed the presence and correlates of camouflaging strategies in individuals with ASD. Although the literature available on the topic is still scarce, some interesting correlations between camouflaging and anxious and depressive symptoms, as well as suicidality, were highlighted. In particular, the controversial and sometime opposite thoughts and results about camouflaging may be clarified and integrated in light of a dimensional approach to psychopathology. Full article

This article summarizes the results of studies in which functional magnetic resonance imaging (fMRI) was performed to investigate the neurofunctional activations involved in processing visual stimuli from food in individuals with anorexia nervosa (AN), bulimia nervosa (BN) and binge eating disorder (BED). A systematic review approach based on the PRISMA guidelines was used. Three databases—Scopus, PubMed and Web of Science (WoS)—were searched for brain correlates of each eating disorder. From an original pool of 688 articles, 30 articles were included and discussed. The selected studies did not always overlap in terms of research design and observed outcomes, but it was possible to identify some regularities that characterized each eating disorder. As if there were two complementary regulatory strategies, AN seems to be associated with general hyperactivity in brain regions involved in top-down control and emotional areas, such as the amygdala, insula and hypothalamus. The insula and striatum are hyperactive in BN patients and likely involved in abnormalities of impulsivity and emotion regulation. Finally, the temporal cortex and striatum appear to be involved in the neural correlates of BED, linking this condition to use of dissociative strategies and addictive aspects. Although further studies are needed, this review shows that there are specific activation pathways. Therefore, it is necessary to pay special attention to triggers, targets and maintenance processes in order to plan effective therapeutic interventions. Clinical implications are discussed. Full article

This article reviews the current status of research on the relationship between attachment and trauma in developmental psychopathology. Beginning with a review of the major issues and the state-of-the-art in relation to current thinking in the field of attachment about the impact of trauma and the inter-generational transmission of trauma, the review then considers recent neurobiological work on mentalizing and trauma and suggests areas of new development and implications for clinical practice. Full article

Characterized by high morbidity, mortality, and disability, stroke usually causes symptoms of cerebral hypoxia due to a sudden blockage or rupture of brain vessels, and it seriously threatens human life and health. Rehabilitation is the essential treatment for post-stroke patients suffering from functional impairments, through which hemiparesis, aphasia, dysphagia, unilateral neglect, depression, and cognitive dysfunction can be restored to various degrees. Noninvasive brain stimulation (NIBS) is a popular neuromodulatory technology of rehabilitation focusing on the local cerebral cortex, which can improve clinical functions by regulating the excitability of corresponding neurons. Increasing evidence has been obtained from the clinical application of NIBS, especially repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS). However, without a standardized protocol, existing studies on NIBS show a wide variation in terms of stimulation site, frequency, intensity, dosage, and other parameters. Its application for neurorehabilitation in post-stroke patients is still limited. With advances in neuronavigation technologies, functional near-infrared spectroscopy, and functional MRI, specific brain regions can be precisely located for stimulation. On the basis of our further understanding on neural circuits, neuromodulation in post-stroke rehabilitation has also evolved from single-target stimulation to co-stimulation of two or more targets, even circuits and the network. The present study aims to review the findings of current research, discuss future directions of NIBS application, and finally promote the use of NIBS in post-stroke rehabilitation. Full article

Rehabilitation is a high-potential approach to improving physical and cognitive functions in Parkinson’s disease (PD). Dual-task training innovatively combines motor and cognitive rehabilitation in a comprehensive module. Patients perform motor and cognitive tasks at the same time in dual-task training. The previous studies of dual-task training in PD had high heterogeneity and achieved controversial results. In the current review, we aim to summarize the current evidence of the effect of dual-task training on motor and cognitive functions in PD patients to support the clinical practice of dual-task training. In addition, we also discuss the current opinions regarding the mechanism underlying the interaction between motor and cognitive training. In conclusion, dual-task training is suitable for PD patients with varied disease duration to improve their motor function. Dual-task training can improve motor symptoms, single-task gait speed, single-task steep length, balance, and objective experience of freezing of gait in PD. The improvement in cognitive function after dual-task training is mild. Full article

Schizophrenia is regarded as a neurodevelopmental disorder with its course progressing throughout life. However, the aetiology and development of schizophrenia are still under investigation. Several data suggest that the dysfunction of epigenetic mechanisms is known to be involved in the pathomechanism of this mental disorder. The present article revised the epigenetic background of schizophrenia based on the data available in online databases (PubMed, Scopus). This paper focused on the role of epigenetic regulation, such as DNA methylation, histone modifications, and interference of non-coding RNAs, in schizophrenia development. The article also reviewed the available data related to epigenetic regulation that may modify the severity of the disease as a possible target for schizophrenia pharmacotherapy. Moreover, the effects of antipsychotics on epigenetic malfunction in schizophrenia are discussed based on preclinical and clinical results. The obtainable data suggest alterations of epigenetic regulation in schizophrenia. Moreover, they also showed the important role of epigenetic modifications in antipsychotic action. There is a need for more data to establish the role of epigenetic mechanisms in schizophrenia therapy. It would be of special interest to find and develop new targets for schizophrenia therapy because patients with schizophrenia could show little or no response to current pharmacotherapy and have treatment-resistant schizophrenia. Full article

(1) Background: Aging is the main risk factor for most neurodegenerative diseases, and the inhibition of Phosphodiesterase 4(PDE4) is considered a potential target for the treatment of neurological diseases. The purpose of this study was to investigate the inhibitory effect of moderate-intensity intermittent training (MIIT) on PDE4 in the hippocampus of rats with D-galactose (D-gal)-induced cognitive impairment, and the possible mechanism of improving spatial learning and memory. (2) Methods: the aging rats were treated with D-Gal (150 mg/kg/day, for 6 weeks). The aging rats were treated with MIIT for exercise intervention (45 min/day, 5 days/week, for 8 weeks). The Morris water maze test was performed before and after MIIT to evaluate the spatial learning and memory ability, then to observe the synaptic ultrastructure of the hippocampus CA1 region, to detect the expression of synaptic-related protein synaptophysin (SYP) and postsynaptic density protein 95 (PSD95), and to detect the expression of PDE4 subtypes, cAMP, and its signal pathway protein kinase A (PKA)/cAMP response element binding protein (CREB)/brain-derived neurotrophic factor (BDNF), and the PDE4 methylation level. (3) Results: we found that MIIT for 8 weeks alleviated the decline in spatial learning and memory ability, and improved the synaptic structure of the hippocampus and the expression of synaptic protein SYP and PSD95 in D-Gal aging rats. To elucidate the mechanism of MIIT, we analyzed the expression of PDE4 isoforms PDE4A/PDE4B/PDE4D, cAMP, and the signaling pathway PKA/CREB/BDNF, which play an important role in memory consolidation and maintenance. The results showed that 8 weeks of MIIT significantly up-regulated cAMP, PKA, p-CREB, and BDNF protein expression, and down-regulated PDE4D mRNA and protein expression. Methylation analysis of the PDE4D gene showed that several CG sites in the promoter and exon1 regions were significantly up-regulated. (4) Conclusions: MIIT can improve the synaptic structure of the hippocampus CA1 area and improve the spatial learning and memory ability of aging rats, which may be related to the specific regulation of the PDE4D gene methylation level and inhibition of PDE4D expression. Full article

Since their first application in psychiatry seventy years ago, antipsychotic drugs, besides schizophrenia, have been widely used in the treatment of mood disorders. Such an application of antipsychotics is the subject of this narrative review. Antipsychotic drugs can be arbitrarily classified into three generations. First-generation antipsychotics (FGAs), such as phenothiazines and haloperidol, were mainly applied for the treatment of acute mania, as well as psychotic depression when combined with antidepressants. The second-generation, so-called atypical antipsychotics (SGAs), such as clozapine, risperidone, olanzapine, and quetiapine, have antimanic activity and are also effective for the maintenance treatment of bipolar disorder. Additionally, quetiapine exerts therapeutic action in bipolar depression. Third-generation antipsychotics (TGAs) started with aripiprazole, a partial dopamine D2 receptor agonist, followed by brexpiprazole, lurasidone, cariprazine, and lumateperone. Out of these drugs, aripiprazole and cariprazine have antimanic activity, lurasidone, cariprazine, and lumateperone exert a significant antidepressant effect on bipolar depression, while there is evidence for the efficacy of aripiprazole and lurasidone in the prevention of recurrence in bipolar disorder. Therefore, successive generations of antipsychotic drugs present a diverse spectrum for application in mood disorders. Such a pharmacological overlap in the treatment of schizophrenia and bipolar illness stands in contrast to the dichotomous Kraepelinian division of schizophrenia and mood disorders. Full article

In decision making, the subjective value of a reward declines with the delay to its receipt, describing a hyperbolic function. Although this phenomenon, referred to as delay discounting (DD), has been extensively characterized and reported in many animal species, still, little is known about the neuronal processes that support it. Here, after drawing a comprehensive portrait, we consider the latest neuroimaging and lesion studies, the outcomes of which often appear contradictory among comparable experimental settings. In the second part of the manuscript, we focus on a more recent and effective route of investigation: non-invasive brain stimulation (NIBS). We provide a comprehensive review of the available studies that applied transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) to affect subjects’ performance in DD tasks. The aim of our survey is not only to highlight the superiority of NIBS in investigating DD, but also to suggest targets for future experimental studies, since the regions considered in these studies represent only a fraction of the possible ones. In particular, we argue that, based on the available neurophysiological evidence from lesion and brain imaging studies, a very promising and underrepresented region for future neuromodulation studies investigating DD is the orbitofrontal cortex. Full article

In 2002, the first III generation antipsychotic drug was registered—aripiprazole. Its partial dopaminergic agonism underlies its unique mechanism of action and the potentially beneficial influence on the positive, negative, or cognitive symptoms. Due to its relatively high intrinsic activity, the drug could often cause agitation, anxiety, or akathisia. For this reason, efforts were made to develop a drug which would retain the positive favorable actions of aripiprazole but present a more advantageous clinical profile. This turned out to be brexpiprazole, which was registered in 2015. Its pharmacodynamic and pharmacokinetic profile (similarly to the other most recent antipsychotics, i.e., lurasidone or cariprazine) shows promise of increasing the effectiveness of schizophrenia treatment in the dimensions in which the previous antipsychotics were not sufficiently effective, including negative, depressive, or cognitive symptoms. Like other new antipsychotics, it can also be useful in the treatment of mood disorders, for instance drug-resistant depression. Previous reviews focused on the use of brexpiprazole in specific diagnostic groups. The aim of this article is to provide the readers with an overview of data on the mechanism of action, clinical effectiveness in all studied diagnostic groups, as well as potential drug–food interactions, and the safety of brexpiprazole. Full article

Both Subjective Cognitive Decline (SCD) and mental fatigue are becoming increasingly prevalent as global demographics shifts indicate our aging populations. SCD is a reversible precursor for Alzheimer’s disease, and early identification is important for effective intervention strategies. We aim to investigate the association between mental fatigue—as well as other factors—and SCD. A total of 707 old adults (aged from 60 to 99) from Shanghai, China, participated in this study and completed self-reported instruments covering their cognitive and mental status as well as demographic information. Mental fatigue status was assessed by using four items derived from the functional impairment syndrome of the Old Adult Self Report (OASR). SCD was assessed by using the Memory/Cognition syndrome of OASR. A total of 681 old adults were included in the current study. The means of SCD significantly differed between each group of factors (age, gender, and mental fatigue). The general linear regression models showed that SCD increased with age, females scored higher than males, and SCD was positively associated with mental fatigue factors including difficulty getting things done, poor task performance, sleeping more, and a lack of energy among old adults. The study also found that SCD is negatively associated with the high-income group among young-old (aged from 60 to 75) males and associated with good marital/living status with the companion of spouses/partners among young-old females. These results suggest that gender, income level, marital/living status, and mental fatigue are crucial factors in preventing SCD among old adults and are pivotal in developing early intervention strategies to preserve the mental health of an increasingly aging population. Full article

We propose a hyperscanning research design, where electroencephalographic (EEG) data were collected on an instructor and teams of learners. We compared neurophysiological measures within the frequency domain (delta, theta, alpha, and beta EEG bands) in the two conditions: face-to-face and remote settings. Data collection was carried out using wearable EEG systems. Conversational analysis was previously applied to detect comparable EEG time blocks and semantic topics. The digitalization of training can be considered a challenge but also a chance for organizations. However, if not carefully addressed, it might constitute a criticality. Limited research explored how remote, as opposed to face-to-face, training affects cognitive, (such as memory and attention), affective, and social processes in workgroups. Data showed an alpha desynchronization and, conversely, a theta and beta synchronization for the face-to-face condition. Moreover, trainees showed different patterns for beta power depending on the setting condition, with significantly increased power spectral density (PSD) in the face-to-face condition. These results highlight the relevance of neurophysiological measures in testing the e-learning process, in relation to the emotional engagement, memory encoding, and attentional processing. Full article

Purpose: Brain tumors are diagnosed and classified manually and noninvasively by radiologists using Magnetic Resonance Imaging (MRI) data. The risk of misdiagnosis may exist due to human factors such as lack of time, fatigue, and relatively low experience. Deep learning methods have become increasingly important in MRI classification. To improve diagnostic accuracy, researchers emphasize the need to develop Computer-Aided Diagnosis (CAD) computational diagnostics based on artificial intelligence (AI) systems by using deep learning methods such as convolutional neural networks (CNN) and improving the performance of CNN by combining it with other data analysis tools such as wavelet transform. In this study, a novel diagnostic framework based on CNN and DWT data analysis is developed for the diagnosis of glioma tumors in the brain, among other tumors and other diseases, with T2-SWI MRI scans. It is a binary CNN classifier that treats the disease “glioma tumor” as positive and the other pathologies as negative, resulting in a very unbalanced binary problem. The study includes a comparative analysis of a CNN trained with wavelet transform data of MRIs instead of their pixel intensity values in order to demonstrate the increased performance of the CNN and DWT analysis in diagnosing brain gliomas. The results of the proposed CNN architecture are also compared with a deep CNN pre-trained on VGG16 transfer learning network and with the SVM machine learning method using DWT knowledge. Methods: To improve the accuracy of the CNN classifier, the proposed CNN model uses as knowledge the spatial and temporal features extracted by converting the original MRI images to the frequency domain by performing Discrete Wavelet Transformation (DWT), instead of the traditionally used original scans in the form of pixel intensities. Moreover, no pre-processing was applied to the original images. The images used are MRIs of type T2-SWI sequences parallel to the axial plane. Firstly, a compression step is applied for each MRI scan applying DWT up to three levels of decomposition. These data are used to train a 2D CNN in order to classify the scans as showing glioma or not. The proposed CNN model is trained on MRI slices originated from 382 various male and female adult patients, showing healthy and pathological images from a selection of diseases (showing glioma, meningioma, pituitary, necrosis, edema, non-enchasing tumor, hemorrhagic foci, edema, ischemic changes, cystic areas, etc.). The images are provided by the database of the Medical Image Computing and Computer-Assisted Intervention (MICCAI) and the Ischemic Stroke Lesion Segmentation (ISLES) challenges on Brain Tumor Segmentation (BraTS) challenges 2016 and 2017, as well as by the numerous records kept in the public general hospital of Chania, Crete, “Saint George”. Results: The proposed frameworks are experimentally evaluated by examining MRI slices originating from 190 different patients (not included in the training set), of which 56% are showing gliomas by the longest two axes less than 2 cm and 44% are showing other pathological effects or healthy cases. Results show convincing performance when using as information the spatial and temporal features extracted by the original scans. With the proposed CNN model and with data in DWT format, we achieved the following statistic percentages: accuracy 0.97, sensitivity (recall) 1, specificity 0.93, precision 0.95, FNR 0, and FPR 0.07. These numbers are higher for this data format (respectively: accuracy by 6% higher, recall by 11%, specificity by 7%, precision by 5%, FNR by 0.1%, and FPR is the same) than it would be, had we used as input data the intensity values of the MRIs (instead of the DWT analysis of the MRIs). Additionally, our study showed that when our CNN takes into account the TL of the existing network VGG, the performance values are lower, as follows: accuracy 0.87, sensitivity (recall) 0.91, specificity 0.84, precision 0.86, FNR of 0.08, and FPR 0.14. Conclusions: The experimental results show the outperformance of the CNN, which is not based on transfer learning, but is using as information the MRI brain scans decomposed into DWT information instead of the pixel intensity of the original scans. The results are promising for the proposed CNN based on DWT knowledge to serve for binary diagnosis of glioma tumors among other tumors and diseases. Moreover, the SVM learning model using DWT data analysis performs with higher accuracy and sensitivity than using pixel values. Full article

Physical exercise and cognitive remediation represent the psychosocial interventions with the largest basis of evidence attesting their effectiveness in improving cognitive performance in people living with schizophrenia according to recent international guidance. The aims of this review are to provide an overview of the literature on physical exercise as a treatment for cognitive impairment in schizophrenia and of the studies that have combined physical exercise and cognitive remediation as an integrated rehabilitation intervention. Nine meta-analyses and systematic reviews on physical exercise alone and seven studies on interventions combining physical exercise and cognitive remediation are discussed. The efficacy of physical exercise in improving cognitive performance in people living with schizophrenia is well documented, but more research focused on identifying moderators of participants response and optimal modalities of delivery is required. Studies investigating the effectiveness of integrated interventions report that combining physical exercise and cognitive remediation provides superior benefits and quicker improvements compared to cognitive remediation alone, but most studies included small samples and did not explore long-term effects. While physical exercise and its combination with cognitive remediation appear to represent effective treatments for cognitive impairment in people living with schizophrenia, more evidence is currently needed to better understand how to implement these treatments in psychiatric rehabilitation practice. Full article

Background: There is a growing liberalization of cannabis-based preparations for medical and recreational use. In multiple instances, anxiety and depression are cited as either a primary or a secondary reason for the use of cannabinoids. Aim: The purpose of this review is to explore the association between depression or anxiety and the dysregulation of the endogenous endocannabinoid system (ECS), as well as the use of phytocannabinoids and synthetic cannabinoids in the remediation of depression/anxiety symptoms. After a brief description of the constituents of cannabis, cannabinoid receptors and the endocannabinoid system, the most important evidence is presented for the involvement of cannabinoids in depression and anxiety both in human and from animal models of depression and anxiety. Finally, evidence is presented for the clinical use of cannabinoids to treat depression and anxiety. Conclusions: Although the common belief that cannabinoids, including cannabis, its main studied components—tetrahydrocannabinol (THC) and cannabidiol (CBD)—or other synthetic derivatives have been suggested to have a therapeutic role for certain mental health conditions, all recent systematic reviews that we report have concluded that the evidence that cannabinoids improve depressive and anxiety disorders is weak, of very-low-quality, and offers no guidance on the use of cannabinoids for mental health conditions within a regulatory framework. There is an urgent need for high-quality studies examining the effects of cannabinoids on mental disorders in general and depression/anxiety in particular, as well as the consequences of long-term use of these preparations due to possible risks such as addiction and even reversal of improvement. Full article

Brain tumor-related epilepsy (BTRE) is a common comorbidity in patients with brain neoplasms and it may be either the first symptom or develop after the tumor diagnosis. Increasing evidence suggests that brain tumors and BTRE share common pathophysiological mechanisms. Glutamatergic mechanisms can play a central role in promoting both primary brain tumor growth and epileptogenesis. Perampanel (PER), which acts as a selective antagonist of glutamate α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors, may play a role both in the reduction in tumor growth and the control of epileptiform activity. This systematic review aimed to summarize the pre-clinical and clinical evidence about the antitumor properties, antiseizure effects and tolerability of PER in BTRE. Eight pre-clinical and eight clinical studies were identified. The currently available evidence suggests that PER can be an effective and generally well-tolerated therapeutic option in patients with BTRE. In vitro studies demonstrated promising antitumor activity of PER, while no role in slowing tumor progression has been demonstrated in rat models; clinical data on the potential antitumor activity of PER are scarce. Additional studies are needed to explore further the effects of PER on tumor progression and fully characterize its potentialities in patients with BTRE. Full article

This article assesses the cool–hot executive function (EF) framework during childhood. First, conceptual analyses suggest that cool EF (cEF) is generally distinguished from hot EF (hEF). Second, both EFs can be loaded into different factors using confirmatory factor analyses. Third, the cognitive complexity of EF is similar across cEF tasks, and the cognitive complexity of cEF is similar to hEF tasks. Finally, neuroimaging analysis suggests that children activate the lateral prefrontal regions during all EF tasks. Taken together, we propose that the cool–hot framework is a useful, though not definitive way of characterizing differences in EF. Full article

Depression and anxiety are highly prevalent in most neurological disorders and can have a major impact on the patient’s disability and quality of life. However, mostly due to the heterogeneity of symptoms and the complexity of the underlying comorbidities, depression can be difficult to diagnose, resulting in limited recognition and in undertreatment. The early detection and treatment of depression simultaneously with the neurological disorder is key to avoiding deterioration and further disability. Although the neurologist should be able to identify and treat depression initially, a neuropsychiatry team should be available for severe cases and those who are unresponsive to treatment. Neurologists should be also aware that in neurodegenerative diseases, such as Alzheimer’s or Parkinson’s, different depression symptoms could develop at different stages of the disease. The treatment options for depression in neurological diseases include drugs, cognitive-behavioral therapy, and somatic interventions, among others, but often, the evidence-based efficacy is limited and the results are highly variable. Here, we review recent research on the diagnosis and treatment of depression in the context of Alzheimer’s disease, Parkinson’s disease, and strokes, with the aim of identifying common approaches and solutions for its initial management by the neurologist. Full article

The need to identify new potentially druggable biochemical mechanisms for Alzheimer’s disease (AD) is an ongoing priority. The therapeutic limitations of amyloid-based approaches are further motivating this search. Amino acid metabolism, particularly tryptophan metabolism, has the potential to emerge as a leading candidate and an alternative exploitable biomolecular target. Multiple avenues support this contention. Tryptophan (trp) and its associated metabolites are able to inhibit various enzymes participating in the biosynthesis of β-amyloid, and one metabolite, 3-hydroxyanthranilate, is able to directly inhibit neurotoxic β-amyloid oligomerization; however, whilst certain trp metabolites are neuroprotectant, other metabolites, such as quinolinic acid, are directly toxic to neurons and may themselves contribute to AD progression. Trp metabolites also have the ability to influence microglia and associated cytokines in order to modulate the neuroinflammatory and neuroimmune factors which trigger pro-inflammatory cytotoxicity in AD. Finally, trp and various metabolites, including melatonin, are regulators of sleep, with disorders of sleep being an important risk factor for the development of AD. Thus, the involvement of trp biochemistry in AD is multifactorial and offers a plethora of druggable targets in the continuing quest for AD therapeutics. Full article

Advances in applied machine learning techniques for neuroimaging have encouraged scientists to implement models to diagnose brain disorders such as Alzheimer’s disease at early stages. Predicting the exact stage of Alzheimer’s disease is challenging; however, complex deep learning techniques can precisely manage this. While successful, these complex architectures are difficult to interrogate and computationally expensive. Therefore, using novel, simpler architectures with more efficient pattern extraction capabilities, such as transformers, is of interest to neuroscientists. This study introduced an optimized vision transformer architecture to predict the group membership by separating healthy adults, mild cognitive impairment, and Alzheimer’s brains within the same age group (>75 years) using resting-state functional (rs-fMRI) and structural magnetic resonance imaging (sMRI) data aggressively preprocessed by our pipeline. Our optimized architecture, known as OViTAD is currently the sole vision transformer-based end-to-end pipeline and outperformed the existing transformer models and most state-of-the-art solutions. Our model achieved F1-scores of $97\%\pm 0.0$ and $99.55\%\pm 0.39$ from the testing sets for the rs-fMRI and sMRI modalities in the triple-class prediction experiments. Furthermore, our model reached these performances using 30% fewer parameters than a vanilla transformer. Furthermore, the model was robust and repeatable, producing similar estimates across three runs with random data splits (we reported the averaged evaluation metrics). Finally, to challenge the model, we observed how it handled increasing noise levels by inserting varying numbers of healthy brains into the two dementia groups. Our findings suggest that optimized vision transformers are a promising and exciting new approach for neuroimaging applications, especially for Alzheimer’s disease prediction. Full article

Epilepsy is a neurological disease and approximately 30% of patients have failed to respond to current anti-epilepsy drugs. The neuroinflammation mechanism has raised increasing concerns and been regarded as the novel treatment strategy in epilepsy, but the target molecules require further research. Pyruvate kinase isoform 2 (PKM2) is well studied in peripheral inflammation, but its role in epilepsy neuroinflammation remains unclear. We knocked down microglia PKM2 in the hippocampus using a stereotaxic adeno-associated virus (AAV) microinjection and established a pilocarpine-induced status epilepticus (PISE) model. Racine score was used to evaluate the seizure grade. Next, we used WB, Multiplex tyramide signal amplification (TSA) staining and other methods to determine neuroinflammation and the complement component 3 (C3)–C3aR interaction in primary microglia. Results showed that microglia PKM2 knockdown reduced epilepsy grade and rescued neuron loss. Mechanistically, PKM2 knockdown inhibited microglia activation and inflammation factor secretion through suppressing p65 expression and phosphorylation. The reduced microglia C1q, TNF-α, and IL-1α were responsible for the decreased astrocyte C3 expression and the following neuron damage caused by the C3–C3aR interaction. Our data suggest that microglia PKM2 inhibition ameliorates neuroinflammation and neuron loss through C3-C3aR interaction in epilepsy, which provides an attractive target for the intervention of damaged neuron-glia crosstalk in epilepsy. Full article

Diabetic polyneuropathy (DPN) is the most frequent, although neglected, complication of long-term diabetes. Nearly 30% of hospitalized and 20% of community-dwelling patients with diabetes suffer from DPN; the incidence rate is approximately 2% annually. To date, there has been no curable therapy for DPN. Under these circumstances, cell therapy may be a vital candidate for the treatment of DPN. The epidemiology, classification, and treatment options for DPN are disclosed in the current review. Cell-based therapies using bone marrow-derived cells, embryonic stem cells, pluripotent stem cells, endothelial progenitor cells, mesenchymal stem cells, or dental pulp stem cells are our primary concern, which may be a useful treatment option to ease or to stop the progression of DPN. The importance of cryotherapies for treating DPN has been observed in several studies. These findings may help for the future researchers to establish more focused, accurate, effective, alternative, and safe therapy to reduce DPN. Cell-based therapy might be a permanent solution in the treatment and management of diabetes-induced neuropathy. Full article

Anxiety disorders are the most common group of mental disorders, but they are often underrecognized and undertreated in primary care. Dysfunctional breathing is a hallmark of anxiety disorders; however, mainstays of treatments do not tackle breathing in patients suffering anxiety. This scoping review aims to identify the nature and extent of the available research literature on the efficacy of breathwork interventions for adults with clinically diagnosed anxiety disorders using the DSM-5 classification system. Using the PRISMA extension for scoping reviews, a search of PubMed, Embase, and Scopus was conducted using terms related to anxiety disorders and breathwork interventions. Only clinical studies using breathwork (without the combination of other interventions) and performed on adult patients diagnosed with an anxiety disorder using the DSM-5 classification system were included. From 1081 articles identified across three databases, sixteen were included for the review. A range of breathwork interventions yielded significant improvements in anxiety symptoms in patients clinically diagnosed with anxiety disorders. The results around the role of hyperventilation in treatment of anxiety were contradictory in few of the examined studies. This evidence-based review supports the clinical utility of breathwork interventions and discusses effective treatment options and protocols that are feasible and accessible to patients suffering anxiety. Current gaps in knowledge for future research directions have also been identified. Full article

Intellectual disability (ID) has a prevalence of ~2–3% in the general population, having a large societal impact. The underlying cause of ID is largely of genetic origin; however, identifying this genetic cause has in the past often led to long diagnostic Odysseys. Over the past decades, improvements in genetic diagnostic technologies and strategies have led to these causes being more and more detectable: from cytogenetic analysis in 1959, we moved in the first decade of the 21st century from genomic microarrays with a diagnostic yield of ~20% to next-generation sequencing platforms with a yield of up to 60%. In this review, we discuss these various developments, as well as their associated challenges and implications for the field of ID, which highlight the revolutionizing shift in clinical practice from a phenotype-first into genotype-first approach. Full article

Glioblastoma multiforme (GBM) represents the most common and aggressive central nervous system tumor associated with a poor prognosis. The aim of this study was to depict the role of intraoperative imaging techniques in GBM surgery and how they can ensure the maximal extent of resection (EOR) while preserving the functional outcome. The authors conducted a systematic review following PRISMA guidelines on the PubMed/Medline and Scopus databases. A total of 1747 articles were identified for screening. Studies focusing on GBM-affected patients, and evaluations of EOR and functional outcomes with the aid of advanced image-guided techniques were included. The resulting studies were assessed for methodological quality using the Risk of Bias in Systematic Review tool. Open Science Framework registration DOI 10.17605/OSF.IO/3FDP9. Eighteen studies were eligible for this systematic review. Among the selected studies, eight analyzed Sodium Fluorescein, three analyzed 5-aminolevulinic acid, two evaluated IoMRI imaging, two evaluated IoUS, and three evaluated multiple intraoperative imaging techniques. A total of 1312 patients were assessed. Gross Total Resection was achieved in the 78.6% of the cases. Follow-up time ranged from 1 to 52 months. All studies assessed the functional outcome based on the Karnofsky Performance Status scale, while one used the Neurologic Assessment in Neuro-Oncology score. In 77.7% of the cases, the functional outcome improved or was stable over the pre-operative assessment. Combining multiple intraoperative imaging techniques could provide better results in GBM surgery than a single technique. However, despite good surgical outcomes, patients often present a neurocognitive decline leading to a marked deterioration of the quality of life. Advanced intraoperative image-guided techniques can allow a better understanding of the anatomo-functional relationships between the tumor and the surrounding brain, thus maximizing the EOR while preserving functional outcomes. Full article

Despite proving its usefulness for over a century, the concept of developmental dyslexia (DD) is currently in severe disarray because of the recent introduction of the phonological theory of its causation. Since mastering the phonological principle is essential for all reading, failure to do so cannot be used to distinguish DD from the many other causes of such failure. To overcome this problem, many new psychological, signal detection, and neurological theories have been introduced recently. All these new theories converge on the idea that DD is fundamentally caused by impaired signalling of the timing of the visual and auditory cues that are essential for reading. These are provided by large ‘magnocellular’ neurones which respond rapidly to sensory transients. The evidence for this conclusion is overwhelming. Especially convincing are intervention studies that have shown that improving magnocellular function improves dyslexic children’s reading, together with cohort studies that have demonstrated that the magnocellular timing deficit is present in infants who later become dyslexic, long before they begin learning to read. The converse of the magnocellular deficit in dyslexics may be that they gain parvocellular abundance. This may often impart the exceptional ‘holistic’ talents that have been ascribed to them and that society needs to nurture. Full article

Sleep disturbances are the most prevalent non-motor symptoms in the preclinical stage of Parkinson’s disease (PD). Adenosine, glial-derived neurotrophic factor (GDNF), and associated neurotransmitters are crucial in the control of sleep arousal. This study aimed to detect the serum levels of adenosine, GDNF, and associated neurotransmitters and explored their correlations with PD with sleep disorders. Demographic characteristics and clinical information of PD patients and healthy participants were assessed. Serum concentrations of adenosine, GDNF, and related neurotransmitters were detected by ELISA and LC-MS. The correlation between serum levels of adenosine, GDNF, and associated neurotransmitters and sleep disorders was explored using logistic regression. PD patients with sleep disorders had higher scores of HAMA, HAMD, ESS, UPDRS-III, and H-Y stage. Lower levels of adenosine, GDNF, and γ-GABA were observed in PD patients who had sleep problems. Logistic regression analysis showed adenosine and GDNF were protective factors for preventing sleep disorders. Adenosine combined with GDNF had a higher diagnostic efficiency in predicting PD with sleep disorders by ROC analysis. This study revealed low adenosine and GDNF levels may be risk factors for sleep disorders in PD. The decrease of serum adenosine and GDNF levels may contribute to the diagnosis of PD with sleep disturbances. Full article

Background: The thalamus has been reported to be associated with pain modulation and processing. However, the functional changes that occur in the thalamus of vestibular migraine (VM) patients remain unknown. Methods: In total, 28 VM patients and 28 healthy controls who were matched for age and sex underwent resting-state functional magnetic resonance imaging. They also responded to standardized questionnaires aimed at assessing the clinical features associated with migraine and vertigo. Differences in the amplitude of low-frequency fluctuation (ALFF) were analyzed and brain regions with altered ALFF in the two groups were used for further analysis of whole-brain functional connectivity (FC). The relationship between clusters and clinical features was investigated by correlation analyses. Results: The ALFF in the thalamus was significantly decreased in the VM group versus the control group. In the VM group, the ALFF in the left thalamus negatively correlated with VM episode frequency. Furthermore, the left thalamus showed significantly weaker FC than both regions of the medial prefrontal cortex, both regions of the anterior cingulum cortex, the left superior/middle temporal gyrus, and the left temporal pole in the VM group. Conclusions: The thalamus plays an important role in VM patients and it is suggested that connectivity abnormalities of the thalamocortical region contribute to abnormal pain information processing and modulation, transmission, and multisensory integration in patients with VM. Full article

Gastrodin is the active ingredient in Gastrodia elata. Our previous studies demonstrated that gastrodin ameliorated cerebral ischemia–reperfusion and hypoperfusion injury and improved cognitive deficit in Alzheimer’s disease. This study aims to examine the effects of gastrodin on REM sleep deprivation in rats. Gastrodin (100 and 150 mg/kg) was orally administered for 7 consecutive days before REM sleep deprivation. Seventy-two hours later, pentobarbital-induced sleep tests and a Morris water maze were performed to measure REM sleep quality and learning and memory ability. Histopathology was observed with hematoxylin–eosin staining, and the expression of the NF-κB and Wnt/β-catenin signaling pathways was examined using Western blot. After REM sleep deprivation, sleep latency increased and sleep duration decreased, and the ability of learning and memory was impaired. Neurons in the hippocampal CA1 region and the cortex were damaged. Gastrodin treatment significantly improved REM sleep-deprivation-induced sleep disturbance, cognitive deficits and neuron damage in the hippocampus CA1 region and cerebral cortex. A mechanism analysis revealed that the NF-κB pathway was activated and the Wnt/β-catenin pathway was inhibited after REM sleep deprivation, and gastrodin ameliorated these aberrant changes. Gastrodin improves REM sleep-deprivation-induced sleep disturbance and cognitive dysfunction by regulating the TLR4/NF-κB and Wnt/β-catenin signaling pathways and can be considered a potential candidate for the treatment of REM sleep deprivation. Full article

Chemsex is described as the use of certain drugs—commonly methamphetamine, gamma-butyrolactone (GBL)/gammahydroxybutyrate (GHB), and mephedrone—before or during planned sexual activity primarily among men who have sex with men (MSM). Evidence shows that MSM who engage in chemsex are at increased risk of physical harm, such as sexually transmittable infections (STIs), and are more likely to experience mental health symptoms. To further assess this, we reviewed the recent literature to evaluate whether the psychological impact of chemsex behavior includes suicidal ideation and suicidal attempts. Pubmed/MEDLINE was searched for articles reporting suicidal ideation and behavior among chemsex users with the terms “chemsex”, “sexualized drug use”, “suicide”, and “mental health”. Twelve articles (three case reports and nine cross-sectional studies) were included in the final narrative review. Overall, we retrieved mixed results regarding the relationship between chemsex practice and suicidality outcomes. Considering the inhomogeneous nature of the studies, the findings indicate that suicidality could be an issue of concern among MSM in general but among chemsex users in particular. Possible risk factors for suicidality among chemsex participants may include adversities experienced due to one’s sexual orientation and an increased risk for HIV and other STI infections and the resulting negative impact on mental well-being. These aspects warrant further investigations. Full article

Short sleep is a common issue nowadays. The purpose of this study was to investigate prefrontal cortical hemodynamics by evaluating changes in concentrations of oxygenated hemoglobin (HbO) in cognitive tests among short-sleep young adults and to explore the relationship between sleep duration, physical activity level, and cognitive function in this specific population. A total of 46 participants (25 males and 21 females) were included in our study, and among them, the average sleep duration was 358 min/day. Stroop performance in the short sleep population was linked to higher levels cortical activation in distinct parts of the left middle frontal gyrus. This study found that moderate-to-vigorous physical activity (MVPA) was significantly associated with lower accuracy of incongruent Stroop test. The dose-response relationship between sleep duration and Stroop performance under different levels of light-intensity physical activity (LPA) and MVPA was further explored, and increasing sleep time for different PA level was associated with better Stroop performance. In summary, this present study provided neurobehavioral evidence between cortical hemodynamics and cognitive function in the short sleep population. Furthermore, our findings indicated that, in younger adults with short sleep, more MVPA was associated with worse cognitive performance. Short sleep young adults should increase sleep time, rather than more MVPA, to achieve better cognitive function. Full article

Brain-derived neurotrophic factor (BDNF) belongs to the family of neurotrophins, which are growth factors with trophic effects on neurons. BDNF is the most widely distributed neurotrophin in the central nervous system (CNS) and is highly expressed in the prefrontal cortex (PFC) and hippocampus. Its distribution outside the CNS has also been demonstrated, but most studies have focused on its effects in neuropsychiatric disorders. Despite the advances in medicine in recent decades, neurological and psychiatric diseases are still characterized by high drug resistance. This review focuses on the use of BDNF in the developmental assessment, treatment monitoring, and pharmacotherapy of selected diseases, with a particular emphasis on epilepsy, depression, anorexia, obesity, schizophrenia, and Alzheimer’s disease. The limitations of using a molecule with such a wide distribution range and inconsistent method of determination are also highlighted. Full article

Background: Existing studies indicate that some computed tomography perfusion (CTP) parameters may predict hemorrhagic transformation (HT) after acute ischemic stroke (AIS), but there is an inconsistency in the conclusions alongside a lack of comprehensive comparison. Objective: To comprehensively evaluate the predictive value of CTP parameters in HT after AIS. Data sources: A systematical literature review of existing studies was conducted up to 1st October 2022 in six mainstream databases that included original data on the CTP parameters of HT and non-HT groups or on the diagnostic performance of relative cerebral blood flow (rCBF), relative permeability-surface area product (rPS), or relative cerebral blood volume (rCBV) in patients with AIS that completed CTP within 24 h of onset. Data Synthesis: Eighteen observational studies were included. HT and non-HT groups had statistically significant differences in CBF, CBV, PS, rCBF, rCBV, and rPS (p < 0.05 for all). The hierarchical summary receiver operating characteristic (HSROC) revealed that rCBF (area under the curve (AUC) = 0.9), rPS (AUC = 0.89), and rCBV (AUC = 0.85) had moderate diagnostic performances in predicting HT. The pooled sensitivity and specificity of rCBF were 0.85 (95% CI, 0.75–0.91) and 0.83 (95% CI, 0.63–0.94), respectively. Conclusions: rCBF, rPS, and rCBV had moderate diagnostic performances in predicting HT, and rCBF had the best pooled sensitivity and specificity. Full article

Synucleinopathies are a group of neurodegenerative diseases with common pathological lesions associated with the excessive accumulation and abnormal intracellular deposition of toxic species of α-synuclein. The shared clinical features are chronic progressive decline of motor, cognitive, and behavioral functions. These disorders include Parkinson’s disease, dementia with Lewy body, and multiple system atrophy. Vigorous research in the mechanisms of pathology of these illnesses is currently under way to find disease-modifying treatment and molecular markers for early diagnosis. α-Synuclein is a prone-to-aggregate, small amyloidogenic protein with multiple roles in synaptic vesicle trafficking, neurotransmitter release, and intracellular signaling events. Its expression is controlled by several mechanisms, one of which is epigenetic regulation. When transmitted to the nucleus, α-synuclein binds to DNA and histones and participates in epigenetic regulatory functions controlling specific gene transcription. Here, we discuss the various aspects of α-synuclein involvement in epigenetic regulation in health and diseases. Full article

Neurodegenerative diseases (ND) include a wide range of conditions that result from progressive damage to the neurons. Alzheimer’s disease (AD) is one of the most common NDs, and neuroinflammation and oxidative stress (OS) are the major factors in the development and progression of the disease. Many naturally occurring phytochemical compounds exhibit antioxidant and anti-inflammatory activities with potential neuroprotective effects. Several plant species, including Alpinia katsumadai and Alpinia conchigera, contain cardamonin (CD). CD (2′,4′-dihydroxy-6′methoxychalcone) has many therapeutic properties, including anticancer, anti-inflammatory, antioxidant, antiviral, and antibiotic activities. CD is a potent compound that can reduce OS and modulate the inflammatory processes that play a significant part in developing neurodegenerative diseases. CD has been shown to modulate a variety of signaling molecules involved in the development and progression of ND, including transcription factors (NF-kB and STAT3), cytokines (TNF-α, IL-1, and IL-6), enzymes (COX-2, MMP-9, and ALDH1), and other proteins and genes (Bcl-2, XIAP, and cyclin D1). Additionally, CD effectively modulates miRNA levels and autophagy-related CD-protective mechanisms against neurodegeneration. In summary, this review provides mechanistic insights into CD’s ability to modify multiple oxidative stress–antioxidant system pathways, Nrf2, and neuroinflammation. Additionally, it points to the possible therapeutic potential and preventive utilization of CD in neurodegenerative diseases, most specifically AD. Full article

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder that interferes with normal brain development. Brain connectivity may serve as a biomarker for ASD in this respect. This study enrolled a total of 179 children aged 3−10 years (90 typically developed (TD) and 89 with ASD). We used a weighted phase lag index and a directed transfer function to investigate the functional and effective connectivity in children with ASD and TD. Our findings indicated that patients with ASD had local hyper-connectivity of brain regions in functional connectivity and simultaneous significant decrease in effective connectivity across hemispheres. These connectivity abnormalities may help to find biomarkers of ASD. Full article

Lithium has been a cornerstone treatment for bipolar disorder (BD). Despite descriptions in the literature regarding associations between long-term lithium therapy (LTLT) and development of a thyroid disorder (overt/subclinical hypo/hyperthyroidism, thyroid nodule, and goiter) in BD, factors such as time to onset of thyroid abnormalities and impact on clinical outcomes in the course of illness have not been fully characterized. In this study we aimed to compare clinical characteristics of adult BD patients with and without thyroid disorders who were on LTLT. We aimed to identify the incidence of thyroid disorders in patients with BD on LTLT and response to lithium between patients with and without thyroid disorders in BD. The Cox proportional model was used to find the median time to the development of a thyroid disorder. Our results showed that up to 32% of patients with BD on LTLT developed a thyroid disorder, of which 79% developed hypothyroidism, which was corrected with thyroid hormone replacement. We did not find significant differences in lithium response between patients with or without thyroid disorders in BD. Findings from this study suggest that patients with BD and comorbid thyroid disorders when adequately treated have a response to lithium similar to patients with BD and no thyroid disorders. Full article

Brain-computer interface (BCI) can be used as a real-time bidirectional information gateway between the brain and machines. In particular, rapid progress in invasive BCI, propelled by recent developments in electrode materials, miniature and power-efficient electronics, and neural signal decoding technologies has attracted wide attention. In this review, we first introduce the concepts of neuronal signal decoding and encoding that are fundamental for information exchanges in BCI. Then, we review the history and recent advances in invasive BCI, particularly through studies using neural signals for controlling external devices on one hand, and modulating brain activity on the other hand. Specifically, regarding modulating brain activity, we focus on two types of techniques, applying electrical stimulation to cortical and deep brain tissues, respectively. Finally, we discuss the related ethical issues concerning the clinical application of this emerging technology. Full article

Resting state networks comprise several brain regions that exhibit complex patterns of interaction. Switching from eyes closed (EC) to eyes open (EO) during the resting state modifies these patterns of connectivity, but precisely how these change remains unclear. Here we use functional magnetic resonance imaging to scan healthy participants in two resting conditions (viz., EC and EO). Seven resting state networks were chosen for this study: salience network (SN), default mode network (DMN), central executive network (CEN), dorsal attention network (DAN), visual network (VN), motor network (MN) and auditory network (AN). We performed functional connectivity (FC) analysis for each network, comparing the FC maps for both EC and EO. Our results show increased connectivity between most networks during EC relative to EO, thereby suggesting enhanced integration during EC and greater modularity or specialization during EO. Among these networks, SN is distinctive: during the transition from EO to EC it evinces increased connectivity with DMN and decreased connectivity with VN. This change might imply that SN functions in a manner analogous to a circuit switch, modulating resting state relations with DMN and VN, when transitioning between EO and EC. Full article

Nonspeech (or paraspeech) parameters are widely used in clinical assessment of speech impairment in persons with dysarthria (PWD). Virtually every standard clinical instrument used in dysarthria diagnostics includes nonspeech parameters, often in considerable numbers. While theoretical considerations have challenged the validity of these measures as markers of speech impairment, only a few studies have directly examined their relationship to speech parameters on a broader scale. This study was designed to investigate how nonspeech parameters commonly used in clinical dysarthria assessment relate to speech characteristics of dysarthria in individuals with movement disorders. Maximum syllable repetition rates, accuracies, and rates of isolated and repetitive nonspeech oral–facial movements and maximum phonation times were compared with auditory–perceptual and acoustic speech parameters. Overall, 23 diagnostic parameters were assessed in a sample of 130 patients with movement disorders of six etiologies. Each variable was standardized for its distribution and for age and sex effects in 130 neurotypical speakers. Exploratory Graph Analysis (EGA) and Confirmatory Factor Analysis (CFA) were used to examine the factor structure underlying the diagnostic parameters. In the first analysis, we tested the hypothesis that nonspeech parameters combine with speech parameters within diagnostic dimensions representing domain–general motor control principles. In a second analysis, we tested the more specific hypotheses that diagnostic parameters split along effector (lip vs. tongue) or functional (speed vs. accuracy) rather than task boundaries. Our findings contradict the view that nonspeech parameters currently used in dysarthria diagnostics are congruent with diagnostic measures of speech characteristics in PWD. Full article

Background: Balance impairment is a common disability in post-stroke survivors, leading to reduced mobility and increased fall risk. Robotic gait training (RAGT) is largely used, along with traditional training. There is, however, no strong evidence about RAGT superiority, especially on balance. This study aims to determine RAGT efficacy on balance of post-stroke survivors. Methods: PubMed, Cochrane Library, and PeDRO databases were investigated. Randomized clinical trials evaluating RAGT efficacy on post-stroke survivor balance with Berg Balance Scale (BBS) or Timed Up and Go test (TUG) were searched. Meta-regression analyses were performed, considering weekly sessions, single-session duration, and robotic device used. Results: A total of 18 trials have been included. BBS pre-post treatment mean difference is higher in RAGT-treated patients, with a pMD of 2.17 (95% CI 0.79; 3.55). TUG pre-post mean difference is in favor of RAGT, but not statistically, with a pMD of −0.62 (95%CI − 3.66; 2.43). Meta-regression analyses showed no relevant association, except for TUG and treatment duration (β = −1.019, 95% CI − 1.827; −0.210, p-value = 0.0135). Conclusions: RAGT efficacy is equal to traditional therapy, while the combination of the two seems to lead to better outcomes than each individually performed. Robot-assisted balance training should be the focus of experimentation in the following years, given the great results in the first available trials. Given the massive heterogeneity of included patients, trials with more strict inclusion criteria (especially time from stroke) must be performed to finally define if and when RAGT is superior to traditional therapy. Full article

Background: The society is aging in China, and the cognitive level of elderly post-stroke patients gradually declines. Face-to-face cognitive functional training is no longer sufficient. Immersive virtual reality (IVR) is a promising rehabilitation training device. In this study, we developed an IVR-based puzzle game to explore its effectiveness, feasibility, and safety in elderly stroke patients with cognitive dysfunction. Methods: A total of 30 patients with mild post-stroke cognitive impairment after stroke were randomly assigned to a control or IVR group. Patients in both groups received routine rehabilitation therapy. Patients in the control group received traditional cognitive training, and those in the IVR group received IVR-based puzzle game therapy. Before and after treatment, Montreal cognitive assessment (MOCA), trail-making test-A (TMT-A), digit symbol substitution test (DSST), digital span test (DST), verbal fluency test (VFT), and modified Barthel index (MBI) were evaluated in both groups. In addition, the IVR group was administered a self-report questionnaire to obtain feedback on user experience. Results: There was no significant difference in the baseline data between the two groups. After six weeks of treatment, the cognitive assessment scores were improved in both groups. Moreover, the IVR group showed more improvements than the control group in the DSST (Z = 2.203, p = 0.028 < 0.05, η² = 0.16); MOCA (T = 1.186, p = 0.246 > 0.05, d = 0.44), TMT-A (T = 1.791, p = 0.084 > 0.05, d = 0.65), MBI (T = 0.783, p = 0.44 > 0.05, d = 0.28), FDST (Z = 0.78, p = 0.435 > 0.05, η² = 0.02), BDST (Z = 0.347, p = 0.728 > 0.05, η² = 0.004), and VFT(Z = 1.087, p = 0.277 > 0.05, η² = 0.039) did not significantly improve. The significant difference in DSST represents an improvement in executive function and visual–spatial cognitive characteristics. The other assessment scores did not show such features. Therefore, we did not observe significant differences through this measure. According to the results of the self-report questionnaire, most of the patients were satisfied with the equipment stability and training content. Several individuals reported mild adverse reactions. Conclusions: This pilot study suggests that IVR-based puzzle games are a promising approach to improve post-stroke cognitive function, especially executive cognitive function, and visual–spatial attention in older adults. Full article

There is currently no simple, widely available screening method for Alzheimer’s disease (AD), partly because the diagnosis of AD is complex and typically involves expensive and sometimes invasive tests not commonly available outside highly specialized clinical settings. Here, we developed an artificial intelligence (AI)-powered end-to-end system to detect AD and predict its severity directly from voice recordings. At the core of our system is the pre-trained data2vec model, the first high-performance self-supervised algorithm that works for speech, vision, and text. Our model was internally evaluated on the ADReSSo (Alzheimer’s Dementia Recognition through Spontaneous Speech only) dataset containing voice recordings of subjects describing the Cookie Theft picture, and externally validated on a test dataset from DementiaBank. The AI model can detect AD with average area under the curve (AUC) of 0.846 and 0.835 on held-out and external test set, respectively. The model was well-calibrated (Hosmer-Lemeshow goodness-of-fit p-value = 0.9616). Moreover, the model can reliably predict the subject’s cognitive testing score solely based on raw voice recordings. Our study demonstrates the feasibility of using the AI-powered end-to-end model for early AD diagnosis and severity prediction directly based on voice, showing its potential for screening Alzheimer’s disease in a community setting. Full article

It is hypothesized that factors associated with bipolar disorder could, uer defined conditions, produce adaptive behaviors. The aim is to verify whether a genetic feature associated with bipolar disorder can be found in people without bipolar disorder but with hyperactivity/exploration traits. Healthy old adults (N = 40) recruited for a previous study on exercise were subdivided using a previously validated tool into those with and without hyperactivity/exploration traits and compared with a group of old patients with bipolar disorder (N = 21). The genetic variant RS1006737 of CACNA1C was analyzed using blood samples, DNA extraction, real-time PCR, FRET probes, and SANGER method sequencing. People with hyperactivity/exploration traits and without bipolar disorder were like people with bipolar disorder regarding the frequency of the genetic variant (OR = 0.79, CI95%: 0.21–2.95), but were different from people without either hyperactivity/exploration traits and bipolar disorder (OR = 4.75, CI95%: 1.19–18.91). The combined group of people with hyperactivity/exploration traits without bipolar disorder plus people with bipolar disorder had a higher frequency of the variant than people without either hyperactivity/exploration traits or bipolar disorder (OR = 4.25, CI95%: 1.24–14.4). To consider the genetic profile of bipolar disorder not an aberrant condition opens the way to a new approach in which the adaptive potential would be a central point in psychosocial treatment in addition to drug therapy. Future research can confirm the results of our study. Full article

Motor and cognitive rehabilitation in individuals with traumatic brain injury (TBI) is a growing field of clinical and research interest. In fact, novel rehabilitative approaches allow a very early verticalization and gait training through robotic devices and other innovative tools boosting neuroplasticity, thanks to the high-intensity, repetitive and task-oriented training. In the same way, cognitive rehabilitation is also evolving towards advanced interventions using virtual reality (VR), computer-based approaches, telerehabilitation and neuromodulation devices. This review aimed to systematically investigate the existing evidence concerning the role of innovative technologies in the motor and cognitive neurorehabilitation of TBI patients. We searched and reviewed the studies published in the Cochrane Library, PEDro, PubMed and Scopus between January 2012 and September 2022. After an accurate screening, only 29 papers were included in this review. This systematic review has demonstrated the beneficial role of innovative technologies when applied to cognitive rehabilitation in patients with TBI, while evidence of their effect on motor rehabilitation in this patient population is poor and still controversial. Full article

This article provides an overview of verbal lie detection research. This type of research began in the 1970s with examining the relationship between deception and specific words. We briefly review this initial research. In the late 1980s, Criteria-Based Content Analysis (CBCA) emerged, a veracity assessment tool containing a list of verbal criteria. This was followed by Reality Monitoring (RM) and Scientific Content Analysis (SCAN), two other veracity assessment tools that contain lists of verbal criteria. We discuss their contents, theoretical rationales, and ability to identify truths and lies. We also discuss similarities and differences between CBCA, RM, and SCAN. In the mid 2000s, ‘Interviewing to deception’ emerged, with the goal of developing specific interview protocols aimed at enhancing or eliciting verbal veracity cues. We outline the four most widely researched interview protocols to date: the Strategic Use of Evidence (SUE), Verifiability Approach (VA), Cognitive Credibility Assessment (CCA), and Reality Interviewing (RI). We briefly discuss the working of these protocols, their theoretical rationales and empirical support, as well as the similarities and differences between them. We conclude this article with elaborating on how neuroscientists can inform and improve verbal lie detection. Full article

Calcitonin gene-related peptide (CGRP) antagonists are a class of medications that act as antagonists of the CGRP receptor or ligand. They can be divided into monoclonal antibodies and non-peptide small molecules, also known as gepants. CGRP antagonists were the first oral agents specifically designed to prevent migraines. The second generation of gepants includes rimegepant (BHV-3000, BMS-927711), ubrogepant (MK-1602), and atogepant (AGN-241689, MK-8031). Zavegepant (BHV-3500, BMS-742413) belongs to the third generation of gepants characterized by different administration routes. The chemical and pharmacological properties of this new generation of gepants were calculated. The clinical trials showed that the new generation of CGRP antagonists is effective for the acute and/or preventive treatment of migraines. No increased mortality risks were observed to be associated with the second- and third-generation gepants. Moreover, the majority of the serious adverse events reported probably occurred unrelated to the medications. Interesting facts about gepants were highlighted, such as potency, hepatotoxicity, concomitant use with monoclonal antibodies targeting the CGRP, comparative analysis with triptans, and the “acute and preventive” treatment of migraine. Further studies should include an elderly population and compare the medications inside this class and with triptans. There are still concerns regarding the long-term side effects of these medications, such as chronic vascular hemodynamic impairment. Meanwhile, careful pharmacovigilance and safety monitoring should be performed in the clinical practice use of gepants. Full article

In the post-COVID-19 era, significant changes have taken place regarding the epidemic, the economy, family and social life. However, it remains unclear how these changes encompass the psychological symptoms of college students. We carried out a cross-sectional study to investigate anxiety, depression, and post-traumatic stress disorder (PTSD) symptoms among college students from 10 November 2020, to 16 November 2020. The questionnaire included a self-designed canvas, Generalized Anxiety Disorder 7 (GAD-7), Patient Health Questionnaire 9 (PHQ-9), and Impact of Event Scale (IES-R). Factors associated with psychological symptoms were estimated by ordered and non-conditional logistic regression analysis. Of 4754 participants, 25.0%, 29.7%, 3.4%, 15.3%, 17.1%, and 2.9% reported anxiety, depression, PTSD symptoms, one, any two, and all three, respectively. In cases with anxiety or depression symptoms, there was a 9.11% comorbidity with PTSD. Factors associated with fears of being infected, social, family, and economic changes increased the risk of psychological symptoms in college students caused by COVID-19. Female college students, identified with anxiety or depression symptoms, were at a lower risk of developing PTSD symptoms (OR, 0.61, 95% CI: 0.43–0.86). Non-medical majors at university, rural residence, higher educational background, fear of taking public transport, and deterioration of family relationships increased the risk for PTSD symptoms among male respondents with anxiety or depression symptoms due to COVID-19. Factors correlated with psychological symptoms had expanded from the fear of being infected to extensive social, family, and economic changes caused by COVID-19. Therefore, screening and interventions for psychological symptoms should be consistently strengthened and more targeted to college students in the post-COVID-19 era. Full article

Resting-state electroencephalography (EEG) microstates reflect sub-second, quasi-stable states of brain activity. Several studies have reported alterations of microstate features in patients with schizophrenia (SZ). Based on these findings, it has been suggested that microstates may represent neurophysiological biomarkers for the classification of SZ. To explore this possibility, machine learning approaches can be employed. Bayesian optimization is a machine learning approach that selects the best-fitted machine learning model with tuned hyperparameters from existing models to improve the classification. In this proof-of-concept preliminary study based on secondary analysis, 20 microstate features were extracted from 14 SZ patients and 14 healthy controls’ EEG signals. These parameters were then ranked as predictors based on their importance, and an optimized machine learning approach was applied to evaluate the performance of the classification. SZ patients had altered microstate features compared to healthy controls. Furthermore, Bayesian optimization outperformed conventional multivariate analyses and showed the highest accuracy (90.93%), AUC (0.90), sensitivity (91.37%), and specificity (90.48%), with reliable results using just six microstate predictors. Altogether, in this proof-of-concept study, we showed that machine learning with Bayesian optimization can be utilized to characterize EEG microstate alterations and contribute to the classification of SZ patients. Full article