Editor’s Choice Articles

Structural magnetic resonance imaging (sMRI) studies have shown abnormalities in the brain structure of ASD patients, but the relationship between structural changes and social communication problems is still unclear. This study aims to explore the structural mechanisms of clinical dysfunction in the brain of ASD children through voxel-based morphometry (VBM). After screening T1 structural images from the Autism Brain Imaging Data Exchange (ABIDE) database, 98 children aged 8–12 years old with ASD were matched with 105 children aged 8–12 years old with typical development (TD). Firstly, this study compared the differences in gray matter volume (GMV) between the two groups. Then, this study evaluated the relationship between GMV and the subtotal score of communications and social interaction on the Autism Diagnostic Observation Schedule (ADOS) in ASD children. Research has found that abnormal brain structures in ASD include the midbrain, pontine, bilateral hippocampus, left parahippocampal gyrus, left superior temporal gyrus, left temporal pole, left middle temporal gyrus and left superior occipital gyrus. In addition, in ASD children, the subtotal score of communications and social interaction on the ADOS were only significantly positively correlated with GMV in the left hippocampus, left superior temporal gyrus and left middle temporal gyrus. In summary, the gray matter structure of ASD children is abnormal, and different clinical dysfunction in ASD children is related to structural abnormalities in specific regions. Full article

The rostral ventromedial medulla (RVM) is a brainstem structure critical for the descending pain modulation system involved in both pain facilitation and inhibition through its projection to the spinal cord. Since the RVM is well connected with pain- and stress-engaged brain structures, such as the anterior cingulate cortex, nucleus accumbens, and amygdala, its involvement in stress responses has become a matter of great interest. While chronic stress has been proposed as a trigger of pain chronification and related psychiatric comorbidities due to maladaptive stress responses, acute stress triggers analgesia and other adaptative responses. Here we reviewed and highlighted the critical role of the RVM in stress responses, mainly in acute stress-induced analgesia (SIA) and chronic stress-induced hyperalgesia (SIH), providing insights into pain chronification processes and comorbidity between chronic pain and psychiatric disorders. Full article

Tactile attention tasks are used in the diagnosis and treatment of neurological and sensory processing disorders, while somatosensory event-related potentials (ERP) measured by electroencephalography (EEG) are used as neural correlates of attention processes. Brain-computer interface (BCI) technology provides an opportunity for the training of mental task execution via providing online feedback based on ERP measures. Our recent work introduced a novel electrotactile BCI for sensory training, based on somatosensory ERP; however, no previous studies have addressed specific somatosensory ERP morphological features as measures of sustained endogenous spatial tactile attention in the context of BCI control. Here we show the morphology of somatosensory ERP responses induced by a novel task introduced within our electrotactile BCI platform i.e., the sustained endogenous spatial electrotactile attention task. By applying pulsed electrical stimuli to the two proximal stimulation hotspots at the user’s forearm, stimulating sequentially the mixed branches of radial and median nerves with equal probability of stimuli occurrence, we successfully recorded somatosensory ERPs for both stimulation locations, in the attended and unattended conditions. Waveforms of somatosensory ERP responses for both mixed nerve branches showed similar morphology in line with previous reports on somatosensory ERP components obtained by stimulation of exclusively sensory nerves. Moreover, we found statistically significant increases in ERP amplitude on several components, at both stimulation hotspots, while sustained endogenous spatial electrotactile attention task is performed. Our results revealed the existence of general ERP windows of interest and signal features that can be used to detect sustained endogenous tactile attention and classify between spatial attention locations in 11 healthy subjects. The current results show that features of N140, P3a and P3b somatosensory ERP components are the most prominent global markers of sustained spatial electrotactile attention, over all subjects, within our novel electrotactile BCI task/paradigm, and this work proposes the features of those components as markers of sustained endogenous spatial tactile attention in online BCI control. Immediate implications of this work are the possible improvement of online BCI control within our novel electrotactile BCI system, while these finding can be used for other tactile BCI applications in the diagnosis and treatment of neurological disorders by employing mixed nerve somatosensory ERPs and sustained endogenous electrotactile attention task as control paradigms. Full article

Mu rhythm, also known as the mu wave, occurs on sensorimotor cortex activity at rest, and the frequency range is defined as 8–13Hz, the same frequency as the alpha band. Mu rhythm is a cortical oscillation that can be recorded from the scalp over the primary sensorimotor cortex by electroencephalogram (EEG) and magnetoencephalography (MEG). The subjects of previous mu/beta rhythm studies ranged widely from infants to young and older adults. Furthermore, these subjects were not only healthy people but also patients with various neurological and psychiatric diseases. However, very few studies have referred to the effect of mu/beta rhythm with aging, and there was no literature review about this theme. It is important to review the details of the characteristics of mu/beta rhythm activity in older adults compared with young adults, focusing on age-related mu rhythm changes. By comprehensive review, we found that, compared with young adults, older adults showed mu/beta activity change in four characteristics during voluntary movement, increased event-related desynchronization (ERD), earlier beginning and later end, symmetric pattern of ERD and increased recruitment of cortical areas, and substantially reduced beta event-related desynchronization (ERS). It was also found that mu/beta rhythm patterns of action observation were changing with aging. Future work is needed in order to investigate not only the localization but also the network of mu/beta rhythm in older adults. Full article

The topic of this narrative review is mood stabilizers. First, the author’s definition of mood-stabilizing drugs is provided. Second, mood-stabilizing drugs meeting this definition that have been employed until now are described. They can be classified into two generations based on the chronology of their introduction into the psychiatric armamentarium. First-generation mood stabilizers (FGMSs), such as lithium, valproates, and carbamazepine, were introduced in the 1960s and 1970s. Second-generation mood stabilizers (SGMSs) started in 1995, with a discovery of the mood-stabilizing properties of clozapine. The SGMSs include atypical antipsychotics, such as clozapine, olanzapine, quetiapine, aripiprazole, and risperidone, as well as a new anticonvulsant drug, lamotrigine. Recently, as a candidate for SGMSs, a novel antipsychotic, lurasidone, has been suggested. Several other atypical antipsychotics, anticonvulsants, and memantine showed some usefulness in the treatment and prophylaxis of bipolar disorder; however, they do not fully meet the author’s criteria for mood stabilizers. The article presents clinical experiences with mood stabilizers of the first and second generations and with “insufficient” ones. Further, current suggestions for their use in preventing recurrences of bipolar mood disorder are provided. Full article

Agomelatine (AGM) is one of the latest atypical antidepressants, prescribed exclusively for the treatment of depression in adults. AGM belongs to the pharmaceutical class of melatonin agonist and selective serotonin antagonist (“MASS”), as it acts both as a selective agonist of melatonin receptors MT1 and MT2, and as a selective antagonist of 5-HT2C/5-HT2B receptors. AGM is involved in the resynchronization of interrupted circadian rhythms, with beneficial effects on sleep patterns, while antagonism on serotonin receptors increases the availability of norepinephrine and dopamine in the prefrontal cortex, with an antidepressant and nootropic effect. The use of AGM in the pediatric population is limited by the scarcity of data. In addition, few studies and case reports have been published on the use of AGM in patients with attention deficit and hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Considering this evidence, the purpose of this review is to report the potential role of AGM in neurological developmental disorders. AGM would increase the expression of the cytoskeleton-associated protein (ARC) in the prefrontal cortex, with optimization of learning, long-term memory consolidation, and improved survival of neurons. Another important feature of AGM is the ability to modulate glutamatergic neurotransmission in regions associated with mood and cognition. With its synergistic activity a melatoninergic agonist and an antagonist of 5-HT2C, AGM acts as an antidepressant, psychostimulant, and promoter of neuronal plasticity, regulating cognitive symptoms, resynchronizing circadian rhythms in patients with autism, ADHD, anxiety, and depression. Given its good tolerability and good compliance, it could potentially be administered to adolescents and children. Full article

Organophosphate (OP) and carbamate pesticides are toxic to pests through targeted inhibition of acetylcholinesterase (AChE). However, OPs and carbamates may be harmful to non-target species including humans and could induce developmental neurotoxicity if differentiated or differentiating neurons are particularly vulnerable to neurotoxicant exposures. Hence, this study compared the neurotoxicity of OPs, chlorpyrifos-oxon (CPO), and azamethiphos (AZO) and the carbamate pesticide, aldicarb, to undifferentiated versus differentiated SH-SY5Y neuroblastoma cells. OP and carbamate concentration-response curves for cell viability were undertaken using 3-(4,5 dimethylthiazol-2-yl)-2,5-diphenyl-tetrazolium bromide (MTT) and lactate dehydrogenase (LDH) assays and cellular bioenergetic capacity assessed via quantitation of cellular ATP levels. Concentration-response curves for inhibition of cellular AChE activity were also generated and the production of reactive oxygen species (ROS) was monitored using a 2′,7′-dichlorofluorescein diacetate (DCFDA) assay. The OPs and aldicarb reduced cell viability, cellular ATP levels, and neurite outgrowth in a concentration-dependent fashion, from a threshold concentration of ≥10 µM. Neurotoxic potency was in the order AZO > CPO > aldicarb for undifferentiated cells but CPO > AZO > aldicarb for differentiated cells and this toxic potency of CPO reflected its more extensive induction of reactive oxygen species (ROS) and generation of carbonylated proteins that were characterized by western blotting. Hence, the relative neurotoxicity of the OPs and aldicarb in part reflects non-cholinergic mechanisms that are likely to contribute to developmental neurotoxicity. Full article

Stroke is the fourth leading cause of mortality and is estimated to be one of the major reasons for long-lasting disability worldwide. There are limited studies that describe the application of physical therapy interventions to prevent disabilities in stroke survivors and promote recovery after a stroke. In this review, we have described a wide range of interventions based on impairments, activity limitations, and goals in recovery during different stages of a stroke. This article mainly focuses on stroke rehabilitation tactics, including those for sensory function impairments, motor learning programs, hemianopia and unilateral neglect, flexibility and joint integrity, strength training, hypertonicity, postural control, and gait training. We conclude that, aside from medicine, stroke rehabilitation must address specific functional limitations to allow for group activities and superior use of a hemiparetic extremity. Medical doctors are often surprised by the variety of physiotherapeutic techniques available; they are unfamiliar with the approaches of researchers such as Bobath, Coulter, and Brunnstrom, among others, as well as the scientific reasoning behind these techniques. Full article

The mechanism behind the onset of depression has been the focus of current research in the neuroscience field. Silent information regulator 1 (SIRT1) is a key player in regulating energy metabolism, and it can regulate depression by mediating the inflammatory response (e.g., nuclear factor-kappa B (NF-κB), tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β)), gene expression in the nucleus accumben (NAc) and CA1 region of the hippocampus (e.g., nescient helix-loop-helix2 (NHLH2), monoamine oxidase (MAO-A), and 5-Hydroxyindole-3-acetic acid (5-HIAA)), and neuronal regeneration in the CA3 region of the hippocampus. Exercise is an important means to improve energy metabolism and depression, but it remains to be established how SIRT1 acts during exercise and improves depression. By induction and analysis, SIRT1 can be activated by exercise and then improve the function of the hypothalamic–pituitary–adrenal (HPA) axis by upregulating brain-derived neurotrophic factors (BDNF), inhibit the inflammatory response (suppression of the NF-κB and TNF-α/indoleamine 2,3-dioxygenase (IDO)/5-Hydroxytryptamine (5-HT) pathways), and promote neurogenesis (activation of the insulin-like growth factor1 (IGF-1) and growth-associated protein-43 (GAP-43) pathways, etc.), thereby improving depression. The present review gives a summary and an outlook based on this finding and makes an analysis, which will provide a new rationale and insight for the mechanism by which exercise improves depression. Full article

Recent studies have proposed valid precision models and valid Research and Diagnostic Algorithmic Rules (RADAR) for recurrent major depressive disorder (MDD). The aim of the current study was to construct precision models and RADAR scores in patients experiencing first-episode MDD and to examine whether adverse childhood experiences (ACE) and negative life events (NLE) are associated with suicidal behaviors (SB), cognitive impairment, and phenome RADAR scores. This study recruited 90 patients with major depressive disorder (MDD) in an acute phase, of whom 71 showed a first-episode MDD (FEM), and 40 controls. We constructed RADAR scores for ACE; NLE encountered in the last year; SB; and severity of depression, anxiety, chronic fatigue, and physiosomatic symptoms using the Hamilton Depression and Anxiety Rating Scales and the FibroFatigue scale. The partial least squares analysis showed that in FEM, one latent vector (labeled the phenome of FEM) could be extracted from depressive, anxiety, fatigue, physiosomatic, melancholia, and insomnia symptoms, SB, and cognitive impairments. The latter were conceptualized as a latent vector extracted from the Verbal Fluency Test, the Mini-Mental State Examination, and ratings of memory and judgement, indicating a generalized cognitive decline (G-CoDe). We found that 60.8% of the variance in the FEM phenome was explained by the cumulative effects of NLE and ACE, in particular emotional neglect and, to a lesser extent, physical abuse. In conclusion, the RADAR scores and plots constructed here should be used in research and clinical settings, rather than the binary diagnosis of MDD based on the DSM-5 or ICD. Full article

Traumatic brain injury (TBI) is a global health concern, that can leave lasting physical, cognitive, and/or behavioral changes for many who sustain this type of injury. Because of the heterogeneity of this population, development of appropriate intervention tools can be difficult. Social determinants of health (SDoH) are factors that may impact TBI incidence, recovery, and outcome. The purpose of this study is to describe and analyze the existing literature regarding the prevailing SDoH and health disparities (HDs) associated with TBI in adults. A scoping review, guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework was used to explore three electronic databases—PubMed, Medline, and CINAHL. Searches identified peer-reviewed empirical literature addressing aspects of SDoH and HDs related to TBI. A total of 123 records were identified and reduced to 27 studies based on inclusion criteria. Results revealed race/ethnicity was the most commonly reported SDoH impacting TBI, followed by an individual’s insurance status. Health disparities were noted to occur across the continuum of TBI, including TBI risk, acute hospitalization, rehabilitation, and recovery. The most frequently reported HD was that Whites are more likely to be discharged to inpatient rehabilitation compared to racial/ethnic minorities. Health disparities associated with TBI are most commonly associated with the race/ethnicity SDoH, though insurance status and socioeconomic status commonly influence health inequities as well. The additional need for evidence related to the impact of other, lesser researched, SDoH is discussed, as well as clinical implications that can be used to target intervention for at-risk groups using an individual’s known SDoH. Full article

Neuro-tourism is the application of neuroscience in tourism to improve marketing methods of the tourism industry by analyzing the brain activities of tourists. Neuro-tourism provides accurate real-time data on tourists’ conscious and unconscious emotions. Neuro-tourism uses the methods of neuromarketing such as brain–computer interface (BCI), eye-tracking, galvanic skin response, etc., to create tourism goods and services to improve tourist experience and satisfaction. Due to the novelty of neuro-tourism and the dearth of studies on this subject, this study offered a comprehensive analysis of the peer-reviewed journal publications in neuro-tourism research for the previous 12 years to detect trends in this field and provide insights for academics. We reviewed 52 articles indexed in the Web of Science (WoS) core collection database and examined them using our suggested classification schema. The results reveal a large growth in the number of published articles on neuro-tourism, demonstrating a rise in the relevance of this field. Additionally, the findings indicated a lack of integrating artificial intelligence techniques in neuro-tourism studies. We believe that the advancements in technology and research collaboration will facilitate exponential growth in this field. Full article

The Internet of Things (IoT) is a well-known technology that has a significant impact on many areas, including connections, work, healthcare, and the economy. IoT has the potential to improve life in a variety of contexts, from smart cities to classrooms, by automating tasks, increasing output, and decreasing anxiety. Cyberattacks and threats, on the other hand, have a significant impact on intelligent IoT applications. Many traditional techniques for protecting the IoT are now ineffective due to new dangers and vulnerabilities. To keep their security procedures, IoT systems of the future will need AI-efficient machine learning and deep learning. The capabilities of artificial intelligence, particularly machine and deep learning solutions, must be used if the next-generation IoT system is to have a continuously changing and up-to-date security system. IoT security intelligence is examined in this paper from every angle available. An innovative method for protecting IoT devices against a variety of cyberattacks is to use machine learning and deep learning to gain information from raw data. Finally, we discuss relevant research issues and potential next steps considering our findings. This article examines how machine learning and deep learning can be used to detect attack patterns in unstructured data and safeguard IoT devices. We discuss the challenges that researchers face, as well as potential future directions for this research area, considering these findings. Anyone with an interest in the IoT or cybersecurity can use this website’s content as a technical resource and reference. Full article

The recognition of emotions is one of the most challenging issues in human–computer interaction (HCI). EEG signals are widely adopted as a method for recognizing emotions because of their ease of acquisition, mobility, and convenience. Deep neural networks (DNN) have provided excellent results in emotion recognition studies. Most studies, however, use other methods to extract handcrafted features, such as Pearson correlation coefficient (PCC), Principal Component Analysis, Higuchi Fractal Dimension (HFD), etc., even though DNN is capable of generating meaningful features. Furthermore, most earlier studies largely ignored spatial information between the different channels, focusing mainly on time domain and frequency domain representations. This study utilizes a pre-trained 3D-CNN MobileNet model with transfer learning on the spatio-temporal representation of EEG signals to extract features for emotion recognition. In addition to fully connected layers, hybrid models were explored using other decision layers such as multilayer perceptron (MLP), k-nearest neighbor (KNN), extreme learning machine (ELM), XGBoost (XGB), random forest (RF), and support vector machine (SVM). Additionally, this study investigates the effects of post-processing or filtering output labels. Extensive experiments were conducted on the SJTU Emotion EEG Dataset (SEED) (three classes) and SEED-IV (four classes) datasets, and the results obtained were comparable to the state-of-the-art. Based on the conventional 3D-CNN with ELM classifier, SEED and SEED-IV datasets showed a maximum accuracy of 89.18% and 81.60%, respectively. Post-filtering improved the emotional classification performance in the hybrid 3D-CNN with ELM model for SEED and SEED-IV datasets to 90.85% and 83.71%, respectively. Accordingly, spatial-temporal features extracted from the EEG, along with ensemble classifiers, were found to be the most effective in recognizing emotions compared to state-of-the-art methods. Full article

Biofeedback training is a method commonly used in various fields of life, for example, in medicine, sports training or business. In recent studies, it has been shown that biofeedback, and neurofeedback, can affect the performance of professional athletes. Training based on the neurofeedback method includes exercising the brain waves. The aim of the article is to evaluate the influence of neurofeedback training on the physical fitness of professional athletes representing various sports disciplines, such as judo, volleyball and soccer. Based on 10 scientific papers from various sources, including PubMed, the latest research on neurofeedback and its impact on athletes has been reviewed. On the basis of the literature review from 2012 to 2022 on the neurofeedback method in sports training, it can be stated that this type of practice has a significant impact on physical fitness and sports performance. This review comprised 10 research studies with 491 participants in the neurofeedback groups, and 62 participants in the control group. Two reviewers independently extracted data and evaluated the quality of the studies utilising the PEDro scale. Properly planned and conducted neurofeedback training affects stimulation and improvement of many variables (reducing stress levels, increasing the ability to self-control physiological factors, enhancing behavioural efficiency and meliorating the speed of reaction to a stimulus). Full article

Objective: The purpose of this study was to investigate the cortical activity and digit classification performance during tactile imagery (TI) of a vibratory stimulus at the index, middle, and thumb digits within the left hand in healthy individuals. Furthermore, the cortical activities and classification performance of the compound TI were compared with similar compound motor imagery (MI) with the same digits as TI in the same subjects. Methods: Twelve healthy right-handed adults with no history of upper limb injury, musculoskeletal condition, or neurological disorder participated in the study. The study evaluated the event-related desynchronization (ERD) response and brain–computer interface (BCI) classification performance on discriminating between the digits in the left-hand during the imagery of vibrotactile stimuli to either the index, middle, or thumb finger pads for TI and while performing a motor activity with the same digits for MI. A supervised machine learning technique was applied to discriminate between the digits within the same given limb for both imagery conditions. Results: Both TI and MI exhibited similar patterns of ERD in the alpha and beta bands at the index, middle, and thumb digits within the left hand. While TI had significantly lower ERD for all three digits in both bands, the classification performance of TI-based BCI (77.74 ± 6.98%) was found to be similar to the MI-based BCI (78.36 ± 5.38%). Conclusions: The results of this study suggest that compound tactile imagery can be a viable alternative to MI for BCI classification. The study contributes to the growing body of evidence supporting the use of TI in BCI applications, and future research can build on this work to explore the potential of TI-based BCI for motor rehabilitation and the control of external devices. Full article

Neural inflammatory response is a crucial pathological change in intracerebral hemorrhage (ICH) which accelerates the formation of perihematomal edema and aggravates neural cell death. Although surgical and drug treatments for ICH have advanced rapidly in recent years, therapeutic strategies that target and control neuroinflammation are still limited. Exosomes are important carriers for information transfer among cells. They have also been regarded as a promising therapeutic tool in translational medicine, with low immunogenicity, high penetration through the blood-brain barrier, and ease of modification. In our previous research, we have found that exogenous administration of miRNA-124-overexpressed microglial exosomes (Exo-124) are effective in improving post-injury cognitive impairment. From this, we evaluated the potential therapeutic effects of miRNA-124-enriched microglial exosomes on the ICH mice in the present study. We found that the gene-edited exosomes could attenuate neuro-deficits and brain edema, improve blood–brain barrier integrity, and reduce neural cell death. Moreover, the protective effect of Exo-124 was abolished in mice depleted of Gr-1⁺ myeloid cells. It suggested that the exosomes exerted their functions by limiting the infiltration of leukocyte into the brain, thus controlling neuroinflammation following the onset of ICH. In conclusion, our findings provided a promising therapeutic strategy for improving neuroinflammation in ICH. It also opens a new avenue for intranasal delivery of exosome therapy using miRNA-edited microglial exosomes. Full article

Chronic neuroinflammation is associated with many neurodegenerative diseases, such as Alzheimer’s. Microglia are the brain’s primary immune cells, and when activated, they release various proinflammatory cytokines. Several natural compounds with anti-inflammatory and antioxidant properties, such as epigallocatechin 3-gallate (EGCG), may provide a promising strategy for inflammation-related neurodegenerative diseases involving activated microglia cells. The objective of the current study was to examine the molecular targets underlying the anti-inflammatory effects of EGCG in activated microglia cells. BV-2 microglia cells were grown, stimulated, and treated with EGCG. Cytotoxicity and nitric oxide (NO) production were evaluated. Immunoassay, PCR array, and WES™ Technology were utilized to evaluate inflammatory, neuroprotective modulators as well as signaling pathways involved in the mechanistic action of neuroinflammation. Our findings showed that EGCG significantly inhibited proinflammatory mediator NO production in LPS-stimulated BV-2 microglia cells. In addition, ELISA analysis revealed that EGCG significantly decreases the release of proinflammatory cytokine IL-6 while it increases the release of TNF-α. PCR array analysis showed that EGCG downregulated MIF, CCL-2, and CSF2. It also upregulated IL-3, IL-11, and TNFS10. Furthermore, the analysis of inflammatory signaling pathways showed that EGCG significantly downregulated mRNA expression of mTOR, NF-κB2, STAT1, Akt3, CCL5, and SMAD3 while significantly upregulating the expression of mRNA of Ins2, Pld2, A20/TNFAIP3, and GAB1. Additionally, EGCG reduced the relative protein expression of NF-κB2, mTOR, and Akt3. These findings suggest that EGCG may be used for its anti-inflammatory effects to prevent neurodegenerative diseases. Full article

Parkinson’s disease (PD) is the second most common neurodegenerative disease, with symptoms such as tremor, bradykinesia with rigidity, and depression appearing in the late stage of life. The key hallmark of PD is the loss or death of dopaminergic neurons in the region substantia nigra pars compacta. Neuroinflammation plays a key role in the etiology of PD, and the contribution of immunity-related events spurred the researchers to identify anti-inflammatory agents for the treatment of PD. Neuroinflammation-based biomarkers have been identified for diagnosing PD, and many cellular and animal models have been used to explain the underlying mechanism; however, the specific cause of neuroinflammation remains uncertain, and more research is underway. So far, microglia and astrocyte dysregulation has been reported in PD. Patients with PD develop neural toxicity, inflammation, and inclusion bodies due to activated microglia and a-synuclein–induced astrocyte conversion into A1 astrocytes. Major phenotypes of PD appear in the late stage of life, so there is a need to identify key early-stage biomarkers for proper management and diagnosis. Studies are under way to identify key neuroinflammation-based biomarkers for early detection of PD. This review uses a constructive analysis approach by studying and analyzing different research studies focused on the role of neuroinflammation in PD. The review summarizes microglia, astrocyte dysfunction, neuroinflammation, and key biomarkers in PD. An approach that incorporates multiple biomarkers could provide more reliable diagnosis of PD. Full article

Brain tumor classification is crucial for medical evaluation in computer-assisted diagnostics (CAD). However, manual diagnosis of brain tumors from magnetic resonance imaging (MRI) can be time-consuming and complex, leading to inaccurate detection and classification. This is mainly because brain tumor identification is a complex procedure that relies on different modules. The advancements in Deep Learning (DL) have assisted in the automated process of medical images and diagnostics for various medical conditions, which benefits the health sector. Convolutional Neural Network (CNN) is one of the most prominent DL methods for visual learning and image classification tasks. This study presents a novel CNN algorithm to classify the brain tumor types of glioma, meningioma, and pituitary. The algorithm was tested on benchmarked data and compared with the existing pre-trained VGG16, VGG19, ResNet50, MobileNetV2, and InceptionV3 algorithms reported in the literature. The experimental results have indicated a high classification accuracy of 98.04%, precision, recall, and f1-score success rate of 98%, respectively. The classification results proved that the most common kinds of brain tumors could be categorized with a high level of accuracy. The presented algorithm has good generalization capability and execution speed that can be helpful in the field of medicine to assist doctors in making prompt and accurate decisions associated with brain tumor diagnosis. Full article

Objective: Sufferers of tinnitus, especially of the prolonged type, frequently suffer from comorbid depression and anxiety. From the perspective of the network model, this comorbidity is thought to be an interacting system of these two symptoms. In our study, we conducted a network analysis of depression and anxiety comorbidity in tinnitus sufferers, aiming to identify the central and bridge symptoms and make informed suggestions for clinical interventions and psychotherapy. Method: A total of 566 tinnitus sufferers were enrolled in our study. The Patient Health Questionnaire-9 (PHQ-9) and the Generalized Anxiety Disorder 7-Item Questionnaire (GAD-7) were selected to evaluate depression and anxiety symptoms, respectively, followed by network analysis to construct the interacting networks. Results: The findings identified six edges of strongest regularized partial correlations in this network. Of these, three were depression symptoms and three were anxiety symptoms. The anxiety symptoms “Unable to control worry” and “Relaxation difficulty” and the depression symptom “Feeling depressed or hopeless” had the highest expected influence centrality. The analysis results also revealed three bridge symptoms: “Afraid something awful might happen”, “Feeling of worthlessness”, and “Trouble concentrating”. As for “Suicidal ideation”, the direct relations between this symptom and “Afraid something awful might happen” and “Feeling depressed or hopeless” were the strongest. Conclusions: The central and bridge symptoms of the interacting network of depression and anxiety symptoms in tinnitus sufferers can be considered a significant transdiagnostic intervention target for the management of this comorbidity. In particular, clinical prevention and psychotherapy should be implemented, targeting the symptoms that have the strongest associations with suicidal ideation. Full article

Sleep changes significantly throughout the human lifespan. Physiological modifications in sleep regulation, in common with many mammals (especially in the circadian rhythms), predispose adolescents to sleep loss until early adulthood. Adolescents are one-sixth of all human beings and are at high risk for mental diseases (particularly mood disorders) and self-injury. This has been attributed to the incredible number of changes occurring in a limited time window that encompasses rapid biological and psychosocial modifications, which predispose teens to at-risk behaviors. Adolescents’ sleep patterns have been investigated as a biunivocal cause for potential damaging conditions, in which insufficient sleep may be both a cause and a consequence of mental health problems. The recent COVID-19 pandemic in particular has made a detrimental contribution to many adolescents’ mental health and sleep quality. In this review, we aim to summarize the knowledge in the field and to explore implications for adolescents’ (and future adults’) mental and physical health, as well as to outline potential strategies of prevention. Full article

Overactive microglia and severe neuroinflammation play crucial roles in the development of major depressive disorder. Preconditioning with lipopolysaccharide (LPS) provides protection against severe neuroinflammation. However, administering high doses of LPS to mice triggers depressive symptoms. Therefore, the optimal dose of LPS preconditioning needs to be determined by further experiments. LPS preconditioning is an effective agent in anti-inflammation and neuroprotection, but the mechanism by which LPS preconditioning acts in depression remain unclear. This study finds that the anti-inflammation mechanism of low-dose LPS preconditioning is mainly dependent on G-protein-coupled receptor 84 (GPR84). We use low-dose LPS for preconditioning and re-challenged mice or BV2 microglia with high-dose LPS. In addition, RNA-seq is used to explore underlying changes with LPS preconditioning. Low-dose LPS preconditioning reduces the expression of pro-inflammatory mediators and inhibits microglial activation, as well as suppresses the depressive-like behavior when the mice are re-challenged with high-dose LPS. Further investigation reveals that the tolerance-like response in microglia is dependent on the GPR84. Here, we show that low-dose LPS preconditioning can exert anti-inflammation effects and alleviates inflammation-induced depressive-like behavior in mice. As a potential therapeutic target for depression, LPS preconditioning needs to be given further attention regarding its effectiveness and safety. Full article

Recognition of lying is a more complex cognitive process than truth-telling because of the presence of involuntary cognitive cues that are useful to lie recognition. Researchers have proposed different approaches in the literature to solve the problem of lie recognition from either handcrafted and/or automatic lie features during court trials and police interrogations. Unfortunately, due to the cognitive complexity and the lack of involuntary cues related to lying features, the performances of these approaches suffer and their generalization ability is limited. To improve performance, this study proposed state transition patterns based on hands, body motions, and eye blinking features from real-life court trial videos. Each video frame is represented according to a computed threshold value among neighboring pixels to extract spatial–temporal state transition patterns (STSTP) of the hand and face poses as involuntary cues using fully connected convolution neural network layers optimized with the weights of ResNet-152 learning. In addition, this study computed an eye aspect ratio model to obtain eye blinking features. These features were fused together as a single multi-modal STSTP feature model. The model was built using the enhanced calculated weight of bidirectional long short-term memory. The proposed approach was evaluated by comparing its performance with current state-of-the-art methods. It was found that the proposed approach improves the performance of detecting lies. Full article

Gliomas are primary malignant brain tumors. These tumors seem to be more and more frequent, not only because of a true increase in their incidence, but also due to the increase in life expectancy of the general population. Among gliomas, malignant gliomas and more specifically glioblastomas (GBM) are a challenge in their diagnosis and treatment. There are few effective therapies for these tumors, and patients with GBM fare poorly, even after aggressive surgery, chemotherapy, and radiation. Over the last decade, it is now appreciated that these tumors are composed of numerous distinct tumoral and non-tumoral cell populations, which could each influence the overall tumor biology and response to therapies. Monocytes have been proved to actively participate in tumor growth, giving rise to the support of tumor-associated macrophages (TAMs). In GBM, TAMs represent up to one half of the tumor mass cells, including both infiltrating macrophages and resident brain microglia. Infiltrating macrophages/monocytes constituted ~ 85% of the total TAM population, they have immune functions, and they can release a wide array of growth factors and cytokines in response to those factors produced by tumor and non-tumor cells from the tumor microenvironment (TME). A brief review of the literature shows that this cell population has been increasingly studied in GBM TME to understand its role in tumor progression and therapeutic resistance. Through the knowledge of its biology and protumoral function, the development of therapeutic strategies that employ their recruitment as well as the modulation of their immunological phenotype, and even the eradication of the cell population, can be harnessed for therapeutic benefit. This revision aims to summarize GBM TME and localization in tumor niches with special focus on TAM population, its origin and functions in tumor progression and resistance to conventional and experimental GBM treatments. Moreover, recent advances on the development of TAM cell targeting and new cellular therapeutic strategies based on monocyte/macrophages recruitment to eradicate GBM are discussed as complementary therapeutics. Full article

Medical treatment for trigeminal neuralgia (TN) is not always a feasible option due to a lack of full response or adverse effects. Open surgery or percutaneous procedures are advocated in these cases. Several articles have compared the results among different techniques. Nevertheless, the findings of these studies are heterogeneous. Umbrella reviews are studies sitting at the peak of the evidence pyramid. With this umbrella review, we provided a systematic review of the outcomes of the surgical procedures used for TN treatment. Only systematic reviews and meta-analyses were included following the PRISMA guidelines. Ten articles were enrolled for qualitative and quantitative assessment. Level of evidence was quantified using a specific tool (AMSTAR-2). Results were heterogenous in terms of outcome and measurements. Microvascular decompression (MVD) appeared to be the most effective procedure both in the short-term (pain relief in 85–96.6% of cases) and long-term follow-up (pain relief in 64–79% of cases), although showed the highest rate of complications. The results of percutaneous techniques were similar but radiosurgery showed the highest variation in term of pain relief and a higher rate of delayed responses. The use of the AMSTAR-2 tool to quantify the evidence level scored three studies as critically low and seven studies as low-level, revealing a lack of good quality studies on this topic. Our umbrella review evidenced the need of well-designed comparative studies and the utilization of validated scales in order to provide more homogenous data for pooled-analyses and meta-analyses in the field of TN surgical treatment. Full article

As there is no curative treatment for dementia, including Alzheimer’s disease (AD), it is important to establish an optimal nonpharmaceutical preventive intervention. Physical inactivity is a representative modifiable risk factor for dementia, especially for AD in later life (>65 years). As physical activity and exercise are inexpensive and easy to initiate, they may represent an effective nonpharmaceutical intervention for the maintenance of cognitive function. Several studies have reported that physical activity and exercise interventions are effective in preventing cognitive decline and dementia. This review outlines the effects of physical activity and exercise-associated interventions in older adults with and without cognitive impairment and subsequently summarizes their possible mechanisms. Furthermore, this review describes the differences between two types of physical exercise—open-skill exercise (OSE) and closed-skill exercise (CSE)—in terms of their effects on cognitive function. Aerobic physical activity and exercise interventions are particularly useful in preventing cognitive decline and dementia, with OSE exerting a stronger protective effect on cognitive functions than CSE. Therefore, the need to actively promote physical activity and exercise interventions worldwide is emphasized. Full article

Craniopharyngiomas are commonly classified as low-grade tumors, although they may harbor a malignant behavior due to their high rate of recurrence and long-term morbidity. Craniopharyngiomas are classically distinguished into two histological types (adamantinomatous and papillary), which have been recently considered by the WHO classification of CNS tumors as two independent entities, due to different epidemiological, radiological, histopathological, and genetic patterns. With regard to papillary craniopharyngioma, a BRAF V600 mutation is detected in 95% of cases. This genetic feature is opening new frontiers in the treatment of these tumors using an adjuvant or, in selected cases, a neo-adjuvant approach. In this article, we present an overview of the more recent literature, focusing on the specificities and the role of oncological treatment in the management of papillary craniopharyngiomas. Based on our research and experience, we strongly suggest a multimodal approach combining clinical, endocrinological, radiological, histological, and oncological findings in both preoperative workup and postoperative follow up to define a roadmap integrating every aspect of this challenging condition. Full article

The involvement of iron in the pathogenesis of Alzheimer’s disease (AD) may be multifaceted. Besides potentially inducing oxidative damage, the bioavailability of iron may be limited within the central nervous system, creating a functionally iron-deficient state. By comparing staining results from baseline and modified iron histochemical protocols, iron was found to be more tightly bound within cortical sections from patients with high levels of AD pathology compared to subjects with a diagnosis of something other than AD. To begin examining whether the bound iron could cause a functional iron deficiency, a protein-coding gene expression dataset of initial, middle, and advanced stages of AD from olfactory bulb tissue was analyzed for iron-related processes with an emphasis on anemia-related changes in initial AD to capture early pathogenic events. Indeed, anemia-related processes had statistically significant alterations, and the significance of these changes exceeded those for AD-related processes. Other changes in patients with initial AD included the expressions of transcripts with iron-responsive elements and for genes encoding proteins for iron transport and mitochondrial-related processes. In the latter category, there was a decreased expression for the gene encoding pitrilysin metallopeptidase 1 (PITRM1). Other studies have shown that PITRM1 has an altered activity in patients with AD and is associated with pathological changes in this disease. Analysis of a gene expression dataset from PITRM1-deficient or sufficient organoids also revealed statistically significant changes in anemia-like processes. These findings, together with supporting evidence from the literature, raise the possibility that a pathogenic mechanism of AD could be a functional deficiency of iron contributing to neurodegeneration. Full article

TBI (traumatic brain injury) is one of the most common causes of deaths and failure to return to society according to the latest statistics. Cerebrolysin is a drug approved for use in patients diagnosed with TBI. It is a mixture of neuropeptides derived from purified porcine brain proteins and multiple experimental studies have proven its neuroprotective and neurorestorative properties both in vitro and in vivo. In our meta-analysis, we analyze the latest clinical study reports on the use of Cerebrolysin in patients with TBI. The authors searched the databases: Pub Med, Cinahl, Web Of Science, and Embase from database inception until 11th July 2022. Ten clinical studies were eligible and included in the final analysis, including both retrospective and prospective studies of 8749 patients. Treatment with Cerebrolysin was associated with a statistically significant change in GCS and GOS. Mortality of any cause and the length of stay was not affected by the treatment. Our findings support and confirm the beneficial effects of Cerebrolysin treatment on the clinical outcome of patients after TBI. Further multi-center studies to optimize dosing and time of administration should be conducted. Full article

Advancements in modern medicine have improved the quality of life across the globe and increased the average lifespan of our population by multiple decades. Current estimates predict by 2030, 12% of the global population will reach a geriatric age and live another 3–4 decades. This swelling geriatric population will place critical stress on healthcare infrastructures due to accompanying increases in age-related diseases and comorbidities. While much research focused on long-lived individuals seeks to answer questions regarding how to age healthier, there is a deficit in research investigating what aspects of our lives accelerate or exacerbate aging. In particular, heavy metals are recognized as a significant threat to human health with links to a plethora of age-related diseases, and have widespread human exposures from occupational, medical, or environmental settings. We believe heavy metals ought to be classified as a class of gerontogens (i.e., chemicals that accelerate biological aging in cells and tissues). Gerontogens may be best studied through their effects on the “Hallmarks of Aging”, nine physiological hallmarks demonstrated to occur in aged cells, tissues, and bodies. Evidence suggests that cellular senescence—a permanent growth arrest in cells—is one of the most pertinent hallmarks of aging and is a useful indicator of aging in tissues. Here, we discuss the roles of heavy metals in brain aging. We briefly discuss brain aging in general, then expand upon observations for heavy metals contributing to age-related neurodegenerative disorders. We particularly emphasize the roles and observations of cellular senescence in neurodegenerative diseases. Finally, we discuss the observations for heavy metals inducing cellular senescence. The glaring lack of knowledge about gerontogens and gerontogenic mechanisms necessitates greater research in the field, especially in the context of the global aging crisis. Full article

Suicide, a global health burden, represents the 17th leading cause of death worldwide (1.3%), but the 4th among young people aged between 15 and 29 years of age, according to World Health Organization (WHO), 2019. Suicidal behaviour is a complex, multi-factorial, polygenic and independent mental health problem caused by a combination of alterations and dysfunctions of several biological pathways and disruption of normal mechanisms in brain regions that remain poorly understood and need further investigation to be deciphered. Suicide complexity and unpredictability gained international interest as a field of research. Several studies have been conducted at the neuropathological, inflammatory, genetic, and molecular levels to uncover the triggers behind suicidal behaviour and develop convenient and effective therapeutic or at least preventive procedures. This review aims to summarise and focus on current knowledge of diverse biological pathways involved in the neurobiology of suicidal behaviour, and briefly highlights future potential therapeutic pathways to prevent or even treat this significant public health problem. Full article

Background. Finding the associations between schizophrenia symptoms and the biomarkers of inflammation, oxidative stress and the kynurenine pathway may lead to the individualization of treatment and increase its effectiveness. Methods. The study group included 82 schizophrenia inpatients. The Positive and Negative Symptoms Scale (PANSS), the Brief Assessment of Cognition in Schizophrenia (BACS) and the Calgary Depression in Schizophrenia Scale were used for symptom evaluation. Biochemical analyses included oxidative stress parameters and brain-derived neurotrophic factor (BDNF). Results. Linear models revealed the following: (1) malondiadehyde (MDA), N-formylkynurenine (N-formKYN), advanced oxidation protein products (AOPP), advanced glycation end-products of proteins (AGE) and total oxidative status (TOS) levels are related to the PANSS-total score; (2) MDA, reduced glutathione (GSH) and BDNF levels are related to the PANSS-negative score; (3) TOS and kynurenine (KYN) levels are related to the PANSS-positive score; (4) levels of total antioxidant status (TAS) and AOPP along with the CDSS score are related to the BACS-total score; (5) TAS and N-formKYN levels are related to the BACS-working memory score. Conclusions. Oxidative stress biomarkers may be associated with the severity of schizophrenia symptoms in positive, negative and cognitive dimensions. The identification of biochemical markers associated with the specific symptom clusters may increase the understanding of biochemical profiles in schizophrenia patients. Full article

The brain–computer interface (BCI), which provides a new way for humans to directly communicate with robots without the involvement of the peripheral nervous system, has recently attracted much attention. Among all the BCI paradigms, BCIs based on steady-state visual evoked potentials (SSVEPs) have the highest information transfer rate (ITR) and the shortest training time. Meanwhile, deep learning has provided an effective and feasible solution for solving complex classification problems in many fields, and many researchers have started to apply deep learning to classify SSVEP signals. However, the designs of deep learning models vary drastically. There are many hyper-parameters that influence the performance of the model in an unpredictable way. This study surveyed 31 deep learning models (2011–2023) that were used to classify SSVEP signals and analyzed their design aspects including model input, model structure, performance measure, etc. Most of the studies that were surveyed in this paper were published in 2021 and 2022. This survey is an up-to-date design guide for researchers who are interested in using deep learning models to classify SSVEP signals. Full article

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

Numerous factors can contribute to the development of neurodegenerative disorders (NDs), such as Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, Huntington’s disease, and multiple sclerosis. Oxidative stress (OS), a fairly common ND symptom, can be caused by more reactive oxygen species being made. In addition, the pathological state of NDs, which includes a high number of protein aggregates, could make chronic inflammation worse by activating microglia. Carotenoids, often known as “CTs”, are pigments that exist naturally and play a vital role in the prevention of several brain illnesses. CTs are organic pigments with major significance in ND prevention. More than 600 CTs have been discovered in nature, and they may be found in a wide variety of creatures. Different forms of CTs are responsible for the red, yellow, and orange pigments seen in many animals and plants. Because of their unique structure, CTs exhibit a wide range of bioactive effects, such as anti-inflammatory and antioxidant effects. The preventive effects of CTs have led researchers to find a strong correlation between CT levels in the body and the avoidance and treatment of several ailments, including NDs. To further understand the connection between OS, neuroinflammation, and NDs, a literature review has been compiled. In addition, we have focused on the anti-inflammatory and antioxidant properties of CTs for the treatment and management of NDs. 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

The second language acquisition (SLA) field has recently seen heightened interest in the study and application of positive psychology (PP). Emotion regulation is one of the concepts that has been stressed in PP. Several studies in PP have delved into how controlling one’s emotions improves second language learning/teaching. One of the concepts that has slipped the minds of researchers in the field is altruistic teaching. Unlike egocentric acts, altruistic teaching acts are performed to improve others’ well-being. Despite their importance in causing positive emotional effects, no study has investigated the impact of altruistic teaching acts on learners’ emotion regulation. To bridge this gap, the present study sought to investigate the effect of learners’ altruistic teaching on their emotion regulation. The study followed a sequential explanatory comparison group pre-test–post-test design. One hundred forty-one English as a Foreign Language (EFL) learners were recruited for this intervention study and were divided into experimental and control groups. Learners in the experimental group performed altruistic teaching by teaching their peers how to write essays in English, whereas learners in the control group did group work tasks on English essay writing. The results of independent-sample t-tests and repeated-measures ANOVA showed that altruistic teaching significantly impacts EFL learners’ emotion regulation. The results of qualitative data pointed to five themes, including enjoyment, self-esteem, bonding, devotion, and progress. Overall, the results suggested that altruistic teaching impacts learners’ emotion regulation by enhancing their enjoyment, self-esteem, bonding, devotion, and progress. The paper has theoretical and pedagogical implications for SLA research and 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

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