Brain Sci., Volume 13, Issue 2 (February 2023) – 214 articles

Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder, where differences are often present relating to the performance of motor skills. Our previous work elucidated unique event-related potential patterns of neural activity in those with ADHD when performing visuomotor and force-matching motor paradigms. The purpose of the current study was to identify whether there were unique neural sources related to somatosensory function and motor performance in those with ADHD. Source localization (sLORETA) software identified areas where neural activity differed between those with ADHD and neurotypical controls when performing a visuomotor tracing task and force-matching task. Median nerve somatosensory evoked potentials (SEPs) were elicited, while whole-head electroencephalography (EEG) was performed. sLORETA localized greater neural activity post-FMT in those with ADHD, when compared with their baseline activity (p < 0.05). Specifically, greater activity was exhibited in BA 31, precuneus, parietal lobe (MNI coordinates: X = −5, Y = −75, and Z = 20) at 156 ms post stimulation. No significant differences were found for any other comparisons. Increased activity within BA 31 in those with ADHD at post-FMT measures may reflect increased activation within the default mode network (DMN) or attentional changes, suggesting a unique neural response to the sensory processing of force and proprioceptive afferent input in those with ADHD when performing motor skills. This may have important functional implications for motor tasks dependent on similar proprioceptive afferent input. Full article

Glutamic acid decarboxylase (GAD) antibody-related encephalitis is an autoimmune disease associated with intracellular neuronal antigens. We report on a rare case of GAD antibody-associated encephalitis complicated with focal segmental stiffness-person syndrome (SPS) in a middle-aged woman. The disease course lasted for >10 years, initially presenting with drug-resistant epilepsy, followed by stiffness of the right lower limb, and right upper limb involvement. The patient experienced anxiety and depression symptoms due to long-term illness. During hospitalization, serum and cerebrospinal fluid GAD antibodies were positive and no tumor was found. The symptoms were significantly relieved after corticosteroid therapy and intravenous immunoglobulin immunomodulation therapy. To the best of our knowledge, this case is the first to discuss the early recognition and treatment of chronic epilepsy and focal segmental SPS caused by anti-GAD antibody-related encephalitis. Full article

Cardiovascular disease (CVD), including heart disease and stroke, continues to be the leading cause of death worldwide. Patients with mental health disorders, including schizophrenia (SCZ) are known to have an increased risk for CVD. Given the association with metabolic syndrome, patients with SCZ are often prescribed metformin and statins but its impact remains unsatisfactory. The use of aspirin (ASA) to decrease cardiovascular risk in the general population has been thoroughly investigated and clear guidelines are currently in place. Since adjuvant treatment with ASA could possibly decrease CVD risk and mortality in SCZ, we conducted a systematic review of the literature to determine the state of the current literature on this subject. Our systematic review points to gaps in the literature on CVD prevention in SCZ and illustrates an obvious need for further research. Although several studies have shown increased CVD risk in SCZ, to date, no research has been conducted on the utilization of CVD preventative treatment such as ASA for SCZ. Full article

Alzheimer’s Disease (AD) and Mild Cognitive Impairment (MCI) are closely associated with Tau proteins accumulation. In this study, we aimed to implement radiomics analysis to discover high-order features from pathological biomarker and improve the classification accuracy based on Tau PET images. Two cross-racial independent cohorts from the ADNI database (121 AD patients, 197 MCI patients and 211 normal control (NC) subjects) and Huashan hospital (44 AD patients, 33 MCI patients and 36 NC subjects) were enrolled. The radiomics features of Tau PET imaging of AD related brain regions were computed for classification using a support vector machine (SVM) model. The radiomics model was trained and validated in the ADNI cohort and tested in the Huashan hospital cohort. The standard uptake value ratio (SUVR) and clinical scores model were also performed to compared with radiomics analysis. Additionally, we explored the possibility of using Tau PET radiomics features as a good biomarker to make binary identification of Tau-negative MCI versus Tau-positive MCI or apolipoprotein E (ApoE) ε4 carrier versus ApoE ε4 non-carrier. We found that the radiomics model demonstrated best classification performance in differentiating AD/MCI patients and NC in comparison to SUVR and clinical scores models, with an accuracy of 84.8 ± 4.5%, 73.1 ± 3.6% in the ANDI cohort. Moreover, the radiomics model also demonstrated greater performance in diagnosing AD than other methods in the Huashan hospital cohort, with an accuracy of 81.9 ± 6.1%. In addition, the radiomics model also showed the satisfactory classification performance in the MCI-tau subgroup experiment (72.3 ± 3.5%, 71.9 ± 3.6% and 63.7 ± 5.9%) and in the MCI-ApoE subgroup experiment (73.5 ± 4.3%, 70.1 ± 3.9% and 62.5 ± 5.4%). In conclusion, our study showed that based on Tau PET radiomics analysis has the potential to guide and facilitate clinical diagnosis, further providing evidence for identifying the risk factors in MCI patients. Full article

Background: As essential techniques, intraoperative indocyanine green video angiography (ICG-VA) and FLOW 800 have been widely used in microsurgery for arteriovenous malformations (AVMs). In the present report, we introduced a supplementary technical trick for judging the degree of lesion resection when there were superficial drainage veins. FLOW 800 analysis is used to verify our conjecture. Methods: A retrospective analysis of a 33 case cohort treated surgically from June 2020 to September 2022 was conducted and their lesions were removed by superficial drainage veins as a supplementary technical trick and analyzed with FLOW800. Results: In our 33 AVMs, the feeding artery was visualized earlier than the draining vein. Intraoperatively, the T1/2 peak and slope of the draining vein were significantly higher than that of the lesion. However, the maximum fluorescence intensity (MFI) of the draining vein decreased as the procedure progressed (p < 0.001). After reducing the blood flow to the nidus by progressive dissection of the feeding artery, the arteriovenous transit time (AVTT) decreased from 0.64 ± 0.47 s, was prolonged to 2.38 ± 0.52 (p < 0.001), and the MFI and slope of the nidus decreased from the pre-resection 435.42 ± 43.90 AI and 139.77 ± 27.55 AI/s, and decreased to 386.70 ± 48.17 AI and 116.12 ± 17.46 AI/s (p < 0.001). After resection of the nidus, the T1/2 peak of the draining vein increased from 21.42 ± 4.70 s, prolonged to after dissection of the blood feeding artery, 23.07 ± 5.29 s (p = 0.424), and after resection of the lesion, 25.13 ± 5.46 s (p = 0.016), with a slope from 135.79 ± 28.17 AI/s increased to 210.86 ± 59.67 AI/s (p < 0.001). Conclusions: ICG-VA integrated with FLOW 800 is an available method for determining the velocity of superficial drainage veins. Whether the color of the superficial drainage veins on the cortical surface returns to normal can determine whether the lesion is completely resected and can reduce the possibility of residual postoperative lesions. Full article

Language influences how we process information from multiple domains. Thus, working in first (L1) or second language (L2) can modulate bilinguals’ performance on basic activities, such as visual search, decision-making, or reading. However, few studies have explored the role of L1 and L2 processing during an essential ability, such as Prospective Memory (PM). This type of memory allows us to set intentions to perform in the future (e.g., to attend an appointment). Thus, this is a novel study that allows us to explore the influence of bilingual language processing on certain cognitive abilities, which have not been deeply studied yet, such as the recall of future intentions. Thereby, this study aimed to explore the neural and behavioural correlates of bilinguals during L1 and L2 processing in a PM task where participants had to carry out an ongoing task while recovering a prospective intention given a PM cue. Importantly, the nature of the PM cue (focal or non-focal) varied the monitoring demands of the task. Behavioural and Event-Related Potential (ERP) results indicated greater engagement of monitoring processes in the PM task during L2 processing. Specifically, in L2, we found lower accuracy rates in the ongoing task and smaller amplitude differences between the focal and non-focal conditions in the P3b. Altogether, these findings suggest an impairment in prospective processing due to working in L2 contexts, supporting previous research on the impact of the bilingual experience over PM. Full article

(1) Background: Cerebrospinal fluid (CSF) and blood biomarkers are emerging tools used to obtain information on secondary brain damage and to improve diagnostic and prognostic accuracy for patients with prolonged post-traumatic disorders of consciousness (DoC). We synthesized available data from studies evaluating CSF and blood biomarkers in these patients. (2) Methods: A scoping review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews checklist to identify and synthesize data from relevant studies. Studies were identified by PubMed and manual searches. Those involving patients with unresponsive wakefulness syndrome or in a minimally conscious state for >28 days, evaluating CSF or blood biomarkers, and conducted on patients with traumatic brain injuries older than 16 years were included in the review. (3) Results: In total, 17 studies were included. Findings on neurofilament light chain, proteins, metabolites, lipids, amyloid-β, tau, melatonin, thyroid hormones, microtubule-associated protein 2, neuron-specific enolase, and brain-derived neurotrophic factor were included in the qualitative synthesis. (4) Conclusions: The most promising applications for CSF and blood biomarkers are the monitoring of secondary neurodegeneration, support of DoC diagnoses, and refinement of prognoses, although current evidence remains too scarce to recommend such uses of these biomarkers in clinical practice. Full article

Objective: To investigate the association between income and post-stroke cognition at 3 months, and the underlying neuroanatomical mechanism. Methods: Patients with first-ever ischemic stroke were enrolled and analyzed. Baseline information on income and neuroimaging measurements with predictive values for post-stroke cognitive impairment (PSCI) were collected within 7 days of the admission. Three months after the index stroke, all participants underwent a detailed neuropsychological test battery. The associations between income and PSCI and between income and brain structural measurements were investigated. Results: A total of 294 patients were recruited for this study. Lower income was independently associated with poor cognitive performance on Stroop tests, Clinical Dementia Rating, Boston Naming Test, and Verbal Fluency Test. Regarding neuroimaging parameters, lower income was associated with a lower total brain volume (TBV)/total intracranial volume (TICV) ratio (p = 0.004). Conclusions: Lower income is associated with an increased chance of post-stroke cognitive decline, particularly in executive function and language domains. Since global brain atrophy (measured by TBV/TICV ratio) is a strong predictor for PSCI, its correlation with income may help explain the neuroanatomical mechanism between income and post-stroke cognition. Full article

Background: Brainstem tumors are rare and extremely heterogeneous and present significant challenges in surgical treatment. Thus, biopsies often set the foundation for the diagnosis of brainstem tumors. Multimodal, image-guided, robot-assisted frameless stereotactic biopsies are increasingly popular in neurosurgery centers. This study aimed to compare the safety, efficacy, and duration of the Remebot robot-assisted (Remebot) frameless brainstem tumor biopsy versus those of frame-based stereotactic biopsy. Method: A retrospective analysis of 33 patients with brainstem tumors who underwent stereotactic brainstem biopsies in the department of neurosurgery from January 2016 to January 2021 was conducted. The patients were divided into two groups: the Remebot group (n = 22) and the frame-based group (n = 11). The clinical characteristics, trajectory strategy, duration of procedure, diagnostic yielding, histopathological diagnosis, and postoperative complications were retrospectively analyzed and compared between the groups. Results: More pediatric patients performed Remebot frameless brainstem tumor biopsy than frame-based biopsy, with a mean age of 17.3 ± 18.7 vs. 32.8 ± 17.1 (p = 0.027). The diagnostic yield had no significant difference in the two groups, with the diagnostic yield of frame-based biopsy and Remebot frameless brain biopsy being 90.9% and 95.5%, respectively. The time of the total process was 124.5 min for the frame-based biopsy and 84.7 min for the Remebot frameless brain biopsy (p < 0.001). There were no significant differences with respect to the occurrence of complication or the duration of the operation between the two groups. Conclusion: Remebot frameless stereotactic brainstem biopsy is as safe and efficacious as frame-based stereotactic biopsy. However, Remebot frameless biopsy can reduce the total duration of the procedure and has better application in young pediatric patients. Remebot frameless stereotactic biopsies can be a better option towards the safe and efficient treatment of brainstem tumors. Full article

Pseudotumor cerebri (PTC) in children is a rare condition whose underlying cause remains largely unknown. No study has yet systematically examined viral infection as a cause of PTC. The current study aimed to characterize PTC in children and investigate the possible role of acute viral infection of the central nervous system in its pathogenesis. A prospective, cross-sectional study was conducted in three centers in Israel. Participants were 50 children aged 0.5–18 years, of whom 27 had a definitive diagnosis of pseudotumor cerebri (the study group) and 23 comprised a control. Data collected included clinical presentation, imaging, treatment, ophthalmic findings, and cerebrospinal fluid (CSF) analysis. Using the ALLPLEX^TM meningitis panel, real-time polymerase chain reaction (PCR) was used to test for the presence of 12 common viruses. PTC patients (mean age 12 ± 4.3 years; 14 males, 13 females) had mean opening pressure of 41.9 ±10.2 mmH2O. All PTC patients had papilledema, and 25 (93%) had PTC symptoms. No viruses were found in the PTC group, while in the control group, one patient tested positive for Epstein–Barr virus and another for human herpesvirus type 6. Overall, in our study, PTC was not found to be associated with the presence of viruses in CSF. Full article

This study examined the prevalence of illegal drug use in UK students and motivators behind such behavior. Additionally, we explored possible relationships between substance use, psychosocial motivators, and psychiatric distress. A group (n = 543) of students completed online measures of substance use, anxiety, depression, perceived stress, and insomnia. A series of reasons behind their use were ranked based on importance. Reported cannabis, cocaine, nitrous oxide, ketamine, and MDMA use were most prevalent based on lifetime, past year, and month assessments. The experience of anxiety, depression, perceived stress, and insomnia were related to increased reports of substance use. Poor self-confidence and self-medication were key motivators of illicit drug use in those presenting greater psychiatric distress. These outcomes add to the sparse body of literature concerning illicit substance use in relation to psychiatric distress amongst UK students. Furthermore, we provided novel insight into the psychosocial motivators of such use. Full article

‘Jumping to Conclusions’, or hasty decision making, is widely studied within clinical and computational psychology. It is typically investigated using the ‘beads task’, a sequential information sampling paradigm, and defining one or two draws as jumping to conclusion. Situational experimental conditions, e.g., group vs. individual testing, abstract vs. cover story, show-up fee or course credit, frequently vary between studies. Little effort has been dedicated to investigating the potential effects of demand characteristics on hasty decision making. We explored this in four samples of participants (n = 336), in different situational experiment conditions, with two distinct variations of the beads task. An abstract ‘Draws to Decision’ (DtD) variant, and a cover story combined DtD and probabilistic inferences variant. Situational conditions did not have a significant effect on overall DtD for either variant. However, when using ‘extreme scores’ (DtD of 1 or 1 to 2) as a measure of hasty decision making, situational conditions had an effect for the abstract variant, with individual testing having the fewest hasty decision makers (DtD1: Mann–Whitney U = 2137.5, p = 0.02; DtD1-2: Mann–Whitney U = 2017.5, p < 0.01), but not for the cover story variant. Our results suggest that the abstract variant is more susceptible to test conditions, especially if a categorisation is used to classify hasty decisions. This does not imply that the cover story variant is better suited to capturing jumping to conclusions behaviour, but highlights the importance of mirroring the situational conditions between different samples. We recommend that testing conditions should be fully disclosed. Full article

Vocal identity processing depends on the ability to tell apart two instances of different speakers whilst also being able to tell together two instances of the same speaker. Whilst previous research has examined these voice processing capabilities under relatively common listening conditions, it has not yet tested the limits of these capabilities. Here, two studies are presented that employ challenging listening tasks to determine just how good we are at these voice processing tasks. In Experiment 1, 54 university students were asked to distinguish between very similar sounding, yet different speakers (celebrity targets and their impersonators). Participants completed a ‘Same/Different’ task and a ‘Which is the Celebrity?’ task to pairs of speakers, and a ‘Real or Not?’ task to individual speakers. In Experiment 2, a separate group of 40 university students was asked to pair very different sounding instances of the same speakers (speaking and singing). Participants were presented with an array of voice clips and completed a ‘Pairs Task’ as a variant of the more traditional voice sorting task. The results of Experiment 1 suggested that significantly more mistakes were made when distinguishing celebrity targets from their impersonators than when distinguishing the same targets from control voices. Nevertheless, listeners were significantly better than chance in all three tasks despite the challenge. Similarly, the results of Experiment 2 suggested that it was significantly more difficult to pair singing and speaking clips than to pair two speaking clips, particularly when the speakers were unfamiliar. Again, however, the performance was significantly above zero, and was again better than chance in a cautious comparison. Taken together, the results suggest that vocal identity processing is a highly adaptable task, assisted by familiarity with the speaker. However, the fact that performance remained above chance in all tasks suggests that we had not reached the limit of our listeners’ capability, despite the considerable listening challenges introduced. We conclude that voice processing is far better than previous research might have presumed. Full article

Objectives: Pregnancy is often associated with reduced sleep quality and an increase in sleep disorders, such as restless leg syndrome, obstructive sleep apnea, and insomnia. There are few studies investigating the prevalence of parasomnias in pregnancy, although they may be expected to be a significant problem, as disturbed sleep in this time period in addition to these sleep disorders may trigger parasomnia episodes. Methods: We conducted a survey using an online questionnaire focusing on a comparison of the prevalence of parasomnias in three time periods: 3 months before pregnancy, during pregnancy, and 3 months after delivery. We also inquired about psychiatric and neurological comorbidities, current anxiety and depression symptoms, and pregnancy complications. Results: A total of 325 women (mean age 30.3 ± 5.3 years) participated in the online survey. The overall number of reported parasomnias increased during pregnancy compared to the 3 months before pregnancy (p < 0.001) and decreased after childbirth (p < 0.001). Specifically, we found a significant increase in sleepwalking (p = 0.02) and night terrors (p < 0.001), as well as in vivid dreams (p < 0.001) and nightmares (p < 0.001) during pregnancy. A similar significant increase during pregnancy was reported for head explosion (p < 0.011). In contrast, the number of episodes of sleep paralysis increased after delivery (p = 0.008). At the individual level, an increase in the severity/frequency of individual parasomnia episodes was also observed during pregnancy. Participants whose vivid dreams/nightmares persisted after delivery had higher BDI-II and STAI-T scores. Our data also suggest a significant impact of migraines and other chronic pain, as well as complications during pregnancy, on the presence of parasomnia episodes in our cohort. Conclusions: We have shown that the prevalence of parasomnias increases during pregnancy and needs to be targeted, especially by non-pharmacological approaches. At the same time, it is necessary to inquire about psychiatric and neurological comorbidities and keep in mind that more sleep disorders may be experienced by mothers who have medical complications during pregnancy. 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

COVID-19 remains a significant clinical issue worldwide, with frequent neurological manifestations. In this study, the authors combine data obtained from the patient’s medical history, physical examinations, and additional test results in the pursuit of any clinically relevant connections. Fifty-eight adult patients hospitalized in the Department of Neurology and Infectiology over a five-months period were retrospectively enrolled in this study. On admission, all patients included in this study were classified as mild or moderate COVID-19 cases, according to the World Health Organization (WHO) guidelines. Laboratory tests, Electroencephalography (EEG), and Magnetic Resonance Imaging (MRI) were performed. There was no statistically significant difference in the Neutrophil–Lymphocyte Ratio (NLR), C-reactive protein (CRP), and Interleukin 6 (IL-6) in patients who reported to the hospital within a week from the symptoms’ onset and in those who reported later. In total, 49.06% of patients with eligible EEG recordings presented abnormal brain activity, while 27.59% of the study population had COVID-19-associated MRI findings. EEG and MRI abnormality occurrence did not correlate with the incidence of mild neurological symptoms (headache, olfactory, and gustatory disorders) of the SARS-CoV-2 infection. In three patients in this study population, unprovoked generalized epileptic seizures occurred for the first time in their life. Non-severe SARS-CoV-2 infection causes functional and structural abnormalities within the central nervous system. Brain microhemorrhages are frequently present in non-severe COVID-19 patients. There is no significant association between mild neurological symptoms of COVID-19 and additional test abnormalities. The time from SARS-CoV-2 infection’s onset to hospital admission does not seem to influence the prognostic value of CRP, IL-6, and NLR in non-severe COVID-19. Mild-to-moderate SARS-CoV-2 infection can be a trigger factor for epilepsy and epileptic seizures. Full article

Understanding how the human brain recognizes faces is a primary scientific goal in cognitive neuroscience. Given the limitations of the monkey model of human face recognition, a key approach in this endeavor is the recording of electrophysiological activity with electrodes implanted inside the brain of human epileptic patients. However, this approach faces a number of challenges that must be overcome for meaningful scientific knowledge to emerge. Here we synthesize a 10 year research program combining the recording of intracerebral activity (StereoElectroEncephaloGraphy, SEEG) in the ventral occipito-temporal cortex (VOTC) of large samples of participants and fast periodic visual stimulation (FPVS), to objectively define, quantify, and characterize the neural basis of human face recognition. These large-scale studies reconcile the wide distribution of neural face recognition activity with its (right) hemispheric and regional specialization and extend face-selectivity to anterior regions of the VOTC, including the ventral anterior temporal lobe (VATL) typically affected by magnetic susceptibility artifacts in functional magnetic resonance imaging (fMRI). Clear spatial dissociations in category-selectivity between faces and other meaningful stimuli such as landmarks (houses, medial VOTC regions) or written words (left lateralized VOTC) are found, confirming and extending neuroimaging observations while supporting the validity of the clinical population tested to inform about normal brain function. The recognition of face identity – arguably the ultimate form of recognition for the human brain – beyond mere differences in physical features is essentially supported by selective populations of neurons in the right inferior occipital gyrus and the lateral portion of the middle and anterior fusiform gyrus. In addition, low-frequency and high-frequency broadband iEEG signals of face recognition appear to be largely concordant in the human association cortex. We conclude by outlining the challenges of this research program to understand the neural basis of human face recognition in the next 10 years. Full article

Major depressive disorder (MDD) is associated with dysfunctional self-reported interoception (i.e., abnormal perception of the body’s physiological state) and systemic inflammation, both of which adversely affect treatment response. In this study, we explored associations between C-reactive protein (CRP) and self-reported interoception, to gain more insight into the pathophysiology of interoceptive impairments in MDD. We also aimed to replicate previous findings on the associations of depression and fatigue severity with CRP. The study included 97 depressed individuals, who completed self-administered questionnaires (Multidimensional Assessment of Interoceptive Awareness (MAIA-2); Beck Depression Inventory-II, Multidimensional Fatigue Inventory). CRP concentrations were analyzed in the serum using a particle-enhanced turbidimetric immunoassay. We applied Bayesian inference to estimate robust effect parameters from posterior distributions based on MCMC sampling, and computed Bayes factors (BF₁₀) as indices of relative evidence. The bivariate analysis supported evidence against associations between CRP and self-reported interoception (BF₁₀ ≤ 0.32), except for one dimension (Not-Distracting: r = 0.11, BF₁₀ > 0.43, absence of evidence). Positive correlations with overall depression (r = 0.21, BF₁₀ = 3.19), physical fatigue (r = 0.28, BF₁₀ = 20.64), and reduced activity (r = 0.22, BF₁₀ = 4.67) were found. The multivariate analysis showed moderate evidence that low-grade inflammation predicted higher scores on the MAIA-2 Not-Worrying scale (β = 0.28, BF₁₀ = 3.97), after controlling for relevant confounders. Inflammatory responses, as measured by CRP, may not be involved in the pathophysiology of dysfunctional self-reported interoception. However, systemic low-grade inflammation could potentially exert a protective effect against worries about pain or discomfort sensations. An immunological involvement in interoceptive impairments cannot be ruled out until future studies considering additional biomarkers of inflammation replicate our findings. Full article

Functional paralysis (FP) or limb weakness is a common presentation of functional movement disorders (FMD), accounting for 18.1% of the clinical manifestations of FMD. The pathophysiology of FP is not known, but imaging studies have identified changes in structural and functional connectivity in multiple brain networks. It has been proposed that noninvasive brain stimulation techniques may be used to understand the pathophysiology of FP and may represent a possible therapeutic option. In this paper, we reviewed transcranial magnetic stimulation studies on functional paralysis, focusing on their pathophysiological and therapeutical implications. Overall, there is general agreement on the integrity of corticospinal pathways in FP, while conflicting results have been found about the net excitability of the primary motor cortex and its excitatory/inhibitory circuitry in resting conditions. The possible involvement of spinal cord circuits remains an under-investigated area. Repetitive transcranial magnetic stimulation appears to have a potential role as a safe and viable option for the treatment of functional paralysis, but more studies are needed to investigate optimal stimulation parameters and clarify its role in the context of other therapeutical options. Full article

This study referred to the standard of electroencephalography (EEG) collection of normative databases and collected the Taiwan normative database to examine the reliability and validation of the Taiwan EEG normative database. We included 260 healthy participants and divided them into five groups in 10-year age-group segments and calculated the EEG means, standard deviation, and z-scores. Internal consistency reliability was verified at different frequencies between the three electrode locations in the Taiwan normative database. We recruited 221 major depressive disorder (MDD) patients for cross-validation between the Taiwan and NeuroGuide normative databases. There were high internal consistency reliabilities for delta, theta, alpha, beta, and high-beta at C3, Cz, and C4 in the HC group. There were high correlations between the two z-scores of the Taiwan and NeuroGuide normative databases in the frontal, central, parietal, temporal, and occipital lobes from MDD patients. The beta z-scores in the frontal lobe and central area, and the high-beta z-scores in the frontal, central, parietal, temporal, and occipital lobes were greater than one for MDD patients; in addition, the beta and high-beta absolute value z-scores in the whole brain were greater than the ones of MDD patients. The Taiwan EEG normative database has good psychometric characteristics of internal consistency reliability and cross-validation. Full article

Glioblastoma multiforme (GBM) is the most common malignant primary brain tumor in adults. Despite multimodal therapy, median survival is poor at 12–15 months. At the molecular level, radio-/chemoresistance and resulting tumor progression are attributed to a small fraction of tumor cells, termed glioblastoma stem-like cells (GSCs). These CD133-expressing, self-renewing cells display the properties of multi-lineage differentiation, resulting in the heterogenous composition of GBM. MicroRNAs (miRNAs) as regulators of gene expression at the post-transcriptional level can alter many pathways pivotal to cancer stem cell fate. This study explored changes in the miRNA expression profiles in patient-derived GSCs altered on differentiation into glial fiber acid protein (GFAP)-expressing, astrocytic tumor cells using a polymerase chain reaction (PCR) array. Initially, 22 miRNAs showed higher expression in GSCs and 9 miRNAs in differentiated cells. The two most downregulated miRNAs in differentiated GSCs were miR-17-5p and miR-425-5p, whilst the most upregulated miRNAs were miR-223-3p and let-7-5p. Among those, miR-425-5p showed the highest consistency in an upregulation in all three GSCs. By transfection of a 425-5p miRNA mimic, we demonstrated downregulation of the GFAP protein in differentiated patient-derived GBM cells, providing potential evidence for direct regulation of miRNAs in the GSC/GBM cell transition. Full article

Deep brain stimulation (DBS) has emerged as an invasive neuromodulation technique for the treatment of several neurological disorders, but the mechanisms underlying its effects remain partially elusive. In this context, the application of Transcranial Magnetic Stimulation (TMS) in patients treated with DBS represents an intriguing approach to investigate the neurophysiology of cortico-basal networks. Experimental studies combining TMS and DBS that have been performed so far have mainly aimed to evaluate the effects of DBS on the cerebral cortex and thus to provide insights into DBS’s mechanisms of action. The modulation of cortical excitability and plasticity by DBS is emerging as a potential contributor to its therapeutic effects. Moreover, pairing DBS and TMS stimuli could represent a method to induce cortical synaptic plasticity, the therapeutic potential of which is still unexplored. Furthermore, the advent of new DBS technologies and novel treatment targets will present new research opportunities and prospects to investigate brain networks. However, the application of the combined TMS-DBS approach is currently limited by safety concerns. In this review, we sought to present an overview of studies performed by combining TMS and DBS in neurological disorders, as well as available evidence and recommendations on the safety of their combination. Additionally, we outline perspectives for future research by highlighting knowledge gaps and possible novel applications of this approach. 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

Prior to the COVID-19 pandemic, we demonstrated the efficacy of a novel Cognitive Behavioural Therapy programme for the treatment of Non-Rapid Eye Movement Parasomnias (CBT-NREMP) in reducing NREM parasomnia events, insomnia and associated mood severities. Given the increased prevalence and worsening of sleep and affective disorders during the pandemic, we examined the sustainability of CBT-NREMP following the U.K.’s longest COVID-19 lockdown (6 January 2021–19 July 2021) by repeating the investigations via a mail survey in the same 46 patient cohort, of which 12 responded. The survey included validated clinical questionnaires relating to NREM parasomnia (Paris Arousal Disorder Severity Scale), insomnia (Insomnia Severity Index) and anxiety and depression (Hospital Anxiety and Depression Scale). Patients also completed a targeted questionnaire (i.e., Impact of COVID-19 Lockdown Questionnaire, ICLQ) to assess the impact of COVID-19 lockdown on NREM parasomnia severity, mental health, general well-being and lifestyle. Clinical measures of NREM parasomnia, insomnia, anxiety and depression remained stable, with no significant changes demonstrated in questionnaire scores by comparison to the previous investigatory period prior to the COVID-19 pandemic: p (ISI) = 1.0; p (HADS) = 0.816; p (PADSS) = 0.194. These findings support the longitudinal effectiveness of CBT-NREMP for up to three years following the clinical intervention, and despite of the COVID-19 pandemic. Full article

Background: Children with obesity have a higher risk of future health and psychological problems. Executive functions (EFs) play a key role in successful dietetic and exercise planning; therefore, new treatments aimed at improving EFs may optimize outcomes. Objectives: This study evaluates the impact of EF training on body mass index (BMI), food choice, and cognition in children with obesity. We also examine their real-life executive functioning, emotional state, and quality of life. Methods: Randomized controlled double-blind trial. Forty-six children with obesity were randomly allocated into an executive functions training or a control task training group and attended 30–45 min of daily training (5/week over 6 weeks), with both groups receiving counseling on diet and wearing an activity/sleep tracker. Participants were evaluated at baseline and after treatment. Results: BMI decreased over time in the whole sample, although there were no differences between groups at post-training in BMI, food choice, and cognition. Both groups showed significant improvements in attention, speed, cognitive flexibility, and inhibitory control. Additionally, there were some benefits in real-life executive functioning and self-esteem. Over the 6 weeks, participants showed worse food choices in both groups. Conclusions: EFs training showed a lack of significant effects. The executive function enhancement alone did not explain these changes, as there were no significant differences between the experimental groups. It might be that the control task training could also produce some benefits, and multi-component interventions might be useful for weight loss. Full article

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder that can be associated with intellectual disability (ID) and epilepsy (E). The etiology and the pathogenesis of this disorder is in most cases still to be clarified. Several studies have underlined that the EEG recordings in children with these clinical pictures are abnormal, however the precise frequency of these abnormalities and their relationship with the pathogenic mechanisms and in particular with epileptic seizures are still unknown. We retrospectively reviewed 292 routine polysomnographic EEG tracings of preschool children (age < 6 years) who had received a first multidisciplinary diagnosis of ASD according to DSM-5 clinical criteria. Children (mean age: 34.6 months) were diagnosed at IRCCS E. Medea (Bosisio Parini, Italy). We evaluated: the background activity during wakefulness and sleep, the presence and the characteristics (focal or diffuse) of the slow-waves abnormalities and the interictal epileptiform discharges. In 78.0% of cases the EEG recordings were found to be abnormal, particularly during sleep. Paroxysmal slowing and epileptiform abnormalities were found in the 28.4% of the subjects, confirming the high percentage of abnormal polysomnographic EEG recordings in children with ASD. These alterations seem to be more correlated with the characteristics of the underlying pathology than with intellectual disability and epilepsy. In particular, we underline the possible significance of the prevalence of EEG abnormalities during sleep. Moreover, we analyzed the possibility that EEG data reduces the ASD clinical heterogeneity and suggests the exams to be carried out to clarify the etiology of the disorder. Full article

Data linking heart rate variability (HRV) and cognitive status remains controversial and scarce, particularly in cerebral small vessel disease (CSVD) patients. Whether the association between HRV and cognitive performance exists in CSVD patients is unclear. Hence, we aimed to investigate the association between HRV and cognitive performance in patients with CSVD. This cross-sectional study was conducted among 117 CSVD patients. All patients underwent HRV assessment and global cognitive evaluation by the Mini-Mental-State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Multivariable analyses were performed to evaluate the association between HRV and cognitive status. The mean age of study population was 59.5 ± 11.8 years and 39.3% were female. After adjusting for confounding factors, a higher high frequency (HF) norm was independently associated with better MMSE scores (β = 0.051; 95% confidence interval (CI): 0.012~0.090; p = 0.011) and MoCA scores (β = 0.061; 95% CI: 0.017~0.105; p = 0.007), while a higher low frequency (LF)/HF ratio was independently associated with worse MMSE scores (β = −0.492; 95% CI: −0.893~−0.092; p = 0.017) and MoCA scores (β = −0.691; 95% CI: −1.134~−0.248; p = 0.003). The HF norm was positively associated with global cognitive performance, whereas the LF/HF ratio was negatively associated with global cognitive performance among CSVD patients. Further study of the relationship between autonomic function and cognitive performance is warranted. Full article

Pulmonary embolism (PE) is a significant consequence that is becoming more common in COVID-19 patients. The current study sought to determine the prevalence and risk factors for PE in a study population of COVID-19 patients, as well as the relationship between PE and neurological sequelae. The research also sought to analyze the consistency of neurological examination and imaging techniques in detecting neurological problems. The research comprised a total of 63 individuals with COVID-19. The incidence of PE in the study group was 9.5% for smokers, 23.8% for obese patients, 33.3% for hypertensive patients, and 19% for diabetic patients, according to the findings. After adjusting for possible confounders such as age, gender, BMI, smoking, hypertension, and diabetes, a logistic regression analysis indicated that the probabilities of having neurological complications were 3.5 times greater in individuals who had PE. In conclusion, the present study highlights the high incidence of PE among patients with COVID-19 and the association between PE and neurological complications. The study also emphasizes the importance of a thorough neurological examination and imaging studies in the detection of neurological complications in patients with PE. Full article

In certain circumstances, speech and language therapy is proposed in telepractice as a practical alternative to in-person services. However, little is known about the minimum quality requirements of recordings in the teleassessment of motor speech disorders (MSD) utilizing validated tools. The aim here is to examine the comparability of offline analyses based on speech samples acquired from three sources: (1) in-person recordings with high quality material, serving as the baseline/gold standard; (2) in-person recordings with standard equipment; (3) online recordings from videoconferencing. Speech samples were recorded simultaneously from these three sources in fifteen neurotypical speakers performing a screening battery of MSD and analyzed by three speech and language therapists. Intersource and interrater agreements were estimated with intraclass correlation coefficients on seventeen perceptual and acoustic parameters. While the interrater agreement was excellent for most speech parameters, especially on high quality in-person recordings, it decreased in online recordings. The intersource agreement was excellent for speech rate and mean fundamental frequency measures when comparing high quality in-person recordings to the other conditions. The intersource agreement was poor for voice parameters, but also for perceptual measures of intelligibility and articulation. Clinicians who plan to teleassess MSD should adapt their recording setting to the parameters they want to reliably interpret. Full article

Anhedonia, a central depression symptom, is associated with impairments in reward processing. However, it is not well understood which sub-components of reward processing (anticipation, motivation, consummation, and learning) are impaired in association with anhedonia in depression. In particular, it is unclear how learning about different rewards and the effort needed to obtain them might be associated with anhedonia and depression symptoms. Therefore, we examined learning in young people (N = 132, mean age 20, range 17–25 yrs.) with a range of depression and anhedonia symptoms using a probabilistic instrumental learning task. The task required participants to learn which options to choose to maximize their reward outcomes across three conditions (chocolate taste, puppy images, or money) and to minimize the physical effort required to obtain the rewards. Additionally, we collected questionnaire measures of anticipatory and consummatory anhedonia, as well as subjective reports of “liking”, “wanting” and “willingness to exert effort” for the rewards used in the task. We found that as anticipatory anhedonia increased, subjective liking and wanting of rewards decreased. Moreover, higher anticipatory anhedonia was significantly associated with lower reward learning accuracy, and participants demonstrated significantly higher reward learning than effort learning accuracy. To our knowledge, this is the first study observing an association of anhedonia with reward liking, wanting, and learning when reward and effort learning are measured simultaneously. Our findings suggest an impaired ability to learn from rewarding outcomes could contribute to anhedonia in young people. Future longitudinal research is needed to confirm this and reveal the specific aspects of reward learning that predict anhedonia. These aspects could then be targeted by novel anhedonia interventions. Full article