Close to me but unreachable: spotting the link between peripersonal space and empathy.

The space surrounding the body [i.e. peripersonal space (PPS)] has a crucial impact on individuals' interactions with the environment. Research showed that the interaction within the PPS increases individuals' behavioral and neural responses. Furthermore, individuals' empathy is affected by the distance between them and the observed stimuli. This study investigated empathic responses to painfully stimulated or gently touched faces presented within the PPS depending on the presence vs absence of a transparent barrier erected to prevent the interaction. To this aim, participants had to determine whether faces were painfully stimulated or gently touched, while their electroencephalographic signals were recorded. Brain activity [i.e. event-related potentials (ERPs) and source activations] was separately compared for the two types of stimuli (i.e. gently touched vs painfully stimulated faces) across two barrier conditions: (i) no-barrier between participants and the screen (i.e. no-barrier) and (ii) a plexiglass barrier erected between participants and the screen (i.e. barrier). While the barrier did not affect performance behaviorally, it reduced cortical activation at both the ERP and source activation levels in brain areas that regulate the interpersonal interaction (i.e. primary, somatosensory, premotor cortices and inferior frontal gyrus). These findings suggest that the barrier, precluding the possibility of interacting, reduced the observer's empathy.

SARS-CoV-2 associated posterior reversible encephalopathy syndrome (PRES) - a review of 82 cases.

OBJECTIVES: Severe, acute, respiratory syndromecoronavirus- 2 (SARS-CoV-2) infections can be complicated by central nervous system (CNS) disease. One of the CNS disorders associated with Coronavirus Disease-19 (COVID- 19) is posterior reversible encephalopathy syndrome (PRES). This narrative review summarises and discusses previous and recent findings on SARS-CoV-2 associated PRES. METHODS: A literature search was carried out in PubMed and Google Scholar using suitable search terms and reference lists of articles found were searched for further articles. RESULTS: By the end of February 2023, 82 patients with SARS-CoV-2 associated PRES were recorded. The latency between the onset of COVID-19 and the onset of PRES ranged from 1 day to 70 days. The most common presentations of PRES were mental deterioration (n=47), seizures (n=46) and visual disturbances (n=18). Elevated blood pressure was reported on admission or during hospitalisation in 48 patients. The most common comorbidities were arterial hypertension, diabetes, hyperlipidemia and atherosclerosis. PRES was best diagnosed by multimodal cerebral magnetic resonance imaging (MRI). Complete recovery was reported in 35 patients and partial recovery in 21 patients, while seven patients died. CONCLUSIONS: PRES can be a CNS complication associated with COVID-19. COVID-19 patients with mental dysfunction, seizures or visual disturbances should immediately undergo CNS imaging through multimodal MRI, electroencephalography (EEG) and cerebrospinal fluid (CSF) studies in order not to miss PRES.

EEG Findings in Coronavirus Disease.

PURPOSE: Neurologic manifestations of coronavirus disease (COVID-19) such as encephalopathy and seizures have been described. To our knowledge, detailed EEG findings in COVID-19 have not yet been reported. This report adds to the scarce body of evidence. METHODS: We identified eight COVID-19 positive patients who underwent EEG monitoring in our hospital system. RESULTS: EEGs were most commonly ordered for an altered level of consciousness, a nonspecific neurologic manifestation. We observed generalized background slowing in all patients and generalized epileptiform discharges with triphasic morphology in three patients. Focal electrographic seizures were observed in one patient with a history of focal epilepsy and in another patient with no such history. Five of eight patients had a previous diagnosis of epilepsy, suggesting that pre-existing epilepsy can be a potential risk factor for COVID-19-associated neurological manifestations. Five of eight patients who underwent EEG experienced a fatal outcome of infection. CONCLUSIONS: Our findings underscore previous observations that neurologic manifestations are common in severe cases. COVID-19 patients with epilepsy may have an increased risk of neurological manifestations and abnormal EEG.

Machine Learning Model for Computer-Aided Depression Screening among Young Adults Using Wireless EEG Headset.

Depression is a disorder that if not treated can hamper the quality of life. EEG has shown great promise in detecting depressed individuals from depression control individuals. It overcomes the limitations of traditional questionnaire-based methods. In this study, a machine learning-based method for detecting depression among young adults using EEG data recorded by the wireless headset is proposed. For this reason, EEG data has been recorded using an Emotiv Epoc+ headset. A total of 32 young adults participated and the PHQ9 screening tool was used to identify depressed participants. Features such as skewness, kurtosis, variance, Hjorth parameters, Shannon entropy, and Log energy entropy from 1 to 5 sec data filtered at different band frequencies were applied to KNN and SVM classifiers with different kernels. At AB band (8-30 Hz) frequency, 98.43 ± 0.15% accuracy was achieved by extracting Hjorth parameters, Shannon entropy, and Log energy entropy from 5 sec samples with a 5-fold CV using a KNN classifier. And with the same features and classifier overall accuracy = 98.10 ± 0.11, NPV = 0.977, precision = 0.984, sensitivity = 0.984, specificity = 0.976, and F1 score = 0.984 was achieved after splitting the data to 70/30 ratio for training and testing with 5-fold CV. From the findings, it can be concluded that EEG data from an Emotiv headset can be used to detect depression with the proposed method.

Anxiolytic-like Effects and Quantitative EEG Profile of Palmitone Induces Responses Like Buspirone Rather Than Diazepam as Clinical Drugs.

Anxiety is a mental disorder with a growing worldwide incidence due to the SARS-CoV-2 virus pandemic. Pharmacological therapy includes drugs such as benzodiazepines (BDZs) or azapirones like buspirone (BUSP) or analogs, which unfortunately produce severe adverse effects or no immediate response, respectively. Medicinal plants or their bioactive metabolites are a shared global alternative to treat anxiety. Palmitone is one active compound isolated from Annona species due to its tranquilizing activity. However, its influence on neural activity and possible mechanism of action are unknown. In this study, an electroencephalographic (EEG) spectral power analysis was used to corroborate its depressant activity in comparison with the anxiolytic-like effects of reference drugs such as diazepam (DZP, 1 mg/kg) and BUSP (4 mg/kg) or 8-OH-DPAT (1 mg/kg), alone or in the presence of the GABAA (picrotoxin, PTX, 1 mg/kg) or serotonin 5-HT1A receptor antagonists (WAY100634, WAY, 1 mg/kg). The anxiolytic-like activity was assayed using the behavioral response of mice employing open-field, hole-board, and plus-maze tests. EEG activity was registered in both the frontal and parietal cortex, performing a 10 min baseline and 30 min recording after the treatments. As a result, anxiety-like behavior was significantly decreased in mice administered with palmitone, DZP, BUSP, or 8-OH-DPAT. The effect of palmitone was equivalent to that produced by 5-HT1A receptor agonists but 50% less effective than DZP. The presence of PTX and WAY prevented the anxiolytic-like response of DZP and 8-OH-DPAT, respectively. Whereas only the antagonist of the 5-HT1A receptor (WAY) inhibited the palmitone effects. Palmitone and BUSP exhibited similar changes in the relative power bands after the spectral power analysis. This response was different to the changes induced by DZP. In conclusion, brain electrical activity was associated with the anxiolytic-like effects of palmitone implying a serotoninergic rather than a GABAergic mechanism of action.

Effects of EEG burst suppression on cerebral oxygen metabolism and postoperative cognitive function in elderly surgical patients: A randomized clinical trial.

BACKGROUND: This randomized clinical trial determined the effects of electroencephalographic burst suppression on cerebral oxygen metabolism and postoperative cognitive function in elderly surgical patients. METHODS: The patients were placed into burst suppression (BS) and non-burst suppression (NBS) groups. All patients were under bispectral index monitoring of an etomidate target-controlled infusion for anesthesia induction and intraoperative combination sevoflurane and remifentanil for anesthesia maintenance. The cerebral oxygen extraction ratio (CERO2), jugular bulb venous saturation (SjvO2), and difference in arteriovenous oxygen (Da-jvO2) were measured at T0, T1, and T2. One day before surgery, and 1, 3, and 7 days after surgery, postoperative cognitive dysfunction was assessed using the mini-mental state examination (MMSE). RESULTS: Compared with T0, the Da-jvO2 and CERO2 values were decreased, and SjvO2 was increased in the 2 groups at T1 and T2 (P < .05). There was no statistical difference in the SjvO2, Da-jvO2, and CERO2 values between T1 and T2. Compared with the NBS group, the SjvO2 value increased, and the Da-jvO2 and CERO2 values decreased at T1 and T2 in the BS group (P < .05). The MMSE scores on the 1st and 3rd days postoperatively were significantly lower in the 2 groups compared to the preoperative MMSE scores (P < .05). The MMSE scores of the NBS group were higher than the BS group on the 1st and 3rd days postoperatively (P < .05). CONCLUSION: In elderly patients undergoing surgery, intraoperative BS significantly reduced cerebral oxygen metabolism, which temporarily affected postoperative neurocognitive function.

ERS technical standards for using type III devices (limited channel studies) in the diagnosis of sleep disordered breathing in adults and children.

For more than three decades, type III devices have been used in the diagnosis of sleep disordered breathing in supervised as well as unsupervised settings. They have satisfactory positive and negative predictive values for detecting obstructive and central sleep apnoea in populations with moderately high pre-test probability of symptoms associated with these events. However, standardisation of commercially available type III devices has never been undertaken and the technical specifications can vary widely. None have been subjected to the same rigorous processes as most other diagnostic modalities in the medical field. Although type III devices do not include acquisition of electroencephalographic signals overnight, the minimum number of physical sensors required to allow for respiratory event scoring using standards outlined by the American Academy of Sleep Medicine remains debatable. This technical standard summarises data on type III studies published since 2007 from multiple perspectives in both adult and paediatric sleep practice. Most importantly, it aims to provide a framework for considering current type III device limitations in the diagnosis of sleep disordered breathing while raising research- and practice-related questions aimed at improving our use of these devices in the present and future.

Epilepsia partialis continua due to COVID-19 pneumonia.

BACKGROUND: Epilepsia partialis continua (EPC) is an uncommon condition with several different etiological causes. In this article, we presented a case of EPC due to COVID-19 infection. CASE REPORT: A 77-year-old woman with diabetes, asthma, hypertension, and chronic renal failure went to the emergency room with shortness of breath. The patient was awake and had slight hemiparesis sequela on the left due to a cerebrovascular incident 20 years earlier on neurological assessment. Non-contrast thorax computed CT revealed patchy ground-glass alveolo-acinar density increases in bilateral lung subzones, confirming COVID-19 pneumonia. After getting a positive COVID-19 PCR test, the patient was admitted to the department of infectious diseases. After a week in the hospital, seizures involving the right arm, leg, and part of the face appeared. The patient could not respond to questions. The patient's seizures lasted 12-24 hours. EEG was compatible with Epilepsia partialis continua. The cerebrospinal fluid examination was normal. Both clinical and EEG findings of the patient improved with treatment. CONCLUSIONS: Several causes may contribute to the onset of Epilepsia partialis continua. COVID-19 infection might be one of the etiological explanations for the diagnosis of Epilepsia partialis continua and the prognosis may be very good too.

SARS-CoV-2 alters neural synchronies in the brain with more severe effects in younger individuals.

Coronavirus disease secondary to infection by SARS-CoV-2 (COVID19 or C19) causes respiratory illness, as well as severe neurological symptoms that have not been fully characterized. In a previous study, we developed a computational pipeline for the automated, rapid, high-throughput and objective analysis of electroencephalography (EEG) rhythms. In this retrospective study, we used this pipeline to define the quantitative EEG changes in patients with a PCR-positive diagnosis of C19 (n = 31) in the intensive care unit (ICU) of Cleveland Clinic, compared to a group of age-matched PCR-negative (n = 38) control patients in the same ICU setting. Qualitative assessment of EEG by two independent teams of electroencephalographers confirmed prior reports with regards to the high prevalence of diffuse encephalopathy in C19 patients, although the diagnosis of encephalopathy was inconsistent between teams. Quantitative analysis of EEG showed distinct slowing of brain rhythms in C19 patients compared to control (enhanced delta power and attenuated alpha-beta power). Surprisingly, these C19-related changes in EEG power were more prominent in patients below age 70. Moreover, machine learning algorithms showed consistently higher accuracy in the binary classification of patients as C19 versus control using EEG power for subjects below age 70 compared to older ones, providing further evidence for the more severe impact of SARS-CoV-2 on brain rhythms in younger individuals irrespective of PCR diagnosis or symptomatology, and raising concerns over potential long-term effects of C19 on brain physiology in the adult population and the utility of EEG monitoring in C19 patients.

[Clinical and neurophysiological parameters in patients with epilepsy in the long-term period after COVID-19]. / Kliniko-neirofiziologicheskie pokazateli u patsientov s epilepsiei v otdalennom periode novoi koronavirusnoi infektsii.

OBJECTIVE: Clinical and psychophysiological assessment of the dynamics of the condition of patients with epilepsy in 4-6 months after the coronavirus infection. MATERIAL AND METHODS: An open controlled prospective comparative outpatient clinical and physiological study of patients diagnosed with epilepsy after suffering from COVID-19 (after 4-6 months) of moderate severity (n=16), patients diagnosed with epilepsy who did not suffer from COVID-19 (n=7), a control group (n=11) after confirmed COVID-19 (after 4-6 months). All groups were in the age range 23 to 50 years. Clinical/neurological and somatic research included: anamnesis, neurological examination, questioning, ECG, EEG, clinical and psychometric tests. RESULTS: There was an increase in the representation of epileptiform activity in the background EEG and more pronounced activity in provoking samples compared with background recording in 26.5% of patients who had suffered COVID-19 compared with the group of patients with epilepsy who had not suffered COVID-19. The detection of rare epileptic seizures in 18.8% of cases in the group of epilepsy patients, who underwent COVID-19, indicates an increase in epileptogenesis and a decrease in therapeutic control over seizures. At the same time, 87.5% of patients in this group showed a statistically significant increase in the influence of the sympathetic nervous system on the regulation of heart rhythm and an increase in anxiety and depression. CONCLUSION: The results can complement the understanding of the neuropsychiatric status of patients with epilepsy after COVID-19, which provides prerequisites for the development of optimal recovery directions in the rehabilitation period to maintain drug remission of epilepsy and reduce the possible progression of the disease.

Protective down-regulated states in the human brain: A possible lesson from COVID-19.

The COVID-19 pandemic has created a large population of patients who are slow to recover consciousness following mechanical ventilation and sedation in the intensive care unit. Few clinical scenarios are comparable. Possible exceptions are the rare patients in post-cardiac arrest coma with minimal to no structural brain injuries who recovered cognitive and motor functions after prolonged delays. A common electroencephalogram (EEG) signature seen in these patients is burst suppression [8]. Biophysical modeling has shown that burst suppression is likely a signature of a neurometabolic state that preserves basic cellular function "during states of lowered energy availability." These states likely act as a brain protective mechanism [9]. Similar EEG patterns are observed in the anoxia resistant painted turtle [24]. We present a conceptual analysis to interpret the brain state of COVID-19 patients suffering prolonged recovery of consciousness. We begin with the Ching model and integrate findings from other clinical scenarios and studies of the anoxia-tolerant physiology of the painted turtle. We postulate that prolonged recovery of consciousness in COVID-19 patients could reflect the effects of modest hypoxic injury to neurons and the unmasking of latent neuroprotective mechanisms in the human brain. This putative protective down-regulated state appears similar to that observed in the painted turtle and suggests new approaches to enhancing coma recovery [12].

Cognitive deficit in post-acute COVID-19: an opportunity for EEG evaluation?

BACKGROUND AND PURPOSE: Among the most common post-COVID symptoms, many patients experienced subjective cognitive deficit, commonly named "brain fog," that might be present also in those individuals without severe acute COVID-19 respiratory involvement. Some studies have investigated some of the mechanisms that might be associated with the brain fog with objective techniques including transcranial magnetic stimulation and neuroimaging. METHODS: The aim of this study was to investigate the presence of electroencephalographic (EEG) alterations in people with post-COVID self-reported cognitive deficit. RESULTS: Out of the 90 patients attending the post-COVID neurology ambulatory service, twenty patients presenting brain fog at least 4 weeks after acute non-severe COVID-19 infection, and without previous history of epilepsy, were investigated with 19-channel EEG, Montreal Cognitive Assessment (MoCA), and magnetic resonance imaging (MRI). EEG was found altered in 65% of the sample, among which 69% presented a slowing activity and 31% were characterized by epileptic discharges principally in the frontal areas. None of the patients showed DWI MRI lesions. CONCLUSIONS: These findings highlight the usefulness of EEG analysis to objectively describe possible neurophysiological abnormalities in post-COVID patients presenting subjective cognitive deficit.

Review of EEG-based neurofeedback as a therapeutic intervention to treat depression.

Depression, or major depressive disorder, is a common mental disorder that affects individuals' behavior, mood, and physical health, and its prevalence has increased during the lockdowns implemented to curb the COVID-19 pandemic. There is an urgent need to update the treatment recommendations for mental disorders during such crises. Conventional interventions to treat depression include long-term pharmacotherapy and cognitive behavioral therapy. Electroencephalogram-neurofeedback (EEG-NF) training has been suggested as a non-invasive option to treat depression with minimal side effects. In this systematic review, we summarize the recent literature on EEG-NF training for treating depression. The 12 studies included in our final sample reported that despite several issues related to EEG-NF practices, patients with depression showed significant cognitive, clinical, and neural improvements following EEG-NF training. Given its low cost and the low risk of side effects due to its non-invasive nature, we suggest that EEG-NF is worth exploring as an augmented tool for patients who already receive standard medications but remain symptomatic, and that EEG-NF training may be an effective intervention tool that can be utilized as a supplementary treatment for depression. We conclude by providing some suggestions related to experimental designs and standards to improve current EEG-NF training practices for treating depression.

COVID-19 Continuous-EEG Case Series: A Descriptive Study.

PURPOSE: Corona virus disease 2019 (COVID-19) refers to coronavirus disease secondary to SARS-CoV2 infection mainly affecting the human respiratory system. The SARS-CoV2 has been reported to have neurotropic and neuroinvasive features and neurological sequalae with wide range of reported neurological manifestations, including cerebrovascular disease, skeletal muscle injury, meningitis, encephalitis, and demyelination, as well as seizures and focal status epilepticus. In this case series, we analyzed the continuous video-EEGs of patients with COVID-19 infection to determine the presence of specific EEG features or epileptogenicity. METHODS: All continuous video-EEG tracings done on SARS-CoV2-positive patients during a 2-week period from April 5, 2020, to April 19, 2020, were reviewed. The demographics, clinical characteristics, imaging, and EEG features were analyzed and presented. RESULTS: Of 23 patients undergoing continuous video-EEG, 16 were COVID positive and were included. Continuous video-EEG monitoring was ordered for "altered mental status" in 11 of 16 patients and for "clinical seizure" in 5 of 16 patients. None of the patients had seizures or status epilepticus as a presenting symptom of COVID-19 infection. Instead, witnessed clinical seizures developed as results of COVID-19-related medical illness(es): anoxic brain injury, stroke/hemorrhage, lithium (Li) toxicity (because of kidney failure), hypertension, and renal disease. Three patients required therapeutic burst suppression because of focal nonconvulsive status epilepticus, status epilepticus/myoclonus secondary to anoxic injury from cardiac arrest, and one for sedation (and with concomitant EEG abnormalities secondary to Li toxicity). CONCLUSIONS: In this observational case series of 16 patients with COVID-19 who were monitored with continuous video-EEG, most patients experienced a nonspecific encephalopathy. Clinical seizures and electrographic status epilepticus were the second most commonly observed neurological problem.

Impact of the COVID-19 Pandemic on Continuous EEG Utilization.

PURPOSE: The coronavirus disease 2019 (COVID-19) has significantly impacted healthcare delivery and utilization. The aim of this article was to assess the impact of the COVID-19 pandemic on in-hospital continuous electroencephalography (cEEG) utilization and identify areas for process improvement. METHODS: A 38-question web-based survey was distributed to site principal investigators of the Critical Care EEG Monitoring Research Consortium, and institutional contacts for the Neurodiagnostic Credentialing and Accreditation Board. The survey addressed the following aspects of cEEG utilization: (1) general center characteristics, (2) cEEG utilization and review, (3) staffing and workflow, and (4) health impact on EEG technologists. RESULTS: The survey was open from June 12, 2020 to June 30, 2020 and distributed to 174 centers with 79 responses (45.4%). Forty centers were located in COVID-19 hotspots. Fifty-seven centers (72.1%) reported cEEG volume reduction. Centers in the Northeast were most likely to report cEEG volume reduction (odds ratio [OR] 7.19 [1.53-33.83]; P = 0.012). Additionally, centers reporting decrease in outside hospital transfers reported cEEG volume reduction; OR 21.67 [4.57-102.81]; P ≤ 0.0001. Twenty-six centers (32.91%) reported reduction in EEG technologist coverage. Eighteen centers had personal protective equipment shortages for EEG technologists. Technologists at these centers were more likely to quarantine for suspected or confirmed COVID-19; OR 3.14 [1.01-9.63]; P = 0.058. CONCLUSIONS: There has been a widespread reduction in cEEG volume during the pandemic. Given the anticipated duration of the pandemic and the importance of cEEG in managing hospitalized patients, methods to optimize use need to be prioritized to provide optimal care. Because the survey provides a cross-sectional assessment, follow-up studies can determine the long-term impact of the pandemic on cEEG utilization.

Climate change, vaccines, GMO: The N400 effect as a marker of attitudes toward scientific issues.

While the psychological predictors of antiscience beliefs have been extensively studied, neural underpinnings of the antiscience beliefs have received relatively little interest. The aim of the current study is to investigate whether attitudes towards the scientific issues are reflected in the N400 potential. Thirty-one individuals were asked to judge whether six different issues presented as primes (vaccines, medicines, nuclear energy, solar energy, genetically-modified organisms (GMO), natural farming) are well-described by ten positive and ten negative target words. EEG was recorded during the task. Furthermore, participants were asked to rate their own expertise in each of the six topics. Both positive and negative target words related to GMO elicited larger N400, than targets associated with vaccines and natural farming. The results of the current study show that N400 may be an indicator of the ambiguous attitude toward scientific issues.

Enhancing the feasibility of cognitive load recognition in remote learning using physiological measures and an adaptive feature recalibration convolutional neural network.

The precise assessment of cognitive load during a learning phase is an important pathway to improving students' learning efficiency and performance. Physiological measures make it possible to continuously monitor learners' cognitive load in remote learning during the COVID-19 outbreak. However, maintaining a good balance between performance and computational cost is still a major challenge in advancing cognitive load recognition technology to real-world applications. This paper introduced an adaptive feature recalibration (AFR) convolutional neural network to overcome this challenge by capturing the most discriminative physiological features (EEG and eye-tracking). The results revealed that the optimal average classification accuracy of the feature combination obtained by the AFR method reached 95.56% with only 60 feature dimensions. Additionally, compared with the best result of the conventional correlation-based feature selection (CFS) method, the introduced AFR algorithm achieved higher accuracy and cheaper computational cost, as well as a 2.06% improvement in accuracy and a 51.21% reduction in feature dimension, which is more in line with the requirements of low delay and real-time performance in practical BCI applications.

Psychogenic non-epileptic seizures (PNES) in the COVID-19 pandemic era: A systematic review with individual patients' analysis.

OBJECTIVE: Psychogenic non-epileptic seizures (PNES) resemble epileptic seizures but are not due to underlying epileptic activity and in some cases coexist alongside epilepsy. We described the clinical characteristics of patients with PNES as reported in the literature from the outbreak of the COVID-19 pandemic. We evaluated differences between patients with a diagnosis made immediately before the pandemic (pPNES) and those newly diagnosed during it (nPNES). METHODS: A systematic search with individual patient analysis of PNES cases published since the COVID-19 pandemic outbreak was performed. Differences between pPNES and nPNES were analyzed using Chi-square or Fisher exact test. RESULTS: Eleven articles were included, with 133 patients (106 pPNES and 27 nPNES). In the pPNES group, PNES frequency increased during the pandemic in 20/106 patients, whereas in 78/106, the frequency remained stable or decreased. nPNES was associated with higher risks of SARS-CoV-2 infection and epilepsy diagnosis, whereas psychiatric comorbidities were less frequent. CONCLUSIONS: During the pandemic, most patients with pPNES remained stable or improved, whereas nPNES was associated with a lower burden of psychiatric comorbidities. These intriguing findings suggest that, at least in some patients, the COVID-19 pandemic may not necessarily lead to worsening in the frequency of PNES and quality of life.