CubicPat: Investigations on the Mental Performance and Stress Detection Using EEG Signals.

Solving the secrets of the brain is a significant challenge for researchers. This work aims to contribute to this area by presenting a new explainable feature engineering (XFE) architecture designed to obtain explainable results related to stress and mental performance using electroencephalography (EEG) signals. Two EEG datasets were collected to detect mental performance and stress.

Zipper Pattern: An Investigation into Psychotic Criminal Detection Using EEG Signals.

Electroencephalography (EEG) signal-based machine learning models are among the most cost-effective methods for information retrieval. In this context, we aimed to investigate the cortical activities of psychotic criminal subjects by deploying an explainable feature engineering (XFE) model using an EEG psychotic criminal dataset. In this study, a new EEG psychotic criminal dataset was curated, containing EEG signals from psychotic criminal and control groups.

ChMinMaxPat: Investigations on Violence and Stress Detection Using EEG Signals.

Background And Objectives: Electroencephalography (EEG) signals, often termed the letters of the brain, are one of the most cost-effective methods for gathering valuable information about brain activity. This study presents a new explainable feature engineering (XFE) model designed to classify EEG data for violence detection. The primary objective is to assess the classification capability of the proposed XFE model, which uses a next-generation feature extractor, and to obtain interpretable findings for EEG-based violence and stress detection.

Black-white hole pattern: an investigation on the automated chronic neuropathic pain detection using EEG signals.

Electroencephalography (EEG) signals provide information about the brain activities, this study bridges neuroscience and machine learning by introducing an astronomy-inspired feature extraction model. In this work, we developed a novel feature extraction function, black-white hole pattern (BWHPat) which dynamically selects the most suitable pattern from 14 options. We developed BWHPat in a four-phase feature engineering model, involving multileveled feature extraction, feature selection, classification, and cortex map generation.

QuadTPat: Quadruple Transition Pattern-based explainable feature engineering model for stress detection using EEG signals.

The most cost-effective data collection method is electroencephalography (EEG), which obtains meaningful information about the brain. Therefore, EEG signal processing is crucial for neuroscience and machine learning (ML). Therefore, a new EEG stress dataset has been collected, and an explainable feature engineering (XFE) model has been proposed using the Directed Lobish (DLob) symbolic language.

TATPat based explainable EEG model for neonatal seizure detection.

The most cost-effective data collection method is electroencephalography (EEG) to obtain meaningful information about the brain. Therefore, EEG signal processing is very important for neuroscience and machine learning (ML). The primary objective of this research is to detect neonatal seizures and explain these seizures using the new version of Directed Lobish.

Lobish: Symbolic Language for Interpreting Electroencephalogram Signals in Language Detection Using Channel-Based Transformation and Pattern.

Electroencephalogram (EEG) signals contain information about the brain's state as they reflect the brain's functioning. However, the manual interpretation of EEG signals is tedious and time-consuming. Therefore, automatic EEG translation models need to be proposed using machine learning methods.

Evaluation of neurological disorders that develop concurrently with COVID-19 pneumonia: a retrospective analysis.

Background: During the pandemic, many neurological symptoms have been evaluated as complications of COVID-19 pneumonia.

Objective: To investigate the frequency and characteristics of neurological findings, and their effects on the prognosis of patients with COVID-19 pneumonia who consulted with the Neurology department.

Methods: Data on 2329 patients who were hospitalized with the diagnosis of COVID-19 pneumonia in our hospital were scanned.

A Case of Neuroleptic Malignant Syndrome After COVID-19 Vaccination and Possible Mechanisms of Vaccines in the Formation of This Syndrome.

Neuroleptic malignant syndrome is characterized by muscle stiffness, hyperthermia, autonomic dysfunction, elevation in serum creatine phosphokinase, and changes in consciousness, which usually occur due to the side effects of life-threatening neuroleptic and antipsychotic drugs, and it can cause high mortality. A few cases of neuroleptic malignant syndrome associated with coronavirus disease 2019 infection and vaccination have been reported in the literature. Our case presented with epileptic seizure and neuroleptic malignant syndrome signs 10 days after receiving a single dose of the BNT162b2 vaccine when under low-dose olanzapine treatment with a diagnosis of autism and epilepsy.

Physical exercise may improve problem-solving skills and emotional intelligence in patients with relapsing-remitting multiple sclerosis: A cross-sectional study.

Background: Multiple sclerosis is a disease that can reduce the quality of life with a physical disability, neuropsychiatric disorders, and cognitive dysfunctions. Therefore, multiple sclerosis treatment should include treatments for cognitive and neuropsychiatric disorders and pharmacological treatments. This study aimed to examine the effects of exercise on neuropsychiatric disorders, problem-solving skills, and emotional intelligence in multiple sclerosis patients.

Positive effects of ocrelizumab in patients with familial mediterranean fever and coexistent multiple sclerosis.

Objectives: This study aims to evaluate the effects of ocrelizumab (OCZ) on familial Mediterranean fever (FMF) attacks in multiple sclerosis (MS) patients with FMF (MS+FMF patients).

Patients And Methods: This retrospective observational study included 11 patients (2 males, 9 females; mean age 46.6±9.

A case of syncopal convulsions triggered by glossopharyngeal neuralgia.

Syncopal convulsions and epileptic seizures are clinically hard to distinguish and differ in terms of treatment approaches. It is important to consider the cardiac arrhythmias that impair cerebral perfusion in the differential diagnosis of antiepileptic treatment-resistant convulsions. Here we offer a 72 year old male patient glossopharengial neuralgia after swallowing associated with recurrent episodes of syncopal convulsions.

Protective effect of pregabalin on the brain tissue of diabetic rats.

Purpose: Diabetes mellitus (DM) is a metabolic disorder characterized by insulin deficiency or insulin resistance. Pregabalin (PGB) is an antiepileptic drug with proven efficacy in the treatment of epilepsy, generalized anxiety disorder, and neuropathic pain. In this study, we aimed to investigate the protective effects of PGB in brain tissue of rats with streptozotocin (STZ)-induced experimental diabetes.

Epileptic olfactory auras: a clinical spectrum.

Objective: To investigate the relative frequency of olfactory aura in a large number of patients with focal epilepsy, and examine the full clinical spectrum of epileptic olfactory auras (OAs) and their relationship to hemispheric lateralization and localization of epileptogenic focus.

Methods: This retrospective study was based on the medical records of 1384 patients with focal epilepsy. Of these, 71 (5.

Temporal arteritis and trigeminal neuralgia overlap syndrome: A case report.

Temporal arteritis and trigeminal neuralgia are rare causes of a headache, and the combination is rarer still. The present patient was diagnosed with temporal arteritis at the age of 60 years and presented with trigeminal neuralgia after the sedimentation rate had returned to normal under treatment. The underlying cause of neuralgia in cases of temporal arteritis varies.

Suboccipital steroid injection alone as a preventive treatment for cluster headache.

Background: Suboccipital steroid injection can be used as a preventive treatment for episodic and chronic cluster headache (CH). In recent studies, prophylactic treatment has been used in addition to suboccipital steroid injection. In this study, we aimed to investigate the effectivity of the sole use of rapid- and long-acting steroid injections without prophylactic treatment in patients with episodic and chronic CH.

Acute Rhinosinusitis as an Infrequent Cause of Symptomatic Cluster Headache: Report of Seven Cases.

Cluster headache (CH) is a primary headache disorder characterized by unilateral headache attacks lasting 15 to 180 minutes, occurring between two and eight times a day, and accompanied by autonomic symptoms ipsilateral to the pain. However, cases of symptomatic CH that occur secondary to an underlying structural pathology have also been reported in the literature. In this report, seven patients are presented who were admitted with signs of CH and diagnosed with acute rhinosinusitis depending on extensive clinical and radiologic examinations.

Effects of Alpha Lipoic Acid on Loss of Myelin Sheath of Sciatic Nerve in Experimentally Induced Diabetic Rats.

Objectives: Diabetic neuropathy is the most frequent chronic complication of diabetes. It may attack to sensory, motor or autonomous fibers. Varied mechanisms account for the development of diabetic neuropathy such as metabolic disorders, microvascular damages, neurotrophic support deficit, alternation in neuro-immune interactions, neural and glial cell apoptosis, and inflammation.