Novel knowledge about the interrelationships and reciprocal effects of migraine and epilepsy, migraine and mood disorders, or migraine and irritable bowel syndrome has emerged in recent decades. Over time, comorbid pathologies associated with migraine that share common physiopathological mechanisms were studied. Among these studied pathologies is epilepsy, a disorder with common ion channel dysfunctions as well as dysfunctions in glutamatergic transmission. A high degree of neuronal excitement and ion channel abnormalities are associated with epilepsy and migraine and antiepileptic drugs are useful in treating both disorders. The coexistence of epilepsy and migraine may occur independently in the same individual or the two may be causally connected. The relationship between cortical spreading depression (CSD) and epileptic foci has been suggested by basic and clinical neuroscience research. The most relevant psychiatric comorbidities associated with migraine are anxiety and mood disorders, which influence its clinical course, treatment response, and clinical outcome. The association between migraine and major depressive disorder can be explained by a robust molecular genetic background. In addition to its role as a potent vasodilator, CGRP is also involved in the transmission of nociception, a phenomenon inevitably linked with the stress and anxiety caused by frequent migraine attacks. Another aspect is the role of gut microbiome in migraine’s pathology and the gut–brain axis involvement. Irritable bowel syndrome patients are more likely to suffer migraines, according to other studies. There is no precise explanation for how the gut microbiota contributes to neurological disorders in general and migraines in particular. This study aims to show that migraines and comorbid conditions, such as epilepsy, microbiota, or mood disorders, can be connected from the bench to the bedside. It is likely that these comorbid migraine conditions with common pathophysiological mechanisms will have a significant impact on best treatment choices and may provide clues for future treatment options.

Introduction. Many recent studies have suggested that generalised epilepsy is associated with cortical epileptogenic focus, and therefore distinguishing between focal and generalised often becomes difficult. Aim of study. We aimed to detect differences between default mode function in patients with idiopathic generalised epilepsy who have discharges on EEG, and healthy persons. Material and methods. This was a case-control study; we performed EEG analysis with LORETA in 17 patients with a type of generalised epilepsy and a control group represented by 17 healthy age-matched persons. We performed statistical non- -parametric tests for current density electrical distribution for our two groups (‘t-statistic on Log transformed data’) and we defined regions of interest (ROIs) from the default mode network. In the second part, we compared the average activation for each ROI for each timeframe in the epoch for the group with epilepsy, and for controls (we performed a Wilcoxon rank-sum test for two means). Results. In the first part, we obtained that in the medial frontal gyrus (BA 9) delta oscillations significantly differed in patients with epilepsy who had electrical discharges on EEG in resting state conditions compared to healthy controls (medial frontal gyrus in this group had a greater number of synchronously oscillating neurons than did the controls). In the second part, we ran statistics on our localised activity from the default mode network (defined ROIs) and we obtained statistically significant differences in the left medial frontal gyrus (the values were higher for the group with epilepsy, p-value = 0.0066). Conclusions and clinical implications. It may be possible to move from a ‘generalised theory’ about epilepsy to a ‘focused theory’ by understanding how various areas of interest are activated within default mode networks. Insights into the pathophysiology of generalised epilepsy may lead to new treatment options. Introduction. Many recent studies have suggested that generalised epilepsy is associated with cortical epileptogenic focus, and therefore distinguishing between focal and generalised often becomes difficult. Aim of study. We aimed to detect differences between default mode function in patients with idiopathic generalised epilepsy who have discharges on EEG, and healthy persons. Material and methods. This was a case-control study; we performed EEG analysis with LORETA in 17 patients with a type of generalised epilepsy and a control group represented by 17 healthy age-matched persons. We performed statistical non- -parametric tests for current density electrical distribution for our two groups (‘t-statistic on Log transformed data’) and we defined regions of interest (ROIs) from the default mode network. In the second part, we compared the average activation for each ROI for each timeframe in the epoch for the group with epilepsy, and for controls (we performed a Wilcoxon rank-sum test for two means). Results. In the first part, we obtained that in the medial frontal gyrus (BA 9) delta oscillations significantly differed in patients with epilepsy who had electrical discharges on EEG in resting state conditions compared to healthy controls (medial frontal gyrus in this group had a greater number of synchronously oscillating neurons than did the controls). In the second part, we ran statistics on our localised activity from the default mode network (defined ROIs) and we obtained statistically significant differences in the left medial frontal gyrus (the values were higher for the group with epilepsy, p-value = 0.0066). Conclusions and clinical implications. It may be possible to move from a ‘generalised theory’ about epilepsy to a ‘focused theory’ by understanding how various areas of interest are activated within default mode networks. Insights into the pathophysiology of generalised epilepsy may lead to new treatment options.

Background: Recent studies have described unique aspects of default mode network connectivity in patients with idiopathic generalized epilepsy (IGE). A complete background in this field could be gained by combining this research with spectral analysis. Objectives: An important objective of this study was to compare linear connectivity and power spectral densities across different activity bands of patients with juvenile absence epilepsy (JAE), juvenile myoclonic epilepsy (JME), generalized tonic–clonic seizures alone (EGTCSA), and drug-resistant IGE (DR-IGE) with healthy, age-matched controls. Methods: This was an observational case–control study. We performed EEG spectral analysis in MATLAB and connectivity analysis with LORETA for 39 patients with IGE and 12 drug-resistant IGE (DR-IGE) and healthy, age-matched subjects. We defined regions of interest (ROIs) from the default mode network (DMN) and performed connectivity statistics using time-varying spectra for paired samples. Using the same EEG data, we compared mean power spectral density (PSD) with epilepsy subgroups and controls across different activity bands. Results: We obtained a modified value for the mean power spectral density in the beta band for the JME group as follows. The connectivity analysis showed that, in general, there was increased linear connectivity in the DMN for the JAE, JME, and EGCTSA groups compared to the healthy controls. Reduced linear connectivity between regions of the DMN was found for DR-IGE. Conclusions: Spectral analysis of electroencephalography (EEG) for generalized epilepsy syndromes seems to be less informative than connectivity analysis for DMN. DMN connectivity analysis, especially for DR-IGE, opens up the possibility of finding biomarkers related to drug response in IGE.

In recent decades, information technology has grown. Computers have become a daily activity, facilitating access to information, faster communication and faster work. If used responsibly, it has many advantages. Objectives: To explore the potential link between prolonged use of computer input devices—such as keyboards and mice—and the development of compressive neuropathies, including carpal tunnel syndrome (CTS) and cubital tunnel syndrome (CuTS), in individuals whose daily routines are heavily reliant on computer-based activities. Methods: A comprehensive review of the literature was undertaken to assess the correlation between the use of computer input devices and the incidence of compressive neuropathies in the upper limbs, with particular attention to repetitive strain, ergonomic posture deviations, and personal risk factors. Results: Current evidence indicates a potential association between prolonged computer use and the development of upper limb compressive neuropathies; however, a definitive consensus within the scientific literature remains elusive. Repetitive movements and non-neutral postures appear to be significant contributing factors, particularly among individuals with predisposing risk factors. Despite increasing awareness of this issue, standardized, evidence-based clinical guidelines for the evaluation and management of work-related nerve disorders remain lacking. Conclusions: While the relationship between computer use and compressive neuropathies remains debated, healthcare professionals should be aware of the risks, particularly in individuals exposed to repetitive strain and ergonomic stress. Further research and the development of clinical guidelines are needed to better understand and manage these work-related conditions.

Neurologia i Neurochirurgia Polska