In recent decades, there has been a growing interest in the impact of electric fields generated in the brain. Transmembrane ionic currents originate electric fields in the extracellular space and are capable of affecting nearby neurons, a phenomenon called ephaptic neuronal communication. In the present work, the Quadratic Integrated-and-Fire model (QIF-E) underwent an adjustment/improvement to include the ephaptic entrainment behavior between neurons and electric fields. Indeed, the aim of our study is to validate the QIF-E model, which is a model to estimate the influence of electric fields on neurons. For this purpose, we evaluated whether the main properties observed in an experiment by Anastassiou et al. (Nat Neurosci 14:217–223, 2011), which analyzed the effect of an electric field on cortical pyramidal neurons, are reproduced with the QIF-E model. In this way, the analysis tools are employed according to the neuronal activity regime: (i) for the subthreshold regime, the circular statistic is used to describe the phase differences between the input stimulus signal (electrode) and the modeled membrane response; (ii) in the suprathreshold regime, the Population Vector and the Spike Field Coherence are used to estimate phase preferences and the entrainment intensity between the input stimulus and Action Potentials. The results observed are (i) in the subthreshold regime the values of the phase differences change with distinct frequencies of the input stimulus; (ii) in the supra-threshold regime the preferential phase of Action Potentials changes for different frequencies. In addition, we explore other parameters of the model, such as noise and membrane characteristic-time, in order to understand different types of neurons and extracellular environment related to ephaptic communication. Such results are consistent with results observed in empirical experiments based on ephaptic phenomenon. In addition, the QIF-E model allows further studies on the physiological importance of ephaptic communication in the brain, and its simplicity may open a door to simulate the ephaptic response in neuronal networks and assess the impact of ephaptic communication in such scenarios.

Schistosomiasis is caused by Schistosoma mansoni and is a public health problem in Brazil. The typical granulomatous lesion is associated with the increase in the oxidative damage by generation of free radicals. The aim of this work was to correlate some oxidative stress markers with the worm burden on carriers of schistosomiasis (n = 30) in the acute phase in comparison to healthy subjects (n = 30). The pro-oxidant parameter used was the colorimetric quantification of reactive substances to thiobarbituric acid, while the antioxidant markers used were blood content of reduced glutathione and determination of the activity of catalase. The worm burden was assessed by Kato-Katz method. The results pointed out that initially there was no difference in the catalase activity. However, there was a positive correlation between the increase in parasitic load and intensity of lipid peroxidation, and decrease in the content of reduced glutathione. Additionally, only the aspartate aminotransferase levels presented to be high, while there was a decrease in bilirubin level. Therefore, a possible association between the establishment of the oxidative stress in tissue and the parasitic load of Schistosoma mansoni is suggested.

The large number of neurons in the human brain are connected to form a functionally specialize system. The brain is typically understood as a complex network system with a particular organization and topology that can functionally result in specific electrophysiological patterns. Among all the dynamic elements resulting from the circuits of the brain’s network, ephapticity is a barely explored cellular mechanism. In this work, we investigated, through numerical simulation, the relationship between alterations in ephaptic neuronal communication and preference for frequency peak entrainment, when the electrophysiological properties of the neuronal membrane are impaired. This change in frequency band amplitude is observed in some neurodegenerative diseases, such as Parkinson’s Disease (increased amplitude in the β band) or Alzheimer’s Disease (increased amplitude in the β, θ and δ bands). In this context, a damaged model was proposed based on the impairment of both in the resistance of the ion channels (b) and in the capacitance of the lipid membrane (h). With the new parameters, b and h, the ephaptic communication is simulated using the hybrid neural model Integrate-and-Fire Quadratic Ephaptic (QIF-E). Our results show a link between the peak entrainment (ephapticity) preference shifted to some frequency band when the damage occurs mainly in ion channels (b). Finally, possible relationships of ephaptic communication and neurodegenerative diseases associated with aging factors are discussed.

The brain is commonly understood as a complex network system with a particular organization and topology that can result in specific electrophysiological patterns. Among all the dynamic elements resulting from the circuits of the brain’s network, ephapticity is a cellular communication mechanism that has received little attention. To understand the network’s properties of ephaptic entrainment, we start investigating the ephaptic effect on a single neuron. In this study, we used numerical simulations to examine the relationship between alterations in ephaptic neuronal entrainment and impaired electrophysiological properties of the neuronal membrane, which can occur via spike field coherence (SFC). This change in frequency band amplitude is observed in some neurodegenerative diseases, such as Parkinson’s or Alzheimer’s. To further investigate these phenomena, we proposed a damaged model based on the impairment of both the resistance of the ion channels and the capacitance of the lipid membrane. Therefore, we simulated ephaptic entrainment with the hybrid neural model quadratic integrate-and-fire ephaptic (QIF-E), which mimics an ephaptic entrainment generated by an LFP (simulate a neuronal group). Our results indicate a link between peak entrainment (ephapticity) preference and a shift in frequency band when damage occurs mainly in ion channels. Finally, we discuss possible relationships between ephaptic entrainment and neurodegenerative diseases associated with aging factors.

In recent decades, there has been growing interest in the impact of electric fields generated in the brain. Transmembrane ionic currents originate electric fields in the extracellular space and are capable of affecting nearby neurons, a phenomenon called ephaptic neuronal communication. In the present work, the Quadratic Integrate-and-Trigger model (QIF-E) underwent an adjustment/improvement to include the ephaptic coupling behavior between neurons and their results are compared to the empirical results. In this way, the analysis tools are employed according to the neuronal activity regime: (i) for the subthreshold regime, the circular statistic is used to describe the phase differences between the input stimulus signal and the modeled membrane response; (ii) in the suprathreshold regime, the Population Vector and the Spike Field Coherence are employed to estimate phase preferences and the coupling intensity between the input stimulus and the Action Potentials. The results observed are i) in the subthreshold regime the values of the phase differences change with distinct frequencies of an input stimulus; ii) in the supra-threshold regime the preferential phase of Action Potentials changes for different frequencies. In addition, we explore other parameters of the model, such as noise and membrane characteristic-time, in order to understand different types of neurons and extracellular environment related to ephaptic communication. Such results are consistent with results observed in empirical experiments based on ephaptic coupling behavior. In addition, the QIF-E model allows further studies on the physiological importance of ephaptic coupling in the brain, and its simplicity can open a door to simulating ephaptic coupling in neuron networks and evaluating the impact of ephaptic communication in such scenarios.