Revisiting neural information, computing and linking capacity.

Neural information theory represents a fundamental method to model dynamic relations in biological systems. However, the notion of information, its representation, its content and how it is processed are the subject of fierce debates. Since the limiting capacity of neuronal links strongly depends on how neurons are hypothesized to work, their operating modes are revisited by analyzing the differences between the results of the communication models published during the past seven decades and those of the recently developed generalization of the classical information theory.

The impact of SARS-CoV-2 infection on the outcome of acute ischemic stroke-A retrospective cohort study.

Background: Acute ischemic stroke (AIS) is a common complication of severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) infection (COVID-19), but the prognosis of these patients is poorly understood.

Purpose: To explore the impact of COVID-19 on neurological outcomes in AIS patients.

Methods: A comparative retrospective cohort study was conducted in 32 consecutive AIS patients with and 51 without COVID-19 between the 1st of March 2020 and 1st of May 2021.

On the Role of Speed in Technological and Biological Information Transfer for Computations.

In all kinds of implementations of computing, whether technological or biological, some material carrier for the information exists, so in real-world implementations, the propagation speed of information cannot exceed the speed of its carrier. Because of this limitation, one must also consider the transfer time between computing units for any implementation. We need a different mathematical method to consider this limitation: classic mathematics can only describe infinitely fast and small computing system implementations.

Towards Generalizing the Information Theory for Neural Communication.

Neuroscience extensively uses the information theory to describe neural communication, among others, to calculate the amount of information transferred in neural communication and to attempt the cracking of its coding. There are fierce debates on how information is represented in the brain and during transmission inside the brain. The neural information theory attempts to use the assumptions of electronic communication; despite the experimental evidence that the neural spikes carry information on non-discrete states, they have shallow communication speed, and the spikes' timing precision matters.

Short-Term Amygdala Low-Frequency Stimulation Does not Influence Hippocampal Interneuron Changes Observed in the Pilocarpine Model of Epilepsy.

Temporal lobe epilepsy (TLE) is characterized by changes in interneuron numbers in the hippocampus. Deep brain stimulation (DBS) is an emerging tool to treat TLE seizures, although its mechanisms are not fully deciphered. We aimed to depict the effect of amygdala DBS on the density of the most common interneuron types in the CA1 hippocampal subfield in the lithium-pilocarpine model of epilepsy.

Amygdala Low-Frequency Stimulation Reduces Pathological Phase-Amplitude Coupling in the Pilocarpine Model of Epilepsy.

Temporal-lobe epilepsy (TLE) is the most common type of drug-resistant epilepsy and warrants the development of new therapies, such as deep-brain stimulation (DBS). DBS was applied to different brain regions for patients with epilepsy; however, the mechanisms of action are not fully understood. Therefore, we tried to characterize the effect of amygdala DBS on hippocampal electrical activity in the lithium-pilocarpine model in male Wistar rats.