Despite recent advances in the reconstruction of biological neural networks, the generative principles underlying the structural properties of these networks remain incompletely understood. Neurons in the brain belonging to different functional class...
Conventional deep learning models rely heavily on the McCulloch–Pitts (MCP) neuron, limiting their interpretability and biological plausibility. The Dendritic Neuron Model (DNM) offers a more realistic alternative by simulating nonlinear and co...
The mechanism of brain information processing unfolds within spatial and temporal domains inherently linked to the concept of space–time symmetry. Biological evolution, beginning with the prevalent molecular chirality, results in the handedness...
To mimic the homeostatic functionality of biological neurons, a split-gate field-effect transistor (S-G FET) with a charge trap layer is proposed within a neuron circuit. By adjusting the number of charges trapped in the Si3N4 layer, the threshold vo...
In this paper, a method of generating controllable spikes utilizing symmetric semiconductor ring lasers (SRLs) is investigated, and various optical behaviors of biological neurons are successfully emulated on a faster timescale. We demonstrate the sy...
Advances in neuroscience have been closely linked to mathematical modeling beginning with the integrate-and-fire model of Lapicque and proceeding through the modeling of the action potential by Hodgkin and Huxley to the current era. The fundamental b...
Simulated spiking neural networks have been explored for over a hundred years. Many of these networks are driven by biological considerations and an attempt to simulate brains, but others are used with little biological consideration. This paper give...
Spike structures appear in several phenomena, whereas spike trains (STs) are of particular importance, since they can carry temporal encoding of information. Regarding the STs of the biological neuron type, several models have already been proposed....
Antioxidant activity and neuroprotective activity of three stilbenoids, namely, trans-4-hydroxystilbene (THS), trans-3,5,4′-trihydroxy-stilbene (resveratrol, RES), and trans-3′,4′,3,5-tetrahydroxy-stilbene (piceatannol, PIC), agains...
Time crystal was conceived in the 1970s as an autonomous engine made of only clocks to explain the life-like features of a virus. Later, time crystal was extended to living cells like neurons. The brain controls most biological clocks that regenerate...
The classification of biological neuron types and networks poses challenges to the full understanding of the human brain’s organisation and functioning. In this paper, we develop a novel objective classification model of biological neuronal mor...
Salt, commonly known as sodium chloride, is an important ingredient that the body requires in relatively minute quantities. However, consuming too much salt can lead to high blood pressure, heart disease and even disruption of circadian rhythms. The...
Parkinson’s disease (PD) is one of the most common neurodegenerative disease characterized by a specific and progressive loss of dopaminergic (DA) neurons and dopamine, causing motor dysfunctions and impaired movements. Unfortunately, available thera...
Neurons are crucial components of neural networks, but implementing biologically accurate neuron models in hardware is challenging due to their nonlinearity and time variance. This paper introduces the SC-IZ neuron model, a low-cost digital implement...
JNK is a protein kinase, which induces transactivation of c-jun. The three isoforms of JNK, JNK1, JNK2, and JNK3, are encoded by three distinct genes. JNK1 and JNK2 are expressed ubiquitously throughout the body. By contrast, the expression of JNK3 i...
We report the design of a Spiking Neural Network (SNN) edge detector with biologically inspired neurons that has a conceptual similarity with both Hodgkin-Huxley (HH) model neurons and Leaky Integrate-and-Fire (LIF) neurons. The computation of the me...
Recreational use of synthetic cannabinoids (SCs) before and during pregnancy poses a major public health risk, due to the potential onset of neurodevelopmental disorders in the offspring. Herein, we report the assessment of the neurotoxic potential o...
Background: Translational circuit neuroscience delivers many candidate neurons whose manipulation could ameliorate psychiatric symptoms. However, the translation of these cellular targets into molecular targets—proteins selectively expressed in...
Gold nanoparticles (AuNPs) are one of the most remarkable nanomaterials. Due to their small size, these NPs can cross the blood–brain barrier making them good candidates for the treatment of diseases related to the central nervous system. The m...
Design and implementation of biological neural networks is a vital research field in the neuromorphic engineering. This paper presents LUT-based modeling of the Adaptive Exponential integrate-and-fire (ADEX) model using Nyquist frequency method. In t...
A new process for obtaining dibenzo[c,f][1,2,5]thiadiazepines (DBTDs) and their effects on GABAA receptors of guinea pig myenteric neurons are described. Synthesis of DBTD derivatives began with two commercial aromatic compounds. An azide group was o...
Magnetoencephalography (MEG) has revolutionized neuroscience, offering a tool with [...]
Integrated information theory (IIT) is a powerful tool that provides a framework for evaluating consciousness, whether in the human brain or in other systems. In Computing the Integrated Information of a Quantum Mechanism, the authors extend IIT from...
Inspired by the adaptation phenomenon of neuronal firing, we propose the regularity normalization (RN) as an unsupervised attention mechanism (UAM) which computes the statistical regularity in the implicit space of neural networks under the Minimum D...
Biological sex influences disease development and progression. The steroid hormone 17β-oestradiol (E2), along with its receptors, is expected to play a major role in the manifestation of sex differences. E2 exerts pleiotropic effects in a system...
In this paper, the transport phenomena of synaptic electric impulses are considered. The FitzHugh–Nagumo and FitzHugh–Rinzel models appear mathematically appropriate for evaluating these scientific issues. Moreover, applications of such m...
In this work, we compare the basketball scoring performance of two imaginary (simulated) mechanical robots in conditions of erroneous information-processing circuits: Machine, whose moves are controlled by a conventional digital computer and Man, con...
The prediction of outcomes following cardiac arrest continues to provide significant difficulties. A preferred strategy involves adopting a multimodal approach, which encompasses the careful evaluation of the biomarker neuron-specific enolase (NSE)....
The aim of this work is to introduce a computer science solution to manage emotions and affections and connect them to the causes as in humans. The scientific foundation of this work lies in the ability to model the affective and emotional states of...
Model optimization in neuroscience has focused on inferring intracellular parameters from time series observations of the membrane voltage and calcium concentrations. These parameters constitute the fingerprints of ion channel subtypes and may identi...
Spiking neural P systems (SNP systems), as computational models abstracted by the biological nervous system, have been a major research topic in biological computing. In conventional SNP systems, the rules in a neuron remain unchanged during the comp...
There is a growing technological interest in combining biological neuronal networks with electronic ones, specifically for biological computation, human–machine interfacing and robotic implants. A major challenge for the development of these technolo...
We present a novel closed-loop system designed to integrate biological and artificial neurons of the oscillatory type into a unified circuit. The system comprises an electronic circuit based on the FitzHugh-Nagumo model, which provides stimulation to...
The molecular structure and dynamics of the neuronal plasma membrane are essential for neuronal biology and function. We employed time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging to investigate the lipid composition and turnover at t...
Motion perception is a fundamental function of biological visual systems, enabling organisms to navigate dynamic environments, detect threats, and track moving objects. Inspired by the mechanisms of biological motion processing, we propose an Unsuper...
Spiking neural networks (SNNs) aim to simulate human neural networks with biologically plausible neurons. However, conventional SNNs based on point neurons ignore the inherent dendritic computation of biological neurons. Additionally, these point neu...
In order to enrich the dynamic behaviors of discrete neuron models and more effectively mimic biological neural networks, this paper proposes a bistable locally active discrete memristor (LADM) model to mimic synapses. We explored the dynamic behavio...
Recently, research on artificial neuron circuits imitating biological systems has been actively studied. The neuron circuit can implement an artificial neural network (ANN) capable of low-power parallel processing by configuring a biological neural n...
The dynamics of signal transmission in neuronal networks remain incompletely understood. In this study, we propose a novel Rulkov neuronal network model that incorporates Q-learning, a reinforcement learning method, to establish efficient signal tran...
We present a novel set of quantitative measures for “likeness” (error function) designed to alleviate the time-consuming and subjective nature of manually comparing biological recordings from electrophysiological experiments with the outcomes of thei...
In this paper, we considered potential benefits of the neuromorphic control technique for solving specific challenges in robotic control. Developing a neuromorphic control system for a robot involves simulating the architecture and dynamics of biolog...
This work presents a new approach based on a spiking neural network for sound preprocessing and classification. The proposed approach is biologically inspired by the biological neuron’s characteristic using spiking neurons, and Spike-Timing-Dependent...
As an important part of the nervous system, the human visual system can provide visual perception for humans. The research on it is of great significance to improve our understanding of biological vision and the human brain. Orientation detection, in...
The past decade has witnessed the great success of deep neural networks in various domains. However, deep neural networks are very resource-intensive in terms of energy consumption, data requirements, and high computational costs. With the recent inc...
Gonadotropin releasing hormone (GnRH) neurons are hypothalamic neuroendocrine cells that control sexual reproduction. During embryonic development, GnRH neurons migrate from the nose to the hypothalamus, where they receive inputs from several afferen...
Zika virus (ZIKV) has recently surged in human populations, causing an increase in congenital and Guillain-Barré syndromes. While sexual transmission and presence of ZIKV in urine, semen, vaginal secretions, and saliva have been established, the orig...
As the key hardware of a brain-like chip based on a spiking neuron network (SNN), memristor has attracted more attention due to its similarity with biological neurons and synapses to deal with the audio signal. However, designing stable artificial ne...
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The biological evidence of neural plasticity implies revisiting the notion of determinism, in general as well as in the psychological dimension. Indeed, through the mechanisms of plasticity, experience leaves a trace in the neuronal network. This vie...
Neuronal migration is a fundamental biological process that underlies proper brain development and neuronal circuit formation. In the developing cerebral cortex, distinct neuronal populations, producing excitatory, inhibitory and modulatory neurotran...
The imitative modelling of processes in the brain of living beings is an ambitious task. However, advances in the complexity of existing hardware brain models are limited by their low speed and high energy consumption. A superconducting circuit with...
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