Modes Of Electrical Activity Research Articles

Influence of external current and noise on modes of electrical activities and energy of Hindmarsh-Rose model coupled by memristive synapses

The progress of medicine and biological have lengthen life, thus increasing the incidence of degenerative illnesses such as Parkinson, Alzheimer. To help patients suffering from those illnesses, we can use a therapy technique which consists to deliver within a precise region of the central nervous system an electrical signal in order to regulate unnatural impulses. That therapeutic method, since it requires surgical procedure is only needed when medication stops to have effect on the patients. In this work, we study the effects of periodic external current and noise on the modes of electrical activities; Furthermore we estimate the energy of a 2D Hindmarsh-Rose coupled by memristive synapses. Results show that the neuronal network exhibits bursting regime in the presence of periodic external force and noise. Noises make those bursts irregular over time evolution. Concerning the energy analysis, we observe an increase of the energy when the amplitude of the external force increases. Lastly, we show that noise makes the energy of the neuronal network to oscillate with different amplitudes. Large amplitude is observed in the presence of large values of the amplitude of the noise.

Investigation of an improved FitzHugh-Rinzel neuron and its multiplier-less circuit implementation.

Circuit implementation of the mathematical model of neurons represents an alternative approach for the validation of their dynamical behaviors for their potential applications in neuromorphic engineering. In this work, an improved FitzHugh-Rinzel neuron, in which the traditional cubic nonlinearity is swapped with a sine hyperbolic function, is introduced. This model has the advantage that it is multiplier-less since the nonlinear component is just implemented with two diodes in anti-parallel. The stability of the proposed model revealed that it has both stable and unstable nodes around its fixed points. Based on the Helmholtz theorem, a Hamilton function that enables the estimation of the energy released during the various modes of electrical activity is derived. Furthermore, numerical computation of the dynamic behavior of the model revealed that it was able to experience coherent and incoherent states involving both bursting and spiking. In addition, the simultaneous appearance of two different types of electric activity for the same neuron parameters is also recorded by just varying the initial states of the proposed model. Finally, the obtained results are validated using the designed electronic neural circuit, which has been analyzed in the Pspice simulation environment.

Modes of electrical activities and energy of Hindmarsh–Rose model coupled by memristive synapses

Modes of electrical activities and energy of Hindmarsh–Rose model coupled by memristive synapses

Dynamical response of a neuron–astrocyte coupling system under electromagnetic induction and external stimulation**Project supported by the National Natural Science Foundation of China (Grant No. 11772242) and China Postdoctoral Science Foundation (Grant No. 2018M631140).

Previous studies have observed that electromagnetic induction can seriously affect the electrophysiological activity of the nervous system. Considering the role of astrocytes in regulating neural firing, we studied a simple neuron–astrocyte coupled system under electromagnetic induction in response to different types of external stimulation. Both the duration and intensity of the external stimulus can induce different modes of electrical activity in this system, and thus the neuronal firing patterns can be subtly controlled. When the external stimulation ceases, the neuron will continue to fire for a long time and then reset to its resting state. In this study, “delay” is defined as the delayed time from the firing state to the resting state, and it is highly sensitive to changes in the duration or intensity of the external stimulus. Meanwhile, the self-similarity embodied in the aforementioned sensitivity can be quantified by fractal dimension. Moreover, a hysteresis loop of calcium activity in the astrocyte is observed in the specific interval of the external stimulus when the stimulus duration is extended to infinity, since astrocytic calcium or neuron electrical activity in the resting state or during periodic oscillation depends on the initial state. Finally, the regulating effect of electromagnetic induction in this system is considered. It is clarified that the occurrence of “delay” depends purely on the existence of electromagnetic induction. This model can reveal the dynamic characteristics of the neuron–astrocyte coupling system with magnetic induction under external stimulation. These results can provide some insights into the effects of electromagnetic induction and stimulation on neuronal activity.

A physical view of computational neurodynamics

The nervous system is made of a large number of neurons. Time-varying balance between excitatory and inhibitory neurons is important to activate appropriate modes of electrical activity. A realistic biological neuron is complex, often presenting various electrophysiological activities and diffusive propagation of ions in the cell. Therefore, the physical effects of electromagnetic induction become very important and should be considered when estimating signal encoding and mode selection. Synaptic plasticity and anatomical structure have been developed to enhance the self-adaption of neurons. Thus, the electrical mode with the most effective links and weights can be selected to benefit information encoding and signal propagation between neurons in the network. As a result, the demand for metabolic energy can be greatly reduced. In this review, neuron model setting with biophysical effects, modulation of astrocytes, autapse formation and biological function, synaptic plasticity, memristive synapses, and field coupling between neurons and networks are reviewed briefly to provide guidance in the field of neurodynamics.

Electrical Activity in a Time-Delay Four-Variable Neuron Model under Electromagnetic Induction.

To investigate the effect of electromagnetic induction on the electrical activity of neuron, the variable for magnetic flow is used to improve Hindmarsh–Rose neuron model. Simultaneously, due to the existence of time-delay when signals are propagated between neurons or even in one neuron, it is important to study the role of time-delay in regulating the electrical activity of the neuron. For this end, a four-variable neuron model is proposed to investigate the effects of electromagnetic induction and time-delay. Simulation results suggest that the proposed neuron model can show multiple modes of electrical activity, which is dependent on the time-delay and external forcing current. It means that suitable discharge mode can be obtained by selecting the time-delay or external forcing current, which could be helpful for further investigation of electromagnetic radiation on biological neuronal system.

Autaptic Modulation of Electrical Activity in a Network of Neuron-Coupled Astrocyte

Autapse connection is considered on a biological neuron coupled by astrocyte, and the effect of autapse driving-induced response in electrical activities is investigated. In this paper, a simple network is developed on the Hodgkin-Huxley (HH) neuron coupled by astrocyte and the autapse effect is also considered. The modulation of autapse connected to HH neuron can change the membrane potential by applying time-delayed feedback along a close loop. It is found that the self-adaption of autapse driving can make the network of neuron-astrocyte generate different modes of electrical activities, and oscillating behavior of Ca2+and IP3setting is controlled. This new network model can give potential understanding about self-adaption of neuron to external forcing when the coupling of astrocyte and autapse is considered.

Formation of Autapse Connected to Neuron and Its Biological Function

Autapse is a specific synapse connected to the neuron via close loop, and its functional adjusting is described by applying time-delayed feedback on the membrane potential of the neuron. This paper discussed the possible formation mechanism and biological function of autapse connection on neurons. We believe that the formation and growth of autapse connected to neuron can be associated with injury on axon and blocking in signal transmission; thus auxiliary loop is developed to form an autapse. When autapse is set up, it can propagate the signals and change the modes of electrical activities under self-adaption. Based on the cable neuron model, the injury on axon is generated by poisoning and blocking in ion channels (of sodium); thus the conductance of ion channels are changed to form injury-associated defects. Furthermore, auxiliary loop with time delay is designed to restore and enhance signal propagation by setting different time delays and feedback gains. The numerical studies confirmed that appropriate time delay and feedback gain in electric or chemical autapse can help signal (or wave generated by external forcing) propagation across the blocked area. As a result, formation of autapse could be dependent on the injury of neuron and further enhances the self-adaption to external stimuli.

Dynamical responses in a new neuron model subjected to electromagnetic induction and phase noise

Abstract Complex electrical activities in neuron can induce time-varying electromagnetic field and the effect of various electromagnetic inductions should be considered in dealing with electrical activities of neuron. Based on an improved neuron model, the effect of electromagnetic induction is described by using magnetic flux, and the modulation of magnetic flux on membrane potential is realized by using memristor coupling. Furthermore, additive phase noise is imposed on the neuron to detect the dynamical response of neuron and phase transition in modes. The dynamical properties of electrical activities are detected and discussed, and double coherence resonance behavior is observed, respectively. Furthermore, multiple modes of electrical activities can be observed in the sampled time series for membrane potential of the neuron model.

Multiple modes of electrical activities in a new neuron model under electromagnetic radiation

The three-variable Hindmarsh–Rose model is improved to describe the dynamical behaviors of neuronal activities with electromagnetic induction being considered, and the mode transition of electrical activities in neuron are detected when external electromagnetic radiation is imposed on the neuron. The improved neuron model holds more bifurcation parameters and the mode of electric activities can be selected in larger parameter region. It is found that the electromagnetic radiation can excite quiescent neuron but also can suppress the electrical activities in neuron as well. Particularly, it is important to find that multiple modes of electrical activities can emerge alternatively, and these results are consistent with biological experiments.

An interlocked oscillator model for firing of the mesencephalic dopaminergic neuron.

Dopaminergic (DA) neurons display two functionally distinct modes of electrical activity: low- and high-frequency firing. We suggest a new minimal computational model that unites data on these firing modes obtained under different experimental conditions. The model reproduces the separation of maximal frequencies under NMDA synaptic stimulation vs. other treatments. In accord to recent experimental data, NMDA stimulation restricted to the soma effectively evokes high-frequency oscillations in the model. We have also reproduced low- and high-frequency oscillations under blockade of the SK current. Thus, the new model suggests a way that overcomes all major limitations of the switching dominance mechanism for controlling the frequency of the DA neuron. We explain recent experimental facts and make further predictions.

Frequency switching in a two-compartmental model of the dopaminergic neuron

Mid-brain dopaminergic (DA) neurons display two functionally distinct modes of electrical activity: low- and high-frequency firing. The high-frequency firing is linked to important behavioral events in vivo. However, it cannot be elicited by standard manipulations in vitro. We had suggested a two-compartmental model of the DA cell that united data on firing frequencies under different experimental conditions. We now analyze dynamics of this model. The analysis was possible due to introduction of timescale separation among variables. We formulate the requirements for low and high frequencies. We found that the modulation of the SK current gating controls the frequency rise under applied depolarization. This provides a new mechanism that limits the frequency in the control conditions and allows high-frequency responses to depolarization if the SK current gating is downregulated. The mechanism is based on changing Ca(2+) balance and can also be achieved by direct modulation of the balance. Interestingly, such changes do not affect the high-frequency oscillations under NMDA. Therefore, altering Ca(2+) balance allows combining the high-frequency response to NMDA activation with the inability of other treatments to effectively elevate the frequency. We conclude that manipulations affecting Ca(2+) balance are most effective in controlling the frequency range. This modeling prediction gives a clue to the mechanism of the high-frequency firing in the DA neuron in vivo and in vitro.

Bistability and its regulation by serotonin in the endogenously bursting neuron R15 in Aplysia.

1. Previous computational studies of models of neuron R15 in Aplysia have indicated that several distinct modes of electrical activity may coexist at a given set of parameters, that this multistability can be modulated by transmitters such as serotonin (5-HT) and that brief perturbations of the membrane potential can induce persistent changes in the mode of electrical activity. To test these predictions, the responses of R15 neurons to injections of brief (1.5 s) current pulses were recorded intracellularly in the absence and presence of 5-HT. 2. In the absence of 5-HT, brief perturbations induced abrupt transitions in the electrical activity from bursting to beating. Such transitions were observed in approximately 20% of the cases. The duration of beating activity varied from several seconds to tens of minutes. In the presence of low concentrations (1 microM) of 5-HT, both the probability of mode transitions and the duration of induced beating activity increased significantly. 3. These results indicate that at least two stable modes of electrical activity can coexist in R15 neurons and that this bistability can be regulated by 5-HT. In general, these conclusions agree with the results from analyses of mathematical models of R15. Although the function of these dynamic properties in R15 is speculative, our results, interpreted on the background of the model, support the notion that nonlinear dynamical properties of individual neurons can endow them with richer forms of information processing than has generally been appreciated.

Nonlinear dynamics in a model neuron provide a novel mechanism for transient synaptic inputs to produce long-term alterations of postsynaptic activity

1. A mathematical model of a bursting molluscan neuron has been found to possess multiple modes of electrical activity, such as periodic beating (tonic firing), periodic bursting (bursts of action potentials separated by quiescent periods), and potentially chaotic bursting, all at a single set of parameters. The multiple modes correspond to multiple stable attractors, whose existence is an emergent property of the nonlinear dynamics of the system. 2. Transient synaptic inputs can switch the activity of the neuron between different modes. These mode transitions, which do not require any changes in the biochemical or biophysical parameters of the neuron, provide an enduring response to a transient input, as well as a mechanism for phasic sensitivity (i.e., temporal specificity). 3. These results provide new insights into the role of nonlinear dynamics in information processing and storage at the level of the single neuron.

Role of Nonlinear Dynamical Properties of a Modelled Bursting Neuron in Information Processing and Storage

Enduring changes in the electrical activity of individual neurons have generally been attributed to persistent modulation of one or more of the biophysical parameters that govern neuronal membrane conductances. An implicit assumption has been that once all parameters are fixed, the ultimate mode of electrical activity exhibited is determined. An alternative possibility is that several stable modes of activity coexist at a single set of parameters and that transient perturbations could switch the neuron from one stable mode of activity to another. By using a realistic mathematical model and computer simulations of the R15 neuron in Aplysia, we identified a new, and potentially fundamental, role for nonlinear dynamics in information processing and storage at the single-cell level. We found that transient synaptic input could shift the dynamic activity of the neuron among as many as eight different patterns, or modes, of activity. Once established, each mode persisted indefinitely or until subsequent synaptic input perturbed the neuron into another mode. We also investigated the ways in which changes in a model parameter, the slow inward calcium conductance (gSI), affected not only the intrinsic activity of R15 but also the ability of the neuron to exhibit parameter-independent mode transitions. gSI was selected since it is a key determinant of bursting activity and, also, because it is known to be modulated by dopamine and serotonin. We found that small changes in this parameter could annihilate or create coexisting modes of electrical activity. These results provide new insights into the role of nonlinear dynamics in information processing and storage at the level of the single neuron and indicate that individual neurons can have extensive parameter-independent plastic capabilities in addition to the more extensively analyzed parameter-dependent ones.

Routes to chaos in a model of a bursting neuron

Chaotic regimens have been observed experimentally in neurons as well as in deterministic neuronal models. The R15 bursting cell in the abdominal ganglion of Aplysia has been the subject of extensive mathematical modeling. Previously, the model of Plant and Kim has been shown to exhibit both bursting and beating modes of electrical activity. In this report, we demonstrate (a) that a chaotic regime exists between the bursting and beating modes of the model, and (b) that the model approaches chaos from both modes by a period doubling cascade. The bifurcation parameter employed is the external stimulus current. In addition to the period doubling observed in the model-generated trajectories, a period three "window" was observed, power spectra that demonstrate the approaches to chaos were generated, and the Lyaponov exponents and the fractal dimension of the chaotic attractors were calculated. Chaotic regimes have been observed in several similar models, which suggests that they are a general characteristic of cells that exhibit both bursting and beating modes.