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In this paper, bidirectional-coupled neurons through an asymmetric electrical synapse are investigated. These coupled neurons involve 2D Hindmarsh–Rose (HR) and 2D FitzHugh–Nagumo (FN) neurons. The equilibria of the coupled neurons model are investigated, and their stabilities have revealed that, for some values of the electrical synaptic weight, the model under consideration can display either self-excited or hidden firing patterns. In addition, the hidden coexistence of chaotic bursting with periodic spiking, chaotic spiking with period spiking, chaotic bursting with a resting pattern, and the coexistence of chaotic spiking with a resting pattern are also found for some sets of electrical synaptic coupling. For all the investigated phenomena, the Hamiltonian energy of the model is computed. It enables the estimation of the amount of energy released during the transition between the various electrical activities. Pspice simulations are carried out based on the analog circuit of the coupled neurons to support our numerical results. Finally, an STM32F407ZE microcontroller development board is exploited for the digital implementation of the proposed coupled neurons model.

Biological neurons keep sensitive to external stimuli and appropriate firing modes can be triggered to give effective response to external chemical and physical signals. A piezoelectric neural circuit can perceive external voice and nonlinear vibration by generating equivalent piezoelectric voltage, which can generate an equivalent trans-membrane current for inducing a variety of firing modes in the neural activities. Biological neurons can receive external stimuli from more ion channels and synapse synchronously, but the further encoding and priority in mode selection are competitive. In particular, noisy disturbance and electromagnetic radiation make it more difficult in signals identification and mode selection in the firing patterns of neurons driven by multi-channel signals. In this paper, two different periodic signals accompanied by noise are used to excite the piezoelectric neural circuit, and the signal processing in the piezoelectric neuron driven by acoustic waves under noise is reproduced and explained. The physical energy of the piezoelectric neural circuit and Hamilton energy in the neuron driven by mixed signals are calculated to explain the biophysical mechanism of auditory neuron when external stimuli are applied. It is found that the neuron prefers to respond to the external stimulus with higher physical energy and the signal which can increase the Hamilton energy of the neuron. For example, stronger inputs used to inject higher energy and it is detected and responded more sensitively. The involvement of noise is helpful to detect the external signal under stochastic resonance, and the additive noise changes the excitability of neuron as the external stimulus. The results indicate that energy controls the firing patterns and mode selection in neurons, and it provides clues to control the neural activities by injecting appropriate energy into the neurons and network.

Two different bifurcation scenarios of firing patterns with decreasing extracellular calcium concentrations were observed in identical sciatic nerve fibers of a chronic constriction injury (CCI) model when the extracellular 4-aminopyridine concentrations were fixed at two different levels. Both processes proceeded from period-1 bursting to period-1 spiking via complex or simple processes. Multiple typical experimental examples manifested dynamics closely matching those simulated in a recently proposed 4-dimensional model to describe the nonlinear dynamics of the CCI model, which included most cases of the bifurcation scenarios. As the extracellular 4-aminopyridine concentrations is increased, the structure of the bifurcation scenario becomes more complex. The results provide a basic framework for identifying the relationships between different neural firing patterns and different bifurcation scenarios and for revealing the complex nonlinear dynamics of neural firing patterns. The potential roles of the basic bifurcation structures in identifying the information process mechanism are discussed.

Healthy brains display a wide range of firing patterns, from synchronized oscillations during slow-wave sleep to desynchronized firing during movement. These physiological activities coexist with periods of pathological hyperactivity in the epileptic brain, where neurons can fire in synchronized bursts. Most cortical neurons are pyramidal regular spiking (RS) cells with frequency adaptation and do not exhibit bursts in current-clamp experiments (in vitro). In this work, we investigate the transition mechanism of spike-to-burst patterns due to slow potassium and calcium currents, considering a conductance-based model of a cortical RS cell. The joint influence of potassium and calcium ion channels on high synchronous patterns is investigated for different synaptic couplings (gsyn) and external current inputs (I). Our results suggest that slow potassium currents play an important role in the emergence of high-synchronous activities, as well as in the spike-to-burst firing pattern transitions. This transition is related to the bistable dynamics of the neuronal network, where physiological asynchronous states coexist with pathological burst synchronization. The hysteresis curve of the coefficient of variation of the inter-spike interval demonstrates that a burst can be initiated by firing states with neuronal synchronization. Furthermore, we notice that high-threshold (IL) and low-threshold (IT) ion channels play a role in increasing and decreasing the parameter conditions (gsyn and I) in which bistable dynamics occur, respectively. For high values of IL conductance, a synchronous burst appears when neurons are weakly coupled and receive more external input. On the other hand, when the conductance IT increases, higher coupling and lower I are necessary to produce burst synchronization. In light of our results, we suggest that channel subtype-specific pharmacological interactions can be useful to induce transitions from pathological high bursting states to healthy states.

Reelin is a large extracellular glycoprotein that is secreted by Cajal-Retzius cells during embryonic development to regulate neuronal migration and cell proliferation but it also seems to regulate ion channel distribution and synaptic vesicle release properties of excitatory neurons well into adulthood. Mouse mutants with a compromised reelin signaling cascade show a highly disorganized neocortex but the basic connectional features of the displaced excitatory principal cells seem to be relatively intact. Very little is known, however, about the intrinsic electrophysiological and morphological properties of individual cells in the reeler cortex. Repetitive burst-spiking (RB) is a unique property of large, thick-tufted pyramidal cells of wild type layer Vb exclusively, which project to several subcortical targets. In addition, they are known to possess sparse but far-reaching intracortical recurrent collaterals. Here, we compared the electrophysiological properties and morphological features of neurons in the reeler primary somatosensory cortex with those of wild type controls. Whereas in wild type mice RB pyramidal cells were only detected in layer Vb, the vast majority of reeler RB pyramidal cells were found in the superficial third of the cortical depth. There were no obvious differences in the intrinsic electrophysiological properties and basic morphological features (like soma size or number of dendrites) were also well preserved. However, the spatial orientation of the entire dendritic tree was highly variable in reeler neocortex whereas it was completely stereotyped in wild type mice. It seems that basic quantitative features of layer Vb-fated RB pyramidal cells are well conserved in the highly disorganized mutant neocortex whereas qualitative morphological features vary, possibly to properly orient toward the appropriate input pathways, which are known to show an atypical oblique path through the reeler cortex. The oblique dendritic orientation thus presumably reflects a re-orientation of dendritic input domains toward spatially highly disorganized afferent projections.

The γ-aminobutyric acid neurons（GABAergic neurons） in the inferior colliculus are classified into various patterns based on their intrinsic electrical properties to a constant current injection. Although this classification is associated with physiological function, the exact role for neurons with various firing patterns in acoustic processing remains poorly understood. In the present study, we analyzed characteristics of inferior colliculus neurons in vitro, and recorded responses to stimulation of the dorsal nucleus of the lateral lemniscus using the wholecell patch clamp technique. Seven inferior colliculus neurons were tested and were classified into two firing patterns： sustained-regular（n = 4） and sustained-adapting firing patterns（n = 3）. The majority of inferior colliculus neurons exhibited slight changes in response to stimulation and bicuculline. The responses of one neuron with a sustained-adapting firing pattern were suppressed after stimulation, but recovered to normal levels following application of the γ-aminobutyric acid receptor antagonist. One neuron with a sustained-regular pattern showed suppressed stimulation responses, which were not affected by bicuculline. Results suggest that GABAergic neurons in the inferior colliculus exhibit sustained-regular or sustained-adapting firing patterns. Additionally, GABAergic projections from the dorsal nucleus of the lateral lemniscus to the inferior colliculus are associated with sound localization. The different neuronal responses of various firing patterns suggest a role in sound localization. A better understanding of these mechanisms and functions will provide better clinical treatment paradigms for hearing deficiencies.

Human induced pluripotent stem cells (hiPSCs) are a promising approach to study neurological and neuropsychiatric diseases. Most methods to record the activity of these cells have major drawbacks as they are invasive or they do not allow single cell resolution. Genetically encoded voltage indicators (GEVIs) open the path to high throughput visualization of undisturbed neuronal activity. However, conventional GEVIs perturb membrane integrity through inserting multiple copies of transmembrane domains into the plasma membrane. To circumvent large add-ons to the plasma membrane, we used a minimally invasive novel hybrid dark quencher GEVI to record the physiological and pathological firing patterns of hiPSCs-derived sensory neurons from patients with inherited erythromelalgia, a chronic pain condition associated with recurrent attacks of redness and swelling in the distal extremities. We observed considerable differences in action potential firing patterns between patient and control neurons that were previously overlooked with other recording methods. Our system also performed well in hiPSC-derived forebrain neurons where it detected spontaneous synchronous bursting behavior, thus opening the path to future applications in other cell types and disease models including Parkinson’s disease, Alzheimer’s disease, epilepsy, and schizophrenia, conditions associated with disturbances of neuronal activity and synchrony.

Inter-discharge interval distribution modeling of the motor unit firing pattern plays an important role in electromyographic decomposition and the statistical analysis of firing patterns. When modeling firing patterns obtained from automatic procedures, false positives and false negatives can be taken into account to enhance performance in estimating firing pattern statistics. Available models of this type, however, are only approximate and use Gaussian distributions, which are not strictly suitable for modeling renewal point processes. In this paper, the theory of point processes is used to derive an exact solution to the distribution when a gamma distribution is used to model the physiological firing pattern. Besides being exact, the solution provides a way to model the skewness of the inter-discharge distribution, and this may make it possible to obtain a better fit with available experimental data. In order to demonstrate potential applications of the model, we use it to obtain a maximum likelihood estimator of firing pattern statistics. Our tests found this estimator to be reliable over a wide range of firing conditions, whether dealing with real or simulated firing patterns, the proposed solution had better agreement than other models.

The membranes of auditory and vestibular afferent neurons each contain diverse groups of ion channels that lead to heterogeneity in their intrinsic biophysical properties. Pioneering work in both auditory- and vestibular-ganglion physiology have individually examined this remarkable diversity, but there are few direct comparisons between the two ganglia. Here the firing patterns recorded by whole-cell patch-clamping in neonatal vestibular- and spiral ganglion neurons are compared. Indicative of an overall heterogeneity in ion channel composition, both ganglia exhibit qualitatively similar firing patterns ranging from sustained-spiking to transient-spiking in response to current injection. The range of resting potentials, voltage thresholds, current thresholds, input-resistances, and first-spike latencies are similarly broad in both ganglion groups. The covariance between several biophysical properties (e.g., resting potential to voltage threshold and their dependence on postnatal age) was similar between the two ganglia. Cell sizes were on average larger and more variable in VGN than in SGN. One sub-group of VGN stood out as having extra-large somata with transient-firing patterns, very low-input resistance, fast first-spike latencies, and required large current amplitudes to induce spiking. Despite these differences, the input resistance per unit area of the large-bodied transient neurons was like that of smaller-bodied transient-firing neurons in both VGN and SGN, thus appearing to be size-scaled versions of other transient-firing neurons. Our analysis reveals that although auditory and vestibular afferents serve very different functions in distinct sensory modalities, their biophysical properties are more closely related by firing pattern and cell size than by sensory modality.

We studied the rapid changes in electrical properties of lumbar motoneurons between postnatal days 3 and 9 just before mice weight-bear and walk. The input conductance and rheobase significantly increased up to P8. A negative correlation exists between the input resistance (Rin) and rheobase. Both parameters are significantly correlated with the total dendritic surface area of motoneurons, the largest motoneurons having the lowest Rin and the highest rheobase. We classified the motoneurons into three groups according to their discharge firing patterns during current pulse injection (transient, delayed onset, sustained). The delayed onset firing type has the highest rheobase and the fastest action potential (AP) whereas the transient firing group has the lowest rheobase and the less mature AP. We found 32 and 10% of motoneurons with a transient firing at P3-P5 and P8, respectively. About 20% of motoneurons with delayed onset firing were detected at P8. At P9, all motoneurons exhibit a sustained firing. We defined five groups of motoneurons according to their discharge firing patterns in response to ascending and descending current ramps. In addition to the four classical types, we defined a fifth type called transient for the quasi-absence of discharge during the descending phase of the ramp. This transient type represents about 40% between P3-P5 and tends to disappear with age. Types 1 and 2 (linear and clockwise hysteresis) are the most preponderant at P6-P7. Types 3 and 4 (prolonged sustained and counter clockwise hysteresis) emerge at P8-P9. The emergence of types 3 and 4 probably depends on the maturation of L type calcium channels in the dendrites of motoneurons. No correlation was found between groups defined by step or triangular ramp of currents with the exception of transient firing patterns. Our data support the idea that a switch in the electrical properties of lumbar motoneurons might exist in the second postnatal week of life in mice.