Theoretical Analysis of Coupled Modified Hindmarsh-rose Model Under Transcranial Magnetic-acoustic Electrical Stimulation

Transcranial magnetic-acoustic electrical stimulation (TMAES) is a new technology with ultrasonic waves and a static magnetic field to generate an electric current in nerve tissues to modulate neuronal firing activities. The existing neuron models only simulate a single neuron, and there are few studies on coupled neurons models about TMAES. Most of the neurons in the cerebral cortex are not isolated but are coupled to each other. It is necessary to study the information transmission of coupled neurons. The types of neuron coupled synapses include electrical synapse and chemical synapse. A neuron model without considering chemical synapses is not comprehensive. Here, we modified the Hindmarsh-Rose (HR) model to simulate the smallest nervous system—two neurons coupled electrical synapses and chemical synapses under TMAES. And the environmental variables describing the synaptic coupling between two neurons and the nonlinearity of the nervous system are also taken into account. The firing behavior of the nervous system can be modulated by changing the intensity or the modulation frequency. The results show that within a certain range of parameters, the discharge frequency of coupled neurons could be increased by altering the modulation frequency, and intensity of stimulation, modulating the excitability of neurons, reducing the response time of chemical postsynaptic neurons, and accelerating the information transferring. Moreover, the discharge frequency of neurons was selective to stimulus parameters. These results demonstrate the possible theoretical regulatory mechanism of the neurons' firing frequency characteristics by TMAES. The study establishes the foundation for large-scale neural network modeling and can be taken as the theoretical basis for TMAES experimental and clinical application.

A theory of synaptic transmission

Rapid and precise neuronal communication is enabled through a highly synchronous release of signaling molecules neurotransmitters within just milliseconds of the action potential. Yet neurotransmitter release lacks a theoretical framework that is both phenomenologically accurate and mechanistically realistic. Here, we present an analytic theory of the action-potential-triggered neurotransmitter release at the chemical synapse. The theory is demonstrated to be in detailed quantitative agreement with existing data on a wide variety of synapses from electrophysiological recordings in vivo and fluorescence experiments in vitro. Despite up to ten orders of magnitude of variation in the release rates among the synapses, the theory reveals that synaptic transmission obeys a simple, universal scaling law, which we confirm through a collapse of the data from strikingly diverse synapses onto a single master curve. This universality is complemented by the ability of the theory to readily extract, through a fit to the data, the kinetic and energetic parameters that uniquely identify each synapse. The theory provides a means to detect cooperativity among the SNARE complexes that mediate vesicle fusion and reveals such cooperativity in several existing data sets. The theory is further applied to establish connections between molecular constituents of synapses and synaptic function. The theory allows competing hypotheses of short-term plasticity to be tested and identifies the regimes where particular mechanisms of synaptic facilitation dominate or, conversely, fail to account for the existing data for the paired-pulse ratio. The derived trade-off relation between the transmission rate and fidelity shows how transmission failure can be controlled by changing the microscopic properties of the vesicle pool and SNARE complexes. The established condition for the maximal synaptic efficacy reveals that no fine tuning is needed for certain synapses to maintain near-optimal transmission. We discuss the limitations of the theory and propose possible routes to extend it. These results provide a quantitative basis for the notion that the molecular-level properties of synapses are crucial determinants of the computational and information-processing functions in synaptic transmission.

Markov Chain Abstractions of Electrochemical Reaction-Diffusion in Synaptic Transmission for Neuromorphic Computing

Progress in computational neuroscience toward understanding brain function is challenged both by the complexity of molecular-scale electrochemical interactions at the level of individual neurons and synapses and the dimensionality of network dynamics across the brain covering a vast range of spatial and temporal scales. Our work abstracts an existing highly detailed, biophysically realistic 3D reaction-diffusion model of a chemical synapse to a compact internal state space representation that maps onto parallel neuromorphic hardware for efficient emulation at a very large scale and offers near-equivalence in input-output dynamics while preserving biologically interpretable tunable parameters.

Synchronization Mode Transitions Induced by Chaos in Modified Morris-Lecar Neural Systems with Weak Coupling

Based on a modified Morris–Lecar neural model, the synchronization modes transitions between two coupled neurons or star-coupled neural network connected by weak electrical and chemical coupling are respectively investigated. For the two coupled neurons, by increasing the calcium conductivity, it is found that the period-2 synchronization of action potential of neurons is transformed to desynchronization first, and then to period-3 synchronization. By increasing the potassium conductivity, however, the synchronization mode transition is a reversal direction process as mentioned above. The bifurcation analysis of inter-spike interval shows that the synchronization modes transition is induced by the chaos. The stronger the coupling strength is, the smaller the period-2 synchronization region in the parameters plane is, while the larger the period-3 synchronization region will be. For the star-coupled neural network, in the presence of weak electrical coupling, it can exhibit the complete synchronization, desynchronization, and drum head mode states under different parameter values, respectively. In the presence of chemical synapse, however, the completely synchronized state can not be observed in the star-coupled neural network. Our results might provide novel insights into synchronization modes transition and related biological experiments.

Dual-Cell Patch-Clamp Recording Revealed a Mechanism for a Ribbon Synapse to Process Both Digital and Analog Inputs and Outputs

A chemical synapse is either an action potential (AP) synapse or a graded potential (GP) synapse but not both. This study investigated how signals passed the glutamatergic synapse between the rod photoreceptor and its postsynaptic hyperpolarizing bipolar cells (HBCs) and light responses of retinal neurons with dual-cell and single-cell patch-clamp recording techniques. The results showed that scotopic lights evoked GPs in rods, whose depolarizing Phase 3 associated with the light offset also evoked APs of a duration of 241.8 ms and a slope of 4.5 mV/ms. The depolarization speed of Phase 3 (Speed) was 0.0001–0.0111 mV/ms and 0.103–0.469 mV/ms for rods and cones, respectively. On pairs of recorded rods and HBCs, only the depolarizing limbs of square waves applied to rods evoked clear currents in HBCs which reversed at −6.1 mV, indicating cation currents. We further used stimuli that simulated the rod light response to stimulate rods and recorded the rod-evoked excitatory current (rdEPSC) in HBCs. The normalized amplitude (R/Rmax), delay, and rising slope of rdEPSCs were differentially exponentially correlated with the Speed (all p < 0.001). For the Speed < 0.1 mV/ms, R/Rmax grew while the delay and duration reduced slowly; for the Speed between 0.1 and 0.4 mV/ms, R/Rmax grew fast while the delay and duration dramatically decreased; for the Speed > 0.4 mV/ms, R/Rmax reached the plateau, while the delay and duration approached the minimum, resembling digital signals. The rdEPSC peak was left-shifted and much faster than currents in rods. The scotopic-light-offset-associated major and minor cation currents in retinal ganglion cells (RGCs), the gigantic excitatory transient currents (GTECs) in HBCs, and APs and Phase 3 in rods showed comparable light-intensity-related locations. The data demonstrate that the rod-HBC synapse is a perfect synapse that can differentially decode and code analog and digital signals to process enormously varied rod and coupled-cone inputs.

Modeling the role of gap junctions between excitatory neurons in the developing visual cortex

Recent experiments in the developing mammalian visual cortex have revealed that gap junctions couple excitatory cells and potentially influence the formation of chemical synapses. In particular, cells that were coupled by a gap junction during development tend to share an orientation preference and are preferentially coupled by a chemical synapse in the adult cortex, a property that is diminished when gap junctions are blocked. In this work, we construct a simplified model of the developing mouse visual cortex including spike-timing-dependent plasticity of both the feedforward synaptic inputs and recurrent cortical synapses. We use this model to show that synchrony among gap-junction-coupled cells underlies their preference to form strong recurrent synapses and develop similar orientation preference; this effect decreases with an increase in coupling density. Additionally, we demonstrate that gap-junction coupling works, together with the relative timing of synaptic development of the feedforward and recurrent synapses, to determine the resulting cortical map of orientation preference.

Gap Junctions Between Striatal D1 Neurons and Cholinergic Interneurons

The striatum participates in numerous important behaviors. Its principal projection neurons use GABA and peptides as neurotransmitters and interact extensively with interneurons, including cholinergic interneurons (ChIs) that are tonically active. Dissecting the interactions between projection neurons and ChIs is important for uncovering the role and mechanisms of the striatal microcircuits. Here, by combining several optogenetic tools with cell type-specific electrophysiological recordings, we uncovered direct electrical coupling between D1-type projection neurons and ChIs, in addition to the chemical transmission between these two major cell types. Optogenetic stimulation or inhibition led to bilateral current exchanges between D1 neurons and ChIs, which can be abolished by gap junction blockers. We further confirmed the presence of gap junctions through paired electrophysiological recordings and dye microinjections. Finally, we found that activating D1 neurons promotes basal activity of ChIs via gap junctions. Collectively, these results reveal the coexistence of the chemical synapse and gap junctions between D1 neurons and ChIs, which contributes to maintaining the tonically active firing patterns of ChIs.

Neuronal Glycoprotein M6a: An Emerging Molecule in Chemical Synapse Formation and Dysfunction

The cellular and molecular mechanisms underlying neuropsychiatric and neurodevelopmental disorders show that most of them can be categorized as synaptopathies—or damage of synaptic function and plasticity. Synaptic formation and maintenance are orchestrated by protein complexes that are in turn regulated in space and time during neuronal development allowing synaptic plasticity. However, the exact mechanisms by which these processes are managed remain unknown. Large-scale genomic and proteomic projects led to the discovery of new molecules and their associated variants as disease risk factors. Neuronal glycoprotein M6a, encoded by the GPM6A gene is emerging as one of these molecules. M6a has been involved in neuron development and synapse formation and plasticity, and was also recently proposed as a gene-target in various neuropsychiatric disorders where it could also be used as a biomarker. In this review, we provide an overview of the structure and molecular mechanisms by which glycoprotein M6a participates in synapse formation and maintenance. We also review evidence collected from patients carrying mutations in the GPM6A gene; animal models, and in vitro studies that together emphasize the relevance of M6a, particularly in synapses and in neurological conditions.

Impacts of autapse on chaotic resonance in single neurons and small-world neuronal networks

Chaotic resonance (CR) is a new phenomenon induced by an intermediate level of chaotic signal intensity in neuronal systems. In the current study, we investigated the effects of autapse on the CR phenomenon in single neurons and small-world (SW) neuronal networks. In single neurons, we assume that the neuron has only one autapse modelled as electrical, excitatory chemical and inhibitory chemical synapse, respectively. Then, we analysed the effects of each one on the CR, separately. Obtained results revealed that, regardless of its type, autapse significantly increases the chaotic resonance of the appropriate autaptic parameter’s values. It is also observed that, at the optimal chaotic current intensity, the multiple CR emerges depending on autaptic time delay for all the autapse types when the autaptic delay time or its integer multiples match the half period or period of the weak signal. In SW networks, we investigated the effects of chaotic activity on the prorogation of pacemaker activity, where pacemaker neurons have different kinds of autapse as considered in single neuron cases. Obtained results revealed that excitatory and electrical autapses prominently increase the prorogation of pacemaker activity, whereas inhibitory autapse reduces or does not change it. Also, the best propagation was obtained when the autapse was excitatory. This article is part of the theme issue ‘Vibrational and stochastic resonance in driven nonlinear systems (part 2)’.

Synaptic polarity and sign-balance prediction using gene expression data in the Caenorhabditis elegans chemical synapse neuronal connectome network

Graph theoretical analyses of nervous systems usually omit the aspect of connection polarity, due to data insufficiency. The chemical synapse network of Caenorhabditis elegans is a well-reconstructed directed network, but the signs of its connections are yet to be elucidated. Here, we present the gene expression-based sign prediction of the ionotropic chemical synapse connectome of C. elegans (3,638 connections and 20,589 synapses total), incorporating available presynaptic neurotransmitter and postsynaptic receptor gene expression data for three major neurotransmitter systems. We made predictions for more than two-thirds of these chemical synapses and observed an excitatory-inhibitory (E:I) ratio close to 4:1 which was found similar to that observed in many real-world networks. Our open source tool (http://EleganSign.linkgroup.hu) is simple but efficient in predicting polarities by integrating neuronal connectome and gene expression data.